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100 Commits

Author SHA1 Message Date
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
Nickolay Shmyrev 80e60b9118 LM Rescoring 2020-04-28 22:17:34 +02:00
Nickolay Shmyrev e3a95a44bc Added Turkish model 2020-04-28 10:10:35 +02:00
Nickolay Shmyrev 86caf526f5 New model layout and model config file with beams for decoding 2020-04-28 01:06:41 +02:00
Nickolay Shmyrev e09f32b4b4 Properly stop listening so it can continue later 2020-04-27 09:00:32 +02:00
Nickolay Shmyrev 3803ab345d Proper reference couting of the models to avoid memory issus 2020-04-23 23:37:52 +02:00
Nickolay V. Shmyrev 889b43136f Update README.zh.md 2020-04-23 12:43:00 +02:00
John Baber-Lucero b517cf46af Fix some grammar/punctuation 2020-04-23 00:28:34 -04:00
Nickolay Shmyrev ffd810fe00 Fix threading bug 2020-04-22 22:15:45 +02:00
Nickolay V. Shmyrev a1a0ed70a1 Update README.zh.md 2020-04-22 18:29:01 +03:00
Nickolay Shmyrev 1554d9ede7 Added per-language readme 2020-04-22 13:21:36 +02:00
Nickolay Shmyrev 6f3190d83d Version 0.3.4 and arm wheels for python 3.6 2020-04-21 11:38:56 +02:00
Nickolay Shmyrev 3caaa32ec0 How to ask for the accuracy updates 2020-04-20 23:11:52 +02:00
Nickolay Shmyrev 3facf3ccf5 UI updates 2020-04-20 11:08:18 +03:00
Nickolay Shmyrev fad954e6e3 Full iOS project 2020-04-19 22:48:47 +03:00
Nickolay Shmyrev c4809cb618 Added Vietnamese model 2020-04-19 20:14:05 +02:00
Nickolay Shmyrev a241423baf Added iOS bits 2020-04-18 17:34:03 +03:00
Nickolay Shmyrev 1e9421dd38 Add a note about iOS 2020-04-18 15:41:51 +02:00
Nickolay Shmyrev b09ffda760 Fixes links and issue #59 2020-04-11 22:15:46 +02:00
Nickolay Shmyrev aeff663a7c Fix pocketsphinx references in Android sources 2020-04-09 21:50:38 +02:00
Nickolay Shmyrev fcd17fcd4c Added Russian model 0.9 2020-04-07 17:48:29 +02:00
Nickolay Shmyrev feffb2711d Repair travis build 2020-04-04 20:49:06 +02:00
Nickolay Shmyrev f76e5b592f kaldi-ru-0.8 2020-04-04 10:27:02 +02:00
Nickolay Shmyrev 71bdc900e3 C-only wrapper 2020-04-04 10:22:01 +02:00
Nickolay Shmyrev 96bbf5abc2 Add C API 2020-04-04 10:04:49 +02:00
Nickolay Shmyrev df9424a228 Introduce pure C api to deal with Windows runtime issues and make it easy to wrap in Swift 2020-04-04 00:35:56 +02:00
Nickolay Shmyrev 3310acaf54 Add lm to kaldi-android 2020-03-28 22:45:38 +01:00
Nickolay V. Shmyrev e8722d462d Merge pull request #54 from andremendesc/master
Fixes folder name instruction for python model on microphone test
2020-03-25 08:37:25 +03:00
André Mendes 14b2c13ed6 Fixes folder name instruction for python model on microphone test 2020-03-25 01:01:23 -03:00
Nickolay Shmyrev 19af324096 Small fix by Funny Jingl 2020-03-19 23:24:41 +01:00
Nickolay Shmyrev 0ca7b94e08 Add link on kaldi-ru-0.7 2020-03-19 20:14:41 +01:00
Nickolay Shmyrev 04ed310229 Move models list to doc 2020-03-15 22:39:57 +01:00
Nickolay Shmyrev 7ac33d521c Added information about models 2020-03-15 22:27:47 +01:00
Nickolay V. Shmyrev 08ada63da4 Added note about other projects 2020-03-15 02:48:49 +03:00
Nickolay Shmyrev cef3fd72fb Disable NEON fpu on ARMv6
Fixes issue #46
2020-03-10 00:24:57 +01:00
Nayan Kalita bca0b86e37 android build support on macOS 2020-03-06 20:57:56 +05:30
Nickolay V. Shmyrev bf973ff434 Merge pull request #43 from camillem/patch-1
Typo in folder name
2020-03-02 15:47:25 +03:00
camillem a172d60b20 Typo in folder name 2020-03-02 13:46:34 +01:00
Nickolay Shmyrev 060e4395c2 Fix repeating results issue #42
Thanks to Yondu Tsai
2020-03-02 13:41:27 +01:00
Nickolay Shmyrev 03f1417454 Added small readme 2020-03-01 09:12:09 +01:00
65 changed files with 2398 additions and 630 deletions
+25 -2
View File
@@ -24,14 +24,37 @@ wheelhouse
__pycache__
*.egg-info
python/dist
python/vosk/*.cc
python/vosk/*.c
python/vosk/*.h
python/vosk/*.i
python/vosk/vosk.py
python/vosk/vosk_wrap.cpp
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
java/model-spk/
java/model/
# CSharp
csharp/gen
csharp/*.exe
csharp/*.cc
csharp/*.c
csharp/model/
csharp/test.wav
# Node
nodejs/vosk_wrap.cc
nodejs/example/model
nodejs/example/test.wav
nodejs/node_modules
nodejs/package-lock.json
nodejs/build
+17 -105
View File
@@ -1,114 +1,26 @@
Vosk is an open source speech recognition toolkit which supports 9
languages - English, German, French, Spanish, Portuguese, Chinese,
Russian, Turkish, Vietnamese. Vosk works offline with small (50 Mb), but
accurate model, zero-latency response with streaming API, reconfigurable
vocabulary and speaker identification.
