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343 Commits

Author SHA1 Message Date
Nickolay Shmyrev 81c82935ac Add usage example 2022-07-07 01:09:32 +02:00
Nickolay Shmyrev ac3ec56584 Add notes about Go and Rust 2022-07-05 01:18:08 +02:00
Nickolay Shmyrev 2cbe12d4d0 Add link to rust bindings 2022-07-05 01:17:43 +02:00
Nickolay Shmyrev 1475b0e986 Async ffmpeg for trancriber and code refactoring 2022-07-05 01:13:05 +02:00
vadimdddd 8ceab0b9b1 Add vosk-server to transcriber (#1024)
Allow to use vosk-server for transcription
2022-07-04 13:50:38 +03:00
Nickolay Shmyrev 1496b597d3 Fixes issues with models without alignment 2022-07-03 13:00:05 +02:00
vadimdddd 983519e629 Add compatibility with python 3.5 issue(#1021) (#1041)
Added format for python3.5
2022-06-29 18:00:40 +03:00
Nickolay Shmyrev 58fa98ccd7 Wait for microphone to finalize. Fixes crash in issue #1034 2022-06-28 01:01:53 +03:00
Nickolay Shmyrev a7bc5a22d4 We support Polish now 2022-06-05 23:03:57 +02:00
Rémi Bernon 23bbff0b56 build: Add a CMakeLists.txt. (#992) 2022-06-04 17:34:42 +03:00
Kay Gosho a47b58e2f4 Specify device to get microphone input (#993) 2022-06-03 15:33:50 +03:00
Nickolay Shmyrev 8cf64ee93e Add RISCV support 2022-06-02 01:44:16 +02:00
vadimdddd 630edeb3d6 fixed error if parent directory doesn't exist #988 (#990)
Create missing parent directory
2022-06-01 17:52:16 +03:00
Nickolay Shmyrev b1b216d4c8 Bump versions 2022-05-26 15:22:16 +02:00
Nickolay Shmyrev 55dd29b0ff Fix transcriber bugs while processing folder 2022-05-26 14:05:54 +02:00
Nickolay Shmyrev ea0568a38d Change target binary library name and copy header 2022-05-26 13:29:14 +02:00
Nickolay Shmyrev 298c86d0d4 Bump version and add python requirements 2022-05-26 12:46:06 +02:00
Nickolay Shmyrev 859420809b Add extra comments 2022-05-26 11:45:16 +02:00
Nickolay Shmyrev 0fe3a89768 Update to 0.3.40 2022-05-26 11:41:14 +02:00
Nickolay Shmyrev 5b892fbfc5 Architecture should be universal2 2022-05-25 19:52:05 +03:00
Nickolay Shmyrev fb4ed21a7f Shave transcriber code 2022-05-24 22:53:57 +02:00
vadimdddd 4209f3a9fe Vosk model loader(#871) (#941)
* methods get_model_by_name, get_model_by_lang, get_model were added into the model class

* importing modules changed to using components; introduced constant MODELS_HOME_DIR; simplified code

* added new model folders into init; changed samples and transcriber bin for new mode loader

* changed back in cli.py lang arg to args.lang

* added 3 directories instead of 1 to check for models

* cli.py: added 3 args instead of 1 for model; __init__.py: changed script get_model_path for run get_model_by_name/lang inside current directory

* deleted default env var

* cli.py: changed arg_name; __init__.py: changed const name, changed model loading only for last directory

* deleted unused method

* changed by_name, by_lang methods, added download_model method

* deleted env variable initialization

* deleted print()

* deteled unused modules

* added progress_bar, added folder AppData/Local/vosk for model search

* changed download_model methond; added my_hook method
2022-05-24 21:06:13 +03:00
Nickolay Shmyrev ff2c80d5f1 Add x86 crossbuild 2022-05-24 20:00:03 +02:00
Nickolay Shmyrev 3a07a08121 Universal binary in node 2022-05-24 17:30:49 +02:00
Nickolay Shmyrev 592da81a8c Update nuget package for 0.3.38 2022-05-24 17:05:14 +02:00
Nickolay Shmyrev def8c93711 Remove semicolon 2022-05-24 15:23:03 +03:00
Nickolay Shmyrev f73088da58 We create universal binary on OSX 2022-05-24 15:11:05 +03:00
Nickolay Shmyrev 06a761ecbd Bump openblas 2022-05-15 23:58:30 +02:00
Nickolay Shmyrev 97d737a30a Bump version 2022-05-15 23:36:46 +02:00
Nickolay Shmyrev c7bffbf603 No need for g++ in C code, fix osx warning 2022-05-15 23:20:33 +02:00
Nickolay Shmyrev 02c40ea612 Bring back incremental decoder, now works better with kaldi fix 2022-05-15 23:20:19 +02:00
Mark Delk ce5ffb980a use comma instead of equal sign in rpath linker opts (#963)
Using `=` for linker options is a GNU extension which doesn't work with
clang.

Using `,` should work for both gcc and clang.
2022-05-12 00:34:43 +03:00
Nickolay Shmyrev d5ca98a982 Revert incremental decoder patch, leads to very slow decoding in some cases due to lattice blow-up 2022-05-06 00:34:50 +02:00
Nickolay Shmyrev b0146782d6 Reorganize transcriber binary 2022-04-29 03:01:09 +02:00
Nickolay Shmyrev 5aaea8fc90 Simplify makefile 2022-04-29 02:35:17 +02:00
Chupligin Sergey 5d7752b657 Allow build with shared librares (#939) 2022-04-29 03:23:22 +03:00
vadimdddd 9d94746479 Add transcriber tool (#851)
Add transcriber tool
2022-04-20 14:48:22 +03:00
Nickolay V. Shmyrev a87f2e1e07 Czech model 2022-04-13 22:31:45 +02:00
Nickolay Shmyrev 7b7d814484 Introduce incremental decoder with confidences in partial results 2022-04-07 01:07:47 +02:00
Nickolay Shmyrev 2daf67f31c C# style method name 2022-03-29 23:05:27 +02:00
Nickolay V. Shmyrev 62dd631379 Merge pull request #894 from gauthiersornet/patch-1
Update VoskDemo.cs
2022-03-22 22:35:16 +03:00
gauthiersornet 2511192ecb Update VoskDemo.cs
To read shorts from a binary buffer => fbuffer[i] = BitConverter.ToInt16(buffer, n);
2022-03-22 20:29:59 +01:00
Nickolay Shmyrev 22cb90de4a Add Hindi 2022-03-17 20:08:39 +01:00
Nickolay Shmyrev 3951834df2 Move decoding parts to decoding stage. Enable upsampling/downsampling 2022-03-05 14:52:11 +01:00
Nickolay Shmyrev 1ea0de106c Add trainign setup 2022-03-05 00:28:27 +01:00
Nickolay Shmyrev a9bf929ebd Add NLSML output for GPU recognizer 2022-03-03 23:01:49 +01:00
Nickolay Shmyrev 3336cd704b Add resampler 2022-03-03 21:48:25 +01:00
Nickolay Shmyrev a57a84f90e Refactor GPU API to hide the ID and keep it closer to CPU recognizer 2022-03-03 21:09:09 +01:00
Nickolay Shmyrev ad546a8f1a Also read processing options 2022-02-17 10:43:05 +01:00
Nickolay Shmyrev 1f447a8dfc Rename according to Kaldi changes 2022-02-10 20:52:55 +01:00
Nickolay Shmyrev f574d896e9 Emtpy result should be also xml 2022-02-03 23:43:00 +01:00
Nickolay Shmyrev a561c2d6d4 Don't add space before string 2022-02-03 23:26:53 +01:00
Nickolay Shmyrev 79b8395be0 Add NLSML output 2022-02-03 23:08:09 +01:00
Nickolay Shmyrev d2c11a611f Read list of files from arguments 2022-01-30 22:57:36 +01:00
Nickolay Shmyrev b0903413b1 Set soname for Android library 2022-01-21 13:22:26 +01:00
Nickolay Shmyrev 2135223490 Put stream information in a single structure 2022-01-12 14:58:43 +01:00
Nickolay Shmyrev 6f86944a06 Implement wave chunking for cuda decoder 2022-01-12 01:32:20 +01:00
Nickolay Shmyrev 9861be2787 Add libs as dependencies in Makefile 2022-01-10 20:21:24 +01:00
Nickolay Shmyrev c6fab363e6 Don't close channel which not yet started 2022-01-09 15:15:20 +01:00
Nickolay Shmyrev c32099705f Fix branch name and add implib dump 2022-01-07 17:33:47 +01:00
Nickolay Shmyrev a1eac015dc Add Esperanto 2022-01-07 16:27:57 +01:00
Nickolay Shmyrev 64dfc65d51 Merge branch 'master' of github.com:alphacep/vosk-api 2022-01-05 20:32:25 +01:00
Nickolay Shmyrev 70d5cbd0e0 Update README with Japanese 2022-01-05 20:32:08 +01:00
Nickolay Shmyrev 5428d36d16 Round times 2021-12-26 01:12:18 +01:00
Nickolay V. Shmyrev ed4c15b7aa Merge pull request #800 from alphacep/batch
Batch GPU decoding
2021-12-24 03:35:51 +03:00
Nickolay Shmyrev 525b722c44 Compile without CUDA too 2021-12-24 01:35:06 +01:00
Nickolay Shmyrev 72bf210164 Put the demo into main folder 2021-12-24 01:07:38 +01:00
Nickolay Shmyrev 93e81c3bc8 Bigger frames per chunk for our big models 2021-12-24 00:22:42 +01:00
Nickolay Shmyrev cb0f8e6411 Per-stream wait API 2021-12-23 22:34:47 +01:00
Nickolay Shmyrev 848b2dc753 Expose results in Python 2021-12-17 22:57:00 +01:00
Nickolay Shmyrev 60f0396fe0 Reset lattice on endpoint 2021-12-17 01:13:09 +01:00
Nickolay Shmyrev 344e137a61 Decoding works, results are empty yet 2021-12-13 01:21:59 +01:00
Nickolay Shmyrev 6977be7fb7 Batch recognizer draft 2021-12-12 21:37:44 +01:00
Nickolay V. Shmyrev a4721de8aa Merge pull request #759 from bertyhell/patch-1
Output correct SRT format using milliseconds (NodeJS SRT example)
2021-11-11 12:52:00 +03:00
Bert Verhelst 378ba122c8 Output correct SRT format using miliseconds 2021-11-11 10:49:50 +01:00
Nickolay Shmyrev 287160622f Update to latest state 0.3.32 2021-11-10 22:26:31 +03:00
Nickolay Shmyrev a5d788a2e9 One more fix to expose aar dependencies 2021-11-10 00:33:03 +01:00
Nickolay Shmyrev 7f651e1e45 Expose JNA dependency. Fix issue #757 2021-11-09 23:02:17 +01:00
Nickolay Shmyrev ad5bec114d Fix issue with empty lattice 2021-11-08 13:46:35 +01:00
Nickolay Shmyrev f71c62ad0f Publish Java jars on Mavencentral too 2021-11-07 21:26:33 +01:00
Nickolay Shmyrev 44f7dd2d8b Publish to sonatype 2021-11-07 20:41:49 +01:00
Nickolay Shmyrev 15a9508a78 Use ndk directory instead of sdk 2021-11-07 14:32:29 +01:00
Nickolay Shmyrev bdea9a53e8 Bump android version 2021-11-07 14:30:08 +01:00
Nickolay Shmyrev 81f58667ff Update Android build 2021-11-07 13:45:27 +01:00
Nickolay V. Shmyrev 680a2e4c31 Merge pull request #752 from sskorol/cuda-fix
Added missing cuda lib to Vosk compilation flags
2021-11-06 19:04:22 +03:00
sskorol 13993db542 Added missing cuda lib to Vosk compilation flags 2021-11-06 17:24:49 +02:00
Nickolay Shmyrev 59d595a4f0 Replace about in readme 2021-10-31 00:15:52 +02:00
Nickolay Shmyrev 4c562e15a4 Bump version to 0.3.32 2021-10-30 22:45:10 +02:00
Nickolay Shmyrev 5bcdf454ec Add fbank feature support 2021-10-30 22:45:01 +02:00
Nickolay Shmyrev 4ccdda44ac Extend documentation 2021-10-12 22:35:31 +02:00
Nickolay Shmyrev 5e46825474 Add try/catch wrapper for C++ method to raise native exceptions. Python and Java
are implemented, others on the way
2021-10-12 22:31:36 +02:00
Nickolay Shmyrev fcab5a9581 Revert CFFI bump 2021-10-10 22:09:55 +02:00
Nickolay Shmyrev e7f5e0ac23 Bump cffi version 2021-10-10 21:21:32 +02:00
Nickolay Shmyrev 9a3906831b Properly convert lattice. Fixes issue #713 2021-10-08 21:11:00 +02:00
Nickolay Shmyrev 195db43b9e Rename branches in kaldi repo 2021-10-07 01:18:47 +02:00
Nickolay Shmyrev 332553ec1e Revert rescoring to more accurate pure fst composition 2021-10-04 01:05:04 +02:00
Nickolay Shmyrev 646af3f652 Explain more about sample rate in constructor 2021-09-17 11:17:38 +02:00
Nickolay V. Shmyrev f24ac65fcb Merge pull request #688 from scroot/patch-1
Update vosk.go
2021-09-16 18:42:03 +03:00
scroot 14312c93f9 Update vosk.go
* fix partial result
+ Free
2021-09-16 09:55:26 +08:00
Nickolay Shmyrev 4346d4155d Fix go example 2021-09-02 10:48:19 +02:00
Nickolay Shmyrev 7790ac5040 Update versions in bindings 2021-08-31 22:42:42 +02:00
Nickolay Shmyrev 7b3ea0b59d Merge branch 'master' of github.com:alphacep/vosk-api 2021-08-31 21:56:49 +02:00
Nickolay Shmyrev e2af710369 Rework rescoring for faster and more accurate results 2021-08-31 21:56:21 +02:00
Nickolay V. Shmyrev 6b1b620f39 Merge pull request #678 from agorman/go-bindings
Cleaning up and completing go bindings
2021-08-31 22:34:19 +03:00
Andy Gorman 966524da16 gofmt 2021-08-31 12:24:19 -07:00
Andy Gorman 83c999f298 Cleaning up and completing go bindings 2021-08-31 12:18:34 -07:00
Nickolay Shmyrev abff8a4f56 Organize makefile structure 2021-07-29 11:58:31 +02:00
Timur 188575f3a2 Added MKL build options (#647)
Co-authored-by: Kasimov Timur <t.kasimov@cft.ru>
2021-07-29 11:03:39 +03:00
Nickolay Shmyrev 9f4d8ca187 Update doc 2021-07-12 20:29:42 +02:00
Nickolay Shmyrev 72cc8f3a5e Added test doc 2021-07-12 20:23:49 +02:00
Nickolay Shmyrev 915dcab597 Add doc 2021-07-11 15:54:42 +02:00
Nickolay Shmyrev d82052b168 Better have it here 2021-07-11 11:26:32 +02:00
Nickolay Shmyrev dbb65bc71c Unify example 2021-07-11 11:01:56 +02:00
Nickolay Shmyrev 2498bc595b Add module file 2021-07-11 10:22:24 +02:00
Nickolay Shmyrev fee63d712f Add go bindings 2021-07-10 23:44:15 +02:00
Nickolay Shmyrev 5965ea30e6 Fetch_sub returns original value 2021-07-06 12:11:12 +02:00
Nickolay Shmyrev 5c75495c03 Atomic refcounting for thread safety. See
https://github.com/alphacep/vosk-api/issues/606

for more details
2021-07-06 11:09:34 +02:00
Nickolay Shmyrev 98ae3c66cb Bump version 2021-06-28 02:09:06 +02:00
Nickolay Shmyrev 942e15484a Protect against multiple resets 2021-06-28 01:59:43 +02:00
Lars Kiesow 2349e66a97 Subtitles require word times (#607)
This is a port of the recent addition of commit 7ccf743, adding
`KaldiRecognizer.SetWords(True)` to the other examples dealing with
subtitles to the WebVTT example.

Without this, the example will not work with the most recent `vosk`
(0.3.30) Python package.
2021-06-27 18:06:11 +03:00
Nickolay Shmyrev 5750e3224f Merge branch 'master' of github.com:alphacep/vosk-api 2021-06-24 20:09:12 +02:00
Nickolay Shmyrev 558b4dd69e Don't align lattice twice 2021-06-24 20:08:54 +02:00
Lars Kiesow 02ef49f67e Allow Saving WebVTT (#605)
This patch is a small extension to the WebVTT example which allows to
directly save the WebVTT output to a file like this:

    ./test_webvtt.py test.wav out.vtt
2021-06-24 19:35:30 +03:00
Lars Kiesow 7cdf8f1d03 Add Python WebVTT Example (#601)
This patch adds an example for using webvtt-py to generate WebVTT files
from Vosk output. This is similar to the SRT example but still very
useful for generating an example video subtitle usable in web contexts.
2021-06-23 01:16:33 +03:00
Nickolay Shmyrev 7f894f784a Better check for the model files 2021-06-21 00:19:55 +02:00
Nickolay Shmyrev a770251151 Bump nodejs version to 0.3.30 2021-06-20 21:30:58 +02:00
Nickolay Shmyrev 7ccf743bb6 SRT requires word times 2021-06-10 10:37:15 +02:00
Nickolay Shmyrev 75bedfe06d Add a method to show/hide words and their times 2021-06-07 01:04:37 +02:00
Nickolay Shmyrev 4ea9885d44 Bump version 2021-05-30 21:59:46 +02:00
Nickolay Shmyrev 0930def9ec Fix critical accuracy issues, actually use rescoring 2021-05-30 21:58:06 +02:00
Nickolay Shmyrev 6aa5af7640 Add reset test 2021-05-26 21:22:07 +02:00
Nickolay Shmyrev e74fe5edf7 Reset reset flag 2021-05-26 21:01:27 +02:00
Nickolay Shmyrev cbb5d0fcdf Implement reset method in SpeechService 2021-05-26 20:51:44 +02:00
Nickolay Shmyrev d489bc40e4 Update Java part too 2021-05-26 00:59:08 +02:00
Nickolay Shmyrev 499b2f183a Introduce new API to set speaker model to already initialized recognizer.
Introduce a method to reset recognizer results to start from scratch without
computation of the result.
2021-05-26 00:46:32 +02:00
Nickolay Shmyrev f57b926f66 Unpack library, loading works on Windows 2021-05-23 01:29:29 +02:00
Nickolay Shmyrev 733dca5aea Attempt to fix loading on Windows 2021-05-22 00:41:30 +02:00
Nickolay Shmyrev 1ab7e8ca87 Use older API for backward compatibility 2021-05-20 20:48:21 +02:00
Nickolay Shmyrev 53426f794c Add note about Ukrainian 2021-05-20 01:29:15 +02:00
Nickolay Shmyrev f8189685e5 Add max alternatives output 2021-05-19 18:47:25 +02:00
Nickolay Shmyrev e6bd200c85 Proper path delimiter on windows 2021-05-13 09:36:56 +02:00
Nickolay Shmyrev 4a4c33fd9d Load dependent libraries 2021-05-10 01:39:26 +02:00
Nickolay Shmyrev dc44922b92 Add code to expand path 2021-05-10 01:26:05 +02:00
Nickolay Shmyrev 67896cfba7 Bump bindings versions 2021-05-05 20:50:25 +02:00
Nickolay Shmyrev ee8663e6d9 RNNLM rescoring support 2021-05-05 19:34:30 +02:00
Nickolay Shmyrev 652c05f052 Reformat and simplify code a bit 2021-05-02 21:44:54 +02:00
Nickolay Shmyrev 193d129d9e Model can be a symlink 2021-04-30 11:58:11 +02:00
Sadra Sabouri e995df4bc3 New Examples for Nodejs (Base on Python Examples) (#515) 2021-04-30 10:16:36 +03:00
Sergey Korol f6a30c3626 Added missing GPU methods to nuget package. (#514) 2021-04-29 20:57:56 +03:00
Nickolay Shmyrev ee95420f8f Fix spk model initialization 2021-04-27 23:24:10 +02:00
Nickolay Shmyrev 2221cd0209 Reorganize methods a bit 2021-04-26 23:25:05 +02:00
Nickolay Shmyrev 8368d831aa Add async processing demo 2021-04-26 22:34:33 +02:00
Nickolay Shmyrev 91a128b3ed Fix package name 2021-04-15 13:54:48 +02:00
Nickolay Shmyrev 83d8b63351 Merge branch 'master' of github.com:alphacep/vosk-api 2021-04-15 12:57:17 +02:00
Nickolay Shmyrev 0881aa856f Update for new API 2021-04-15 12:56:59 +02:00
Nickolay Shmyrev 77abb02ada Bump version 2021-04-12 12:23:11 +02:00
François Billioud 119c6cd0dc Update ffi-napi and improve dependency to ref-napi (#483)
With this change, we will use the same version of ref-napi than the one declared in ffi-napi, which reduce dependency tree, bundle size, risks of errors that could be fixed in one version and not in the other, etc
2021-04-01 22:12:14 +03:00
Nickolay Shmyrev cc649aa78e Fixes demo 2021-04-01 20:33:01 +02:00
François Billioud 0b0c9fce0e Types for typescript projects, and jsDoc (#461)
Implement Javascript API
2021-04-01 21:25:55 +03:00
Peter Kronenberg d845e2107f Allow libvosk.dll to get loaded on Windows (#478)
* Allow libvosk.dll to get loaded on Windows

Authored-by: Peter Kronenberg <peter.kronenberg@torch.ai>
2021-03-31 18:55:45 +03:00
Nickolay V. Shmyrev 69992a1b39 Android through JNA framework unified with Java (#476)
* Move to JNA

* Update for android

* Joint publishing

* Fix the developer id

* Added grammar constructor for Java
2021-03-30 23:36:26 +03:00
Nickolay Shmyrev f351280f49 Allow extra cflags 2021-03-30 19:24:00 +02:00
Nickolay Shmyrev c15065b044 Wrap short and float 2021-03-30 17:34:00 +02:00
Nickolay Shmyrev db41f16051 Docs are on the separate project 2021-03-29 00:38:54 +02:00
Nickolay Shmyrev e276de61be Give jar a name and fix OSX library path 2021-03-29 00:20:52 +02:00
Nickolay Shmyrev 43c786ab18 Move jars to our own maven and create a demo 2021-03-28 23:38:43 +02:00
Nickolay Shmyrev 1199f39d55 Move project to a library 2021-03-28 13:02:32 +02:00
Nickolay Shmyrev 70aab86257 Remove test code 2021-03-28 10:11:53 +02:00
Nickolay Shmyrev e4b0af7a8e Update nuget package, add osx library 2021-03-27 23:40:02 +01:00
Martin Mende a120d06f6b Fixed nodejs platform check (#464) 2021-03-24 17:08:39 +03:00
Nickolay Shmyrev e01ca37e45 Add osx module 2021-03-18 00:46:51 +01:00
Nickolay Shmyrev f5c3d898e2 Option to compile on Mac 2021-03-18 02:10:56 +03:00
Nickolay Shmyrev a5a3697b7c Copy data before queue, original data can be destroyed.
Fixes issue #444

Thanks to Alexander Zatvornitsky
2021-03-01 21:25:41 +01:00
Nickolay Shmyrev 4be9874ba2 Reformat 2021-02-28 22:40:40 +01:00
Peter Kronenberg 5647a2dc6a Java example with better type safety, Java objects and support for au… (#429)
Java example with better type safety, Java objects and support for autoclosable