### Installation and usage
For Vosk installation instructions, examples and turorial and documentation visit https://alphacephei.com/vosk
### Build
[![Build Status](https://travis-ci.com/alphacep/vosk-api.svg?branch=master)](https://travis-ci.com/alphacep/vosk-api)
Language bindings for Vosk and Kaldi to access speech recognition from various languages and on various platforms
### Models for different languages
* Python on Linux, Windows and RPi
* Node
* Android
* iOS
For information about models see [the documentation on available models](https://alphacephei.com/vosk/models.html).
## Android build
### Contact Us
```
cd android
gradle build
```
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.
## 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
```
## 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
```
#### 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
```
## 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
python3 ./test_simple.py test.wav
```
There are models for other languages (English, Chinese, Spanish, Portuguese, German, French, Russian) available too at https://github.com/alphacep/kaldi-android-demo/releases
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)
## Contact Us
If you have any questions, feel free to
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)
* We have a Wechat group which is pretty big, so it is invitation-only. Mail us to join the group and provide some information about yourself.
+6
View File
@@ -8,6 +8,9 @@ set(KALDI_SUFFIX "arm_32")
elseif ("x${ANDROID_ABI}" STREQUAL "xarm64-v8a")
set(OPENBLAS_ARCH "armv8")
set(KALDI_SUFFIX "arm_64")
elseif ("x${ANDROID_ABI}" STREQUAL "xx86")
set(OPENBLAS_ARCH "atom")
set(KALDI_SUFFIX "x86")
else ("x${ANDROID_ABI}" STREQUAL "xarmeabi-v7a")
set(OPENBLAS_ARCH "atom")
set(KALDI_SUFFIX "x86_64")
@@ -23,6 +26,8 @@ set(API_SOURCES
"${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")
@@ -43,6 +48,7 @@ target_link_libraries( kaldi_jni
${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
+30 -19
View File
@@ -31,36 +31,38 @@ fi
set -x
OS_NAME=`echo $(uname -s) | tr '[:upper:]' '[:lower:]'`
ANDROID_NDK_HOME=$ANDROID_SDK_HOME/ndk-bundle
ANDROID_TOOLCHAIN_PATH=$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/linux-x86_64
ANDROID_TOOLCHAIN_PATH=$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/${OS_NAME}-x86_64
WORKDIR_X86=`pwd`/build/kaldi_x86
WORKDIR_X86_64=`pwd`/build/kaldi_x86_64
WORKDIR_ARM32=`pwd`/build/kaldi_arm_32
WORKDIR_ARM64=`pwd`/build/kaldi_arm_64
PATH=$PATH:$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/linux-x86_64/bin
PATH=$PATH:$ANDROID_NDK_HOME/toolchains/llvm/prebuilt/${OS_NAME}-x86_64/bin
OPENFST_VERSION=1.6.7
mkdir -p $WORKDIR_ARM64/local/lib $WORKDIR_ARM32/local/lib $WORKDIR_X86_64/local/lib
mkdir -p $WORKDIR_ARM64/local/lib $WORKDIR_ARM32/local/lib $WORKDIR_X86_64/local/lib $WORKDIR_X86/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 && \
sed -i.bak -e 's/APP_STL := gnustl_static/APP_STL := c++_static/g' jni/Application.mk && \
sed -i.bak -e 's/android-10/android-21/g' project.properties && \
sed -i.bak -e 's/APP_ABI := armeabi armeabi-v7a/APP_ABI := armeabi-v7a arm64-v8a x86_64 x86/g' jni/Application.mk && \
sed -i.bak -e 's/LOCAL_MODULE:= testlapack/#LOCAL_MODULE:= testlapack/g' jni/Android.mk && \
sed -i.bak -e 's/LOCAL_SRC_FILES:= testclapack.cpp/#LOCAL_SRC_FILES:= testclapack.cpp/g' jni/Android.mk && \
sed -i.bak -e 's/LOCAL_STATIC_LIBRARIES := lapack/#LOCAL_STATIC_LIBRARIES := lapack/g' jni/Android.mk && \
sed -i.bak -e '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
cp obj/local/x86/*.a ${WORKDIR_X86}/local/lib
# Architecture-specific part
for arch in arm32 arm64 x86_64; do
for arch in arm32 arm64 x86_64 x86; do
#for arch in x86_64; do
case $arch in
@@ -91,6 +93,15 @@ case $arch in
CXX=x86_64-linux-android21-clang++
ARCHFLAGS=""
;;
x86)
BLAS_ARCH=ATOM
WORKDIR=$WORKDIR_X86
HOST=i686-linux-android
AR=i686-linux-android-ar
CC=i686-linux-android21-clang
CXX=i686-linux-android21-clang++
ARCHFLAGS=""
;;
esac
# openblas first
@@ -101,12 +112,9 @@ 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-${OPENFST_VERSION}
git clone https://github.com/alphacep/openfst
cd openfst
autoreconf -i
CXX=$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
@@ -117,6 +125,9 @@ make install
cd $WORKDIR
git clone -b android-mix --single-branch https://github.com/alphacep/kaldi
cd $WORKDIR/kaldi/src
if [ "`uname`" == "Darwin" ]; then
sed -i.bak -e 's/libfst.dylib/libfst.a/' configure
fi
CXX=$CXX CXXFLAGS="$ARCHFLAGS -O3 -DFST_NO_DYNAMIC_LINKING" ./configure --use-cuda=no \
--mathlib=OPENBLAS --shared \
@@ -125,6 +136,6 @@ CXX=$CXX CXXFLAGS="$ARCHFLAGS -O3 -DFST_NO_DYNAMIC_LINKING" ./configure --use-cu
--fst-root=${WORKDIR}/local --fst-version=${OPENFST_VERSION}
make -j 8 depend
make -j 8 online2
make -j 8 online2 lm
done
+1 -1
View File
@@ -31,7 +31,7 @@ android {
}
}
ndk {
abiFilters 'armeabi-v7a', 'arm64-v8a', 'x86_64'
abiFilters 'armeabi-v7a', 'arm64-v8a', 'x86_64', 'x86'
}
}
sourceSets {
+1 -1
View File
@@ -1,3 +1,3 @@
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android" package="edu.cmu.pocketsphinx">
<manifest xmlns:android="http://schemas.android.com/apk/res/android" package="org.kaldi">
</manifest>
@@ -241,10 +241,6 @@ public class Assets {
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());
@@ -252,13 +248,11 @@ public class Assets {
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);
@@ -31,7 +31,7 @@ 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
* Pocketsphinx engine. Recognition events are passed to a client using
* VOSK engine. Recognition events are passed to a client using
* {@link RecognitionListener}
*
*/
@@ -74,6 +74,22 @@ public class SpeechRecognizer {
}
}
public SpeechRecognizer(Model model, SpkModel spkModel) throws IOException {
recognizer = new KaldiRecognizer(model, spkModel, 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.
*/
@@ -148,8 +164,7 @@ public class SpeechRecognizer {
public boolean stop() {
boolean result = stopRecognizerThread();
if (result) {
Log.i(TAG, "Stop recognition");
mainHandler.post(new ResultEvent(recognizer.FinalResult(), true));
mainHandler.post(new ResultEvent(recognizer.Result(), true));
}
return result;
}
@@ -162,10 +177,7 @@ public class SpeechRecognizer {
*/
public boolean cancel() {
boolean result = stopRecognizerThread();
if (result) {
Log.i(TAG, "Cancel recognition");
}
recognizer.Result(); // Reset recognizer state
return result;
}
@@ -206,8 +218,6 @@ public class SpeechRecognizer {
return;
}
Log.d(TAG, "Starting decoding");
short[] buffer = new short[bufferSize];
while (!interrupted()
+14 -7
View File
@@ -11,6 +11,7 @@ KALDI_LIBS = \
${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 \
@@ -21,7 +22,7 @@ KALDI_LIBS = \
${KALDI_ROOT}/tools/openfst/lib/libfst.a \
${KALDI_ROOT}/tools/openfst/lib/libfstngram.a \
${KALDI_ROOT}/tools/OpenBLAS/libopenblas.a \
-lgfortran
-lgfortran -lstdc++
all: test.exe
@@ -29,20 +30,26 @@ test.exe: libkaldiwrap.so test.cs
mcs test.cs gen/*.cs
VOSK_SOURCES = \
vosk_wrap.cc \
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/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.cc: ../src/vosk.i
swig -csharp -dllimport "libkaldiwrap.so" \
-namespace "Kaldi" -c++ -outdir gen -o vosk_wrap.cc ../src/vosk.i
vosk_wrap.c: ../src/vosk.i
mkdir -p gen
swig -csharp -DSWIG_CSHARP_NO_EXCEPTION_HELPER -dllimport "libkaldiwrap" \
-namespace "Kaldi" -outdir gen -o vosk_wrap.c ../src/vosk.i
run: test.exe
mono test.exe
clean:
$(RM) *.so vosk_wrap.cc *.o gen/*.cs test.exe
$(RM) *.so vosk_wrap.c *.o gen/*.cs test.exe
+1
View File
@@ -7,6 +7,7 @@ public class Test
public static void Main()
{
Vosk.SetLogLevel(0);
Model model = new Model("model");
KaldiRecognizer rec = new KaldiRecognizer(model, 16000.0f);
+1
View File
@@ -0,0 +1 @@
See https://alphacephei.com/vosk/accuracy.html
+1
View File
@@ -0,0 +1 @@
See https://alphacephei.com/vosk/adaptation.html
-42
View File
@@ -1,42 +0,0 @@
## Updating the language model
The Kaldi model used in Vosk is compiled from 3 data sources:
* dictionary
* acoustic model
* language model
You can rebuild all three with different level of effort, but sometimes you just
need to adjust the probability of the words to improve the recognition. For
that it is enough to recompile the language model from the text. To do that
1) Take a text that reflects the speech you want to recognize
2) Remove punctuation, convert everything to the lowercase, you can do it with a python script
3) Build openfst and opengrm inside kaldi
```
export KALDI_ROOT=`pwd`/kaldi
git clone https://github.com/kaldi-asr/kaldi
cd kaldi/tools
make
# install all required dependencies and repeat `make` if needed
extras/install_opengrm.sh
```
4) Now lets build a grammar
```
export PATH=$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.