Authored-by: Peter Kronenberg <peter.kronenberg@torch.ai>
2021-03-01 00:35:31 +03:00
Nickolay Shmyrev a067a5b5f3 Enable pitch if conf/pitch.conf is present
Fixes issue #442
2021-02-26 20:34:17 +01:00
Nickolay Shmyrev 475b0ecfc1 Free symbol table only if we loaded it 2021-02-25 19:17:13 +01:00
Nickolay V. Shmyrev 2a9a605144 Merge pull request #436 from sskorol/435-sync-master-with-gpu
Sync master with GPU
2021-02-22 13:41:37 +03:00
sskorol eea7ca571b - Added an optional HAVE_CUDA flag to build Vosk with GPU support.
- Added missing GpuInit/ThreadInit python wrappers.
2021-02-22 12:30:46 +02:00
Nickolay Shmyrev 11c16610ee Fix memory leaks for big models. Fixes issue #425. 2021-02-19 19:25:07 +01:00
Nickolay Shmyrev 2f4124eb66 Demonstrate speaker 2021-02-16 17:40:21 +01:00
Nickolay Shmyrev db3e31d7ce Automatically put .so file in resources 2021-02-16 17:33:09 +01:00
Nickolay Shmyrev d917af21ab Better search for Windows dlls 2021-02-12 22:24:54 +01:00
Nickolay Shmyrev 948c8c7cfd Update to 0.3.21 2021-02-12 10:13:50 +01:00
Nickolay Shmyrev dec8e1acf3 Move to JNA instead of JNR-FFI for better Android compatibility 2021-02-11 00:04:19 +01:00
Nickolay Shmyrev 3c020526ce No need for byte buffer 2021-02-10 23:32:47 +01:00
Nickolay Shmyrev b0da19b07f Java API through JNR-FFI 2021-02-10 23:16:20 +01:00
Nickolay Shmyrev 70bcd9b018 Platform is hardcoded now 2021-02-09 23:43:56 +01:00
Nickolay Shmyrev d2604b609d Copy out lib files too 2021-02-09 23:36:32 +01:00
Nickolay Shmyrev e960e0cacf Proper libraries and demo 2021-02-09 21:43:21 +01:00
Nickolay Shmyrev 77b114d434 Rework node bindings to use node-ffi-napi 2021-02-08 23:00:56 +01:00
Nickolay V. Shmyrev 2860092cef Merge pull request #401 from proger/patch-1
test_microphone: AcceptWaveform wants bytes
2021-02-08 01:50:07 +03:00
Vlad Ki c6119c4835 test_microphone: AcceptWavform wants bytes 2021-02-08 00:38:28 +02:00
Nickolay Shmyrev 415d1927e0 Add win32 wheel 2021-02-07 23:08:27 +01:00
Nickolay Shmyrev 3d1e21d242 Update dockcross build to cffi 2021-02-07 21:33:39 +01:00
Nickolay Shmyrev 7a75e1c3f4 Add arm architectures 2021-02-07 20:28:14 +01:00
Nickolay Shmyrev c3430e448a Add build for Windows wheel 2021-02-07 18:11:38 +01:00
Nickolay Shmyrev ae49ea60d2 Rework manylinux to use cffi 2021-02-07 15:26:23 +01:00
Nickolay Shmyrev 02dc0ce0c8 Take source location from environment 2021-02-07 15:17:35 +01:00
Nickolay Shmyrev 15697a18e8 Platform-specific wheel 2021-02-07 14:58:10 +01:00
Nickolay Shmyrev 481881e59d Fully move python to cffi 2021-02-07 13:23:03 +01:00
Nickolay Shmyrev 11a25b26a7 Add cffi wrapper 2021-02-07 10:57:57 +01:00
Nickolay Shmyrev bf87358f6c Add win32 build 2021-02-07 10:12:32 +01:00
Nickolay Shmyrev 04a8242230 Add vosk-api build 2021-02-07 01:55:47 +01:00
Nickolay Shmyrev ceb96c301c Separate openfst root 2021-02-07 01:48:45 +01:00
Nickolay Shmyrev 307df8fdc0 Add Win cross-compilation docker 2021-02-07 01:41:37 +01:00
Nickolay Shmyrev c44875a2dd Build libvosk in src folder, will be used for many bindings 2021-02-07 00:42:25 +01:00
Nickolay Shmyrev 31f11990ca Rename voskrecognizer 2021-02-07 00:32:47 +01:00
Nickolay Shmyrev b79b85856d Refactor C# API to properly work with nuget and precompiled libvosk.so library 2021-02-06 23:10:51 +01:00
Nickolay Shmyrev 6e861c6a19 Add nuget platforms 2021-02-05 00:39:27 +01:00
Nickolay Shmyrev cf62296a51 Update flags to hopefully fix the build 2021-02-02 14:43:12 +01:00
Nickolay Shmyrev 387b132814 Fix model version in Makefile. Thanks to Peter Kronenberg. 2021-01-26 23:19:34 +01:00
Nickolay Shmyrev de83de8624 Implement decoding on iOS with a microphone 2021-01-24 21:59:21 +01:00
Nickolay Shmyrev fe91b5a717 Preprocess header on the fly 2021-01-10 21:11:35 +01:00
Nickolay Shmyrev a052506a5d Add cffi example 2021-01-10 20:53:43 +01:00
Nickolay Shmyrev 6f2d6d0d69 Proper microphone recognizer with the queue 2021-01-09 23:16:35 +01:00
Nickolay Shmyrev a8ae6025bd Add a bit more optimization 2021-01-09 16:16:32 +01:00
Nickolay Shmyrev 1b8332a609 Raise to 0.3.17 2021-01-09 02:29:56 +01:00
Nickolay Shmyrev fe16ec7e57 Set lowest arch for linux 2021-01-09 01:47:23 +01:00
Nickolay Shmyrev c5ce5e46bd Add c++17 2021-01-09 01:46:13 +01:00
Nickolay Shmyrev 99d66670bc Update Android build 2021-01-08 13:30:28 +01:00
Nickolay Shmyrev 072b42cac6 Use our own dockcross 2021-01-08 00:56:18 +01:00
Nickolay Shmyrev acadb5b4c2 Add optimization 2021-01-07 23:41:13 +01:00
Nickolay Shmyrev 2e1de6c3af No need for python 3.5 anymore 2021-01-07 23:20:54 +01:00
Nickolay Shmyrev 67de30908b Use openblas_clapack 2021-01-07 22:37:56 +01:00
Nickolay Shmyrev 9d398eff0e Remove armv6, too slow anyway. Build with new dockcross. 2021-01-06 16:26:23 +01:00
Nickolay Shmyrev 02b7312a00 Build with openblas-clapack to avoid fortran 2021-01-06 01:11:03 +01:00
Nickolay Shmyrev 08c35e84f3 Update demo with spk vector check 2020-12-23 22:21:12 +01:00
Nickolay Shmyrev b92a5c1fc7 Update wheels to openfst 1.8.0 2020-12-22 23:27:01 +01:00
Nickolay Shmyrev 8997a587c5 Fix warnings in preparation for openfst 1.8.0 2020-12-22 21:16:20 +01:00
Nickolay Shmyrev dc3d03d742 Make sure we have result field in json 2020-11-29 19:19:50 +01:00
Nickolay Shmyrev 84df40715c Add Filipino 2020-11-19 14:53:46 +01:00
Nickolay Shmyrev b639fb501a Package US model on bintray 2020-11-04 22:08:03 +01:00
Nickolay Shmyrev 746ff47757 Split long lines in subtitles 2020-11-03 15:13:16 +01:00
Nickolay Shmyrev 2d62db8118 Update link in readme 2020-10-31 10:03:25 +01:00
Nickolay Shmyrev 7a2adcd9ba Add nuget wraps 2020-10-26 15:57:40 +01:00
Nickolay Shmyrev 9ccf3ef0e8 Introduce CMVN in feature pipeline 2020-10-22 23:56:36 +02:00
Nickolay V. Shmyrev 0edab6d558 Merge pull request #259 from ThThoma/add-valid-word-check
add isWordRecognizable()
2020-10-22 15:53:04 +03:00
Athanasios Thoma 4b344f0cd8 rename 2020-10-22 14:09:50 +03:00
Athanasios Thoma 17ddc4d5ba add isWordRecognizable() 2020-10-21 10:00:39 +03:00
Nickolay Shmyrev 3e33860c47 Update to latest 0.3.15 changes 2020-10-20 23:50:39 +03:00
Nickolay Shmyrev 0269a10833 Critical ivector bugfix and version 0.3.15 2020-10-13 01:28:46 +02:00
Nickolay Shmyrev 7af3e9a334 Add srt example 2020-10-07 13:43:09 +02:00
Nickolay Shmyrev d666876be1 Revert compile flags 2020-10-05 01:24:32 +02:00
Nickolay Shmyrev 564fab7ec1 Update documentation 2020-10-05 00:16:15 +02:00
Nickolay Shmyrev 155c6c2a2a Don't crash with grammar and static graphs 2020-10-05 00:13:25 +02:00
Nickolay Shmyrev d43cbe9344 Add 0.3.14 2020-10-04 23:45:34 +02:00
Nickolay Shmyrev 57cc474c9f Build bigram language model from grammars 2020-10-04 23:42:50 +02:00
Nickolay Shmyrev 586603f8e1 Add Farsi 2020-10-03 12:42:54 +02:00
Nickolay Shmyrev d57887d22a Add Greek 2020-09-30 13:42:20 +02:00
Nickolay Shmyrev 6183bcfc5f Add Arabic model 2020-09-30 13:29:43 +02:00
Nickolay Shmyrev 65f6113b4d Add Catalan 2020-09-27 11:57:20 +02:00
Nickolay Shmyrev 8d88b89db1 Fix reserved identifier violation. Closes issue #226
Thanks to Markus Elfring
2020-09-23 21:16:34 +02:00
Nickolay Shmyrev 62885e8963 Update descriptions 2020-09-22 11:30:27 +02:00
qo6xup6 9fc094a5da Update kaldi_recognizer.h 2020-09-22 10:11:29 +08:00
Nickolay Shmyrev f97383c17f Update models location 2020-09-22 00:00:24 +02:00
Nickolay Shmyrev 4b892ec5e7 Bump version 2020-09-21 23:49:55 +02:00
Nickolay Shmyrev 41035485db Fix x-vectors, now they actually work. Requires new version spk-model-0.4 with whitening transform matrix 2020-09-21 23:31:30 +02:00
Nickolay Shmyrev 9696f4c917 Mention Dutch 2020-09-18 17:31:17 +02:00
Nickolay Shmyrev 55abf5f5ac Dynamic arch in pip module 2020-09-13 22:08:36 +02:00
Nickolay Shmyrev a1b2e41710 Mention we support Indian English 2020-09-09 23:28:55 +02:00
Nickolay Shmyrev dff4ab26e4 Library is now vosk_jni 2020-09-01 18:27:54 +02:00
Nickolay Shmyrev 83b6e1cdf7 Speech service for more flexible recognizer initialization
Publish repo on jcenter
2020-09-01 16:32:15 +02:00
Nickolay Shmyrev 38dbaa15ea Load JNI inside library itself 2020-09-01 12:44:44 +02:00
Nickolay Shmyrev 0e531b6061 Organize Makefile 2020-08-23 20:10:48 +02:00
Nickolay Shmyrev de94ef5537 Add speaker C demo 2020-08-14 11:33:41 +02:00
Nickolay Shmyrev 6ef9d13877 Add Italian 2020-08-03 01:31:30 +02:00
Nickolay Shmyrev 1c7b94757d Don't attempt to resize to empty matrix 2020-07-31 16:45:05 +02:00
Nickolay Shmyrev 83486e0bef Spk vector fix 2020-07-31 12:58:23 +02:00
Nickolay Shmyrev 9787e8a53f No .html in links 2020-07-21 10:15:27 +02:00
Nickolay Shmyrev f59d6685ad Fix confidences 2020-07-15 10:24:08 +02:00
Nickolay Shmyrev 8a986ef384 Require KALDI_MKL to be 1 2020-07-12 11:03:22 +02:00
Nickolay Shmyrev 78f9f55e14 Fixes description 2020-07-12 10:37:56 +02:00
Nickolay Shmyrev c2e006f664 Some probably helpful flags for npm on osx 2020-07-11 20:54:13 +02:00
Nickolay V. Shmyrev 4b8e9737a5 Update README.md 2020-07-08 01:38:03 +02:00
Nickolay Shmyrev 722b09eaa4 Ignore words missing in the vocabulary 2020-07-08 01:35:50 +02:00
Nickolay Shmyrev f5b4f5a1f2 Added C test 2020-07-08 01:35:50 +02:00
Nickolay Shmyrev 4407d8da55 Another timestamp bugfix 2020-07-08 01:35:50 +02:00
Nickolay Shmyrev 73b73527cd Release memory when final result is received to reduce memory pressure. 2020-07-08 01:35:50 +02:00
Nickolay Shmyrev 4df0e3a741 Actually show the distance 2020-07-08 01:35:49 +02:00
He1nr1chK 1a771e0172 Added cosine distance function 2020-06-23 20:10:14 +02:00
Nickolay Shmyrev 4333c3c242 Build dockcross with python 3.8 2020-06-23 01:11:07 +02:00
Nickolay V. Shmyrev b831c9ad57 Merge pull request #151 from hviana/patch-1
Add support for speaker model in Android
2020-06-23 00:07:26 +03:00
Nickolay Shmyrev e5c08f7710 Allow to continue after final result. See for discussion
https://github.com/alphacep/vosk-api/issues/146
2020-06-22 23:04:09 +02:00
Henrique Emanoel Viana 51c2968595 fix 2020-06-22 18:01:42 -03:00
Henrique Emanoel Viana 5993376322 Add suport to SpkModel 2020-06-22 17:51:55 -03:00
Nickolay Shmyrev c4281622b9 Added node speaker demo 2020-06-22 21:45:50 +02:00
Nickolay Shmyrev 9d26014de2 Use wider beams by default to avoid accuracy confusion 2020-06-19 16:10:30 +02:00
Nickolay Shmyrev f6c115d215 Update to 0.3.9 and use our fork of openfst based on openfst 1.7.7 2020-06-16 19:13:57 +02:00
Nickolay Shmyrev 6bd102d778 Fixes timing issue #125 2020-06-15 02:04:02 +02:00
Nickolay Shmyrev d3d6af5712 Define os in a single place 2020-06-12 10:35:58 +02:00
Nickolay V. Shmyrev 876093446f Merge pull request #127 from nnkalita/master
added android build support on macOS
2020-06-12 11:32:27 +03:00
Nickolay Shmyrev 336f219f09 No Qr code for wechat anymore 2020-06-11 12:57:32 +02:00
Nickolay Shmyrev 584251cbdc Remove chinese-only 2020-06-11 09:18:34 +02:00
Nickolay Shmyrev a34995a788 Process audio in chunks for imporved accuracy 2020-06-11 01:06:11 +02:00
Nickolay Shmyrev 998e5da227 Update rules for joining wechat 2020-06-10 15:07:10 +02:00
Nickolay Shmyrev e04c15e367 Fix 2020-06-06 11:15:23 +02:00
Nickolay Shmyrev b81f69d407 Avoid overflow. See issue #128 2020-06-06 10:43:44 +02:00
Nickolay Shmyrev 0ac2064281 Few more words 2020-06-06 10:07:12 +02:00
Nickolay Shmyrev 1d00bd244e Multithreaded testing 2020-06-06 00:40:15 +02:00
Nickolay Shmyrev 8f5efc58c9 Disable ivector pipeline without ivectors 2020-06-05 19:34:04 +02:00
Nayan Kalita a0c5ae1b5e Update build-kaldi.sh
added android build from mac.
2020-06-05 20:10:28 +05:30
Nayan Kalita 99f48f9de1 Merge remote-tracking branch 'upstream/master' 2020-06-05 19:15:42 +05:30
Nayan Kalita 1948b23f32 Update build-kaldi.sh
Updated based feedback.
2020-06-05 18:03:01 +05:30
Nickolay Shmyrev c9eb572fc5 Move documentation to our website 2020-06-05 01:31:13 +02:00
Nickolay Shmyrev 7d9895ff81 Add API documentation in the header 2020-06-04 22:47:54 +02:00
Nickolay Shmyrev d507210ef8 Add npmignore and pure javascript package 2020-06-03 17:47:15 +02:00
Nickolay Shmyrev db0a3d23d5 Add repackages librispeech model 2020-06-03 17:24:28 +02:00
Nickolay Shmyrev f4f920f3cd Proper cross-compilation with setuptools 2020-06-02 00:36:16 +02:00
Nickolay Shmyrev 75993ea276 Update to 0.3.8 2020-06-01 00:55:28 +02:00
Nickolay Shmyrev ee9bacb092 Reset pipeline to save memory 2020-06-01 00:54:47 +02:00
Nickolay Shmyrev b1e775c67b Better speaker identification without silence frames 2020-05-31 23:46:42 +02:00
Nickolay Shmyrev d631e567aa Add README 2020-05-31 02:21:07 +02:00
Nickolay Shmyrev 9edf45be42 Sync version 2020-05-31 02:08:35 +02:00
Nickolay Shmyrev 8b4b3c646a Nodejs support 2020-05-31 02:07:01 +02:00
Nickolay Shmyrev 31bb0557d9 Add mkl support 2020-05-30 23:22:14 +02:00
Nickolay Shmyrev 4593183cf9 Create gen if doens't exist. Thanks to BMI24. 2020-05-25 00:32:42 +02:00
Nickolay Shmyrev fdc45f1187 Better link on wechat 2020-05-23 21:13:23 +02:00
Nickolay Shmyrev b3d3c6d12c Fix mistake, thanks to Shaheen 2020-05-23 01:12:31 +02:00
Nickolay Shmyrev f5f0794def Add logo 2020-05-22 15:24:57 +02:00
Nickolay Shmyrev 55664fcca0 Add wechat group 2020-05-22 09:56:54 +02:00
Nickolay Shmyrev afbf330f16 Make ivector extractor optional 2020-05-18 23:56:42 +02:00
Nickolay Shmyrev 25aadf61bc Fix travis 2020-05-09 17:36:55 +02:00
Nickolay Shmyrev be47056467 Updates for osx 2020-05-09 15:49:24 +03:00
Nickolay Shmyrev 8f623e0aea Get rid of broken cmake 2020-05-09 14:32:46 +02:00
Nickolay Shmyrev 78025435e4 Windows is fully supported now 2020-05-09 09:18:10 +02:00
Nickolay Shmyrev 910455802e Don't link to the library explicitely to allow relocations 2020-05-08 15:16:50 +03:00
Nickolay Shmyrev b12914955c Add x86 build 2020-05-08 11:33:25 +02:00
Nickolay Shmyrev dfe11eaf83 Linux build fix 2020-05-08 09:04:14 +02:00
Nickolay Shmyrev 37fbe1a52b OSX build 2020-05-08 09:55:15 +03:00
Nickolay Shmyrev af11bb2361 No need for external dependencies 2020-05-07 21:48:03 +02:00
Nickolay Shmyrev 8da8697c1e Add ffmpeg test 2020-05-07 21:07:17 +02:00
Nickolay V. Shmyrev 944dc87531 Update readme to mention aarch64 2020-05-05 00:55:29 +02:00
Nickolay Shmyrev 5c4dd4644e Update version 2020-05-03 20:52:43 +02:00
Nickolay Shmyrev 9bbd172cfd Some more links 2020-05-02 01:37:10 +02:00
Nickolay Shmyrev dbf9de77c3 Document model training and model structure 2020-05-02 01:11:25 +02:00
Nickolay Shmyrev 8b790cd162 Better android logging 2020-05-01 20:02:46 +02:00
Nickolay Shmyrev 80219066e9 Expose verbose level in the API 2020-05-01 19:02:57 +02:00
Nickolay Shmyrev 26fa5f098f Updated link to English model 2020-04-30 15:19:13 +02:00
Nickolay Shmyrev d75bb36131 Fix model download path 2020-04-30 11:04:35 +02:00
Nickolay Shmyrev 30c5e8ca79 Link to lm library for rescoring 2020-04-30 10:52:15 +02:00
Nickolay Shmyrev c00e36fab6 Rearrange models 2020-04-30 10:47:10 +02:00
Nayan Kalita bca0b86e37 android build support on macOS 2020-03-06 20:57:56 +05:30
170 changed files with 8577 additions and 2740 deletions
+49 -15
View File
@@ -1,19 +1,25 @@
# Built application files
*.apk
*.ap_
# Object files
*.o
# Java class files
*.class
# Temp files
nohup.out
# Gradle files
.gradle/
build/
gradlew
gradlew.bat
gradle
# Local configuration file (sdk path, etc)
local.properties
gradle.properties
# Android
android/build
android/lib/build
android/model-en/build
android/model-en/src/main/assets/model-en-us
android/repo
*.apk
*.ap_
# Cmake
.cxx
@@ -24,14 +30,42 @@ wheelhouse
__pycache__
*.egg-info
python/dist
python/build
python/vosk/*.so
python/test/db
python/test/hyp
python/test/model
python/test/ref
python/test/result.txt
python/test/wav.scp
# Java
*.so
java/org
java/model-en
java/*.cc
*.class
java/lib/model
java/demo/model
java/lib/build
java/demo/build
# CSharp
csharp/gen
csharp/*.exe
csharp/*.c
*.dll
*.so
*.dylib
*.nupkg
csharp/demo/model
csharp/demo/test.wav
csharp/demo/bin
csharp/demo/obj
# Node
nodejs/demo/model
nodejs/demo/model-spk
nodejs/demo/test.wav
nodejs/node_modules
nodejs/package-lock.json
# C
c/test_vosk
c/test_vosk_speaker
c/oprofile_data
c/model
c/test.wav
+1 -2
View File
@@ -7,11 +7,10 @@ matrix:
services:
- docker
env: DOCKER_IMAGE=alphacep/kaldi-manylinux:latest
PLAT=manylinux2010_x86_64
install:
- docker pull $DOCKER_IMAGE
script:
- docker run --rm -e PLAT=$PLAT -v `pwd`:/io $DOCKER_IMAGE $PRE_CMD /io/travis/build-wheels.sh
- docker run --rm -v `pwd`:/io $DOCKER_IMAGE $PRE_CMD /io/travis/build-wheels.sh
- ls wheelhouse/
+20
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@@ -0,0 +1,20 @@
cmake_minimum_required(VERSION 3.13)
project(vosk-api CXX)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_EXTENSIONS OFF)
add_library(vosk
src/language_model.cc
src/model.cc
src/recognizer.cc
src/spk_model.cc
src/vosk_api.cc
)
find_package(kaldi REQUIRED)
target_link_libraries(vosk PUBLIC kaldi-base kaldi-online2 kaldi-rnnlm fstngram)
include(GNUInstallDirs)
install(TARGETS vosk DESTINATION ${CMAKE_INSTALL_LIBDIR})
install(FILES src/vosk_api.h DESTINATION ${CMAKE_INSTALL_INCLUDEDIR})
+20 -135
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@@ -1,142 +1,27 @@
[![Build Status](https://travis-ci.com/alphacep/vosk-api.svg?branch=master)](https://travis-ci.com/alphacep/vosk-api)
# Vosk Speech Recognition Toolkit
[РУС](README.ru.md)
Vosk is an offline open source speech recognition toolkit. It enables
speech recognition for 20+ languages and dialects - English, Indian
English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish,
Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino,
Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish.
More to come.
[中文](README.zh.md)
Vosk models are small (50 Mb) but provide continuous large vocabulary
transcription, zero-latency response with streaming API, reconfigurable
vocabulary and speaker identification.
Vosk is a speech recognition toolkit. The best things in Vosk are:
Speech recognition bindings implemented for various programming languages
like Python, Java, Node.JS, C#, C++, Rust, Go and others.
1. Supports 9 languages - English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese. More to come.
1. Works offline, even on lightweight devices - Raspberry Pi, Android, iOS
1. Installs with simple `pip3 install vosk`
1. Portable per-language models are only 50Mb each, but there are much bigger server models available.
1. Provides streaming API for the best user experience (unlike popular speech-recognition python packages)
1. There are bindings for different programming languages, too - java/csharp/javascript etc.
1. Allows quick reconfiguration of vocabulary for best accuracy.
1. Supports speaker identification beside simple speech recognition.
Vosk supplies speech recognition for chatbots, smart home appliances,
virtual assistants. It can also create subtitles for movies,
transcription for lectures and interviews.
## Android build
Vosk scales from small devices like Raspberry Pi or Android smartphone to
big clusters.
```
cd android
gradle build
```
# Documentation
Please note that medium blog post about 64-bit is not relevant anymore, the script builds x86, arm64 and armv7 libraries automatically without any modifications.
For example of Android application using Vosk-API check https://github.com/alphacep/kaldi-android-demo project
## iOS build
Available on request. Drop as a mail at [contact@alphacephei.com](mailto:contact@alphacephei.com).
## Python installation from Pypi
The easiest way to install vosk api is with pip. You do not have to compile anything. We currently support only Linux on x86_64 and Raspberry Pi. Other systems (windows, mac) will come soon.
Make sure you have newer pip and python:
* Python version >= 3.4
* pip version >= 19.0
Uprade python and pip if needed. Then install vosk on Linux with a simple command
```
pip3 install vosk
```
## Websocket Server and GRPC server
We also provide a websocket server and grpc server which can be used in telephony and other applications. With bigger models adapted for 8khz audio it provides more accuracy.
The server is installed with docker and can run with a single command:
```
docker run -d -p 2700:2700 alphacep/kaldi-en:latest
```
For details see https://github.com/alphacep/vosk-server
## Compilation from source
If you still want to build from scratch, you can compile Kaldi and Vosk yourself. The compilation is straightforward but might be a little confusing for newbie. In case you want to follow this, please watch the errors.
#### Kaldi compilation for local python, node and java modules
```
git clone -b lookahead --single-branch https://github.com/alphacep/kaldi
cd kaldi/tools
make
```
install all dependencies and repeat `make` if needed
```
extras/install_openblas.sh
cd ../src
./configure --mathlib=OPENBLAS --shared --use-cuda=no
make -j 10
```
#### Python module build
Then build the python module
```
export KALDI_ROOT=<KALDI_ROOT>
cd python
python3 setup.py install
```
#### Running the example code with python
Run like this:
```
cd vosk-api/python/example
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model-en
python3 ./test_simple.py test.wav
```
To run with your audio file make sure it has proper format - PCM 16khz 16bit mono, otherwise decoding will not work.
You can find other examples of using a microphone, decoding with a fixed small vocabulary or speaker identification setup in [python/example subfolder](https://github.com/alphacep/vosk-api/tree/master/python/example)
#### Java example API build
Or Java
```
cd java && KALDI_ROOT=<KALDI_ROOT> make
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model
make run
```
#### C# build
Or C#
```
cd csharp && KALDI_ROOT=<KALDI_ROOT> make
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model
mono test.exe
```
## Models for different languages
For information about models see [the documentation on available models](https://github.com/alphacep/vosk-api/blob/master/doc/models.md).
## Contact Us
If you have any questions, feel free to
* Post an issue here on github
* Send us an e-mail at [contact@alphacephei.com](mailto:contact@alphacephei.com)
* Join our group dedicated to speech recognition on Telegram [@speech_recognition](https://t.me/speech_recognition)
For installation instructions, examples and documentation visit [Vosk
Website](https://alphacephei.com/vosk).
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[![Build Status](https://travis-ci.com/alphacep/vosk-api.svg?branch=master)](https://travis-ci.com/alphacep/vosk-api)
[EN](README.md)
[中文](README.zh.md)
Библитека для распознавания речи "Воск". Преимущества библиотеки:
1. Поддерживает 9 языков - русский, английский, немецкий, французский, португальский, испанский, китайский, турецкий, вьетнамский. В скором времени будут добавлены и другие
1. Работает без доступа к сети даже на мобильных устройствах - Raspberry Pi, Android, iOS
1. Устанавливается с помощью простой команды `pip3 install vosk` без дополнительных шагов
1. Модели для каждого языка занимают всего 50Мб, но есть и гораздо более точные большие модели для более точного распознавания
1. Сделана для потоковой обработки звука, что позволяет реализовать мгновенную реакцию на команды
1. Поддерживает несколько популярных языков программирования - Java, C#, Javascript
1. Позволяет быстро настраивать словарь распознавания для улучшения точности распознавания
1. Позволяет идентифицировать говорящего
## Сборка для Android
```
cd android
gradle build
```
Сборка включает платформы x86, armv7, arm64
Для примера приложения, созданного с помощью библиотеки "Воск" смотрите [демо проект](https://github.com/alphacep/kaldi-android-demo).
## Сборка для iOS
Доступна позапросу. Напишите нам [contact@alphacephei.com](mailto:contact@alphacephei.com).
## Установка для работы Python из Pypi
Проще всего установить "Воск" с помощью pip. Собирать ничего не нужно. Мы поддерживаем платформы Linux, RPi и Windows. Сборка для OSX будет скоро доступна.
Для начала убедитесь, что используются достаточно новые версии pip и Python:
* Python версия >= 3.5
* pip версия >= 19.0
Обновите Python и Pip если нужно, а затем установите "Воск" такой командой:
```
pip3 install vosk
```
Для использования "Воск" смотрите примеры ниже.
## Сервер для протоколов Websocket и GRPC
We also provide a websocket server and grpc server which can be used in telephony and other applications. With bigger models adapted for 8khz audio it provides more accuracy.
The server is installed with docker and can run with a single command:
```
docker run -d -p 2700:2700 alphacep/kaldi-en:latest
```
Смотрите проект https://github.com/alphacep/vosk-server
## Сборка из исходников
Если нужно собрать проект из исходного кода, необходимо будет собрать
Kaldi самостоятельно. Сборка досаточно простая и прямолинейная, но может
быть непривычной для начинающих. Обращайте внимания на сообщения об ошибках
в процессе сборки.
#### Сборка Kaldi для модулей на Python, Java, C#
```
git clone https://github.com/kaldi-asr/kaldi
cd kaldi/tools
make
```
установите все рекомандуемые пакеты и повторите `make` если потребуется.
```
extras/install_openblas.sh
cd ../src
./configure --mathlib=OPENBLAS --shared --use-cuda=no
make -j 10
```
#### Сборка модуля на Python
После Kaldi можно собрать модуль Python
```
export KALDI_ROOT=<KALDI_ROOT>
cd python
python3 setup.py install
```
#### Запуск примера для Python
Выполните следующие команды:
```
cd vosk-api/python/example
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model-en
python3 ./test_simple.py test.wav
```
Для того, чтобы распознавать другой файл, переведите его в нужный формат - PCM 16кГц 16бит 1канал. Это можно сделать с помощью ffmpeg.
Другие примеры, в том числе использования микрофона, распознавание с небольшим словарём и распознавание говорящего можно найти в [каталоге python/example](https://github.com/alphacep/vosk-api/tree/master/python/example)
#### Сборка для Java
Перейдите в каталог Java и запустите сборку
```
cd java && KALDI_ROOT=<KALDI_ROOT> make
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model
make run
```
#### Сборка для C#
Для сборки в среде Mono.
```
cd csharp && KALDI_ROOT=<KALDI_ROOT> make
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model
mono test.exe
```
.NET тоже должен работать, хотя мы не пробовали.
## Модели для разных языков
По информации о моделях смотрите соответствующую [страницу документации](https://github.com/alphacep/vosk-api/blob/master/doc/models.md).
## Contact Us
Если возникли вопросы, свяжитесь с нами:
* Создайте проблему тут на github
* Напишите нам по почте [contact@alphacephei.com](mailto:contact@alphacephei.com)
* Заходите в нашу группу в Телеграмме [@speech_recognition_ru](https://t.me/speech_recognition_ru)
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[![Build Status](https://travis-ci.com/alphacep/vosk-api.svg?branch=master)](https://travis-ci.com/alphacep/vosk-api)
Vosk是言语识别工具包。Vosk最好的事情是:
1. 支持九种语言 - 中文, 英语,德语,法语,西班牙语,葡萄牙语,俄语,土耳其语,越南语
1. 移动设备上脱机工作-Raspberry PiAndroidiOS
1. 使用简单的 pip3 install vosk 安装
1. 每种语言的手提式模型只有是50Mb, 但还有更大的服务器模型可用
1. 提供流媒体API,以提供最佳用户体验(与流行的语音识别python包不同)
1. 还有用于不同编程语言的包装器-java / csharp / javascript等
1. 可以快速重新配置词汇以实现最佳准确性
1. 支持说话人识别
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# Vosk CMake File
cmake_minimum_required(VERSION 3.4.1)
if ("x${ANDROID_ABI}" STREQUAL "xarmeabi-v7a")
set(OPENBLAS_ARCH "armv7")
set(KALDI_SUFFIX "arm_32")
elseif ("x${ANDROID_ABI}" STREQUAL "xarm64-v8a")
set(OPENBLAS_ARCH "armv8")
set(KALDI_SUFFIX "arm_64")
else ("x${ANDROID_ABI}" STREQUAL "xarmeabi-v7a")
set(OPENBLAS_ARCH "atom")
set(KALDI_SUFFIX "x86_64")
endif ("x${ANDROID_ABI}" STREQUAL "xarmeabi-v7a")
set(KALDI_ROOT "${PROJECT_SOURCE_DIR}/build/kaldi_${KALDI_SUFFIX}/kaldi")
set(LIB_ROOT "${PROJECT_SOURCE_DIR}/build/kaldi_${KALDI_SUFFIX}/local")
set(API_SOURCES
"${PROJECT_SOURCE_DIR}/../src/kaldi_recognizer.cc"
"${PROJECT_SOURCE_DIR}/../src/kaldi_recognizer.h"
"${PROJECT_SOURCE_DIR}/../src/model.cc"
"${PROJECT_SOURCE_DIR}/../src/model.h"
"${PROJECT_SOURCE_DIR}/../src/spk_model.cc"
"${PROJECT_SOURCE_DIR}/../src/spk_model.h"
"${PROJECT_SOURCE_DIR}/../src/vosk_api.cc"
"${PROJECT_SOURCE_DIR}/../src/vosk_api.h"
)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3 -DFST_NO_DYNAMIC_LINKING")
add_library( kaldi_jni SHARED
build/generated-src/cpp/vosk_wrap.cc
${API_SOURCES}
)
include_directories("${PROJECT_SOURCE_DIR}/../src" "build/kaldi_${KALDI_SUFFIX}/kaldi/src" "build/kaldi_${KALDI_SUFFIX}/local/include")
target_link_libraries( kaldi_jni
${KALDI_ROOT}/src/online2/kaldi-online2.a
${KALDI_ROOT}/src/decoder/kaldi-decoder.a
${KALDI_ROOT}/src/ivector/kaldi-ivector.a
${KALDI_ROOT}/src/gmm/kaldi-gmm.a
${KALDI_ROOT}/src/nnet3/kaldi-nnet3.a
${KALDI_ROOT}/src/tree/kaldi-tree.a
${KALDI_ROOT}/src/feat/kaldi-feat.a
${KALDI_ROOT}/src/lat/kaldi-lat.a
${KALDI_ROOT}/src/hmm/kaldi-hmm.a
${KALDI_ROOT}/src/transform/kaldi-transform.a
${KALDI_ROOT}/src/cudamatrix/kaldi-cudamatrix.a
${KALDI_ROOT}/src/matrix/kaldi-matrix.a
${KALDI_ROOT}/src/fstext/kaldi-fstext.a
${KALDI_ROOT}/src/util/kaldi-util.a
${KALDI_ROOT}/src/base/kaldi-base.a
${LIB_ROOT}/lib/libfst.a
${LIB_ROOT}/lib/libfstngram.a
${LIB_ROOT}/lib/libopenblas_${OPENBLAS_ARCH}-r0.3.7.a
${LIB_ROOT}/lib/libclapack.a
${LIB_ROOT}/lib/liblapack.a
${LIB_ROOT}/lib/libblas.a
${LIB_ROOT}/lib/libf2c.a
log
)
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This is still work in progress, more to come
Vosk library for Android
## TODO
* Optimize graph construction, current one is below accuracy
* Load model from the AAR (mmap them in tflite style)
* Add decoding speed measurement
* Add wakeup word
* Add speakerid
* Integrate proper hardware optimized neural network library. Candidates are:
* https://github.com/XiaoMi/mace
* https://github.com/Tencent/ncnn
* https://developer.android.com/ndk/guides/neuralnetworks/ (since API level 27)
* https://github.com/google/XNNPACK
* Quantization for the models
See for details https://alphacephei.com/vosk/android
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#!/bin/bash
# Copyright 2019 Alpha Cephei Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
if [ "x$ANDROID_SDK_HOME" == "x" ]; then
echo "ANDROID_SDK_HOME environment variable is undefined, define it with local.properties or with export"
exit 1
fi
if [ ! -d "$ANDROID_SDK_HOME" ]; then
echo "ANDROID_SDK_HOME ($ANDROID_SDK_HOME) is missing. Make sure you have sdk installed"
exit 1
fi
if [ ! -d "$ANDROID_SDK_HOME/ndk-bundle" ]; then
echo "$ANDROID_SDK_HOME/ndk-bundle is missing. Make sure you have ndk installed within sdk"
exit 1
fi
set -x
ANDROID_NDK_HOME=$ANDROID_SDK_HOME/ndk-bundle
ANDROID_TOOLCHAIN_PATH=$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/linux-x86_64
WORKDIR_X86_64=`pwd`/build/kaldi_x86_64
WORKDIR_ARM32=`pwd`/build/kaldi_arm_32
WORKDIR_ARM64=`pwd`/build/kaldi_arm_64
PATH=$PATH:$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/linux-x86_64/bin
OPENFST_VERSION=1.6.7
mkdir -p $WORKDIR_ARM64/local/lib $WORKDIR_ARM32/local/lib $WORKDIR_X86_64/local/lib
# Build standalone CLAPACK since gfortran is missing
cd build
git clone https://github.com/simonlynen/android_libs
cd android_libs/lapack
sed -i 's/APP_STL := gnustl_static/APP_STL := c++_static/g' jni/Application.mk && \
sed -i 's/android-10/android-21/g' project.properties && \
sed -i 's/APP_ABI := armeabi armeabi-v7a/APP_ABI := armeabi-v7a arm64-v8a x86_64/g' jni/Application.mk && \
sed -i 's/LOCAL_MODULE:= testlapack/#LOCAL_MODULE:= testlapack/g' jni/Android.mk && \
sed -i 's/LOCAL_SRC_FILES:= testclapack.cpp/#LOCAL_SRC_FILES:= testclapack.cpp/g' jni/Android.mk && \
sed -i 's/LOCAL_STATIC_LIBRARIES := lapack/#LOCAL_STATIC_LIBRARIES := lapack/g' jni/Android.mk && \
sed -i 's/include $(BUILD_SHARED_LIBRARY)/#include $(BUILD_SHARED_LIBRARY)/g' jni/Android.mk && \
${ANDROID_NDK_HOME}/ndk-build && \
cp obj/local/armeabi-v7a/*.a ${WORKDIR_ARM32}/local/lib && \
cp obj/local/arm64-v8a/*.a ${WORKDIR_ARM64}/local/lib
cp obj/local/x86_64/*.a ${WORKDIR_X86_64}/local/lib
# Architecture-specific part
for arch in arm32 arm64 x86_64; do
#for arch in x86_64; do
case $arch in
arm32)
BLAS_ARCH=ARMV7
WORKDIR=$WORKDIR_ARM32
HOST=arm-linux-androideabi
AR=arm-linux-androideabi-ar
CC=armv7a-linux-androideabi21-clang
CXX=armv7a-linux-androideabi21-clang++
ARCHFLAGS="-mfloat-abi=softfp -mfpu=neon"
;;
arm64)
BLAS_ARCH=ARMV8
WORKDIR=$WORKDIR_ARM64
HOST=aarch64-linux-android
AR=aarch64-linux-android-ar
CC=aarch64-linux-android21-clang
CXX=aarch64-linux-android21-clang++
ARCHFLAGS=""
;;
x86_64)
BLAS_ARCH=ATOM
WORKDIR=$WORKDIR_X86_64
HOST=x86_64-linux-android
AR=x86_64-linux-android-ar
CC=x86_64-linux-android21-clang
CXX=x86_64-linux-android21-clang++
ARCHFLAGS=""
;;
esac
# openblas first
cd $WORKDIR
git clone -b v0.3.7 --single-branch https://github.com/xianyi/OpenBLAS
make -C OpenBLAS TARGET=$BLAS_ARCH ONLY_CBLAS=1 AR=$AR CC=$CC HOSTCC=gcc ARM_SOFTFP_ABI=1 USE_THREAD=0 NUM_THREADS=1 -j4
make -C OpenBLAS install PREFIX=$WORKDIR/local
# tools directory --> we'll only compile OpenFST
cd $WORKDIR
wget -c -T 10 -t 1 http://www.openfst.org/twiki/pub/FST/FstDownload/openfst-${OPENFST_VERSION}.tar.gz || \
wget -c -T 10 -t 3 http://www.openslr.org/resources/2/openfst-${OPENFST_VERSION}.tar.gz
tar -zxvf openfst-${OPENFST_VERSION}.tar.gz
cd openfst-${OPENFST_VERSION}
CXX=$CXX CXXFLAGS="$ARCHFLAGS -O3 -DFST_NO_DYNAMIC_LINKING" ./configure --prefix=${WORKDIR}/local \
--enable-shared --enable-static --with-pic --disable-bin \
--enable-lookahead-fsts --enable-ngram-fsts --host=$HOST --build=x86-linux-gnu
make -j 8
make install
# Kaldi itself
cd $WORKDIR
git clone -b android-mix --single-branch https://github.com/alphacep/kaldi
cd $WORKDIR/kaldi/src
CXX=$CXX CXXFLAGS="$ARCHFLAGS -O3 -DFST_NO_DYNAMIC_LINKING" ./configure --use-cuda=no \
--mathlib=OPENBLAS --shared \
--android-incdir=${ANDROID_TOOLCHAIN_PATH}/sysroot/usr/include \
--host=$HOST --openblas-root=${WORKDIR}/local \
--fst-root=${WORKDIR}/local --fst-version=${OPENFST_VERSION}
make -j 8 depend
make -j 8 online2 lm
done
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@@ -1,68 +1,65 @@
buildscript {
repositories {
google()
jcenter()
mavenCentral()
}
dependencies {
classpath 'com.android.tools.build:gradle:3.5.3'
classpath 'com.android.tools.build:gradle:4.2.0'
classpath 'com.vanniktech:gradle-maven-publish-plugin:0.18.0'
}
}
allprojects {
repositories {
google()
jcenter()
}
version = '0.3.42'
}
apply plugin: 'com.android.library'
subprojects {
android {
compileSdkVersion 29
defaultConfig {
minSdkVersion 21
targetSdkVersion 29
versionCode 5
versionName "5.2"
setProperty("archivesBaseName", "kaldi-android-$versionName")
externalNativeBuild {
cmake {
arguments "-DCMAKE_VERBOSE_MAKEFILE=ON", "-DANDROID_ARM_NEON=TRUE", "-DCMAKE_CXX_FLAGS_RELEASE=-O3"
apply plugin: 'com.android.library'
apply plugin: 'maven-publish'
apply plugin: 'com.vanniktech.maven.publish'
plugins.withId('com.vanniktech.maven.publish') {
mavenPublish {
group = 'com.alphacephei'
version = version
sonatypeHost = 's01'
androidVariantToPublish = 'release'
}
}
repositories {
google()
mavenCentral()
}
publishing {
publications {
aar(MavenPublication) {
groupId 'com.alphacephei'
version version
pom {
url = 'http://www.alphacephei.com.com/vosk/'
licenses {
license {
name = 'The Apache License, Version 2.0'
url = 'http://www.apache.org/licenses/LICENSE-2.0.txt'
}
}
developers {
developer {
id = 'com.alphacephei'
name = 'Alpha Cephei Inc'
email = 'contact@alphacephei.com'
}
}
scm {
connection = 'scm:git:git://github.com/alphacep/vosk-api.git'
url = 'https://github.com/alphacep/vosk-api/'
}
}
}
}
ndk {
abiFilters 'armeabi-v7a', 'arm64-v8a', 'x86_64'
}
}
sourceSets {
main {
java.srcDirs = ['src/main/java', 'build/generated-src']
}
}
externalNativeBuild {
cmake {
path "CMakeLists.txt"
}
}
}
task swig {
doLast {
mkdir 'build/generated-src/java'
mkdir 'build/generated-src/cpp'
exec {
commandLine 'swig',
"-c++",
"-java", "-package", "org.kaldi",
"-outdir", "build/generated-src/java", "-o", "build/generated-src/cpp/vosk_wrap.cc",
"../src/vosk.i"
}
}
}
task kaldi(type: Exec) {
commandLine './build-kaldi.sh'
environment ANDROID_SDK_HOME: android.getSdkDirectory()
}
preBuild.dependsOn kaldi, swig
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#!/bin/bash
# Copyright 2019-2021 Alpha Cephei Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
if [ "x$ANDROID_NDK_HOME" == "x" ]; then
echo "ANDROID_NDK_HOME environment variable is undefined, define it with local.properties or with export"
exit 1
fi
if [ ! -d "$ANDROID_NDK_HOME" ]; then
echo "ANDROID_NDK_HOME ($ANDROID_NDK_HOME) is missing. Make sure you have ndk installed"
exit 1
fi
set -x
OS_NAME=`echo $(uname -s) | tr '[:upper:]' '[:lower:]'`
ANDROID_TOOLCHAIN_PATH=$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/${OS_NAME}-x86_64
WORKDIR_BASE=`pwd`/build
PATH=$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/${OS_NAME}-x86_64/bin:$PATH
OPENFST_VERSION=1.8.0
for arch in armeabi-v7a arm64-v8a x86_64 x86; do
WORKDIR=${WORKDIR_BASE}/kaldi_${arch}
case $arch in
armeabi-v7a)
BLAS_ARCH=ARMV7
HOST=arm-linux-androideabi
AR=llvm-ar
RANLIB=llvm-ranlib
CC=armv7a-linux-androideabi21-clang
CXX=armv7a-linux-androideabi21-clang++
ARCHFLAGS="-mfloat-abi=softfp -mfpu=neon"
;;
arm64-v8a)
BLAS_ARCH=ARMV8
HOST=aarch64-linux-android
AR=llvm-ar
RANLIB=llvm-ranlib
CC=aarch64-linux-android21-clang
CXX=aarch64-linux-android21-clang++
ARCHFLAGS=""
;;
x86_64)
BLAS_ARCH=ATOM
HOST=x86_64-linux-android
AR=llvm-ar
RANLIB=llvm-ranlib
CC=x86_64-linux-android21-clang
CXX=x86_64-linux-android21-clang++
ARCHFLAGS=""
;;
x86)
BLAS_ARCH=ATOM
HOST=i686-linux-android
AR=llvm-ar
RANLIB=llvm-ranlib
CC=i686-linux-android21-clang
CXX=i686-linux-android21-clang++
ARCHFLAGS=""
;;
esac
mkdir -p $WORKDIR/local/lib
# openblas first
cd $WORKDIR
git clone -b v0.3.13 --single-branch https://github.com/xianyi/OpenBLAS
make -C OpenBLAS TARGET=$BLAS_ARCH ONLY_CBLAS=1 AR=$AR CC=$CC HOSTCC=gcc ARM_SOFTFP_ABI=1 USE_THREAD=0 NUM_THREADS=1 -j4
make -C OpenBLAS install PREFIX=$WORKDIR/local
# CLAPACK
cd $WORKDIR
git clone -b v3.2.1 --single-branch https://github.com/alphacep/clapack
mkdir -p clapack/BUILD && cd clapack/BUILD
cmake -DCMAKE_C_FLAGS=$ARCHFLAGS -DCMAKE_C_COMPILER_TARGET=$HOST \
-DCMAKE_C_COMPILER=$CC -DCMAKE_SYSTEM_NAME=Generic -DCMAKE_AR=$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/${OS_NAME}-x86_64/bin/$AR \
-DCMAKE_TRY_COMPILE_TARGET_TYPE=STATIC_LIBRARY \
-DCMAKE_CROSSCOMPILING=True ..
make -j 8 -C F2CLIBS/libf2c
make -j 8 -C BLAS/SRC
make -j 8 -C SRC
find . -name "*.a" | xargs cp -t $WORKDIR/local/lib
# tools directory --> we'll only compile OpenFST
cd $WORKDIR
git clone https://github.com/alphacep/openfst
cd openfst
autoreconf -i
CXX=$CXX CXXFLAGS="$ARCHFLAGS -O3 -DFST_NO_DYNAMIC_LINKING" ./configure --prefix=${WORKDIR}/local \
--enable-shared --enable-static --with-pic --disable-bin \
--enable-lookahead-fsts --enable-ngram-fsts --host=$HOST --build=x86-linux-gnu
make -j 8
make install
# Kaldi itself
cd $WORKDIR
git clone -b vosk-android --single-branch https://github.com/alphacep/kaldi
cd $WORKDIR/kaldi/src
CXX=$CXX AR=$AR RANLIB=$RANLIB CXXFLAGS="$ARCHFLAGS -O3 -DFST_NO_DYNAMIC_LINKING" ./configure --use-cuda=no \
--mathlib=OPENBLAS_CLAPACK --shared \
--android-incdir=${ANDROID_TOOLCHAIN_PATH}/sysroot/usr/include \
--host=$HOST --openblas-root=${WORKDIR}/local \
--fst-root=${WORKDIR}/local --fst-version=${OPENFST_VERSION}
make -j 8 depend
cd $WORKDIR/kaldi/src
make -j 8 online2 lm rnnlm
# Vosk-api
cd $WORKDIR
mkdir -p $WORKDIR/vosk
make -j 8 -C ${WORKDIR_BASE}/../../../src \
OUTDIR=$WORKDIR/vosk \
KALDI_ROOT=${WORKDIR}/kaldi \
OPENFST_ROOT=${WORKDIR}/local \
OPENBLAS_ROOT=${WORKDIR}/local \
CXX=$CXX \
EXTRA_LDFLAGS="-llog -static-libstdc++ -Wl,-soname,libvosk.so"
cp $WORKDIR/vosk/libvosk.so $WORKDIR/../../src/main/jniLibs/$arch/libvosk.so
done
+55
View File
@@ -0,0 +1,55 @@
def archiveName = "vosk-android"
def pomName = "Vosk Android"
def pomDescription = "Vosk speech recognition library for Android"
android {
compileSdkVersion 29
defaultConfig {
minSdkVersion 21
targetSdkVersion 29
versionCode 6
versionName = version
archivesBaseName = archiveName
ndkVersion = "22.1.7171670"
}
compileOptions {
sourceCompatibility JavaVersion.VERSION_1_8
targetCompatibility JavaVersion.VERSION_1_8
}
}
task buildVosk(type: Exec) {
commandLine './build-vosk.sh'
environment ANDROID_NDK_HOME: android.getNdkDirectory()
}
dependencies {
api 'net.java.dev.jna:jna:4.4.0@aar'
}
//preBuild.dependsOn buildVosk
publishing {
publications {
aar(MavenPublication) {
artifactId = archiveName
artifact("$buildDir/outputs/aar/$archiveName-release.aar")
pom {
name = pomName
description = pomDescription
}
//generate pom nodes for dependencies
pom.withXml {
def dependenciesNode = asNode().appendNode('dependencies')
configurations.implementation.allDependencies.each { dependency ->
if (dependency.name != 'unspecified') {
def dependencyNode = dependenciesNode.appendNode('dependency')
dependencyNode.appendNode('groupId', dependency.group)
dependencyNode.appendNode('artifactId', dependency.name)
dependencyNode.appendNode('version', dependency.version)
}
}
}
}
}
}
@@ -1,3 +1,3 @@
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android" package="org.kaldi">
<manifest xmlns:android="http://schemas.android.com/apk/res/android" package="org.vosk">
</manifest>
@@ -0,0 +1,62 @@
package org.vosk;
import com.sun.jna.Native;
import com.sun.jna.Library;
import com.sun.jna.Platform;
import com.sun.jna.Pointer;
import java.io.File;
import java.io.InputStream;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.StandardCopyOption;
public class LibVosk {
static {
Native.register(LibVosk.class, "vosk");
}
public static native void vosk_set_log_level(int level);
public static native Pointer vosk_model_new(String path);
public static native void vosk_model_free(Pointer model);
public static native Pointer vosk_spk_model_new(String path);
public static native void vosk_spk_model_free(Pointer model);
public static native Pointer vosk_recognizer_new(Model model, float sample_rate);
public static native Pointer vosk_recognizer_new_spk(Pointer model, float sample_rate, Pointer spk_model);
public static native Pointer vosk_recognizer_new_grm(Pointer model, float sample_rate, String grammar);
public static native void vosk_recognizer_set_max_alternatives(Pointer recognizer, int max_alternatives);
public static native void vosk_recognizer_set_words(Pointer recognizer, boolean words);
public static native void vosk_recognizer_set_partial_words(Pointer recognizer, boolean partial_words);
public static native void vosk_recognizer_set_spk_model(Pointer recognizer, Pointer spk_model);
public static native boolean vosk_recognizer_accept_waveform(Pointer recognizer, byte[] data, int len);
public static native boolean vosk_recognizer_accept_waveform_s(Pointer recognizer, short[] data, int len);
public static native boolean vosk_recognizer_accept_waveform_f(Pointer recognizer, float[] data, int len);
public static native String vosk_recognizer_result(Pointer recognizer);
public static native String vosk_recognizer_final_result(Pointer recognizer);
public static native String vosk_recognizer_partial_result(Pointer recognizer);
public static native void vosk_recognizer_reset(Pointer recognizer);
public static native void vosk_recognizer_free(Pointer recognizer);
public static void setLogLevel(LogLevel loglevel) {
vosk_set_log_level(loglevel.getValue());
}
}
@@ -0,0 +1,17 @@
package org.vosk;
public enum LogLevel {
WARNINGS(-1), // Print warning and errors
INFO(0), // Print info, along with warning and error messages, but no debug
DEBUG(1); // Print debug info
private final int value;
LogLevel(int value) {
this.value = value;
}
public int getValue() {
return this.value;
}
}
@@ -0,0 +1,17 @@
package org.vosk;
import com.sun.jna.PointerType;
public class Model extends PointerType implements AutoCloseable {
public Model() {
}
public Model(String path) {
super(LibVosk.vosk_model_new(path));
}
@Override
public void close() {
LibVosk.vosk_model_free(this.getPointer());
}
}
@@ -0,0 +1,66 @@
package org.vosk;
import com.sun.jna.PointerType;
public class Recognizer extends PointerType implements AutoCloseable {
public Recognizer(Model model, float sampleRate) {
super(LibVosk.vosk_recognizer_new(model, sampleRate));
}
public Recognizer(Model model, float sampleRate, SpeakerModel spkModel) {
super(LibVosk.vosk_recognizer_new_spk(model.getPointer(), sampleRate, spkModel.getPointer()));
}
public Recognizer(Model model, float sampleRate, String grammar) {
super(LibVosk.vosk_recognizer_new_grm(model.getPointer(), sampleRate, grammar));
}
public void setMaxAlternatives(int maxAlternatives) {
LibVosk.vosk_recognizer_set_max_alternatives(this.getPointer(), maxAlternatives);
}
public void setWords(boolean words) {
LibVosk.vosk_recognizer_set_words(this.getPointer(), words);
}
public void setPartialWords(boolean partial_words) {
LibVosk.vosk_recognizer_set_partial_words(this.getPointer(), partial_words);
}
public void setSpeakerModel(SpeakerModel spkModel) {
LibVosk.vosk_recognizer_set_spk_model(this.getPointer(), spkModel.getPointer());
}
public boolean acceptWaveForm(byte[] data, int len) {
return LibVosk.vosk_recognizer_accept_waveform(this.getPointer(), data, len);
}
public boolean acceptWaveForm(short[] data, int len) {
return LibVosk.vosk_recognizer_accept_waveform_s(this.getPointer(), data, len);
}
public boolean acceptWaveForm(float[] data, int len) {
return LibVosk.vosk_recognizer_accept_waveform_f(this.getPointer(), data, len);
}
public String getResult() {
return LibVosk.vosk_recognizer_result(this.getPointer());
}
public String getPartialResult() {
return LibVosk.vosk_recognizer_partial_result(this.getPointer());
}
public String getFinalResult() {
return LibVosk.vosk_recognizer_final_result(this.getPointer());
}
public void reset() {
LibVosk.vosk_recognizer_reset(this.getPointer());
}
@Override
public void close() {
LibVosk.vosk_recognizer_free(this.getPointer());
}
}
@@ -0,0 +1,17 @@
package org.vosk;
import com.sun.jna.PointerType;
public class SpeakerModel extends PointerType implements AutoCloseable {
public SpeakerModel() {
}
public SpeakerModel(String path) {
super(LibVosk.vosk_spk_model_new(path));
}
@Override
public void close() {
LibVosk.vosk_spk_model_free(this.getPointer());
}
}
@@ -12,28 +12,35 @@
// See the License for the specific language governing permissions and
// limitations under the License.
package org.kaldi;
package org.vosk.android;
/** Interface to receive recognition results */
/**
* Interface to receive recognition results
*/
public interface RecognitionListener {
/**
* Called when partial recognition result is available.
*/
public void onPartialResult(String hypothesis);
void onPartialResult(String hypothesis);
/**
* Called after the recognition is ended.
* Called after silence occured.
*/
public void onResult(String hypothesis);
void onResult(String hypothesis);
/**
* Called after stream end.
*/
void onFinalResult(String hypothesis);
/**
* Called when an error occurs.
*/
public void onError(Exception exception);
void onError(Exception exception);
/**
* Called after timeout expired
*/
public void onTimeout();
void onTimeout();
}
@@ -0,0 +1,257 @@
// Copyright 2019 Alpha Cephei Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package org.vosk.android;
import android.media.AudioFormat;
import android.media.AudioRecord;
import android.media.MediaRecorder.AudioSource;
import android.os.Handler;
import android.os.Looper;
import org.vosk.Recognizer;
import java.io.IOException;
/**
* Service that records audio in a thread, passes it to a recognizer and emits
* recognition results. Recognition events are passed to a client using
* {@link RecognitionListener}
*/
public class SpeechService {
private final Recognizer recognizer;
private final int sampleRate;
private final static float BUFFER_SIZE_SECONDS = 0.2f;
private final int bufferSize;
private final AudioRecord recorder;
private RecognizerThread recognizerThread;
private final Handler mainHandler = new Handler(Looper.getMainLooper());
/**
* Creates speech service. Service holds the AudioRecord object, so you
* need to call {@link #shutdown()} in order to properly finalize it.
*
* @throws IOException thrown if audio recorder can not be created for some reason.
*/
public SpeechService(Recognizer recognizer, float sampleRate) throws IOException {
this.recognizer = recognizer;
this.sampleRate = (int) sampleRate;
bufferSize = Math.round(this.sampleRate * BUFFER_SIZE_SECONDS);
recorder = new AudioRecord(
AudioSource.VOICE_RECOGNITION, this.sampleRate,
AudioFormat.CHANNEL_IN_MONO,
AudioFormat.ENCODING_PCM_16BIT, bufferSize * 2);
if (recorder.getState() == AudioRecord.STATE_UNINITIALIZED) {
recorder.release();
throw new IOException(
"Failed to initialize recorder. Microphone might be already in use.");
}
}
/**
* Starts recognition. Does nothing if recognition is active.
*
* @return true if recognition was actually started
*/
public boolean startListening(RecognitionListener listener) {
if (null != recognizerThread)
return false;
recognizerThread = new RecognizerThread(listener);
recognizerThread.start();
return true;
}
/**
* Starts recognition. After specified timeout listening stops and the
* endOfSpeech signals about that. Does nothing if recognition is active.
* <p>
* timeout - timeout in milliseconds to listen.
*
* @return true if recognition was actually started
*/
public boolean startListening(RecognitionListener listener, int timeout) {
if (null != recognizerThread)
return false;
recognizerThread = new RecognizerThread(listener, timeout);
recognizerThread.start();
return true;
}
private boolean stopRecognizerThread() {
if (null == recognizerThread)
return false;
try {
recognizerThread.interrupt();
recognizerThread.join();
} catch (InterruptedException e) {
// Restore the interrupted status.
Thread.currentThread().interrupt();
}
recognizerThread = null;
return true;
}
/**
* Stops recognition. Listener should receive final result if there is
* any. Does nothing if recognition is not active.
*
* @return true if recognition was actually stopped
*/
public boolean stop() {
return stopRecognizerThread();
}
/**
* Cancel recognition. Do not post any new events, simply cancel processing.
* Does nothing if recognition is not active.
*
* @return true if recognition was actually stopped
*/
public boolean cancel() {
if (recognizerThread != null) {
recognizerThread.setPause(true);
}
return stopRecognizerThread();
}
/**
* Shutdown the recognizer and release the recorder
*/
public void shutdown() {
recorder.release();
}