+1
View File
@@ -0,0 +1 @@
See https://alphacephei.com/vosk/models.html
+3
View File
@@ -0,0 +1,3 @@
This is a baseline for the vosk-api iOS demo. It requires a build of a
Vosk-API library, mail contact@alphacephei.com for the details.
+477
View File
@@ -0,0 +1,477 @@
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CLANG_WARN_INT_CONVERSION = YES;
CLANG_WARN_NON_LITERAL_NULL_CONVERSION = YES;
CLANG_WARN_OBJC_LITERAL_CONVERSION = YES;
CLANG_WARN_OBJC_ROOT_CLASS = YES_ERROR;
CLANG_WARN_RANGE_LOOP_ANALYSIS = YES;
CLANG_WARN_STRICT_PROTOTYPES = YES;
CLANG_WARN_SUSPICIOUS_MOVE = YES;
CLANG_WARN_UNREACHABLE_CODE = YES;
CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "iPhone Developer";
COPY_PHASE_STRIP = NO;
DEBUG_INFORMATION_FORMAT = dwarf;
ENABLE_STRICT_OBJC_MSGSEND = YES;
ENABLE_TESTABILITY = YES;
GCC_C_LANGUAGE_STANDARD = gnu99;
GCC_DYNAMIC_NO_PIC = NO;
GCC_NO_COMMON_BLOCKS = YES;
GCC_OPTIMIZATION_LEVEL = 0;
GCC_PREPROCESSOR_DEFINITIONS = (
"DEBUG=1",
"$(inherited)",
);
GCC_WARN_64_TO_32_BIT_CONVERSION = YES;
GCC_WARN_ABOUT_RETURN_TYPE = YES_ERROR;
GCC_WARN_UNDECLARED_SELECTOR = YES;
GCC_WARN_UNINITIALIZED_AUTOS = YES_AGGRESSIVE;
GCC_WARN_UNUSED_FUNCTION = YES;
GCC_WARN_UNUSED_VARIABLE = YES;
IPHONEOS_DEPLOYMENT_TARGET = 10.3;
MTL_ENABLE_DEBUG_INFO = YES;
ONLY_ACTIVE_ARCH = YES;
SDKROOT = iphoneos;
SWIFT_ACTIVE_COMPILATION_CONDITIONS = DEBUG;
SWIFT_OBJC_BRIDGING_HEADER = bridging.h;
SWIFT_OPTIMIZATION_LEVEL = "-Onone";
SWIFT_SWIFT3_OBJC_INFERENCE = Default;
TARGETED_DEVICE_FAMILY = "1,2";
};
name = Debug;
};
9237522F240C550B00DD6076 /* Release */ = {
isa = XCBuildConfiguration;
buildSettings = {
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;
CLANG_WARN_BLOCK_CAPTURE_AUTORELEASING = YES;
CLANG_WARN_BOOL_CONVERSION = YES;
CLANG_WARN_COMMA = YES;
CLANG_WARN_CONSTANT_CONVERSION = YES;
CLANG_WARN_DIRECT_OBJC_ISA_USAGE = YES_ERROR;
CLANG_WARN_DOCUMENTATION_COMMENTS = YES;
CLANG_WARN_EMPTY_BODY = YES;
CLANG_WARN_ENUM_CONVERSION = YES;
CLANG_WARN_INFINITE_RECURSION = YES;
CLANG_WARN_INT_CONVERSION = YES;
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CLANG_WARN_OBJC_ROOT_CLASS = YES_ERROR;
CLANG_WARN_RANGE_LOOP_ANALYSIS = YES;
CLANG_WARN_STRICT_PROTOTYPES = YES;
CLANG_WARN_SUSPICIOUS_MOVE = YES;
CLANG_WARN_UNREACHABLE_CODE = YES;
CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
"CODE_SIGN_IDENTITY[sdk=iphoneos*]" = "iPhone Developer";
COPY_PHASE_STRIP = NO;
DEBUG_INFORMATION_FORMAT = "dwarf-with-dsym";
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ENABLE_STRICT_OBJC_MSGSEND = YES;
GCC_C_LANGUAGE_STANDARD = gnu99;
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GCC_WARN_UNDECLARED_SELECTOR = YES;
GCC_WARN_UNINITIALIZED_AUTOS = YES_AGGRESSIVE;
GCC_WARN_UNUSED_FUNCTION = YES;
GCC_WARN_UNUSED_VARIABLE = YES;
IPHONEOS_DEPLOYMENT_TARGET = 10.3;
MTL_ENABLE_DEBUG_INFO = NO;
SDKROOT = iphoneos;
SWIFT_OBJC_BRIDGING_HEADER = bridging.h;
SWIFT_OPTIMIZATION_LEVEL = "-Owholemodule";
SWIFT_SWIFT3_OBJC_INFERENCE = Default;
TARGETED_DEVICE_FAMILY = "1,2";
VALIDATE_PRODUCT = YES;
};
name = Release;