public void setPause(boolean paused) {
if (recognizerThread != null) {
recognizerThread.setPause(paused);
}
}
/**
* Resets recognizer in a thread, starts recognition over again
*/
public void reset() {
if (recognizerThread != null) {
recognizerThread.reset();
}
}
private final class RecognizerThread extends Thread {
private int remainingSamples;
private final int timeoutSamples;
private final static int NO_TIMEOUT = -1;
private volatile boolean paused = false;
private volatile boolean reset = false;
RecognitionListener listener;
public RecognizerThread(RecognitionListener listener, int timeout) {
this.listener = listener;
if (timeout != NO_TIMEOUT)
this.timeoutSamples = timeout * sampleRate / 1000;
else
this.timeoutSamples = NO_TIMEOUT;
this.remainingSamples = this.timeoutSamples;
}
public RecognizerThread(RecognitionListener listener) {
this(listener, NO_TIMEOUT);
}
/**
* When we are paused, don't process audio by the recognizer and don't emit
* any listener results
*
* @param paused the status of pause
*/
public void setPause(boolean paused) {
this.paused = paused;
}
/**
* Set reset state to signal reset of the recognizer and start over
*/
public void reset() {
this.reset = true;
}
@Override
public void run() {
recorder.startRecording();
if (recorder.getRecordingState() == AudioRecord.RECORDSTATE_STOPPED) {
recorder.stop();
IOException ioe = new IOException(
"Failed to start recording. Microphone might be already in use.");
mainHandler.post(() -> listener.onError(ioe));
}
short[] buffer = new short[bufferSize];
while (!interrupted()
&& ((timeoutSamples == NO_TIMEOUT) || (remainingSamples > 0))) {
int nread = recorder.read(buffer, 0, buffer.length);
if (paused) {
continue;
}
if (reset) {
recognizer.reset();
reset = false;
}
if (nread < 0)
throw new RuntimeException("error reading audio buffer");
if (recognizer.acceptWaveForm(buffer, nread)) {
final String result = recognizer.getResult();
mainHandler.post(() -> listener.onResult(result));
} else {
final String partialResult = recognizer.getPartialResult();
mainHandler.post(() -> listener.onPartialResult(partialResult));
}
if (timeoutSamples != NO_TIMEOUT) {
remainingSamples = remainingSamples - nread;
}
}
recorder.stop();
if (!paused) {
// If we met timeout signal that speech ended
if (timeoutSamples != NO_TIMEOUT && remainingSamples <= 0) {
mainHandler.post(() -> listener.onTimeout());
} else {
final String finalResult = recognizer.getFinalResult();
mainHandler.post(() -> listener.onFinalResult(finalResult));
}
}
}
}
}
@@ -0,0 +1,165 @@
// Copyright 2019 Alpha Cephei Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package org.vosk.android;
import android.os.Handler;
import android.os.Looper;
import org.vosk.Recognizer;
import java.io.IOException;
import java.io.InputStream;
/**
* Service that recognizes stream audio in a thread, passes it to a recognizer and emits
* recognition results. Recognition events are passed to a client using
* {@link RecognitionListener}
*/
public class SpeechStreamService {
private final Recognizer recognizer;
private final InputStream inputStream;
private final int sampleRate;
private final static float BUFFER_SIZE_SECONDS = 0.2f;
private final int bufferSize;
private Thread recognizerThread;
private final Handler mainHandler = new Handler(Looper.getMainLooper());
/**
* Creates speech service.
**/
public SpeechStreamService(Recognizer recognizer, InputStream inputStream, float sampleRate) {
this.recognizer = recognizer;
this.sampleRate = (int) sampleRate;
this.inputStream = inputStream;
bufferSize = Math.round(this.sampleRate * BUFFER_SIZE_SECONDS * 2);
}
/**
* Starts recognition. Does nothing if recognition is active.
*
* @return true if recognition was actually started
*/
public boolean start(RecognitionListener listener) {
if (null != recognizerThread)
return false;
recognizerThread = new RecognizerThread(listener);
recognizerThread.start();
return true;
}
/**
* Starts recognition. After specified timeout listening stops and the
* endOfSpeech signals about that. Does nothing if recognition is active.
* <p>
* timeout - timeout in milliseconds to listen.
*
* @return true if recognition was actually started
*/
public boolean start(RecognitionListener listener, int timeout) {
if (null != recognizerThread)
return false;
recognizerThread = new RecognizerThread(listener, timeout);
recognizerThread.start();
return true;
}
/**
* Stops recognition. All listeners should receive final result if there is
* any. Does nothing if recognition is not active.
*
* @return true if recognition was actually stopped
*/
public boolean stop() {
if (null == recognizerThread)
return false;
try {
recognizerThread.interrupt();
recognizerThread.join();
} catch (InterruptedException e) {
// Restore the interrupted status.
Thread.currentThread().interrupt();
}
recognizerThread = null;
return true;
}
private final class RecognizerThread extends Thread {
private int remainingSamples;
private final int timeoutSamples;
private final static int NO_TIMEOUT = -1;
RecognitionListener listener;
public RecognizerThread(RecognitionListener listener, int timeout) {
this.listener = listener;
if (timeout != NO_TIMEOUT)
this.timeoutSamples = timeout * sampleRate / 1000;
else
this.timeoutSamples = NO_TIMEOUT;
this.remainingSamples = this.timeoutSamples;
}
public RecognizerThread(RecognitionListener listener) {
this(listener, NO_TIMEOUT);
}
@Override
public void run() {
byte[] buffer = new byte[bufferSize];
while (!interrupted()
&& ((timeoutSamples == NO_TIMEOUT) || (remainingSamples > 0))) {
try {
int nread = inputStream.read(buffer, 0, buffer.length);
if (nread < 0) {
break;
} else {
boolean isSilence = recognizer.acceptWaveForm(buffer, nread);
if (isSilence) {
final String result = recognizer.getResult();
mainHandler.post(() -> listener.onResult(result));
} else {
final String partialResult = recognizer.getPartialResult();
mainHandler.post(() -> listener.onPartialResult(partialResult));
}
}
if (timeoutSamples != NO_TIMEOUT) {
remainingSamples = remainingSamples - nread;
}
} catch (IOException e) {
mainHandler.post(() -> listener.onError(e));
}
}
// If we met timeout signal that speech ended
if (timeoutSamples != NO_TIMEOUT && remainingSamples <= 0) {
mainHandler.post(() -> listener.onTimeout());
} else {
final String finalResult = recognizer.getFinalResult();
mainHandler.post(() -> listener.onFinalResult(finalResult));
}
}
}
}
@@ -0,0 +1,150 @@
// Copyright 2019 Alpha Cephei Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package org.vosk.android;
import android.content.Context;
import android.content.res.AssetManager;
import android.os.Environment;
import android.os.Handler;
import android.os.Looper;
import android.util.Log;
import org.vosk.Model;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.OutputStream;
import java.util.concurrent.Executor;
import java.util.concurrent.Executors;
/**
* Provides utility methods to sync model files to external storage to allow
* C++ code access them. Relies on file named "uuid" to track updates.
*/
public class StorageService {
protected static final String TAG = StorageService.class.getSimpleName();
public interface Callback<R> {
void onComplete(R result);
}
public static void unpack(Context context, String sourcePath, final String targetPath, final Callback<Model> completeCallback, final Callback<IOException> errorCallback) {
Executor executor = Executors.newSingleThreadExecutor(); // change according to your requirements
Handler handler = new Handler(Looper.getMainLooper());
executor.execute(() -> {
try {
final String outputPath = sync(context, sourcePath, targetPath);
Model model = new Model(outputPath);
handler.post(() -> completeCallback.onComplete(model));
} catch (final IOException e) {
handler.post(() -> errorCallback.onComplete(e));
}
});
}
public static String sync(Context context, String sourcePath, String targetPath) throws IOException {
AssetManager assetManager = context.getAssets();
File externalFilesDir = context.getExternalFilesDir(null);
if (externalFilesDir == null) {
throw new IOException("cannot get external files dir, "
+ "external storage state is " + Environment.getExternalStorageState());
}
File targetDir = new File(externalFilesDir, targetPath);
String resultPath = new File(targetDir, sourcePath).getAbsolutePath();
String sourceUUID = readLine(assetManager.open(sourcePath + "/uuid"));
try {
String targetUUID = readLine(new FileInputStream(new File(targetDir, sourcePath + "/uuid")));
if (targetUUID.equals(sourceUUID)) return resultPath;
} catch (FileNotFoundException e) {
// ignore
}
deleteContents(targetDir);
copyAssets(assetManager, sourcePath, targetDir);
// Copy uuid
copyFile(assetManager, sourcePath + "/uuid", targetDir);
return resultPath;
}
private static String readLine(InputStream is) throws IOException {
return new BufferedReader(new InputStreamReader(is)).readLine();
}
private static boolean deleteContents(File dir) {
File[] files = dir.listFiles();
boolean success = true;
if (files != null) {
for (File file : files) {
if (file.isDirectory()) {
success &= deleteContents(file);
}
if (!file.delete()) {
success = false;
}
}
}
return success;
}
private static void copyAssets(AssetManager assetManager, String path, File outPath) throws IOException {
String[] assets = assetManager.list(path);
if (assets == null) {
return;
}
if (assets.length == 0) {
if (!path.endsWith("uuid"))
copyFile(assetManager, path, outPath);
} else {
File dir = new File(outPath, path);
if (!dir.exists()) {
Log.v(TAG, "Making directory " + dir.getAbsolutePath());
if (!dir.mkdirs()) {
Log.v(TAG, "Failed to create directory " + dir.getAbsolutePath());
}
}
for (String asset : assets) {
copyAssets(assetManager, path + "/" + asset, outPath);
}
}
}
private static void copyFile(AssetManager assetManager, String fileName, File outPath) throws IOException {
InputStream in;
Log.v(TAG, "Copy " + fileName + " to " + outPath);
in = assetManager.open(fileName);
OutputStream out = new FileOutputStream(outPath + "/" + fileName);
byte[] buffer = new byte[4000];
int read;
while ((read = in.read(buffer)) != -1) {
out.write(buffer, 0, read);
}
in.close();
out.close();
}
}
+47
View File
@@ -0,0 +1,47 @@
def archiveName = "vosk-model-en"
def pomName = "Vosk English Model"
def pomDescription = "Small English model for Android"
android {
compileSdkVersion 29
defaultConfig {
minSdkVersion 21
targetSdkVersion 29
versionCode 6
versionName = version
archivesBaseName = archiveName
}
buildFeatures {
buildConfig = false
}
sourceSets {
main {
assets.srcDirs += "$buildDir/generated/assets"
}
}
}
tasks.register('genUUID') {
def uuid = UUID.randomUUID().toString()
def odir = file("$buildDir/generated/assets/model-en-us")
def ofile = file("$odir/uuid")
doLast {
mkdir odir
ofile.text = uuid
}
}
preBuild.dependsOn(genUUID)
publishing {
publications {
aar(MavenPublication) {
artifactId = archiveName
artifact("$buildDir/outputs/aar/$archiveName-release.aar")
pom {
name = pomName
description = pomDescription
}
}
}
}
@@ -0,0 +1,3 @@
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="org.vosk.model.en">
</manifest>
@@ -0,0 +1,7 @@
US English model for mobile Vosk applications
Copyright 2020 Alpha Cephei Inc
Accuracy: 10.38 (tedlium test) 9.85 (librispeech test-clean)
Speed: 0.11xRT (desktop)
Latency: 0.15s (right context)
+1
View File
@@ -0,0 +1 @@
include ':lib', ':model-en'
-268
View File
@@ -1,268 +0,0 @@
// Copyright 2019 Alpha Cephei Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package org.kaldi;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.OutputStream;
import java.io.PrintWriter;
import java.io.Reader;
import java.util.ArrayDeque;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Queue;
import android.content.Context;
import android.content.res.AssetManager;
import android.os.Environment;
import android.util.Log;
/**
* Provides utility methods to keep asset files to external storage to allow
* further JNI code access assets from a filesystem.
*
* There must be special file {@value #ASSET_LIST_NAME} among the application
* assets containing relative paths of assets to synchronize. If the
* corresponding path does not exist on the external storage it is copied. If
* the path exists checksums are compared and the asset is copied only if there
* is a mismatch. Checksum is stored in a separate asset with the name that
* consists of the original name and a suffix that depends on the checksum
* algorithm (e.g. MD5). Checksum files are copied along with the corresponding
* asset files.
*
* @author Alexander Solovets
*/
public class Assets {
protected static final String TAG = Assets.class.getSimpleName();
public static final String ASSET_LIST_NAME = "assets.lst";
public static final String SYNC_DIR = "sync";
public static final String HASH_EXT = ".md5";
private final AssetManager assetManager;
private final File externalDir;
/**
* Creates new instance for asset synchronization
*
* @param context
* application context
*
* @throws IOException
* if the directory does not exist
*
* @see android.content.Context#getExternalFilesDir
* @see android.os.Environment#getExternalStorageState
*/
public Assets(Context context) throws IOException {
File appDir = context.getExternalFilesDir(null);
if (null == appDir)
throw new IOException("cannot get external files dir, "
+ "external storage state is " + Environment.getExternalStorageState());
externalDir = new File(appDir, SYNC_DIR);
assetManager = context.getAssets();
}
/**
* Creates new instance with specified destination for assets
*
* @param context
* application context to retrieve the assets
* @param path
* path to sync the files
*/
public Assets(Context context, String dest) {
externalDir = new File(dest);
assetManager = context.getAssets();
}
/**
* Returns destination path on external storage where assets are copied.
*
* @return path to application directory or null if it does not exists
*/
public File getExternalDir() {
return externalDir;
}
/**
* Returns the map of asset paths to the files checksums.
*
* @return path to the root of resources directory on external storage
* @throws IOException
* if an I/O error occurs or "assets.lst" is missing
*/
public Map<String, String> getItems() throws IOException {
Map<String, String> items = new HashMap<String, String>();
for (String path : readLines(openAsset(ASSET_LIST_NAME))) {
Reader reader = new InputStreamReader(openAsset(path + HASH_EXT));
items.put(path, new BufferedReader(reader).readLine());
}
return items;
}
/**
* Returns path to hash mappings for the previously copied files. This
* method can be used to find out assets which must be updated.
*/
public Map<String, String> getExternalItems() {
try {
Map<String, String> items = new HashMap<String, String>();
File assetFile = new File(externalDir, ASSET_LIST_NAME);
for (String line : readLines(new FileInputStream(assetFile))) {
String[] fields = line.split(" ");
items.put(fields[0], fields[1]);
}
return items;
} catch (IOException e) {
return Collections.emptyMap();
}
}
/**
* In case you want to create more smart sync implementation, this method
* returns the list of items which must be synchronized.
*/
public Collection<String> getItemsToCopy(String path) throws IOException {
Collection<String> items = new ArrayList<String>();
Queue<String> queue = new ArrayDeque<String>();
queue.offer(path);
while (!queue.isEmpty()) {
path = queue.poll();
String[] list = assetManager.list(path);
for (String nested : list)
queue.offer(nested);
if (list.length == 0)
items.add(path);
}
return items;
}
private List<String> readLines(InputStream source) throws IOException {
List<String> lines = new ArrayList<String>();
BufferedReader br = new BufferedReader(new InputStreamReader(source));
String line;
while (null != (line = br.readLine()))
lines.add(line);
return lines;
}
private InputStream openAsset(String asset) throws IOException {
return assetManager.open(new File(SYNC_DIR, asset).getPath());
}
/**
* Saves the list of synchronized items. The list is stored as a two-column
* space-separated list of items in a text file. The file is located at the
* root of synchronization directory in the external storage.
*
* @param items
* the items
* @throws IOException
* if an I/O error occurs
*/
public void updateItemList(Map<String, String> items) throws IOException {
File assetListFile = new File(externalDir, ASSET_LIST_NAME);
PrintWriter pw = new PrintWriter(new FileOutputStream(assetListFile));
for (Map.Entry<String, String> entry : items.entrySet())
pw.format("%s %s\n", entry.getKey(), entry.getValue());
pw.close();
}
/**
* Copies raw asset resource to external storage of the device.
*
* @param path
* path of the asset to copy
* @throws IOException
* if an I/O error occurs
*/
public File copy(String asset) throws IOException {
InputStream source = openAsset(asset);
File destinationFile = new File(externalDir, asset);
destinationFile.getParentFile().mkdirs();
OutputStream destination = new FileOutputStream(destinationFile);
byte[] buffer = new byte[1024];
int nread;
while ((nread = source.read(buffer)) != -1) {
if (nread == 0) {
nread = source.read();
if (nread < 0)
break;
destination.write(nread);
continue;
}
destination.write(buffer, 0, nread);
}
destination.close();
return destinationFile;
}
/**
* Performs the sync of assets in the application and on the external
* storage
*
* @return The folder on external storage with data
* @throws IOException
*/
public File syncAssets() throws IOException {
Collection<String> newItems = new ArrayList<String>();
Collection<String> unusedItems = new ArrayList<String>();
Map<String, String> items = getItems();
Map<String, String> externalItems = getExternalItems();
for (String path : items.keySet()) {
if (!items.get(path).equals(externalItems.get(path))
|| !(new File(externalDir, path).exists()))
newItems.add(path);
else
Log.i(TAG,
String.format("Skipping asset %s: checksums are equal", path));
}
unusedItems.addAll(externalItems.keySet());
unusedItems.removeAll(items.keySet());
for (String path : newItems) {
File file = copy(path);
Log.i(TAG, String.format("Copying asset %s to %s", path, file));
}
for (String path : unusedItems) {
File file = new File(externalDir, path);
file.delete();
Log.i(TAG, String.format("Removing asset %s", file));
}
updateItemList(items);
return externalDir;
}
}
@@ -1,293 +0,0 @@
// Copyright 2019 Alpha Cephei Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package org.kaldi;
import static java.lang.String.format;
import java.io.File;
import java.io.IOException;
import java.util.Collection;
import java.util.HashSet;
import android.media.AudioFormat;
import android.media.AudioRecord;
import android.media.MediaRecorder.AudioSource;
import android.os.Handler;
import android.os.Looper;
import android.util.Log;
/**
* Main class to access recognizer functions. After configuration this class
* starts a listener thread which records the data and recognizes it using
* VOSK engine. Recognition events are passed to a client using
* {@link RecognitionListener}
*
*/
public class SpeechRecognizer {
protected static final String TAG = SpeechRecognizer.class.getSimpleName();
private final KaldiRecognizer recognizer;
private final int sampleRate;
private final static float BUFFER_SIZE_SECONDS = 0.4f;
private int bufferSize;
private final AudioRecord recorder;
private Thread recognizerThread;
private final Handler mainHandler = new Handler(Looper.getMainLooper());
private final Collection<RecognitionListener> listeners = new HashSet<RecognitionListener>();
/**
* Creates speech recognizer. Recognizer holds the AudioRecord object, so you
* need to call {@link release} in order to properly finalize it.
*
* @throws IOException thrown if audio recorder can not be created for some reason.
*/
public SpeechRecognizer(Model model) throws IOException {
recognizer = new KaldiRecognizer(model, 16000.0f);
sampleRate = 16000;
bufferSize = Math.round(sampleRate * BUFFER_SIZE_SECONDS);
recorder = new AudioRecord(
AudioSource.VOICE_RECOGNITION, sampleRate,
AudioFormat.CHANNEL_IN_MONO,
AudioFormat.ENCODING_PCM_16BIT, bufferSize * 2);
if (recorder.getState() == AudioRecord.STATE_UNINITIALIZED) {
recorder.release();
throw new IOException(
"Failed to initialize recorder. Microphone might be already in use.");
}
}
/**
* Adds listener.
*/
public void addListener(RecognitionListener listener) {
synchronized (listeners) {
listeners.add(listener);
}
}
/**
* Removes listener.
*/
public void removeListener(RecognitionListener listener) {
synchronized (listeners) {
listeners.remove(listener);
}
}
/**
* Starts recognition. Does nothing if recognition is active.
*
* @return true if recognition was actually started
*/
public boolean startListening() {
if (null != recognizerThread)
return false;
recognizerThread = new RecognizerThread();
recognizerThread.start();
return true;
}
/**
* Starts recognition. After specified timeout listening stops and the
* endOfSpeech signals about that. Does nothing if recognition is active.
*
* @timeout - timeout in milliseconds to listen.
*
* @return true if recognition was actually started
*/
public boolean startListening(int timeout) {
if (null != recognizerThread)
return false;
recognizerThread = new RecognizerThread(timeout);
recognizerThread.start();
return true;
}
private boolean stopRecognizerThread() {
if (null == recognizerThread)
return false;
try {
recognizerThread.interrupt();
recognizerThread.join();
} catch (InterruptedException e) {
// Restore the interrupted status.
Thread.currentThread().interrupt();
}
recognizerThread = null;
return true;
}
/**
* Stops recognition. All listeners should receive final result if there is
* any. Does nothing if recognition is not active.
*
* @return true if recognition was actually stopped
*/
public boolean stop() {
boolean result = stopRecognizerThread();
if (result) {
Log.i(TAG, "Stop recognition");
mainHandler.post(new ResultEvent(recognizer.Result(), true));
}
return result;
}
/**
* Cancels recognition. Listeners do not receive final result. Does nothing
* if recognition is not active.
*
* @return true if recognition was actually canceled
*/
public boolean cancel() {
boolean result = stopRecognizerThread();
recognizer.Result(); // Reset recognizer state
if (result) {
Log.i(TAG, "Cancel recognition");
}
return result;
}
/**
* Shutdown the recognizer and release the recorder
*/
public void shutdown() {
recorder.release();
}
private final class RecognizerThread extends Thread {
private int remainingSamples;
private int timeoutSamples;
private final static int NO_TIMEOUT = -1;
public RecognizerThread(int timeout) {
if (timeout != NO_TIMEOUT)
this.timeoutSamples = timeout * sampleRate / 1000;
else
this.timeoutSamples = NO_TIMEOUT;
this.remainingSamples = this.timeoutSamples;
}
public RecognizerThread() {
this(NO_TIMEOUT);
}
@Override
public void run() {
recorder.startRecording();
if (recorder.getRecordingState() == AudioRecord.RECORDSTATE_STOPPED) {
recorder.stop();
IOException ioe = new IOException(
"Failed to start recording. Microphone might be already in use.");
mainHandler.post(new OnErrorEvent(ioe));
return;
}
Log.d(TAG, "Starting decoding");
short[] buffer = new short[bufferSize];
while (!interrupted()
&& ((timeoutSamples == NO_TIMEOUT) || (remainingSamples > 0))) {
int nread = recorder.read(buffer, 0, buffer.length);
if (nread < 0) {
throw new RuntimeException("error reading audio buffer");
} else {
boolean isFinal = recognizer.AcceptWaveform(buffer, nread);
if (isFinal) {
mainHandler.post(new ResultEvent(recognizer.Result(), true));
} else {
mainHandler.post(new ResultEvent(recognizer.PartialResult(), false));
}
}
if (timeoutSamples != NO_TIMEOUT) {
remainingSamples = remainingSamples - nread;
}
}
recorder.stop();
// Remove all pending notifications.
mainHandler.removeCallbacksAndMessages(null);
// If we met timeout signal that speech ended
if (timeoutSamples != NO_TIMEOUT && remainingSamples <= 0) {
mainHandler.post(new TimeoutEvent());
}
}
}
private abstract class RecognitionEvent implements Runnable {
public void run() {
RecognitionListener[] emptyArray = new RecognitionListener[0];
for (RecognitionListener listener : listeners.toArray(emptyArray))
execute(listener);
}
protected abstract void execute(RecognitionListener listener);
}
private class ResultEvent extends RecognitionEvent {
protected final String hypothesis;
private final boolean finalResult;
ResultEvent(String hypothesis, boolean finalResult) {
this.hypothesis = hypothesis;
this.finalResult = finalResult;
}
@Override
protected void execute(RecognitionListener listener) {
if (finalResult)
listener.onResult(hypothesis);
else
listener.onPartialResult(hypothesis);
}
}
private class OnErrorEvent extends RecognitionEvent {
private final Exception exception;
OnErrorEvent(Exception exception) {
this.exception = exception;
}
@Override
protected void execute(RecognitionListener listener) {
listener.onError(exception);
}
}
private class TimeoutEvent extends RecognitionEvent {
@Override
protected void execute(RecognitionListener listener) {
listener.onTimeout();
}
}
}
+16
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@@ -0,0 +1,16 @@
CFLAGS=-I../src
LDFLAGS=-L../src -lvosk -ldl -lpthread -Wl,-rpath,../src
all: test_vosk test_vosk_speaker