};
92375231240C550B00DD6076 /* Debug */ = {
isa = XCBuildConfiguration;
buildSettings = {
ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
CLANG_ENABLE_MODULES = YES;
ENABLE_BITCODE = NO;
INFOPLIST_FILE = VoskApiTest/Info.plist;
LD_RUNPATH_SEARCH_PATHS = "$(inherited) @executable_path/Frameworks";
LIBRARY_SEARCH_PATHS = (
"$(inherited)",
"$(PROJECT_DIR)/VoskApiTest/Vosk",
);
PRODUCT_BUNDLE_IDENTIFIER = com.alphacephei.VoskApiTest;
PRODUCT_NAME = "$(TARGET_NAME)";
SWIFT_INSTALL_OBJC_HEADER = YES;
SWIFT_OBJC_BRIDGING_HEADER = VoskApiTest/bridging.h;
SWIFT_OPTIMIZATION_LEVEL = "-Onone";
SWIFT_SWIFT3_OBJC_INFERENCE = Default;
SWIFT_VERSION = 4.0;
};
name = Debug;
};
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isa = XCBuildConfiguration;
buildSettings = {
ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
CLANG_ENABLE_MODULES = YES;
ENABLE_BITCODE = NO;
INFOPLIST_FILE = VoskApiTest/Info.plist;
LD_RUNPATH_SEARCH_PATHS = "$(inherited) @executable_path/Frameworks";
LIBRARY_SEARCH_PATHS = (
"$(inherited)",
"$(PROJECT_DIR)/VoskApiTest/Vosk",
);
PRODUCT_BUNDLE_IDENTIFIER = com.alphacephei.VoskApiTest;
PRODUCT_NAME = "$(TARGET_NAME)";
SWIFT_INSTALL_OBJC_HEADER = YES;
SWIFT_OBJC_BRIDGING_HEADER = VoskApiTest/bridging.h;
SWIFT_SWIFT3_OBJC_INFERENCE = Default;
SWIFT_VERSION = 4.0;
};
name = Release;
};
/* End XCBuildConfiguration section */
/* Begin XCConfigurationList section */
92375219240C550A00DD6076 /* Build configuration list for PBXProject "VoskApiTest" */ = {
isa = XCConfigurationList;
buildConfigurations = (
9237522E240C550B00DD6076 /* Debug */,
9237522F240C550B00DD6076 /* Release */,
);
defaultConfigurationIsVisible = 0;
defaultConfigurationName = Release;
};
92375230240C550B00DD6076 /* Build configuration list for PBXNativeTarget "VoskApiTest" */ = {
isa = XCConfigurationList;
buildConfigurations = (
92375231240C550B00DD6076 /* Debug */,
92375232240C550B00DD6076 /* Release */,
);
defaultConfigurationIsVisible = 0;
defaultConfigurationName = Release;
};
/* End XCConfigurationList section */
};
rootObject = 92375216240C550A00DD6076 /* Project object */;
}
@@ -0,0 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<Workspace
version = "1.0">
<FileRef
location = "self:VoskApiTest.xcodeproj">
</FileRef>
</Workspace>
+46
View File
@@ -0,0 +1,46 @@
//
// AppDelegate.swift
// VoskApiTest
//
// Created by Niсkolay Shmyrev on 01.03.20.
// Copyright © 2020 Alpha Cephei. All rights reserved.
//
import UIKit
@UIApplicationMain
class AppDelegate: UIResponder, UIApplicationDelegate {
var window: UIWindow?
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplicationLaunchOptionsKey: Any]?) -> Bool {
// Override point for customization after application launch.
return true
}
func applicationWillResignActive(_ application: UIApplication) {
// Sent when the application is about to move from active to inactive state. This can occur for certain types of temporary interruptions (such as an incoming phone call or SMS message) or when the user quits the application and it begins the transition to the background state.