test_vosk: test_vosk.o
gcc $^ -o $@ $(LDFLAGS)
test_vosk_speaker: test_vosk_speaker.o
gcc $^ -o $@ $(LDFLAGS)
%.o: %.c
gcc $(CFLAGS) -c -o $@ $<
clean:
rm -f *.o *.a test_vosk test_vosk_speaker
+29
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@@ -0,0 +1,29 @@
#include <vosk_api.h>
#include <stdio.h>
int main() {
FILE *wavin;
char buf[3200];
int nread, final;
VoskModel *model = vosk_model_new("model");
VoskRecognizer *recognizer = vosk_recognizer_new(model, 16000.0);
wavin = fopen("test.wav", "rb");
fseek(wavin, 44, SEEK_SET);
while (!feof(wavin)) {
nread = fread(buf, 1, sizeof(buf), wavin);
final = vosk_recognizer_accept_waveform(recognizer, buf, nread);
if (final) {
printf("%s\n", vosk_recognizer_result(recognizer));
} else {
printf("%s\n", vosk_recognizer_partial_result(recognizer));
}
}
printf("%s\n", vosk_recognizer_final_result(recognizer));
vosk_recognizer_free(recognizer);
vosk_model_free(model);
fclose(wavin);
return 0;
}
+30
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@@ -0,0 +1,30 @@
#include <vosk_api.h>
#include <stdio.h>
int main() {
FILE *wavin;
char buf[3200];
int nread, final;
VoskModel *model = vosk_model_new("model");
VoskSpkModel *spk_model = vosk_spk_model_new("spk-model");
VoskRecognizer *recognizer = vosk_recognizer_new_spk(model, 16000.0, spk_model);
wavin = fopen("test.wav", "rb");
fseek(wavin, 44, SEEK_SET);
while (!feof(wavin)) {
nread = fread(buf, 1, sizeof(buf), wavin);
final = vosk_recognizer_accept_waveform(recognizer, buf, nread);
if (final) {
printf("%s\n", vosk_recognizer_result(recognizer));
} else {
printf("%s\n", vosk_recognizer_partial_result(recognizer));
}
}
printf("%s\n", vosk_recognizer_final_result(recognizer));
vosk_recognizer_free(recognizer);
vosk_spk_model_free(spk_model);
vosk_model_free(model);
return 0;
}
-54
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@@ -1,54 +0,0 @@
KALDI_ROOT ?= $(HOME)/kaldi
CFLAGS := -std=c++11 -g -O2 -DPIC -fPIC -Wno-unused-function
CPPFLAGS := -I$(KALDI_ROOT)/src -I$(KALDI_ROOT)/tools/openfst/include -I../src -DFST_NO_DYNAMIC_LINKING
KALDI_LIBS = \
${KALDI_ROOT}/src/online2/kaldi-online2.a \
${KALDI_ROOT}/src/decoder/kaldi-decoder.a \
${KALDI_ROOT}/src/ivector/kaldi-ivector.a \
${KALDI_ROOT}/src/gmm/kaldi-gmm.a \
${KALDI_ROOT}/src/nnet3/kaldi-nnet3.a \
${KALDI_ROOT}/src/tree/kaldi-tree.a \
${KALDI_ROOT}/src/feat/kaldi-feat.a \
${KALDI_ROOT}/src/lat/kaldi-lat.a \
${KALDI_ROOT}/src/lm/kaldi-lm.a \
${KALDI_ROOT}/src/hmm/kaldi-hmm.a \
${KALDI_ROOT}/src/transform/kaldi-transform.a \
${KALDI_ROOT}/src/cudamatrix/kaldi-cudamatrix.a \
${KALDI_ROOT}/src/matrix/kaldi-matrix.a \
${KALDI_ROOT}/src/fstext/kaldi-fstext.a \
${KALDI_ROOT}/src/util/kaldi-util.a \
${KALDI_ROOT}/src/base/kaldi-base.a \
${KALDI_ROOT}/tools/openfst/lib/libfst.a \
${KALDI_ROOT}/tools/openfst/lib/libfstngram.a \
${KALDI_ROOT}/tools/OpenBLAS/libopenblas.a \
-lgfortran -lstdc++
all: test.exe
test.exe: libkaldiwrap.so test.cs
mcs test.cs gen/*.cs
VOSK_SOURCES = \
vosk_wrap.c \
../src/kaldi_recognizer.cc \
../src/kaldi_recognizer.h \
../src/model.cc \
../src/model.h \
../src/spk_model.cc \
../src/spk_model.h \
../src/vosk_api.cc \
../src/vosk_api.h
libkaldiwrap.so: $(VOSK_SOURCES)
$(CXX) -fpermissive $(CFLAGS) $(CPPFLAGS) -shared -o $@ $(VOSK_SOURCES) $(KALDI_LIBS)
vosk_wrap.c: ../src/vosk.i
swig -csharp -DSWIG_CSHARP_NO_EXCEPTION_HELPER -dllimport "libkaldiwrap.so" \
-namespace "Kaldi" -outdir gen -o vosk_wrap.c ../src/vosk.i
run:
mono test.exe
clean:
$(RM) *.so vosk_wrap.c *.o gen/*.cs test.exe
+12
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@@ -0,0 +1,12 @@
This is a nuget-based wrapper for libvosk library
See demo folder for example how to use the library. You can simply run
"dotnet run" to run the demo. Make sure you unpacked the model and the
test file.
See the nuget folder for the sources of the wrapper. Run build.sh to
build nuget package.
Note we only support win64 and linux64 for now. No support for win32
since it is a little bit painful to load the libraries depending on
architecture. In theory we can add OSX some time or even Android.
+80
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@@ -0,0 +1,80 @@
using System;
using System.IO;
using Vosk;
public class VoskDemo
{
public static void DemoBytes(Model model)
{
// Demo byte buffer
VoskRecognizer rec = new VoskRecognizer(model, 16000.0f);
rec.SetMaxAlternatives(0);
rec.SetWords(true);
using(Stream source = File.OpenRead("test.wav")) {
byte[] buffer = new byte[4096];
int bytesRead;
while((bytesRead = source.Read(buffer, 0, buffer.Length)) > 0) {
if (rec.AcceptWaveform(buffer, bytesRead)) {
Console.WriteLine(rec.Result());
} else {
Console.WriteLine(rec.PartialResult());
}
}
}
Console.WriteLine(rec.FinalResult());
}
public static void DemoFloats(Model model)
{
// Demo float array
VoskRecognizer rec = new VoskRecognizer(model, 16000.0f);
using(Stream source = File.OpenRead("test.wav")) {
byte[] buffer = new byte[4096];
int bytesRead;
while((bytesRead = source.Read(buffer, 0, buffer.Length)) > 0) {
float[] fbuffer = new float[bytesRead / 2];
for (int i = 0, n = 0; i < fbuffer.Length; i++, n+=2) {
fbuffer[i] = BitConverter.ToInt16(buffer, n);
}
if (rec.AcceptWaveform(fbuffer, fbuffer.Length)) {
Console.WriteLine(rec.Result());
} else {
Console.WriteLine(rec.PartialResult());
}
}
}
Console.WriteLine(rec.FinalResult());
}
public static void DemoSpeaker(Model model)
{
// Output speakers
SpkModel spkModel = new SpkModel("model-spk");
VoskRecognizer rec = new VoskRecognizer(model, 16000.0f);
rec.SetSpkModel(spkModel);
using(Stream source = File.OpenRead("test.wav")) {
byte[] buffer = new byte[4096];
int bytesRead;
while((bytesRead = source.Read(buffer, 0, buffer.Length)) > 0) {
if (rec.AcceptWaveform(buffer, bytesRead)) {
Console.WriteLine(rec.Result());
} else {
Console.WriteLine(rec.PartialResult());
}
}
}
Console.WriteLine(rec.FinalResult());
}
public static void Main()
{
// You can set to -1 to disable logging messages
Vosk.Vosk.SetLogLevel(0);
Model model = new Model("model");
DemoBytes(model);
DemoFloats(model);
DemoSpeaker(model);
}
}
+17
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@@ -0,0 +1,17 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net5.0</TargetFramework>
<RootNamespace>VoskDemo</RootNamespace>
</PropertyGroup>
<PropertyGroup>
<RestoreSources>$(RestoreSources);../nuget</RestoreSources>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Vosk" Version="0.3.42" />
</ItemGroup>
</Project>
+32
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@@ -0,0 +1,32 @@
<?xml version="1.0"?>
<package>
<metadata>
<id>Vosk</id>
<version>0.3.42</version>
<authors>Alpha Cephei Inc</authors>
<owners>Alpha Cephei Inc</owners>
<license type="expression">Apache-2.0</license>
<projectUrl>https://alphacephei.com/vosk/</projectUrl>
<requireLicenseAcceptance>false</requireLicenseAcceptance>
<title>Vosk Speech Recognition Toolkit</title>
<description>Vosk is an offline open source speech recognition toolkit. It enables speech recognition models for 20+ languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech. More to come.
Vosk models are small (50 Mb) but provide continuous large vocabulary transcription, zero-latency response with streaming API, reconfigurable vocabulary and speaker identification.
Speech recognition bindings implemented for various programming languages like Python, Java, Node.JS, C#, C++ and others.
Vosk supplies speech recognition for chatbots, smart home appliances, virtual assistants. It can also create subtitles for movies, transcription for lectures and interviews.
Vosk scales from small devices like Raspberry Pi or Android smartphone to big clusters.</description>
<releaseNotes>See for details https://github.com/alphacep/vosk-api/releases</releaseNotes>
<repository type="git" url="https://github.com/alphacep/vosk-api.git" branch="master"/>
<copyright>Copyright 2020-2050 Alpha Cephei Inc</copyright>
<tags>speech recognition voice stt asr speech-to-text ai offline privacy</tags>
<dependencies>
<group targetFramework=".NETStandard2.0"/>
</dependencies>
</metadata>
<files>
<file src="**" exclude="src/*.cs;build.sh;**/.keep-me;*.nupkg" />
</files>
</package>
+2
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@@ -0,0 +1,2 @@
mcs -out:lib/netstandard2.0/Vosk.dll -target:library src/*.cs
nuget pack
+11
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@@ -0,0 +1,11 @@
<Project xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
<ItemGroup>
<NativeLibs Include="$(MSBuildThisFileDirectory)\lib\linux-x64\*.so" Condition="'$([MSBuild]::IsOsPlatform(Linux))'" />
<NativeLibs Include="$(MSBuildThisFileDirectory)\lib\win-x64\*.dll" Condition="'$([MSBuild]::IsOsPlatform(Windows))'" />
<NativeLibs Include="$(MSBuildThisFileDirectory)\lib\osx-universal\*.dylib" Condition="'$([MSBuild]::IsOsPlatform(OSX))'" />
<None Include="@(NativeLibs)">
<Link>%(FileName)%(Extension)</Link>
<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
</None>
</ItemGroup>
</Project>
+41
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@@ -0,0 +1,41 @@
namespace Vosk {
public class Model : global::System.IDisposable {
private global::System.Runtime.InteropServices.HandleRef handle;
internal Model(global::System.IntPtr cPtr) {
handle = new global::System.Runtime.InteropServices.HandleRef(this, cPtr);
}
internal static global::System.Runtime.InteropServices.HandleRef getCPtr(Model obj) {
return (obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.handle;
}
~Model() {
Dispose(false);
}
public void Dispose() {
Dispose(true);
global::System.GC.SuppressFinalize(this);
}
protected virtual void Dispose(bool disposing) {
lock(this) {
if (handle.Handle != global::System.IntPtr.Zero) {
VoskPINVOKE.delete_Model(handle);
handle = new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero);
}
}
}
public Model(string model_path) : this(VoskPINVOKE.new_Model(model_path)) {
}
public int FindWord(string word) {
return VoskPINVOKE.Model_vosk_model_find_word(handle, word);
}
}
}
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namespace Vosk {
public class SpkModel : global::System.IDisposable {
private global::System.Runtime.InteropServices.HandleRef handle;
internal SpkModel(global::System.IntPtr cPtr) {
handle = new global::System.Runtime.InteropServices.HandleRef(this, cPtr);
}
internal static global::System.Runtime.InteropServices.HandleRef getCPtr(SpkModel obj) {
return (obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.handle;
}
~SpkModel() {
Dispose(false);
}
public void Dispose() {
Dispose(true);
global::System.GC.SuppressFinalize(this);
}
protected virtual void Dispose(bool disposing) {
lock(this) {
if (handle.Handle != global::System.IntPtr.Zero) {
VoskPINVOKE.delete_SpkModel(handle);
handle = new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero);
}
}
}
public SpkModel(string model_path) : this(VoskPINVOKE.new_SpkModel(model_path)) {
}
}
}
+17
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namespace Vosk {
public class Vosk {
public static void SetLogLevel(int level) {
VoskPINVOKE.SetLogLevel(level);
}
public static void GpuInit() {
VoskPINVOKE.GpuInit();
}
public static void GpuThreadInit() {
VoskPINVOKE.GpuThreadInit();
}
}
}
+78
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namespace Vosk {
class VoskPINVOKE {
static VoskPINVOKE() {
}
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_model_new")]
public static extern global::System.IntPtr new_Model(string jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_model_free")]
public static extern void delete_Model(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_model_find_word")]
public static extern int Model_vosk_model_find_word(global::System.Runtime.InteropServices.HandleRef jarg1, string jarg2);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_spk_model_new")]
public static extern global::System.IntPtr new_SpkModel(string jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_spk_model_free")]
public static extern void delete_SpkModel(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_new")]
public static extern global::System.IntPtr new_VoskRecognizer(global::System.Runtime.InteropServices.HandleRef jarg1, float jarg2);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_new_spk")]
public static extern global::System.IntPtr new_VoskRecognizerSpk(global::System.Runtime.InteropServices.HandleRef jarg1, float jarg2, global::System.Runtime.InteropServices.HandleRef jarg3);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_new_grm")]
public static extern global::System.IntPtr new_VoskRecognizerGrm(global::System.Runtime.InteropServices.HandleRef jarg1, float jarg2, string jarg3);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_free")]
public static extern void delete_VoskRecognizer(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_set_max_alternatives")]
public static extern void VoskRecognizer_SetMaxAlternatives(global::System.Runtime.InteropServices.HandleRef jarg1, int jarg2);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_set_words")]
public static extern void VoskRecognizer_SetWords(global::System.Runtime.InteropServices.HandleRef jarg1, int jarg2);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_set_partial_words")]
public static extern void VoskRecognizer_SetPartialWords(global::System.Runtime.InteropServices.HandleRef jarg1, int jarg2);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_set_spk_model")]
public static extern void VoskRecognizer_SetSpkModel(global::System.Runtime.InteropServices.HandleRef jarg1, global::System.Runtime.InteropServices.HandleRef jarg2);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_accept_waveform")]
public static extern bool VoskRecognizer_AcceptWaveform(global::System.Runtime.InteropServices.HandleRef jarg1, [global::System.Runtime.InteropServices.In, global::System.Runtime.InteropServices.MarshalAs(global::System.Runtime.InteropServices.UnmanagedType.LPArray)]byte[] jarg2, int jarg3);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_accept_waveform_s")]
public static extern bool VoskRecognizer_AcceptWaveformShort(global::System.Runtime.InteropServices.HandleRef jarg1, [global::System.Runtime.InteropServices.In, global::System.Runtime.InteropServices.MarshalAs(global::System.Runtime.InteropServices.UnmanagedType.LPArray)]short[] jarg2, int jarg3);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_accept_waveform_f")]
public static extern bool VoskRecognizer_AcceptWaveformFloat(global::System.Runtime.InteropServices.HandleRef jarg1, [global::System.Runtime.InteropServices.In, global::System.Runtime.InteropServices.MarshalAs(global::System.Runtime.InteropServices.UnmanagedType.LPArray)]float[] jarg2, int jarg3);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_result")]
public static extern global::System.IntPtr VoskRecognizer_Result(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_partial_result")]
public static extern global::System.IntPtr VoskRecognizer_PartialResult(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_final_result")]
public static extern global::System.IntPtr VoskRecognizer_FinalResult(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_recognizer_reset")]
public static extern void VoskRecognizer_Reset(global::System.Runtime.InteropServices.HandleRef jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_set_log_level")]
public static extern void SetLogLevel(int jarg1);
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_gpu_init")]
public static extern void GpuInit();
[global::System.Runtime.InteropServices.DllImport("libvosk", EntryPoint="vosk_gpu_thread_init")]
public static extern void GpuThreadInit();
}
}
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namespace Vosk {
public class VoskRecognizer : System.IDisposable {
private System.Runtime.InteropServices.HandleRef handle;
internal VoskRecognizer(System.IntPtr cPtr) {
handle = new System.Runtime.InteropServices.HandleRef(this, cPtr);
}
internal static System.Runtime.InteropServices.HandleRef getCPtr(VoskRecognizer obj) {
return (obj == null) ? new System.Runtime.InteropServices.HandleRef(null, System.IntPtr.Zero) : obj.handle;
}
~VoskRecognizer() {
Dispose(false);
}
public void Dispose() {
Dispose(true);
System.GC.SuppressFinalize(this);
}
protected virtual void Dispose(bool disposing) {
lock(this) {
if (handle.Handle != System.IntPtr.Zero) {
VoskPINVOKE.delete_VoskRecognizer(handle);
handle = new System.Runtime.InteropServices.HandleRef(null, System.IntPtr.Zero);
}
}
}
public VoskRecognizer(Model model, float sample_rate) : this(VoskPINVOKE.new_VoskRecognizer(Model.getCPtr(model), sample_rate)) {
}
public VoskRecognizer(Model model, float sample_rate, SpkModel spk_model) : this(VoskPINVOKE.new_VoskRecognizerSpk(Model.getCPtr(model), sample_rate, SpkModel.getCPtr(spk_model))) {
}
public VoskRecognizer(Model model, float sample_rate, string grammar) : this(VoskPINVOKE.new_VoskRecognizerGrm(Model.getCPtr(model), sample_rate, grammar)) {
}
public void SetMaxAlternatives(int max_alternatives) {
VoskPINVOKE.VoskRecognizer_SetMaxAlternatives(handle, max_alternatives);
}
public void SetWords(bool words) {
VoskPINVOKE.VoskRecognizer_SetWords(handle, words ? 1 : 0);
}
public void SetPartialWords(bool partial_words) {
VoskPINVOKE.VoskRecognizer_SetPartialWords(handle, partial_words ? 1 : 0);
}
public void SetSpkModel(SpkModel spk_model) {
VoskPINVOKE.VoskRecognizer_SetSpkModel(handle, SpkModel.getCPtr(spk_model));
}
public bool AcceptWaveform(byte[] data, int len) {
return VoskPINVOKE.VoskRecognizer_AcceptWaveform(handle, data, len);
}
public bool AcceptWaveform(short[] sdata, int len) {
return VoskPINVOKE.VoskRecognizer_AcceptWaveformShort(handle, sdata, len);
}
public bool AcceptWaveform(float[] fdata, int len) {
return VoskPINVOKE.VoskRecognizer_AcceptWaveformFloat(handle, fdata, len);
}
private static string PtrToStringUTF8(System.IntPtr ptr) {
int len = 0;
while (System.Runtime.InteropServices.Marshal.ReadByte(ptr, len) != 0)
len++;
byte[] array = new byte[len];
System.Runtime.InteropServices.Marshal.Copy(ptr, array, 0, len);
return System.Text.Encoding.UTF8.GetString(array);
}
public string Result() {
return PtrToStringUTF8(VoskPINVOKE.VoskRecognizer_Result(handle));
}
public string PartialResult() {
return PtrToStringUTF8(VoskPINVOKE.VoskRecognizer_PartialResult(handle));
}
public string FinalResult() {
return PtrToStringUTF8(VoskPINVOKE.VoskRecognizer_FinalResult(handle));
}
public void Reset() {
VoskPINVOKE.VoskRecognizer_Reset(handle);
}
}
}
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using System;
using System.IO;
using Kaldi;
public class Test
{
public static void Main()
{
Model model = new Model("model");
KaldiRecognizer rec = new KaldiRecognizer(model, 16000.0f);
using(Stream source = File.OpenRead("test.wav")) {
byte[] buffer = new byte[4096];
int bytesRead;
while((bytesRead = source.Read(buffer, 0, buffer.Length)) > 0) {
if (rec.AcceptWaveform(buffer, bytesRead)) {
Console.WriteLine(rec.Result());
} else {
Console.WriteLine(rec.PartialResult());
}
}
}
Console.WriteLine(rec.FinalResult());
rec = new KaldiRecognizer(model, 16000.0f);
using(Stream source = File.OpenRead("test.wav")) {
byte[] buffer = new byte[4096];
int bytesRead;
while((bytesRead = source.Read(buffer, 0, buffer.Length)) > 0) {
float[] fbuffer = new float[bytesRead / 2];
for (int i = 0, n = 0; i < fbuffer.Length; i++, n+=2) {
fbuffer[i] = (short)(buffer[n] | buffer[n+1] << 8);
}
if (rec.AcceptWaveform(fbuffer, fbuffer.Length)) {
Console.WriteLine(rec.Result());
GC.Collect();
} else {
Console.WriteLine(rec.PartialResult());
}
}
}
Console.WriteLine(rec.FinalResult());
}
}
-21
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@@ -1,21 +0,0 @@
## Accuracy issues
Accuracy of modern systems is still unstable, that means sometimes you can have a very good accuracy and sometimes it could be bad.
It is hard to make a system that will work good. And there could be many reasons for that:
* Audio has very bad quality
* Vocabulary of the system doesn't match (yes, we still use fixed vocabulary)
* Audio conditions like accent were not really the ones that were used in training
* Some unpredictable audio issues like frame drop or frame coding bugs
* Software bugs
It is hard to guess what is going on under the hood without getting your hands dirty. For that reason in case of any accuracy
issues you must provide the following for analysis:
* Who are you, where are you from and why are you doing that. We don't like dealing with anonymous
* The complete and exact description of the system you want to build - what is it going to do, what do you want to build
* The precise description of hardware you are trying to run the system on
* The detailed list of software versions you are using
* Audio samples to demonstrate the problem together with the reference transcription for those samples
Remember, the more information you provide the faster you get a solution.
-42
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## Updating the language model
The Kaldi model used in Vosk is compiled from 3 data sources:
* dictionary
* acoustic model
* language model
You can rebuild all three with different level of effort, but sometimes you just
need to adjust the probability of the words to improve the recognition. For
that it is enough to recompile the language model from the text. To do that
1) Take a text that reflects the speech you want to recognize
2) Remove punctuation, convert everything to the lowercase, you can do it with a python script
3) Build openfst and opengrm inside kaldi
```
export KALDI_ROOT=`pwd`/kaldi
git clone https://github.com/kaldi-asr/kaldi
cd kaldi/tools
make
# install all required dependencies and repeat `make` if needed
extras/install_opengrm.sh
```
4) Now lets build a grammar
```
export PATH=$KALDI_ROOT/tools/openfst/bin:$PATH
export LD_LIBRARY_PATH=$KALDI_ROOT/tools/openfst/lib/fst
cd model
fstsymbols --save_osymbols=words.txt Gr.fst > /dev/null
farcompilestrings --fst_type=compact --symbols=words.txt --keep_symbols text.txt | \
ngramcount | ngrammake | \
fstconvert --fst_type=ngram > Gr.fst
```
Use created Gr.fst instead of standard one in your model.
For more details see OpenGRM documentation http://www.opengrm.org/twiki/bin/view/GRM/NGramLibrary
You can not introduce new words this way, that is something we will cover later.
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# Models
This is the list of models compatible with Vosk-API.
To add a new model here create an issue on Github.
### English
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [kaldi-en-us-aspire-0.1](http://alphacephei.com/kaldi/kaldi-en-us-aspire-0.1.tar.gz) | 363M | TBD | Trained on Fisher + more or less recent LM. Pretty outdated but still ok even even for calls |
| [alphacep-model-android-en-us-0.3](http://alphacephei.com/kaldi/alphacep-model-android-en-us-0.3.tar.gz) | 36M | TBD | Lightweight wideband model for Android and RPi |
### Chinese
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [kaldi-cn-0.1.tar.gz](http://alphacephei.com/kaldi/kaldi-cn-0.1.tar.gz) | 195M | TBD | Big narrowband Chinese model for server processing |
| [alphacep-model-android-cn-0.3](http://alphacephei.com/kaldi/alphacep-model-android-cn-0.3.tar.gz) | 32M | TBD | Lightweight wideband model for Android and RPi |
### Russian
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [kaldi-ru-0.10.tar.gz](http://alphacephei.com/kaldi/kaldi-ru-0.10.tar.gz) | 2.5G | TBD | Big narrowband Russian model for server processing |
| [alphacep-model-android-ru-0.3](http://alphacephei.com/kaldi/alphacep-model-android-ru-0.3.tar.gz) | 39M | TBD | Lightweight wideband model for Android and RPi |
### French
| Model | Size | Accuracy | Notes |
|-------------------------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [alphacep-model-android-fr-pguyot-0.3](http://alphacephei.com/kaldi/alphacep-model-android-fr-pguyot-0.3.tar.gz) | 39M | TBD | Lightweight wideband model for Android and RPi trained by [Paul Guyot](https://github.com/pguyot/zamia-speech/releases) |
### German
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|------------------------------------------------------------------------------------------------------|
| [tuda-de](http://ltdata1.informatik.uni-hamburg.de/kaldi_tuda_de/de_400k_nnet3chain_tdnn1f_2048_sp_bi.tar.bz2) | 566M | TBD | Wideband server model from [tuda-de](https://github.com/uhh-lt/kaldi-tuda-de) |
| [alphacep-model-android-de-zamia-0.3](http://alphacephei.com/kaldi/alphacep-model-android-de-zamia-0.3.tar.gz) | 49M | TBD | Lightweight wideband model for Android and RPi |
### Spanish
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [alphacep-model-android-es-0.3](http://alphacephei.com/kaldi/alphacep-model-android-es-0.3.tar.gz) | 33M | TBD | Lightweight wideband model for Android and RPi |
### Portuguese
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [alphacep-model-android-pt-0.3](http://alphacephei.com/kaldi/alphacep-model-android-pt-0.3.tar.gz) | 31M | TBD | Lightweight wideband model for Android and RPi |
### Dutch
https://github.com/opensource-spraakherkenning-nl/Kaldi_NL