// Use this method to pause ongoing tasks, disable timers, and invalidate graphics rendering callbacks. Games should use this method to pause the game.
}
func applicationDidEnterBackground(_ application: UIApplication) {
// Use this method to release shared resources, save user data, invalidate timers, and store enough application state information to restore your application to its current state in case it is terminated later.
// If your application supports background execution, this method is called instead of applicationWillTerminate: when the user quits.
}
func applicationWillEnterForeground(_ application: UIApplication) {
// Called as part of the transition from the background to the active state; here you can undo many of the changes made on entering the background.
}
func applicationDidBecomeActive(_ application: UIApplication) {
// Restart any tasks that were paused (or not yet started) while the application was inactive. If the application was previously in the background, optionally refresh the user interface.
}
func applicationWillTerminate(_ application: UIApplication) {
// Called when the application is about to terminate. Save data if appropriate. See also applicationDidEnterBackground:.
}
}
@@ -0,0 +1,98 @@
{
"images" : [
{
"idiom" : "iphone",
"size" : "20x20",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "20x20",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "3x"
},
{
"idiom" : "ipad",
"size" : "20x20",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "20x20",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "83.5x83.5",
"scale" : "2x"
},
{
"idiom" : "ios-marketing",
"size" : "1024x1024",
"scale" : "1x"
}
],
"info" : {
"version" : 1,
"author" : "xcode"
}
}
@@ -0,0 +1,27 @@
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="11134" systemVersion="15F34" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" launchScreen="YES" useTraitCollections="YES" colorMatched="YES" initialViewController="01J-lp-oVM">
<dependencies>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="11106"/>
<capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="EHf-IW-A2E">
<objects>
<viewController id="01J-lp-oVM" sceneMemberID="viewController">
<layoutGuides>
<viewControllerLayoutGuide type="top" id="Llm-lL-Icb"/>
<viewControllerLayoutGuide type="bottom" id="xb3-aO-Qok"/>
</layoutGuides>
<view key="view" contentMode="scaleToFill" id="Ze5-6b-2t3">
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<color key="backgroundColor" red="1" green="1" blue="1" alpha="1" colorSpace="custom" customColorSpace="sRGB"/>
</view>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="iYj-Kq-Ea1" userLabel="First Responder" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="53" y="375"/>
</scene>
</scenes>
</document>
@@ -0,0 +1,32 @@
<?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">
<adaptation id="fullscreen"/>
</device>
<dependencies>
<deployment identifier="iOS"/>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="13772"/>
<capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="tne-QT-ifu">
<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"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
<fontDescription key="fontDescription" type="system" pointSize="14"/>
<textInputTraits key="textInputTraits" autocapitalizationType="sentences"/>
</textView>
<connections>
<outlet property="mainText" destination="CtX-mx-X98" id="oJy-5J-NKp"/>
</connections>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="dkx-z0-nzr" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="32.799999999999997" y="32.833583208395808"/>
</scene>
</scenes>
</document>
+45
View File
@@ -0,0 +1,45 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>LSRequiresIPhoneOS</key>
<true/>
<key>UILaunchStoryboardName</key>
<string>LaunchScreen</string>
<key>UIMainStoryboardFile</key>
<string>Main</string>
<key>UIRequiredDeviceCapabilities</key>
<array>
<string>armv7</string>
</array>
<key>UISupportedInterfaceOrientations</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
<key>UISupportedInterfaceOrientations~ipad</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationPortraitUpsideDown</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
</dict>
</plist>
+34
View File
@@ -0,0 +1,34 @@
//
// ViewController.swift
// VoskApiTest
//
// Created by Niсkolay Shmyrev on 01.03.20.
// Copyright © 2020 Alpha Cephei. All rights reserved.
//
import UIKit
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..."
}
let vosk = Vosk()
let res = vosk.recognizeFile()
DispatchQueue.main.async {
self.mainText.text = res
}
}
}
override func didReceiveMemoryWarning() {
super.didReceiveMemoryWarning()
}
}
+37
View File
@@ -0,0 +1,37 @@
//
// Vosk.swift
// VoskApiTest
//
// Created by Niсkolay Shmyrev on 01.03.20.
// Copyright © 2020 Alpha Cephei. All rights reserved.
//
import Foundation
public final class Vosk {
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);
}
vosk_recognizer_free(recognizer)
vosk_model_free(model)
}
return sres
}
}
+48
View File
@@ -0,0 +1,48 @@
// Copyright 2020 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.