### Greek
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [kaldi-el-gr-0.6.tar.gz](http://alphacephei.com/kaldi/kaldi-el-gr-0.6.tar.gz) | 1.1G | TBD | Big narrowband Greek model for server processing, not extremely accurate though |
### Turkish
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [alphacep-model-android-tr-0.3](http://alphacephei.com/kaldi/alphacep-model-android-tr-0.3.tar.gz) | 35M | TBD | Lightweight wideband model for Android and RPi |
### Vietnamese
| Model | Size | Accuracy | Notes |
|-----------------------------------------------------------------------------------------------------------|-------|------------|----------------------------------------------------------------------------------------------|
| [alphacep-model-android-vn-0.3](http://alphacephei.com/kaldi/alphacep-model-android-vn-0.3.tar.gz) | 32M | TBD | Lightweight wideband model for Android and RPi |
+176
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License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
+1
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@@ -0,0 +1 @@
See example subfolder for instructions how to use the module
+7
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@@ -0,0 +1,7 @@
// Go bindings for Vosk speech recognition toolkit. Vosk is an offline
// open source speech to text API for Android, iOS, Raspberry Pi and
// servers. It enables speech recognition models for 18 languages and
// dialects - English, Indian English, German, French, Spanish, Portuguese,
// Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic,
// Greek, Farsi, Filipino, Ukrainian.
package vosk
+31
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@@ -0,0 +1,31 @@
To try this package do the following steps:
On Linux (we download library and set LD_LIBRARY_PATH)
```
git clone https://github.com/alphacep/vosk-api
cd vosk-api/go/example
wget https://github.com/alphacep/vosk-api/releases/download/v0.3.42/vosk-linux-x86_64-0.3.42.zip
unzip vosk-linux-x86_64-0.3.42.zip
wget https://alphacephei.com/vosk/models/vosk-model-small-en-us-0.15.zip
unzip vosk-model-small-en-us-0.15.zip
mv vosk-model-small-en-us-0.15 model
cp ../../python/example/test.wav .
VOSK_PATH=`pwd`/vosk-linux-x86_64-0.3.42 LD_LIBRARY_PATH=$VOSK_PATH CGO_CPPFLAGS="-I $VOSK_PATH" CGO_LDFLAGS="-L $VOSK_PATH" go run . -f test.wav
```
for Windows (we place DLLs in current folder where linker finds them):
```
git clone https://github.com/alphacep/vosk-api
cd vosk-api/go/example
wget https://github.com/alphacep/vosk-api/releases/download/v0.3.42/vosk-linux-x86_64-0.3.42.zip
unzip vosk-linux-x86_64-0.3.42.zip
cp vosk-linux-x86_64-0.3.42/*.dll .
cp vosk-linux-x86_64-0.3.42/*.h .
wget https://alphacephei.com/vosk/models/vosk-model-small-en-us-0.15.zip
unzip vosk-model-small-en-us-0.15.zip
mv vosk-model-small-en-us-0.15 model
cp ../../python/example/test.wav .
VOSK_PATH=`pwd` LD_LIBRARY_PATH=$VOSK_PATH CGO_CPPFLAGS="-I $VOSK_PATH" CGO_LDFLAGS="-L $VOSK_PATH -lvosk -lpthread -dl" go run . -f test.wav
```
+2
View File
@@ -0,0 +1,2 @@
// Example package for Vosk Go bindings.
package main
+56
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@@ -0,0 +1,56 @@
package main
import (
"bufio"
"flag"
"fmt"
"io"
"log"
"os"
vosk "github.com/alphacep/vosk-api/go"
)
func main() {
var filename string
flag.StringVar(&filename, "f", "", "file to transcribe")
flag.Parse()
model, err := vosk.NewModel("model")
if err != nil {
log.Fatal(err)
}
sampleRate := 16000.0
rec, err := vosk.NewRecognizer(model, sampleRate)
if err != nil {
log.Fatal(err)
}
rec.SetWords(1)
file, err := os.Open(filename)
if err != nil {
panic(err)
}
defer file.Close()
reader := bufio.NewReader(file)
buf := make([]byte, 4096)
for {
_, err := reader.Read(buf)
if err != nil {
if err != io.EOF {
log.Fatal(err)
}
break
}
if rec.AcceptWaveform(buf) != 0 {
fmt.Println(string(rec.Result()))
}
}
fmt.Println(string(rec.FinalResult()))
}
+7
View File
@@ -0,0 +1,7 @@
module github.com/alphacep/vosk-api/go
go 1.16
replace (
github.com/alphacep/vosk-api/go => ./
)
+152
View File
@@ -0,0 +1,152 @@
package vosk
// #cgo CPPFLAGS: -I ${SRCDIR}/../src
// #cgo LDFLAGS: -L ${SRCDIR}/../src -lvosk -ldl -lpthread
// #include <stdlib.h>
// #include <vosk_api.h>
import "C"
// VoskModel contains a reference to the C VoskModel
type VoskModel struct {
model *C.struct_VoskModel
}
// NewModel creates a new VoskModel instance
func NewModel(modelPath string) (*VoskModel, error) {
internal := C.vosk_model_new(C.CString(modelPath))
model := &VoskModel{model: internal}
return model, nil
}
func (m *VoskModel) Free() {
C.vosk_model_free(m.model)
}
func freeModel(model *VoskModel) {
C.vosk_model_free(model.model)
}
// FindWord checks if a word can be recognized by the model.
// Returns the word symbol if the word exists inside the model or
// -1 otherwise.
func (m *VoskModel) FindWord(word []byte) int {
cbuf := C.CBytes(word)
defer C.free(cbuf)
i := C.vosk_model_find_word(m.model, (*C.char)(cbuf))
return int(i)
}
// VoskSpkModel contains a reference to the C VoskSpkModel
type VoskSpkModel struct {
spkModel *C.struct_VoskSpkModel
}
// NewSpkModel creates a new VoskSpkModel instance
func NewSpkModel(spkModelPath string) (*VoskSpkModel, error) {
internal := C.vosk_spk_model_new(C.CString(spkModelPath))
spkModel := &VoskSpkModel{spkModel: internal}
return spkModel, nil
}
func freeSpkModel(model *VoskSpkModel) {
C.vosk_spk_model_free(model.spkModel)
}
func(s *VoskSpkModel) Free() {
C.vosk_spk_model_free(s.spkModel)
}
// VoskRecognizer contains a reference to the C VoskRecognizer
type VoskRecognizer struct {
rec *C.struct_VoskRecognizer
}
func freeRecognizer(recognizer *VoskRecognizer) {
C.vosk_recognizer_free(recognizer.rec)
}
func (r *VoskRecognizer) Free() {
C.vosk_recognizer_free(r.rec)
}
// NewRecognizer creates a new VoskRecognizer instance
func NewRecognizer(model *VoskModel, sampleRate float64) (*VoskRecognizer, error) {
internal := C.vosk_recognizer_new(model.model, C.float(sampleRate))
rec := &VoskRecognizer{rec: internal}
return rec, nil
}
// NewRecognizerSpk creates a new VoskRecognizer instance with a speaker model.
func NewRecognizerSpk(model *VoskModel, sampleRate float64, spkModel *VoskSpkModel) (*VoskRecognizer, error) {
internal := C.vosk_recognizer_new_spk(model.model, C.float(sampleRate), spkModel.spkModel)
rec := &VoskRecognizer{rec: internal}
return rec, nil
}
// NewRecognizerGrm creates a new VoskRecognizer instance with the phrase list.
func NewRecognizerGrm(model *VoskModel, sampleRate float64, grammer []byte) (*VoskRecognizer, error) {
cbuf := C.CBytes(grammer)
defer C.free(cbuf)
internal := C.vosk_recognizer_new_grm(model.model, C.float(sampleRate), (*C.char)(cbuf))
rec := &VoskRecognizer{rec: internal}
return rec, nil
}
// SetSpkModel adds a speaker model to an already initialized recognizer.
func (r *VoskRecognizer) SetSpkModel(spkModel *VoskSpkModel) {
C.vosk_recognizer_set_spk_model(r.rec, spkModel.spkModel)
}
// SetMaxAlternatives configures the recognizer to output n-best results.
func (r *VoskRecognizer) SetMaxAlternatives(maxAlternatives int) {
C.vosk_recognizer_set_max_alternatives(r.rec, C.int(maxAlternatives))
}
// SetWords enables words with times in the ouput.
func (r *VoskRecognizer) SetWords(words int) {
C.vosk_recognizer_set_words(r.rec, C.int(words))
}
// AcceptWaveform accepts and processes a new chunk of the voice data.
func (r *VoskRecognizer) AcceptWaveform(buffer []byte) int {
cbuf := C.CBytes(buffer)
defer C.free(cbuf)
i := C.vosk_recognizer_accept_waveform(r.rec, (*C.char)(cbuf), C.int(len(buffer)))
return int(i)
}
// Result returns a speech recognition result.
func (r *VoskRecognizer) Result() []byte {
return []byte(C.GoString(C.vosk_recognizer_result(r.rec)))
}
// PartialResult returns a partial speech recognition result.
func (r *VoskRecognizer) PartialResult() []byte {
return []byte(C.GoString(C.vosk_recognizer_partial_result(r.rec)))
}
// FinalResult returns a speech recognition result. Same as result, but doesn't wait
// for silence.
func (r *VoskRecognizer) FinalResult() []byte {
return []byte(C.GoString(C.vosk_recognizer_final_result(r.rec)))
}
// Reset resets the recognizer.
func (r *VoskRecognizer) Reset() {
C.vosk_recognizer_reset(r.rec)
}
// SetLogLevel sets the log level for Kaldi messages.
func SetLogLevel(logLevel int) {
C.vosk_set_log_level(C.int(logLevel))
}
// GPUInit automatically selects a CUDA device and allows multithreading.
func GPUInit() {
C.vosk_gpu_init()
}
// GPUThreadInit inits CUDA device in a multi-threaded environment.
func GPUThreadInit() {
C.vosk_gpu_thread_init()
}
+35 -105
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92375252240C6E3D00DD6076 /* splice.conf */,
);
path = ivector;
sourceTree = "<group>";
};
/* End PBXGroup section */
/* Begin PBXNativeTarget section */
@@ -202,8 +122,6 @@
9237521A240C550B00DD6076 /* Sources */,
9237521B240C550B00DD6076 /* Frameworks */,
9237521C240C550B00DD6076 /* Resources */,
92375265240C6ECF00DD6076 /* CopyFiles */,
9237526D240C6F0400DD6076 /* CopyFiles */,
);
buildRules = (
);
@@ -227,7 +145,7 @@
9237521D240C550B00DD6076 = {
CreatedOnToolsVersion = 8.3.2;
LastSwiftMigration = 0920;
ProvisioningStyle = Automatic;
ProvisioningStyle = Manual;
};
};
};
@@ -254,9 +172,11 @@
isa = PBXResourcesBuildPhase;
buildActionMask = 2147483647;
files = (
92BACED125BE125A00B5CC93 /* vosk-model-small-en-us-0.15 in Resources */,
92375274240C6F1E00DD6076 /* 10001-90210-01803.wav in Resources */,
9237522C240C550B00DD6076 /* LaunchScreen.storyboard in Resources */,
92375229240C550B00DD6076 /* Assets.xcassets in Resources */,
92D86BD6253F823F0040D53F /* vosk-model-spk-0.4 in Resources */,
92375227240C550B00DD6076 /* Main.storyboard in Resources */,
);
runOnlyForDeploymentPostprocessing = 0;
@@ -270,6 +190,7 @@
files = (
92375224240C550B00DD6076 /* ViewController.swift in Sources */,
92375222240C550B00DD6076 /* AppDelegate.swift in Sources */,
92D6B8D325BDFEAC007FF08D /* VoskModel.swift in Sources */,
92375234240C558900DD6076 /* Vosk.swift in Sources */,
);
runOnlyForDeploymentPostprocessing = 0;
@@ -302,7 +223,6 @@
ALWAYS_SEARCH_USER_PATHS = NO;
CLANG_ANALYZER_NONNULL = YES;
CLANG_ANALYZER_NUMBER_OBJECT_CONVERSION = YES_AGGRESSIVE;
CLANG_CXX_LANGUAGE_STANDARD = "gnu++0x";
CLANG_CXX_LIBRARY = "libc++";
CLANG_ENABLE_MODULES = YES;
CLANG_ENABLE_OBJC_ARC = YES;
@@ -324,7 +244,7 @@
CLANG_WARN_SUSPICIOUS_MOVE = YES;
CLANG_WARN_UNREACHABLE_CODE = YES;
CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "iPhone Developer";
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "";
COPY_PHASE_STRIP = NO;
DEBUG_INFORMATION_FORMAT = dwarf;
ENABLE_STRICT_OBJC_MSGSEND = YES;
@@ -361,7 +281,6 @@
ALWAYS_SEARCH_USER_PATHS = NO;
CLANG_ANALYZER_NONNULL = YES;
CLANG_ANALYZER_NUMBER_OBJECT_CONVERSION = YES_AGGRESSIVE;
CLANG_CXX_LANGUAGE_STANDARD = "gnu++0x";
CLANG_CXX_LIBRARY = "libc++";
CLANG_ENABLE_MODULES = YES;
CLANG_ENABLE_OBJC_ARC = YES;
@@ -383,7 +302,7 @@
CLANG_WARN_SUSPICIOUS_MOVE = YES;
CLANG_WARN_UNREACHABLE_CODE = YES;
CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "iPhone Developer";
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "";
COPY_PHASE_STRIP = NO;
DEBUG_INFORMATION_FORMAT = "dwarf-with-dsym";
ENABLE_NS_ASSERTIONS = NO;
@@ -398,6 +317,7 @@
GCC_WARN_UNUSED_VARIABLE = YES;
IPHONEOS_DEPLOYMENT_TARGET = 10.3;
MTL_ENABLE_DEBUG_INFO = NO;
ONLY_ACTIVE_ARCH = YES;
SDKROOT = iphoneos;
SWIFT_OBJC_BRIDGING_HEADER = bridging.h;
SWIFT_OPTIMIZATION_LEVEL = "-Owholemodule";
@@ -412,6 +332,9 @@
buildSettings = {
ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
CLANG_ENABLE_MODULES = YES;
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "iPhone Developer";
CODE_SIGN_STYLE = Manual;
DEVELOPMENT_TEAM = "";
ENABLE_BITCODE = NO;
INFOPLIST_FILE = VoskApiTest/Info.plist;
LD_RUNPATH_SEARCH_PATHS = "$(inherited) @executable_path/Frameworks";
@@ -421,11 +344,13 @@
);
PRODUCT_BUNDLE_IDENTIFIER = com.alphacephei.VoskApiTest;
PRODUCT_NAME = "$(TARGET_NAME)";
PROVISIONING_PROFILE_SPECIFIER = "";
SWIFT_INSTALL_OBJC_HEADER = YES;
SWIFT_OBJC_BRIDGING_HEADER = VoskApiTest/bridging.h;
SWIFT_OPTIMIZATION_LEVEL = "-Onone";
SWIFT_SWIFT3_OBJC_INFERENCE = Default;
SWIFT_VERSION = 4.0;
TARGETED_DEVICE_FAMILY = "1,2";
};
name = Debug;
};
@@ -434,6 +359,9 @@
buildSettings = {
ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
CLANG_ENABLE_MODULES = YES;
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "iPhone Developer";
CODE_SIGN_STYLE = Manual;
DEVELOPMENT_TEAM = "";
ENABLE_BITCODE = NO;
INFOPLIST_FILE = VoskApiTest/Info.plist;
LD_RUNPATH_SEARCH_PATHS = "$(inherited) @executable_path/Frameworks";
@@ -443,10 +371,12 @@
);
PRODUCT_BUNDLE_IDENTIFIER = com.alphacephei.VoskApiTest;
PRODUCT_NAME = "$(TARGET_NAME)";
PROVISIONING_PROFILE_SPECIFIER = "";
SWIFT_INSTALL_OBJC_HEADER = YES;
SWIFT_OBJC_BRIDGING_HEADER = VoskApiTest/bridging.h;
SWIFT_SWIFT3_OBJC_INFERENCE = Default;
SWIFT_VERSION = 4.0;
TARGETED_DEVICE_FAMILY = "1,2";
};
name = Release;
};
@@ -2,6 +2,6 @@
<Workspace
version = "1.0">
<FileRef
location = "self:VoskApiTest.xcodeproj">
location = "self:">
</FileRef>
</Workspace>
+42 -13
View File
@@ -1,6 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13771" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" colorMatched="YES" initialViewController="BYZ-38-t0r">
<device id="retina4_7" orientation="portrait">
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13771" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" colorMatched="YES" initialViewController="bdW-KL-Y8Z">
<device id="retina5_5" orientation="portrait">
<adaptation id="fullscreen"/>
</device>
<dependencies>
@@ -10,23 +10,52 @@
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="tne-QT-ifu">
<scene sceneID="nEc-89-Iqu">
<objects>
<viewController id="BYZ-38-t0r" customClass="ViewController" customModule="VoskApiTest" customModuleProvider="target" sceneMemberID="viewController">
<textView key="view" clipsSubviews="YES" multipleTouchEnabled="YES" contentMode="scaleToFill" editable="NO" textAlignment="natural" id="CtX-mx-X98">
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
<viewController id="bdW-KL-Y8Z" customClass="ViewController" customModule="VoskApiTest" customModuleProvider="target" sceneMemberID="viewController">
<layoutGuides>
<viewControllerLayoutGuide type="top" id="Hyr-Dz-4mU"/>
<viewControllerLayoutGuide type="bottom" id="w4A-5X-uBu"/>
</layoutGuides>
<view key="view" contentMode="scaleToFill" id="m5v-US-bvR">
<rect key="frame" x="0.0" y="0.0" width="414" height="736"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<subviews>
<button opaque="NO" contentMode="scaleToFill" fixedFrame="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="IaT-no-U3i" userLabel="Microphone">
<rect key="frame" x="124" y="34" width="157" height="30"/>
<autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
<state key="normal" title="Recognize Microphone"/>
<connections>
<action selector="runRecognizeMicrohpone:" destination="bdW-KL-Y8Z" eventType="touchUpInside" id="hGB-lz-N2B"/>
</connections>
</button>
<button opaque="NO" contentMode="scaleToFill" fixedFrame="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="GC5-nT-FQR" userLabel="File">
<rect key="frame" x="90" y="84" width="221" height="41"/>
<autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
<state key="normal" title="Recognize File"/>
<connections>
<action selector="runRecognizeFile:" destination="bdW-KL-Y8Z" eventType="touchUpInside" id="xp5-Yi-rnN"/>
</connections>
</button>
<textView clipsSubviews="YES" multipleTouchEnabled="YES" contentMode="scaleToFill" fixedFrame="YES" text="Results here" textAlignment="natural" translatesAutoresizingMaskIntoConstraints="NO" id="w4X-cu-USq">
<rect key="frame" x="11" y="112" width="383" height="569"/>
<autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
<fontDescription key="fontDescription" type="system" pointSize="14"/>
<textInputTraits key="textInputTraits" autocapitalizationType="sentences"/>
</textView>
</subviews>
<color key="backgroundColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
<fontDescription key="fontDescription" type="system" pointSize="14"/>
<textInputTraits key="textInputTraits" autocapitalizationType="sentences"/>
</textView>
</view>
<connections>
<outlet property="mainText" destination="CtX-mx-X98" id="oJy-5J-NKp"/>
<outlet property="mainText" destination="w4X-cu-USq" id="rZS-nz-Wql"/>
<outlet property="recognizeFile" destination="GC5-nT-FQR" id="dRe-tc-IA0"/>
<outlet property="recognizeMicrophone" destination="IaT-no-U3i" id="IuM-aa-pAP"/>
</connections>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="dkx-z0-nzr" sceneMemberID="firstResponder"/>
<placeholder placeholderIdentifier="IBFirstResponder" id="nWA-4D-pA6" userLabel="First Responder" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="32.799999999999997" y="32.833583208395808"/>
<point key="canvasLocation" x="-17.39130434782609" y="-285.32608695652175"/>
</scene>
</scenes>
</document>
+95 -12
View File
@@ -3,30 +3,113 @@
// VoskApiTest
//
// Created by Niсkolay Shmyrev on 01.03.20.
// Copyright © 2020 Alpha Cephei. All rights reserved.
// Copyright © 2020-2021 Alpha Cephei. All rights reserved.
//
import UIKit
import AVFoundation
enum WorkMode {
case stopped
case microphone
case file
}
class ViewController: UIViewController {
@IBOutlet var mainText: UITextView!
override func viewDidLoad() {
super.viewDidLoad()
DispatchQueue.global(qos: .userInitiated).async {
DispatchQueue.main.async {
self.mainText.text = "Processing file..."
var mode: WorkMode!
@IBOutlet weak var recognizeFile: UIButton!
@IBOutlet weak var mainText: UITextView!
@IBOutlet weak var recognizeMicrophone: UIButton!
var audioEngine : AVAudioEngine!
var processingQueue: DispatchQueue!
var model : VoskModel!
func setMode(mode: WorkMode) {
switch mode {
case .stopped:
self.recognizeFile.isEnabled = true
self.recognizeMicrophone.isEnabled = true
self.recognizeMicrophone.setTitle("Recognize Microphone",for: .normal)
case .microphone:
self.recognizeFile.isEnabled = false
self.recognizeMicrophone.isEnabled = true
self.recognizeMicrophone.setTitle("Stop Microphone",for: .normal)
self.mainText.text = ""
case .file:
self.recognizeFile.isEnabled = false
self.recognizeMicrophone.isEnabled = false
self.mainText.text = "Processing file..."
}
self.mode = mode
}
func startAudioEngine() {
do {
// Create a new audio engine.
audioEngine = AVAudioEngine()
let inputNode = audioEngine.inputNode
let formatInput = inputNode.inputFormat(forBus: 0)
let formatPcm = AVAudioFormat.init(commonFormat: AVAudioCommonFormat.pcmFormatInt16, sampleRate: formatInput.sampleRate, channels: 1, interleaved: true)
let recognizer = Vosk(model: model, sampleRate: Float(formatInput.sampleRate))
inputNode.installTap(onBus: 0,
bufferSize: UInt32(formatInput.sampleRate / 10),
format: formatPcm) { buffer, time in
self.processingQueue.async {
let res = recognizer.recognizeData(buffer: buffer)
DispatchQueue.main.async {
self.mainText.text = res + "\n" + self.mainText.text
}
}
}
let vosk = Vosk()
let res = vosk.recognizeFile()
// Start the stream of audio data.
audioEngine.prepare()
try audioEngine.start()
} catch {
print("Unable to start AVAudioEngine: \(error.localizedDescription)")
}
}
func stopAudioEngine() {
audioEngine.stop()
}
@IBAction func runRecognizeMicrohpone(_ sender: Any) {
if (mode == .stopped) {
setMode(mode: .microphone)
startAudioEngine()
} else {
stopAudioEngine()
setMode(mode: .stopped)
}
}
@IBAction func runRecognizeFile(_ sender: Any) {
setMode(mode: .file)
processingQueue.async {
let recognizer = Vosk(model: self.model, sampleRate: 16000.0)
let res = recognizer.recognizeFile()
DispatchQueue.main.async {
self.mainText.text = res
self.setMode(mode: .stopped)
}
}
}
override func viewDidLoad() {
super.viewDidLoad()
setMode(mode: .stopped)
processingQueue = DispatchQueue(label: "recognizerQueue")
model = VoskModel()
}
override func didReceiveMemoryWarning() {
super.didReceiveMemoryWarning()
}
+33 -16
View File
@@ -3,35 +3,52 @@
// VoskApiTest
//
// Created by Niсkolay Shmyrev on 01.03.20.
// Copyright © 2020 Alpha Cephei. All rights reserved.
// Copyright © 2020-2021 Alpha Cephei. All rights reserved.
//
import Foundation
import AVFoundation
public final class Vosk {
var recognizer : OpaquePointer!
init(model: VoskModel, sampleRate: Float) {
recognizer = vosk_recognizer_new_spk(model.model, sampleRate, model.spkModel)
}
deinit {
vosk_recognizer_free(recognizer);
}
func recognizeFile() -> String {
var sres = ""
if let resourcePath = Bundle.main.resourcePath {
let modelPath = resourcePath + "/model-en"
let model = vosk_model_new(modelPath);
let recognizer = vosk_recognizer_new(model, 16000.0)
let audioFile = URL(fileURLWithPath: resourcePath + "/10001-90210-01803.wav")
if let data = try? Data(contentsOf: audioFile) {
let _ = data.withUnsafeBytes {
vosk_recognizer_accept_waveform(recognizer, $0, Int32(data.count))
}
let res = vosk_recognizer_final_result(recognizer);
sres = String(validatingUTF8: res!)!;
print(sres);
let _ = data.withUnsafeBytes {
vosk_recognizer_accept_waveform(recognizer, $0, Int32(data.count))
}
let res = vosk_recognizer_final_result(recognizer);
sres = String(validatingUTF8: res!)!;
print(sres);
}
vosk_recognizer_free(recognizer)
vosk_model_free(model)
}
return sres
}
func recognizeData(buffer : AVAudioPCMBuffer) -> String {
let dataLen = Int(buffer.frameLength * 2)
let channels = UnsafeBufferPointer(start: buffer.int16ChannelData, count: 1)
let endOfSpeech = channels[0].withMemoryRebound(to: Int8.self, capacity: dataLen) {
vosk_recognizer_accept_waveform(recognizer, $0, Int32(dataLen))
}
let res = endOfSpeech == 1 ?vosk_recognizer_result(recognizer) :vosk_recognizer_partial_result(recognizer)
return String(validatingUTF8: res!)!;
}
}
+249 -5
View File
@@ -1,4 +1,4 @@
// Copyright 2020 Alpha Cephei Inc.
// Copyright 2020-2021 Alpha Cephei Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
@@ -12,37 +12,281 @@
// See the License for the specific language governing permissions and
// limitations under the License.
/* This header contains the C API for Vosk speech recognition system */
#ifndef _VOSK_API_H_
#define _VOSK_API_H_
#ifndef VOSK_API_H
#define VOSK_API_H
#ifdef __cplusplus
extern "C" {
#endif
/** Model stores all the data required for recognition
* it contains static data and can be shared across processing
* threads. */
typedef struct VoskModel VoskModel;
/** Speaker model is the same as model but contains the data
* for speaker identification. */
typedef struct VoskSpkModel VoskSpkModel;
/** Recognizer object is the main object which processes data.
* Each recognizer usually runs in own thread and takes audio as input.
* Once audio is processed recognizer returns JSON object as a string
* which represent decoded information - words, confidences, times, n-best lists,
* speaker information and so on */
typedef struct VoskRecognizer VoskRecognizer;
/** Loads model data from the file and returns the model object
*
* @param model_path: the path of the model on the filesystem
* @returns model object or NULL if problem occured */
VoskModel *vosk_model_new(const char *model_path);
/** Releases the model memory
*
* The model object is reference-counted so if some recognizer
* depends on this model, model might still stay alive. When
* last recognizer is released, model will be released too. */
void vosk_model_free(VoskModel *model);
/** Check if a word can be recognized by the model
* @param word: the word
* @returns the word symbol if @param word exists inside the model
* or -1 otherwise.
* Reminding that word symbol 0 is for <epsilon> */
int vosk_model_find_word(VoskModel *model, const char *word);
/** Loads speaker model data from the file and returns the model object
*
* @param model_path: the path of the model on the filesystem
* @returns model object or NULL if problem occured */
VoskSpkModel *vosk_spk_model_new(const char *model_path);
/** Releases the model memory
*
* The model object is reference-counted so if some recognizer
* depends on this model, model might still stay alive. When
* last recognizer is released, model will be released too. */
void vosk_spk_model_free(VoskSpkModel *model);
/** Creates the recognizer object
*
* The recognizers process the speech and return text using shared model data
* @param model VoskModel containing static data for recognizer. Model can be
* shared across recognizers, even running in different threads.
* @param sample_rate The sample rate of the audio you going to feed into the recognizer.
* Make sure this rate matches the audio content, it is a common
* issue causing accuracy problems.
* @returns recognizer object or NULL if problem occured */
VoskRecognizer *vosk_recognizer_new(VoskModel *model, float sample_rate);
VoskRecognizer *vosk_recognizer_new_spk(VoskModel *model, VoskSpkModel *spk_model, float sample_rate);
/** Creates the recognizer object with speaker recognition
*
* With the speaker recognition mode the recognizer not just recognize
* text but also return speaker vectors one can use for speaker identification
*
* @param model VoskModel containing static data for recognizer. Model can be
* shared across recognizers, even running in different threads.
* @param sample_rate The sample rate of the audio you going to feed into the recognizer.
* Make sure this rate matches the audio content, it is a common
* issue causing accuracy problems.
* @param spk_model speaker model for speaker identification
* @returns recognizer object or NULL if problem occured */
VoskRecognizer *vosk_recognizer_new_spk(VoskModel *model, float sample_rate, VoskSpkModel *spk_model);
/** Creates the recognizer object with the phrase list
*
* Sometimes when you want to improve recognition accuracy and when you don't need
* to recognize large vocabulary you can specify a list of phrases to recognize. This
* will improve recognizer speed and accuracy but might return [unk] if user said
* something different.
*
* Only recognizers with lookahead models support this type of quick configuration.
* Precompiled HCLG graph models are not supported.
*
* @param model VoskModel containing static data for recognizer. Model can be
* shared across recognizers, even running in different threads.
* @param sample_rate The sample rate of the audio you going to feed into the recognizer.
* Make sure this rate matches the audio content, it is a common
* issue causing accuracy problems.
* @param grammar The string with the list of phrases to recognize as JSON array of strings,
* for example "["one two three four five", "[unk]"]".
*
* @returns recognizer object or NULL if problem occured */
VoskRecognizer *vosk_recognizer_new_grm(VoskModel *model, float sample_rate, const char *grammar);
/** Adds speaker model to already initialized recognizer
*
* Can add speaker recognition model to already created recognizer. Helps to initialize
* speaker recognition for grammar-based recognizer.
*
* @param spk_model Speaker recognition model */
void vosk_recognizer_set_spk_model(VoskRecognizer *recognizer, VoskSpkModel *spk_model);
/** Configures recognizer to output n-best results
*
* <pre>
* {
* "alternatives": [
* { "text": "one two three four five", "confidence": 0.97 },
* { "text": "one two three for five", "confidence": 0.03 },
* ]
* }
* </pre>
*
* @param max_alternatives - maximum alternatives to return from recognition results
*/
void vosk_recognizer_set_max_alternatives(VoskRecognizer *recognizer, int max_alternatives);
/** Enables words with times in the output
*
* <pre>
* "result" : [{
* "conf" : 1.000000,
* "end" : 1.110000,
* "start" : 0.870000,
* "word" : "what"
* }, {
* "conf" : 1.000000,
* "end" : 1.530000,
* "start" : 1.110000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 1.950000,
* "start" : 1.530000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 2.340000,
* "start" : 1.950000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 2.610000,
* "start" : 2.340000,
* "word" : "one"
* }],
* </pre>
*
* @param words - boolean value
*/
void vosk_recognizer_set_words(VoskRecognizer *recognizer, int words);
/** Accept voice data
*
* accept and process new chunk of voice data
*
* @param data - audio data in PCM 16-bit mono format
* @param length - length of the audio data
* @returns 1 if silence is occured and you can retrieve a new utterance with result method
* 0 if decoding continues
* -1 if exception occured */
int vosk_recognizer_accept_waveform(VoskRecognizer *recognizer, const char *data, int length);
/** Same as above but the version with the short data for language bindings where you have
* audio as array of shorts */
int vosk_recognizer_accept_waveform_s(VoskRecognizer *recognizer, const short *data, int length);
/** Same as above but the version with the float data for language bindings where you have
* audio as array of floats */
int vosk_recognizer_accept_waveform_f(VoskRecognizer *recognizer, const float *data, int length);
/** Returns speech recognition result
*
* @returns the result in JSON format which contains decoded line, decoded
* words, times in seconds and confidences. You can parse this result
* with any json parser
*
* <pre>
* {
* "text" : "what zero zero zero one"
* }
* </pre>
*
* If alternatives enabled it returns result with alternatives, see also vosk_recognizer_set_alternatives().
*
* If word times enabled returns word time, see also vosk_recognizer_set_word_times().
*/
const char *vosk_recognizer_result(VoskRecognizer *recognizer);
/** Returns partial speech recognition
*
* @returns partial speech recognition text which is not yet finalized.
* result may change as recognizer process more data.
*
* <pre>
* {
* "partial" : "cyril one eight zero"
* }
* </pre>
*/
const char *vosk_recognizer_partial_result(VoskRecognizer *recognizer);
/** Returns speech recognition result. Same as result, but doesn't wait for silence
* You usually call it in the end of the stream to get final bits of audio. It
* flushes the feature pipeline, so all remaining audio chunks got processed.
*
* @returns speech result in JSON format.
*/
const char *vosk_recognizer_final_result(VoskRecognizer *recognizer);
/** Resets the recognizer
*
* Resets current results so the recognition can continue from scratch */
void vosk_recognizer_reset(VoskRecognizer *recognizer);
/** Releases recognizer object
*
* Underlying model is also unreferenced and if needed released */
void vosk_recognizer_free(VoskRecognizer *recognizer);
/** Set log level for Kaldi messages
*
* @param log_level the level
* 0 - default value to print info and error messages but no debug
* less than 0 - don't print info messages
* greather than 0 - more verbose mode
*/
void vosk_set_log_level(int log_level);
/**
* Init, automatically select a CUDA device and allow multithreading.
* Must be called once from the main thread.
* Has no effect if HAVE_CUDA flag is not set.
*/
void vosk_gpu_init();
/**
* Init CUDA device in a multi-threaded environment.
* Must be called for each thread.
* Has no effect if HAVE_CUDA flag is not set.
*/
void vosk_gpu_thread_init();
#ifdef __cplusplus
}
#endif
#endif /* _VOSK_API_H_ */
#endif /* VOSK_API_H */
+36
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@@ -0,0 +1,36 @@
//
// Vosk.swift
// VoskApiTest
//
// Created by Niсkolay Shmyrev on 01.03.20.
// Copyright © 2020-2021 Alpha Cephei. All rights reserved.
//
import Foundation
public final class VoskModel {
var model : OpaquePointer!
var spkModel : OpaquePointer!
init() {
// Set to -1 to disable logs
vosk_set_log_level(0);
if let resourcePath = Bundle.main.resourcePath {
let modelPath = resourcePath + "/vosk-model-small-en-us-0.15"
let spkModelPath = resourcePath + "/vosk-model-spk-0.4"
model = vosk_model_new(modelPath)
spkModel = vosk_spk_model_new(spkModelPath)
}
}
deinit {
vosk_model_free(model)
vosk_spk_model_free(spkModel)
}
}
-65
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@@ -1,65 +0,0 @@
KALDI_ROOT ?= $(HOME)/kaldi
CFLAGS := -g -O2 -DPIC -fPIC -Wno-unused-function
CPPFLAGS := -I$(JAVA_HOME)/include -I$(JAVA_HOME)/include/linux -I$(KALDI_ROOT)/src -I$(KALDI_ROOT)/tools/openfst/include -I../src
KALDI_LIBS = \
${KALDI_ROOT}/src/online2/kaldi-online2.a \
${KALDI_ROOT}/src/decoder/kaldi-decoder.a \
${KALDI_ROOT}/src/ivector/kaldi-ivector.a \
${KALDI_ROOT}/src/gmm/kaldi-gmm.a \
${KALDI_ROOT}/src/nnet3/kaldi-nnet3.a \
${KALDI_ROOT}/src/tree/kaldi-tree.a \
${KALDI_ROOT}/src/feat/kaldi-feat.a \
${KALDI_ROOT}/src/lat/kaldi-lat.a \
${KALDI_ROOT}/src/lm/kaldi-lm.a \
${KALDI_ROOT}/src/hmm/kaldi-hmm.a \
${KALDI_ROOT}/src/transform/kaldi-transform.a \
${KALDI_ROOT}/src/cudamatrix/kaldi-cudamatrix.a \
${KALDI_ROOT}/src/matrix/kaldi-matrix.a \
${KALDI_ROOT}/src/fstext/kaldi-fstext.a \
${KALDI_ROOT}/src/util/kaldi-util.a \
${KALDI_ROOT}/src/base/kaldi-base.a \
${KALDI_ROOT}/tools/openfst/lib/libfst.a \
${KALDI_ROOT}/tools/openfst/lib/libfstngram.a \
${KALDI_ROOT}/tools/OpenBLAS/libopenblas.a \
-lgfortran
all: libvosk_jni.so
VOSK_SOURCES = \
vosk_wrap.cc \
../src/kaldi_recognizer.cc \
../src/kaldi_recognizer.h \
../src/model.cc \
../src/model.h \
../src/spk_model.cc \
../src/spk_model.h \
../src/vosk_api.cc \
../src/vosk_api.h
libvosk_jni.so: $(VOSK_SOURCES)
$(CXX) -shared -o $@ $(CPPFLAGS) $(CFLAGS) $(VOSK_SOURCES) $(KALDI_LIBS)
vosk_wrap.cc: ../src/vosk.i
mkdir -p org/kaldi
swig -c++ -I../src \
-java -package org.kaldi \
-outdir org/kaldi -o $@ $<
clean:
$(RM) *.so *_wrap.cc *_wrap.o test/*.class
$(RM) -r org model-en
model-en:
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-model-android-en-us-0.3.tar.gz
tar xf alphacep-model-android-en-us-0.3.tar.gz && rm alphacep-model-android-en-us-0.3.tar.gz
mv alphacep-model-android-en-us-0.3 model-en
model-spk:
wget https://github.com/alphacep/kaldi-android-demo/releases/download/2020-01/alphacep-spk-model-0.3.tar.gz
tar xf alphacep-spk-model-0.3.tar.gz && rm alphacep-spk-model-0.3.tar.gz
mv alphacep-spk-model-0.3 model-spk
run: model-en model-spk
javac test/*.java org/kaldi/*.java
java -Djava.library.path=. -cp . test.DecoderTest
+4 -16
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@@ -1,19 +1,7 @@
Java API sample
Java bindings for Vosk API using jnr-ffi
Doesn't work on Windows or Mac yet, help to prepare the packaged jars is welcome.
See demo project for details, build it with Gradle.
For now to try it:
Download model and unpack as "model" folder in the demo project.
On Linux you can do
1. Build recent kaldi
1. `git clone https://github.com/alphacep/vosk-api`
1. `cd vosk-api/java`
1. `export KALDI_ROOT=<KALDI_ROOT>`
1. `export JAVA_HOME=<JAVA_HOME>`
1. `make`
1. `make run`
For details of the code you can check:
https://github.com/alphacep/vosk-api/blob/master/java/test/DecoderTest.java
Make sure you are using recent JDK and Gradle.
+16
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@@ -0,0 +1,16 @@
plugins {
id 'application'
}
application {
mainClass = 'org.vosk.demo.DecoderDemo'
}
repositories {
mavenCentral()
}
dependencies {
implementation group: 'net.java.dev.jna', name: 'jna', version: '5.7.0'
implementation group: 'com.alphacephei', name: 'vosk', version: '0.3.42+'
}
@@ -0,0 +1,38 @@
package org.vosk.demo;
import java.io.FileInputStream;
import java.io.BufferedInputStream;
import java.io.IOException;
import java.io.InputStream;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.UnsupportedAudioFileException;
import org.vosk.LogLevel;
import org.vosk.Recognizer;
import org.vosk.LibVosk;
import org.vosk.Model;
public class DecoderDemo {
public static void main(String[] argv) throws IOException, UnsupportedAudioFileException {
LibVosk.setLogLevel(LogLevel.DEBUG);
try (Model model = new Model("model");
InputStream ais = AudioSystem.getAudioInputStream(new BufferedInputStream(new FileInputStream("../../python/example/test.wav")));
Recognizer recognizer = new Recognizer(model, 16000)) {
int nbytes;
byte[] b = new byte[4096];
while ((nbytes = ais.read(b)) >= 0) {
if (recognizer.acceptWaveForm(b, nbytes)) {
System.out.println(recognizer.getResult());
} else {
System.out.println(recognizer.getPartialResult());
}
}
System.out.println(recognizer.getFinalResult());
}
}
}
+71
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buildscript {
repositories {
mavenCentral()
}
}
plugins {
id 'java-library'
id 'maven-publish'
id 'com.vanniktech.maven.publish' version '0.18.0'
}
repositories {
mavenCentral()
}
archivesBaseName = 'vosk'
group = 'com.alphacephei'
version = '0.3.42'
mavenPublish {
group = 'com.alphacephei'
version = version
sonatypeHost = 's01'
}
dependencies {
api group: 'net.java.dev.jna', name: 'jna', version: '5.7.0'
testImplementation 'junit:junit:4.13'
}
publishing {
publications {
mavenJava(MavenPublication) {
artifactId = 'vosk'
from components.java
pom {
name = 'Vosk'
description = 'Speech recognition library'
url = 'http://www.alphacephei.com.com/vosk/'
licenses {
license {
name = 'The Apache License, Version 2.0'
url = 'http://www.apache.org/licenses/LICENSE-2.0.txt'
}
}
developers {
developer {
id = 'alphacephei'
name = 'Alpha Cephei Inc'
email = 'contact@alphacephei.com'
}
}
scm {
connection = 'scm:git:git://github.com/alphacep/vosk-api.git'
url = 'https://github.com/alphacep/vosk-api/'
}
}
}
}
}
test {
dependsOn cleanTest
testLogging.showStandardStreams = true
}
java {
withSourcesJar()
withJavadocJar()
}
@@ -0,0 +1,88 @@
package org.vosk;
import com.sun.jna.Native;
import com.sun.jna.Library;
import com.sun.jna.Platform;
import com.sun.jna.Pointer;
import java.io.File;
import java.io.InputStream;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.StandardCopyOption;
public class LibVosk {
private static void unpackDll(File targetDir, String lib) throws IOException {
InputStream source = LibVosk.class.getResourceAsStream("/win32-x86-64/" + lib + ".dll");
Files.copy(source, new File(targetDir, lib + ".dll").toPath(), StandardCopyOption.REPLACE_EXISTING);
}
static {
if (Platform.isWindows()) {
// We have to unpack dependencies
try {
// To get a tmp folder we unpack small library and mark it for deletion
File tmpFile = Native.extractFromResourcePath("/win32-x86-64/empty");
File tmpDir = tmpFile.getParentFile();
new File(tmpDir, tmpFile.getName() + ".x").createNewFile();
// Now unpack dependencies
unpackDll(tmpDir, "libwinpthread-1");
unpackDll(tmpDir, "libgcc_s_seh-1");
unpackDll(tmpDir, "libstdc++-6");
} catch (IOException e) {
// Nothing for now, it will fail on next step
} finally {
Native.register(LibVosk.class, "libvosk");
}
} else {
Native.register(LibVosk.class, "vosk");
}
}
public static native void vosk_set_log_level(int level);
public static native Pointer vosk_model_new(String path);
public static native void vosk_model_free(Pointer model);
public static native Pointer vosk_spk_model_new(String path);
public static native void vosk_spk_model_free(Pointer model);
public static native Pointer vosk_recognizer_new(Model model, float sample_rate);
public static native Pointer vosk_recognizer_new_spk(Pointer model, float sample_rate, Pointer spk_model);
public static native Pointer vosk_recognizer_new_grm(Pointer model, float sample_rate, String grammar);
public static native void vosk_recognizer_set_max_alternatives(Pointer recognizer, int max_alternatives);
public static native void vosk_recognizer_set_words(Pointer recognizer, boolean words);
public static native void vosk_recognizer_set_partial_words(Pointer recognizer, boolean partial_words);
public static native void vosk_recognizer_set_spk_model(Pointer recognizer, Pointer spk_model);
public static native boolean vosk_recognizer_accept_waveform(Pointer recognizer, byte[] data, int len);
public static native boolean vosk_recognizer_accept_waveform_s(Pointer recognizer, short[] data, int len);
public static native boolean vosk_recognizer_accept_waveform_f(Pointer recognizer, float[] data, int len);
public static native String vosk_recognizer_result(Pointer recognizer);
public static native String vosk_recognizer_final_result(Pointer recognizer);
public static native String vosk_recognizer_partial_result(Pointer recognizer);
public static native void vosk_recognizer_reset(Pointer recognizer);
public static native void vosk_recognizer_free(Pointer recognizer);
public static void setLogLevel(LogLevel loglevel) {
vosk_set_log_level(loglevel.getValue());
}
}
@@ -0,0 +1,17 @@
package org.vosk;
public enum LogLevel {
WARNINGS(-1), // Print warning and errors
INFO(0), // Print info, along with warning and error messages, but no debug
DEBUG(1); // Print debug info
private final int value;
LogLevel(int value) {
this.value = value;
}
public int getValue() {
return this.value;
}
}
@@ -0,0 +1,22 @@
package org.vosk;
import java.io.IOException;
import com.sun.jna.PointerType;
public class Model extends PointerType implements AutoCloseable {
public Model() {
}
public Model(String path) throws IOException {
super(LibVosk.vosk_model_new(path));
if (getPointer() == null) {
throw new IOException("Failed to create a model");
}
}
@Override
public void close() {
LibVosk.vosk_model_free(this.getPointer());
}
}
@@ -0,0 +1,71 @@
package org.vosk;
import com.sun.jna.PointerType;
import java.io.IOException;
public class Recognizer extends PointerType implements AutoCloseable {
public Recognizer(Model model, float sampleRate) throws IOException {
super(LibVosk.vosk_recognizer_new(model, sampleRate));
if (getPointer() == null) {
throw new IOException("Failed to create a recognizer");
}
}
public Recognizer(Model model, float sampleRate, SpeakerModel spkModel) {
super(LibVosk.vosk_recognizer_new_spk(model.getPointer(), sampleRate, spkModel.getPointer()));
}
public Recognizer(Model model, float sampleRate, String grammar) {
super(LibVosk.vosk_recognizer_new_grm(model.getPointer(), sampleRate, grammar));
}
public void setMaxAlternatives(int maxAlternatives) {
LibVosk.vosk_recognizer_set_max_alternatives(this.getPointer(), maxAlternatives);
}
public void setWords(boolean words) {
LibVosk.vosk_recognizer_set_words(this.getPointer(), words);
}
public void setPartialWords(boolean partial_words) {
LibVosk.vosk_recognizer_set_partial_words(this.getPointer(), partial_words);
}
public void setSpeakerModel(SpeakerModel spkModel) {
LibVosk.vosk_recognizer_set_spk_model(this.getPointer(), spkModel.getPointer());
}
public boolean acceptWaveForm(byte[] data, int len) {
return LibVosk.vosk_recognizer_accept_waveform(this.getPointer(), data, len);
}
public boolean acceptWaveForm(short[] data, int len) {
return LibVosk.vosk_recognizer_accept_waveform_s(this.getPointer(), data, len);
}
public boolean acceptWaveForm(float[] data, int len) {
return LibVosk.vosk_recognizer_accept_waveform_f(this.getPointer(), data, len);
}
public String getResult() {
return LibVosk.vosk_recognizer_result(this.getPointer());
}
public String getPartialResult() {
return LibVosk.vosk_recognizer_partial_result(this.getPointer());
}
public String getFinalResult() {
return LibVosk.vosk_recognizer_final_result(this.getPointer());
}
public void reset() {
LibVosk.vosk_recognizer_reset(this.getPointer());
}
@Override
public void close() {
LibVosk.vosk_recognizer_free(this.getPointer());
}
}
@@ -0,0 +1,22 @@
package org.vosk;
import com.sun.jna.PointerType;
import java.io.IOException;
public class SpeakerModel extends PointerType implements AutoCloseable {
public SpeakerModel() {
}
public SpeakerModel(String path) throws IOException {
super(LibVosk.vosk_spk_model_new(path));
if (getPointer() == null) {
throw new IOException("Failed to create a speaker model");
}
}
@Override
public void close() {
LibVosk.vosk_spk_model_free(this.getPointer());
}
}
+1
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@@ -0,0 +1 @@
Mainly for work around JNA API
@@ -0,0 +1,103 @@
package org.vosk.test;
import java.io.FileInputStream;
import java.io.BufferedInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import org.junit.Test;
import org.junit.Assert;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.UnsupportedAudioFileException;
import org.vosk.LogLevel;
import org.vosk.Recognizer;
import org.vosk.LibVosk;
import org.vosk.Model;
public class DecoderTest {
@Test
public void decoderTest() throws IOException, UnsupportedAudioFileException {
LibVosk.setLogLevel(LogLevel.DEBUG);
try (Model model = new Model("model");
InputStream ais = AudioSystem.getAudioInputStream(new BufferedInputStream(new FileInputStream("../../python/example/test.wav")));
Recognizer recognizer = new Recognizer(model, 16000)) {
recognizer.setMaxAlternatives(10);
recognizer.setWords(true);
recognizer.setPartialWords(true);
int nbytes;
byte[] b = new byte[4096];
while ((nbytes = ais.read(b)) >= 0) {
if (recognizer.acceptWaveForm(b, nbytes)) {
System.out.println(recognizer.getResult());
} else {
System.out.println(recognizer.getPartialResult());
}
}
System.out.println(recognizer.getFinalResult());
}
Assert.assertTrue(true);
}
@Test
public void decoderTestShort() throws IOException, UnsupportedAudioFileException {
LibVosk.setLogLevel(LogLevel.DEBUG);
try (Model model = new Model("model");
InputStream ais = AudioSystem.getAudioInputStream(new BufferedInputStream(new FileInputStream("../../python/example/test.wav")));
Recognizer recognizer = new Recognizer(model, 16000)) {
int nbytes;
byte[] b = new byte[4096];
short[] s = new short[2048];
while ((nbytes = ais.read(b)) >= 0) {
ByteBuffer.wrap(b).order(ByteOrder.LITTLE_ENDIAN).asShortBuffer().get(s);
if (recognizer.acceptWaveForm(s, nbytes / 2)) {
System.out.println(recognizer.getResult());
} else {
System.out.println(recognizer.getPartialResult());
}
}
System.out.println(recognizer.getFinalResult());
}
Assert.assertTrue(true);
}
@Test
public void decoderTestGrammar() throws IOException, UnsupportedAudioFileException {
LibVosk.setLogLevel(LogLevel.DEBUG);
try (Model model = new Model("model");
InputStream ais = AudioSystem.getAudioInputStream(new BufferedInputStream(new FileInputStream("../../python/example/test.wav")));
Recognizer recognizer = new Recognizer(model, 16000, "[\"one two three four five six seven eight nine zero oh\"]")) {
int nbytes;
byte[] b = new byte[4096];
while ((nbytes = ais.read(b)) >= 0) {
if (recognizer.acceptWaveForm(b, nbytes)) {
System.out.println(recognizer.getResult());
} else {
System.out.println(recognizer.getPartialResult());
}
}
System.out.println(recognizer.getFinalResult());
}
Assert.assertTrue(true);
}
@Test(expected = IOException.class)
public void decoderTestException() throws IOException {
Model model = new Model("model_missing");
}
}
-37
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@@ -1,37 +0,0 @@
package test;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.DataOutputStream;
import java.io.IOException;
import java.net.URL;
import java.nio.*;
import org.kaldi.KaldiRecognizer;
import org.kaldi.Model;
import org.kaldi.SpkModel;
public class DecoderTest {
static {
System.loadLibrary("vosk_jni");
}
public static void main(String args[]) throws IOException {
FileInputStream ais = new FileInputStream(new File("../python/example/test.wav"));
Model model = new Model("model");
SpkModel spkModel = new SpkModel("model-spk");
KaldiRecognizer rec = new KaldiRecognizer(model, spkModel, 16000.0f);
int nbytes;
byte[] b = new byte[4096];
while ((nbytes = ais.read(b)) >= 0) {
if (rec.AcceptWaveform(b)) {
System.out.println(rec.Result());
} else {
System.out.println(rec.PartialResult());
}
}
System.out.println(rec.FinalResult());
}
}
+3
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@@ -0,0 +1,3 @@
demo/model
demo/model-spk
demo/test.wav
+34
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@@ -0,0 +1,34 @@
This is an FFI-NAPI wrapper for the Vosk library.
## Usage
Bindings mostly follow Vosk interface, some methods are not yet fully implemented.
See [demo folder](https://github.com/alphacep/vosk-api/tree/master/nodejs/demo) for
details.
## About
Vosk is an offline open source speech recognition toolkit. It enables
speech recognition for 20+ languages and dialects - English, Indian
English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish,
Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino,
Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish.
More to come.
Vosk models are small (50 Mb) but provide continuous large vocabulary
transcription, zero-latency response with streaming API, reconfigurable
vocabulary and speaker identification.
Vosk supplies speech recognition for chatbots, smart home appliances,
virtual assistants. It can also create subtitles for movies,
transcription for lectures and interviews.
Vosk scales from small devices like Raspberry Pi or Android smartphone to
big clusters.
# Documentation
For installation instructions, examples and documentation visit [Vosk
Website](https://alphacephei.com/vosk). See also our project on
[Github](https://github.com/alphacep/vosk-api).
+33
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@@ -0,0 +1,33 @@
var vosk = require('..')
const fs = require("fs");
const { spawn } = require("child_process");
MODEL_PATH = "model"
FILE_NAME = "test.wav"
SAMPLE_RATE = 16000
BUFFER_SIZE = 4000
if (!fs.existsSync(MODEL_PATH)) {
console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
process.exit()
}
if (process.argv.length > 2)
FILE_NAME = process.argv[2]
vosk.setLogLevel(0);
const model = new vosk.Model(MODEL_PATH);
const rec = new vosk.Recognizer({model: model, sampleRate: SAMPLE_RATE});
const ffmpeg_run = spawn('ffmpeg', ['-loglevel', 'quiet', '-i', FILE_NAME,
'-ar', String(SAMPLE_RATE) , '-ac', '1',
'-f', 's16le', '-bufsize', String(BUFFER_SIZE) , '-']);
ffmpeg_run.stdout.on('data', (stdout) => {
if (rec.acceptWaveform(stdout))
console.log(rec.result());
else
console.log(rec.partialResult());
console.log(rec.finalResult());
});
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@@ -0,0 +1,46 @@
var vosk = require('..')
const fs = require("fs");
var mic = require("mic");
MODEL_PATH = "model"
SAMPLE_RATE = 16000
if (!fs.existsSync(MODEL_PATH)) {
console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
process.exit()
}
vosk.setLogLevel(0);
const model = new vosk.Model(MODEL_PATH);
const rec = new vosk.Recognizer({model: model, sampleRate: SAMPLE_RATE});
var micInstance = mic({
rate: String(SAMPLE_RATE),
channels: '1',
debug: false,
device: 'default',
});
var micInputStream = micInstance.getAudioStream();
micInputStream.on('data', data => {
if (rec.acceptWaveform(data))
console.log(rec.result());
else