#ifndef _VOSK_API_H_
#define _VOSK_API_H_
#ifdef __cplusplus
extern "C" {
#endif
typedef struct VoskModel VoskModel;
typedef struct VoskSpkModel VoskSpkModel;
typedef struct VoskRecognizer VoskRecognizer;
VoskModel *vosk_model_new(const char *model_path);
void vosk_model_free(VoskModel *model);
VoskSpkModel *vosk_spk_model_new(const char *model_path);
void vosk_spk_model_free(VoskSpkModel *model);
VoskRecognizer *vosk_recognizer_new(VoskModel *model, float sample_rate);
VoskRecognizer *vosk_recognizer_new_spk(VoskModel *model, VoskSpkModel *spk_model, float sample_rate);
VoskRecognizer *vosk_recognizer_new_grm(VoskModel *model, float sample_rate, const char *grammar);
int vosk_recognizer_accept_waveform(VoskRecognizer *recognizer, const char *data, int length);
int vosk_recognizer_accept_waveform_s(VoskRecognizer *recognizer, const short *data, int length);
int vosk_recognizer_accept_waveform_f(VoskRecognizer *recognizer, const float *data, int length);
const char *vosk_recognizer_result(VoskRecognizer *recognizer);
const char *vosk_recognizer_partial_result(VoskRecognizer *recognizer);
const char *vosk_recognizer_final_result(VoskRecognizer *recognizer);
void vosk_recognizer_free(VoskRecognizer *recognizer);
#ifdef __cplusplus
}
#endif
#endif /* _VOSK_API_H_ */
+1
View File
@@ -0,0 +1 @@
#import "Vosk/vosk_api.h"
+15 -7
View File
@@ -11,6 +11,7 @@ KALDI_LIBS = \
${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 \
@@ -32,14 +33,16 @@ VOSK_SOURCES = \
../src/model.cc \
../src/model.h \
../src/spk_model.cc \
../src/spk_model.h
../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 -I../src -c++ \
swig -c++ -I../src \
-java -package org.kaldi \
-outdir org/kaldi -o $@ $<
@@ -47,11 +50,16 @@ 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:
wget https://alphacephei.com/kaldi/models/vosk-model-small-en-us-0.3.zip
unzip vosk-model-small-en-us-0.3.zip && rm vosk-model-small-en-us-0.3.zip
mv vosk-model-small-en-us-0.3 model
run: model-en
model-spk:
wget https://alphacephei.com/kaldi/models/vosk-model-spk-0.3.zip
unzip vosk-model-spk-0.3.zip && rm vosk-model-spk-0.3.zip
mv vosk-model-spk-0.3 model-spk
run: model model-spk
javac test/*.java org/kaldi/*.java
java -Djava.library.path=. -cp . test.DecoderTest
+19
View File
@@ -0,0 +1,19 @@
Java API sample
Doesn't work on Windows or Mac yet, help to prepare the packaged jars is welcome.
For now to try it:
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
+5 -2
View File
@@ -11,6 +11,7 @@ import java.nio.*;
import org.kaldi.KaldiRecognizer;
import org.kaldi.Model;
import org.kaldi.SpkModel;
import org.kaldi.Vosk;
public class DecoderTest {
static {
@@ -18,15 +19,17 @@ public class DecoderTest {
}
public static void main(String args[]) throws IOException {
Vosk.SetLogLevel(-10);
FileInputStream ais = new FileInputStream(new File("../python/example/test.wav"));
Model model = new Model("model-en");
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, nbytes)) {
if (rec.AcceptWaveform(b)) {
System.out.println(rec.Result());
} else {
System.out.println(rec.PartialResult());
+3
View File
@@ -0,0 +1,3 @@
build
node_modules
vosk_wrap.cc
+20
View File
@@ -0,0 +1,20 @@
Installation requires vosk-api checkout, it doesn't yet work with `npm
install vosk`. We have to figure out how to properly distribute native
modules for Vosk.
The build tested with node-0.10.15, node-0.12 is not yet supported by swig.
Still, you need swig of newest version 4.0.1
Build like this
```
npm install --kaldi_root=/home/suser/kaldi
```
Then test with
```
cd example
node test.js
```
+70
View File
@@ -0,0 +1,70 @@
{
'targets': [
{
'target_name': 'vosk',
'sources': [
'../src/kaldi_recognizer.cc',
'../src/model.cc',
'../src/spk_model.cc',
'../src/vosk_api.cc',
'vosk_wrap.cc',
],
'cflags': [
'-std=c++11',
'-DFST_NO_DYNAMIC_LINKING',
'-Wno-deprecated-declarations',
'-Wno-sign-compare',
'-Wno-unused-local-typedefs',
'-Wno-ignored-quaifiers',
'-Wno-extra',
],
'cflags_cc!' : [
'-fno-rtti',
'-fno-exceptions',
],
'actions': [
{
'action_name': 'swig',
'inputs': [
'../src/vosk.i',
],
'outputs': [
'vosk_wrap.cc',
],
'action': ['swig', '-c++', '-javascript', '-o', 'vosk_wrap.cc', '-v8', '-DV8_MAJOR_VERSION=10', '../src/vosk.i']
},
],
'include_dirs': [
'<@(kaldi_root)/src',
'<@(kaldi_root)/tools/openfst/include',
'../src',
],
'link_settings': {
'libraries': [
'<@(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',
],
'library_dirs': [
'/usr/lib',
],
},
}
]
}
+47
View File
@@ -0,0 +1,47 @@
#!/usr/bin/env node
const fs = require("fs");
const { Readable } = require("stream");
const wav = require("wav");
const { Model, KaldiRecognizer, SpkModel } = require("..");
try {