console.log(rec.partialResult());
});
micInputStream.on('audioProcessExitComplete', function() {
console.log("Cleaning up");
console.log(rec.finalResult());
rec.free();
model.free();
});
process.on('SIGINT', function() {
console.log("\nStopping");
micInstance.stop();
});
micInstance.start();
+48
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@@ -0,0 +1,48 @@
var vosk = require('..')
const fs = require("fs");
const { Readable } = require("stream");
const wav = require("wav");
MODEL_PATH = "model"
FILE_NAME = "test.wav"
if (!fs.existsSync(MODEL_PATH)) {
console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
process.exit()
}
if (process.argv.length > 2)
FILE_NAME = process.argv[2]
vosk.setLogLevel(0);
const model = new vosk.Model(MODEL_PATH);
const wfReader = new wav.Reader();
const wfReadable = new Readable().wrap(wfReader);
wfReader.on('format', async ({ audioFormat, sampleRate, channels }) => {
if (audioFormat != 1 || channels != 1) {
console.error("Audio file must be WAV format mono PCM.");
process.exit(1);
}
const rec = new vosk.Recognizer({model: model, sampleRate: sampleRate});
rec.setMaxAlternatives(10);
rec.setWords(true);
rec.setPartialWords(true);
for await (const data of wfReadable) {
const end_of_speech = rec.acceptWaveform(data);
if (end_of_speech) {
console.log(JSON.stringify(rec.result(), null, 4));
} else {
console.log(JSON.stringify(rec.partialResult(), null, 4));
}
}
console.log(JSON.stringify(rec.finalResult(rec), null, 4));
rec.free();
});
fs.createReadStream(FILE_NAME, {'highWaterMark': 4096}).pipe(wfReader).on('finish',
function (err) {
model.free();
});
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@@ -0,0 +1,46 @@
var vosk = require('..')
const async = require("async");
const fs = require("fs");
const { Readable } = require("stream");
const wav = require("wav");
MODEL_PATH = "model"
if (!fs.existsSync(MODEL_PATH)) {
console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
process.exit()
}
// Process file 4 times in parallel with a single model
files = Array(10).fill("test.wav")
const model = new vosk.Model(MODEL_PATH)
async.filter(files, function(filePath, callback) {
const wfReader = new wav.Reader();
const wfReadable = new Readable().wrap(wfReader);
wfReader.on('format', async ({ audioFormat, sampleRate, channels }) => {
const rec = new vosk.Recognizer({model: model, sampleRate: sampleRate});
if (audioFormat != 1 || channels != 1) {
console.error("Audio file must be WAV format mono PCM.");
process.exit(1);
}
for await (const data of wfReadable) {
const end_of_speech = await rec.acceptWaveformAsync(data);
if (end_of_speech) {
console.log(rec.result());
}
}
console.log(rec.finalResult(rec));
rec.free();
// Signal we are done without errors
callback(null, true);
});
fs.createReadStream(filePath, {'highWaterMark': 4096}).pipe(wfReader);
}, function(err, results) {
model.free();
console.log("Done!!!!!");
});
+53
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@@ -0,0 +1,53 @@
const vosk = require('..');
const fs = require("fs");
const { Readable } = require("stream");
const wav = require("wav");
MODEL_PATH = "model"
SPEAKER_MODEL_PATH = "model-spk"
FILE_NAME = "test.wav"
if (!fs.existsSync(MODEL_PATH)) {
console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
process.exit()
}
if (!fs.existsSync(SPEAKER_MODEL_PATH)) {
console.log("Please download the speaker model from https://alphacephei.com/vosk/models and unpack as " + SPEAKER_MODEL_PATH + " in the current folder.")
process.exit()
}
if (process.argv.length > 2)
FILE_NAME = process.argv[2]
const model = new vosk.Model(MODEL_PATH);
const speakerModel = new vosk.SpeakerModel(SPEAKER_MODEL_PATH);
const wfReader = new wav.Reader();
const wfReadable = new Readable().wrap(wfReader);
wfReader.on('format', async ({ audioFormat, sampleRate, channels }) => {
if (audioFormat != 1 || channels != 1) {
console.error('Audio file must be WAV format mono PCM.');
process.exit(1);
}
// const rec = new vosk.Recognizer({ model: model,
// speakerModel: speakerModel,
// sampleRate: sampleRate });
const rec = new vosk.Recognizer({model: model, sampleRate: sampleRate});
rec.setSpkModel(speakerModel);
for await (const data of wfReadable) {
const end_of_speech = rec.acceptWaveform(data);
if (end_of_speech) {
console.log(rec.finalResult());
}
}
console.log(rec.finalResult());
rec.free();
});
fs.createReadStream(FILE_NAME, { highWaterMark: 4096 }).pipe(wfReader).on('finish', function (err) {
model.free();
speakerModel.free();
});
+84
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@@ -0,0 +1,84 @@
var vosk = require('..')
const fs = require("fs");
const { spawn } = require("child_process");
const { stringifySync } = require('subtitle')
MODEL_PATH = "model"
FILE_NAME = "test.wav"
SAMPLE_RATE = 16000
BUFFER_SIZE = 4000
if (!fs.existsSync(MODEL_PATH)) {
console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
process.exit()
}
if (process.argv.length > 2)
FILE_NAME = process.argv[2]
vosk.setLogLevel(-1);
const model = new vosk.Model(MODEL_PATH);
const rec = new vosk.Recognizer({model: model, sampleRate: SAMPLE_RATE});
rec.setWords(true);
const ffmpeg_run = spawn('ffmpeg', ['-loglevel', 'quiet', '-i', FILE_NAME,
'-ar', String(SAMPLE_RATE) , '-ac', '1',
'-f', 's16le', '-bufsize', String(BUFFER_SIZE), '-']);
WORDS_PER_LINE = 7
const subs = []
const results = []
ffmpeg_run.stdout.on('data', (stdout) => {
if (rec.acceptWaveform(stdout))
results.push(rec.result());
results.push(rec.finalResult());
});
ffmpeg_run.on('exit', code => {
rec.free();
model.free();
results.forEach(element =>{
if (!element.hasOwnProperty('result'))
return;
const words = element.result;
if (words.length == 1) {
subs.push({
type: 'cue',
data: {
start: words[0].start * 1000,
end: words[0].end * 1000,
text: words[0].word
}
});
return;
}
var start_index = 0;
var text = words[0].word + " ";
for (let i = 1; i < words.length; i++) {
text += words[i].word + " ";
if (i % WORDS_PER_LINE == 0) {
subs.push({
type: 'cue',
data: {
start: words[start_index].start * 1000,
end: words[i].end * 1000,
text: text.slice(0, text.length-1)
}
});
start_index = i;
text = "";
}
}
if (start_index != words.length - 1)
subs.push({
type: 'cue',
data: {
start: words[start_index].start * 1000,
end: words[words.length-1].end * 1000,
text: text
}
});
});
console.log(stringifySync(subs, {format: "SRT"}));
});
+432 -2
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@@ -1,3 +1,433 @@
exports.printMsg = function() {
console.log("This is a message from the Vosk package");
// @ts-check
'use strict'
/**
* @module vosk
*/
const os = require('os');
const path = require('path');
/** @type {import('ffi-napi')} */
const ffi = require('ffi-napi');
/** @type {import('ref-napi')} */
const ref = require('ref-napi');
const vosk_model = ref.types.void;
const vosk_model_ptr = ref.refType(vosk_model);
const vosk_spk_model = ref.types.void;
const vosk_spk_model_ptr = ref.refType(vosk_spk_model);
const vosk_recognizer = ref.types.void;
const vosk_recognizer_ptr = ref.refType(vosk_recognizer);
/**
* @typedef {Object} WordResult
* @property {number} conf The confidence rate in the detection. 0 For unlikely, and 1 for totally accurate.
* @property {number} start The start of the timeframe when the word is pronounced in seconds
* @property {number} end The end of the timeframe when the word is pronounced in seconds
* @property {string} word The word detected
*/
/**
* @typedef {Object} RecognitionResults
* @property {WordResult[]} result Details about the words that have been detected
* @property {string} text The complete sentence that have been detected
*/
/**
* @typedef {Object} SpeakerResults
* @property {number[]} spk A floating vector representing speaker identity. It is usually about 128 numbers which uniquely represent speaker voice.
* @property {number} spk_frames The number of frames used to extract speaker vector. The more frames you have the more reliable is speaker vector.
*/
/**
* @typedef {Object} BaseRecognizerParam
* @property {Model} model The language model to be used
* @property {number} sampleRate The sample rate. Most models are trained at 16kHz
*/
/**
* @typedef {Object} GrammarRecognizerParam
* @property {string[]} grammar The list of sentences to be recognized.
*/
/**
* @typedef {Object} SpeakerRecognizerParam
* @property {SpeakerModel} speakerModel The SpeakerModel that will enable speaker identification
*/
/**
* @template {SpeakerRecognizerParam | GrammarRecognizerParam} T
* @typedef {T extends SpeakerRecognizerParam ? SpeakerResults & RecognitionResults : RecognitionResults} Result
*/
/**
* @typedef {Object} PartialResults
* @property {string} partial The partial sentence that have been detected until now
*/
/** @typedef {string[]} Grammar The list of strings to be recognized */
let soname;
if (os.platform() == 'win32') {
// Update path to load dependent dlls
let currentPath = process.env.Path;
let dllDirectory = path.resolve(path.join(__dirname, "lib", "win-x86_64"));
process.env.Path = currentPath + path.delimiter + dllDirectory;
soname = path.join(__dirname, "lib", "win-x86_64", "libvosk.dll")
} else if (os.platform() == 'darwin') {
soname = path.join(__dirname, "lib", "osx-universal", "libvosk.dylib")
} else {
soname = path.join(__dirname, "lib", "linux-x86_64", "libvosk.so")
}
const libvosk = ffi.Library(soname, {
'vosk_set_log_level': ['void', ['int']],
'vosk_model_new': [vosk_model_ptr, ['string']],
'vosk_model_free': ['void', [vosk_model_ptr]],
'vosk_spk_model_new': [vosk_spk_model_ptr, ['string']],
'vosk_spk_model_free': ['void', [vosk_spk_model_ptr]],
'vosk_recognizer_new': [vosk_recognizer_ptr, [vosk_model_ptr, 'float']],
'vosk_recognizer_new_spk': [vosk_recognizer_ptr, [vosk_model_ptr, 'float', vosk_spk_model_ptr]],
'vosk_recognizer_new_grm': [vosk_recognizer_ptr, [vosk_model_ptr, 'float', 'string']],
'vosk_recognizer_free': ['void', [vosk_recognizer_ptr]],
'vosk_recognizer_set_max_alternatives': ['void', [vosk_recognizer_ptr, 'int']],
'vosk_recognizer_set_words': ['void', [vosk_recognizer_ptr, 'bool']],
'vosk_recognizer_set_partial_words': ['void', [vosk_recognizer_ptr, 'bool']],
'vosk_recognizer_set_spk_model': ['void', [vosk_recognizer_ptr, vosk_spk_model_ptr]],
'vosk_recognizer_accept_waveform': ['bool', [vosk_recognizer_ptr, 'pointer', 'int']],
'vosk_recognizer_result': ['string', [vosk_recognizer_ptr]],
'vosk_recognizer_final_result': ['string', [vosk_recognizer_ptr]],
'vosk_recognizer_partial_result': ['string', [vosk_recognizer_ptr]],
'vosk_recognizer_reset': ['void', [vosk_recognizer_ptr]],
});
/**
* Set log level for Kaldi messages
* @param {number} level The higher, the more verbose. 0 for infos and errors. Less than 0 for silence.
*/
function setLogLevel(level) {
libvosk.vosk_set_log_level(level);
}
/**
* Build a Model from a model file.
* @see models [models](https://alphacephei.com/vosk/models)
*/
class Model {
/**
* Build a Model to be used with the voice recognition. Each language should have it's own Model
* for the speech recognition to work.
* @param {string} modelPath The abstract pathname to the model
* @see models [models](https://alphacephei.com/vosk/models)
*/
constructor(modelPath) {
/**
* Store the handle.
* For internal use only
* @type {unknown}
*/
this.handle = libvosk.vosk_model_new(modelPath);
}
/**
* Releases the model memory
*
* The model object is reference-counted so if some recognizer
* depends on this model, model might still stay alive. When
* last recognizer is released, model will be released too.
*/
free() {
libvosk.vosk_model_free(this.handle);
}
}
/**
* Build a Speaker Model from a speaker model file.
* The Speaker Model enables speaker identification.
* @see models [models](https://alphacephei.com/vosk/models)
*/
class SpeakerModel {
/**
* Loads speaker model data from the file and returns the model object
*
* @param {string} modelPath the path of the model on the filesystem
* @see models [models](https://alphacephei.com/vosk/models)
*/
constructor(modelPath) {
/**
* Store the handle.
* For internal use only
* @type {unknown}
*/
this.handle = libvosk.vosk_spk_model_new(modelPath);
}
/**
* Releases the model memory
*
* The model object is reference-counted so if some recognizer
* depends on this model, model might still stay alive. When
* last recognizer is released, model will be released too.
*/
free() {
libvosk.vosk_spk_model_free(this.handle);
}
}
/**
* Helper to narrow down type while using `hasOwnProperty`.
* @see hasOwnProperty [typescript issue](https://fettblog.eu/typescript-hasownproperty/)
* @template {Object} Obj
* @template {PropertyKey} Key
* @param {Obj} obj
* @param {Key} prop
* @returns {obj is Obj & Record<Key, unknown>}
*/
function hasOwnProperty(obj, prop) {
return obj.hasOwnProperty(prop)
}
/**
* @template T
* @template U
* @typedef {{ [P in Exclude<keyof T, keyof U>]?: never }} Without
*/
/**
* @template T
* @template U
* @typedef {(T | U) extends object ? (Without<T, U> & U) | (Without<U, T> & T) : T | U} XOR
*/
/**
* Create a Recognizer that will be able to transform audio streams into text using a Model.
* @template {XOR<SpeakerRecognizerParam, Partial<GrammarRecognizerParam>>} T extra parameter
* @see Model
*/
class Recognizer {
/**
* Create a Recognizer that will handle speech to text recognition.
* @constructor
* @param {T & BaseRecognizerParam} param The Recognizer parameters
*
* Sometimes when you want to improve recognition accuracy and when you don't need
* to recognize large vocabulary you can specify a list of phrases to recognize. This
* will improve recognizer speed and accuracy but might return [unk] if user said
* something different.
*
* Only recognizers with lookahead models support this type of quick configuration.
* Precompiled HCLG graph models are not supported.
*/
constructor(param) {
const { model, sampleRate } = param
// Prevent the user to receive unpredictable results
if (hasOwnProperty(param, 'speakerModel') && hasOwnProperty(param, 'grammar')) {
throw new Error('grammar and speakerModel cannot be used together for now.')
}
/**
* Store the handle.
* For internal use only
* @type {unknown}
*/
this.handle = hasOwnProperty(param, 'speakerModel')
? libvosk.vosk_recognizer_new_spk(model.handle, sampleRate, param.speakerModel.handle)
: hasOwnProperty(param, 'grammar')
? libvosk.vosk_recognizer_new_grm(model.handle, sampleRate, JSON.stringify(param.grammar))
: libvosk.vosk_recognizer_new(model.handle, sampleRate);
}
/**
* Releases the model memory
*
* The model object is reference-counted so if some recognizer
* depends on this model, model might still stay alive. When
* last recognizer is released, model will be released too.
*/
free() {
libvosk.vosk_recognizer_free(this.handle);
}
/** Configures recognizer to output n-best results
*
* <pre>
* {
* "alternatives": [
* { "text": "one two three four five", "confidence": 0.97 },
* { "text": "one two three for five", "confidence": 0.03 },
* ]
* }
* </pre>
*
* @param max_alternatives - maximum alternatives to return from recognition results
*/
setMaxAlternatives(max_alternatives) {
libvosk.vosk_recognizer_set_max_alternatives(this.handle, max_alternatives);
}
/** Configures recognizer to output words with times
*
* <pre>
* "result" : [{
* "conf" : 1.000000,
* "end" : 1.110000,
* "start" : 0.870000,
* "word" : "what"
* }, {
* "conf" : 1.000000,
* "end" : 1.530000,
* "start" : 1.110000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 1.950000,
* "start" : 1.530000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 2.340000,
* "start" : 1.950000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 2.610000,
* "start" : 2.340000,
* "word" : "one"
* }],
* </pre>
*
* @param words - boolean value
*/
setWords(words) {
libvosk.vosk_recognizer_set_words(this.handle, words);
}
/** Same as above, but for partial results*/
setPartialWords(partial_words) {
libvosk.vosk_recognizer_set_partial_words(this.handle, partial_words);
}
/** Adds speaker recognition model to already created recognizer. Helps to initialize
* speaker recognition for grammar-based recognizer.
*
* @param spk_model Speaker recognition model
*/
setSpkModel(spk_model) {
libvosk.vosk_recognizer_set_spk_model(this.handle, spk_model.handle);
}
/**
* Accept voice data
*
* accept and process new chunk of voice data
*
* @param {Buffer} data audio data in PCM 16-bit mono format
* @returns true if silence is occured and you can retrieve a new utterance with result method
*/
acceptWaveform(data) {
return libvosk.vosk_recognizer_accept_waveform(this.handle, data, data.length);
};
/**
* Accept voice data
*
* accept and process new chunk of voice data
*
* @param {Buffer} data audio data in PCM 16-bit mono format
* @returns true if silence is occured and you can retrieve a new utterance with result method
*/
acceptWaveformAsync(data) {
return new Promise((resolve, reject) => {
libvosk.vosk_recognizer_accept_waveform.async(this.handle, data, data.length, function(err, result) {
if (err) {
reject(err);
} else {
resolve(result);
}
});
});
};
/** Returns speech recognition result in a string
*
* @returns the result in JSON format which contains decoded line, decoded
* words, times in seconds and confidences. You can parse this result
* with any json parser
* <pre>
* {
* "result" : [{
* "conf" : 1.000000,
* "end" : 1.110000,
* "start" : 0.870000,
* "word" : "what"
* }, {
* "conf" : 1.000000,
* "end" : 1.530000,
* "start" : 1.110000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 1.950000,
* "start" : 1.530000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 2.340000,
* "start" : 1.950000,
* "word" : "zero"
* }, {
* "conf" : 1.000000,
* "end" : 2.610000,
* "start" : 2.340000,
* "word" : "one"
* }],
* "text" : "what zero zero zero one"
* }
* </pre>
*/
resultString() {
return libvosk.vosk_recognizer_result(this.handle);
};
/**
* Returns speech recognition results
* @returns {Result<T>} The results
*/
result() {
return JSON.parse(libvosk.vosk_recognizer_result(this.handle));
};
/**
* speech recognition text which is not yet finalized.
* result may change as recognizer process more data.
*
* @returns {PartialResults} The partial results
*/
partialResult() {
return JSON.parse(libvosk.vosk_recognizer_partial_result(this.handle));
};
/**
* Returns speech recognition result. Same as result, but doesn't wait for silence
* You usually call it in the end of the stream to get final bits of audio. It
* flushes the feature pipeline, so all remaining audio chunks got processed.
*
* @returns {Result<T>} speech result.
*/
finalResult() {
return JSON.parse(libvosk.vosk_recognizer_final_result(this.handle));
};
/**
*
* Resets current results so the recognition can continue from scratch
*/
reset() {
libvosk.vosk_recognizer_reset(this.handle);
}
}
exports.setLogLevel = setLogLevel
exports.Model = Model
exports.SpeakerModel = SpeakerModel
exports.Recognizer = Recognizer
+13 -4
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@@ -1,7 +1,7 @@
{
"name": "vosk",
"version": "0.1.0",
"description": "Node binding for continuous voice recoginition through pocketsphinx.",
"version": "0.3.42",
"description": "Node binding for continuous offline voice recoginition with Vosk library.",
"repository": {
"type": "git",
"url": "git://github.com/alphacep/vosk-api.git"
@@ -13,6 +13,15 @@
"voice"
],
"author": "Alpha Cephei Inc.",
"license": "Apache 2.0",
"engines": { "node" : ">= 12.x.x" }
"license": "Apache-2.0",
"engines": {
"node": ">= 12.x.x"
},
"dependencies": {
"async": "^3.2.0",
"ffi-napi": "^4.0.3",
"mic": "^2.1.2",
"ref-napi": ">=2.0.0",
"wav": "^1.0.2"
}
}
-51
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@@ -1,51 +0,0 @@
cmake_minimum_required(VERSION 3.12.0)
project(vosk)
set(TOP_SRCDIR "${CMAKE_SOURCE_DIR}/..")
if("x$ENV{WHEEL_FLAGS}" STREQUAL "x")
find_package (Python3 COMPONENTS Interpreter Development)
else()
# docker case
set(Python3_INCLUDE_DIRS "")
set(TOP_SRCDIR "/io")
endif()
set(KALDI_ROOT "$ENV{KALDI_ROOT}")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -DFST_NO_DYNAMIC_LINKING")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} $ENV{WHEEL_FLAGS}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${CMAKE_C_FLAGS} -std=c++11")
include_directories("${TOP_SRCDIR}/src" "${KALDI_ROOT}/src" "${KALDI_ROOT}/tools/openfst/include" ${Python3_INCLUDE_DIRS})
find_package(SWIG REQUIRED)
include(${SWIG_USE_FILE})
swig_add_library(vosk TYPE SHARED LANGUAGE Python OUTPUT_DIR "${CMAKE_LIBRARY_OUTPUT_DIRECTORY}" OUTFILE_DIR "."
SOURCES "${TOP_SRCDIR}/src/kaldi_recognizer.cc"
"${TOP_SRCDIR}/src/spk_model.cc"
"${TOP_SRCDIR}/src/model.cc"
"${TOP_SRCDIR}/src/vosk_api.cc"
"${TOP_SRCDIR}/src/vosk.i")
swig_link_libraries(vosk
${KALDI_ROOT}/src/online2/kaldi-online2.a
${KALDI_ROOT}/src/decoder/kaldi-decoder.a
${KALDI_ROOT}/src/ivector/kaldi-ivector.a
${KALDI_ROOT}/src/gmm/kaldi-gmm.a
${KALDI_ROOT}/src/nnet3/kaldi-nnet3.a
${KALDI_ROOT}/src/tree/kaldi-tree.a
${KALDI_ROOT}/src/feat/kaldi-feat.a
${KALDI_ROOT}/src/lat/kaldi-lat.a
${KALDI_ROOT}/src/lm/kaldi-lm.a
${KALDI_ROOT}/src/hmm/kaldi-hmm.a
${KALDI_ROOT}/src/transform/kaldi-transform.a
${KALDI_ROOT}/src/cudamatrix/kaldi-cudamatrix.a
${KALDI_ROOT}/src/matrix/kaldi-matrix.a
${KALDI_ROOT}/src/fstext/kaldi-fstext.a
${KALDI_ROOT}/src/util/kaldi-util.a
${KALDI_ROOT}/src/base/kaldi-base.a
${KALDI_ROOT}/tools/openfst/lib/libfst.a
${KALDI_ROOT}/tools/openfst/lib/libfstngram.a
${KALDI_ROOT}/tools/OpenBLAS/libopenblas.a
-lgfortran -lstdc++)
set_target_properties(_vosk PROPERTIES LINK_FLAGS_RELEASE -s)
+24 -2
View File
@@ -1,3 +1,25 @@
Python module for vosk-api
This is a Python module for Vosk.
See for details https://github.com/alphacep/vosk-api
Vosk is an offline open source speech recognition toolkit. It enables
speech recognition for 20+ languages and dialects - English, Indian
English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish,
Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino,
Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish.
More to come.
Vosk models are small (50 Mb) but provide continuous large vocabulary
transcription, zero-latency response with streaming API, reconfigurable
vocabulary and speaker identification.
Vosk supplies speech recognition for chatbots, smart home appliances,
virtual assistants. It can also create subtitles for movies,
transcription for lectures and interviews.
Vosk scales from small devices like Raspberry Pi or Android smartphone to
big clusters.
# Documentation
For installation instructions, examples and documentation visit [Vosk
Website](https://alphacephei.com/vosk). See also our project on
[Github](https://github.com/alphacep/vosk-api).
-76
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@@ -1,76 +0,0 @@
# From https://github.com/raydouglass/cmake_setuptools
import os
import subprocess
import shutil
import sys
from setuptools import Extension
from setuptools.command.build_ext import build_ext
from setuptools.command.build_py import build_py
CMAKE_EXE = os.environ.get('CMAKE_EXE', shutil.which('cmake'))
def check_for_cmake():
if not CMAKE_EXE:
print('cmake executable not found. '
'Set CMAKE_EXE environment or update your path')
sys.exit(1)
class CMakeExtension(Extension):
"""
setuptools.Extension for cmake
"""
def __init__(self, name, pkg_name, sourcedir=''):
check_for_cmake()
Extension.__init__(self, name, sources=[])
self.sourcedir = os.path.abspath(sourcedir)
self.pkg_name = pkg_name
class CMakeBuildExt(build_ext):
"""
setuptools build_exit which builds using cmake & make
You can add cmake args with the CMAKE_COMMON_VARIABLES environment variable
"""
def build_extension(self, ext):
check_for_cmake()
if isinstance(ext, CMakeExtension):
output_dir = os.path.abspath(
os.path.dirname(self.get_ext_fullpath(ext.pkg_name + "/" + ext.name)))
build_type = 'Debug' if self.debug else 'Release'
cmake_args = [CMAKE_EXE,
ext.sourcedir,
'-Wno-dev',
'-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=' + output_dir,
'-DCMAKE_BUILD_TYPE=' + build_type]
cmake_args.extend(
[x for x in
os.environ.get('CMAKE_COMMON_VARIABLES', '').split(' ')
if x])
env = os.environ.copy()
if not os.path.exists(self.build_temp):
os.makedirs(self.build_temp)
subprocess.check_call(cmake_args,
cwd=self.build_temp,
env=env)
subprocess.check_call(['make', 'VERBOSE=1', ext.name],
cwd=self.build_temp,
env=env)
print()
else:
super().build_extension(ext)
class CMakeBuildExtFirst(build_py):
def run(self):
self.run_command("build_ext")
return super().run()
__all__ = ['CMakeBuildExt', 'CMakeExtension', 'CMakeBuildExtFirst']
+30
View File
@@ -0,0 +1,30 @@
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer, SetLogLevel
import sys
import os
import wave
import json
SetLogLevel(0)
wf = wave.open(sys.argv[1], "rb")
if wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getcomptype() != "NONE":
print ("Audio file must be WAV format mono PCM.")
exit (1)
model = Model(lang="en-us")
rec = KaldiRecognizer(model, wf.getframerate())
rec.SetMaxAlternatives(10)
rec.SetWords(True)
while True:
data = wf.readframes(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
print(json.loads(rec.Result()))
else:
print(json.loads(rec.PartialResult()))
print(json.loads(rec.FinalResult()))

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