fs.accessSync("model", fs.constants.R_OK);
} catch(err) {
console.error("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model' in the current folder.");
process.exit(1);
}
try {
fs.accessSync("model-spk", fs.constants.R_OK);
} catch(err) {
console.error("Please download the speaker model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model-spk' in the current folder.");
process.exit(1);
}
const wfStream = fs.createReadStream("test.wav", {'highWaterMark': 4096});
const wfReader = new wav.Reader();
const model = new Model("model");
const spkModel = new SpkModel("model-spk");
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 KaldiRecognizer(model, spkModel, sampleRate);
for await (const data of new Readable().wrap(wfReader)) {
const result = await rec.AcceptWaveform(data);
if (result != 0) {
console.log(await rec.Result());
} else {
console.log(await rec.PartialResult());
}
}
console.log(await rec.FinalResult());
});
wfStream.pipe(wfReader);
+38
View File
@@ -0,0 +1,38 @@
#!/usr/bin/env node
const fs = require("fs");
const { Readable } = require("stream");
const wav = require("wav");
const { Model, KaldiRecognizer } = require("..");
try {
fs.accessSync("model", fs.constants.R_OK);
} catch(err) {
console.error("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model' in the current folder.");
process.exit(1);
}
const wfStream = fs.createReadStream("test.wav", {'highWaterMark': 4096});
const wfReader = new wav.Reader();
const model = new Model("model");
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 KaldiRecognizer(model, sampleRate);
for await (const data of new Readable().wrap(wfReader)) {
const result = await rec.AcceptWaveform(data);
if (result != 0) {
console.log(await rec.Result());
} else {
console.log(await rec.PartialResult());
}
}
console.log(await rec.FinalResult());
});
wfStream.pipe(wfReader);
+3 -3
View File
@@ -1,3 +1,3 @@
exports.printMsg = function() {
console.log("This is a message from the Vosk package");
}
const voskNativeModule = require('./build/Release/vosk.node');
module.exports = voskNativeModule;
+9 -3
View File
@@ -1,6 +1,6 @@
{
"name": "vosk",
"version": "0.1.0",
"version": "0.3.8",
"description": "Node binding for continuous voice recoginition through pocketsphinx.",
"repository": {
"type": "git",
@@ -13,6 +13,12 @@
"voice"
],
"author": "Alpha Cephei Inc.",
"license": "Apache 2.0",
"engines": { "node" : ">= 12.x.x" }
"license": "Apache-2.0",
"engines": {
"node": ">= 10.x.x"
},
"dependencies": {
"node-gyp": "^5.1.1",
"wav": "^1.0.2"
}
}
-50
View File
@@ -1,50 +0,0 @@
cmake_minimum_required(VERSION 3.12.0)
project(vosk)
set(TOP_SRCDIR "${CMAKE_SOURCE_DIR}/..")
if("x$ENV{WHEEL_FLAGS}" STREQUAL "x")
find_package (Python COMPONENTS Interpreter Development)
else()
# docker case
set(Python_INCLUDE_DIR "")
set(Python_LIBRARY "")
set(TOP_SRCDIR "/io")
endif()
set(KALDI_ROOT "$ENV{KALDI_ROOT}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -O3 -DFST_NO_DYNAMIC_LINKING")
include_directories("${TOP_SRCDIR}/src" "${KALDI_ROOT}/src" "${KALDI_ROOT}/tools/openfst/include" ${Python_INCLUDE_DIR})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} $ENV{WHEEL_FLAGS}")
find_package(SWIG REQUIRED)
include(${SWIG_USE_FILE})
set_property(SOURCE "${TOP_SRCDIR}/src/vosk.i" PROPERTY CPLUSPLUS ON)
swig_add_library(vosk TYPE SHARED LANGUAGE Python OUTPUT_DIR "${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.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/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)
set_target_properties(_vosk PROPERTIES LINK_FLAGS_RELEASE -s)
-76
View File
@@ -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']
+2 -2
View File
@@ -1,10 +1,10 @@
#!/usr/bin/python3
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer
import sys
import json
model = Model("model-en")
model = Model("model")
rec = KaldiRecognizer(model, 8000)
res = json.loads(rec.FinalResult())
+33
View File
@@ -0,0 +1,33 @@
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer, SetLogLevel
import sys
import os
import wave
import subprocess
SetLogLevel(0)
if not os.path.exists("model"):
print ("Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as 'model' in the current folder.")
exit (1)
sample_rate=16000
model = Model("model")
rec = KaldiRecognizer(model, sample_rate)
process = subprocess.Popen(['ffmpeg', '-loglevel', 'quiet', '-i',
sys.argv[1],
'-ar', str(sample_rate) , '-ac', '1', '-f', 's16le', '-'],
stdout=subprocess.PIPE)
while True:
data = process.stdout.read(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
print(rec.Result())
else:
print(rec.PartialResult())
print(rec.FinalResult())
+7 -7
View File
@@ -1,23 +1,23 @@
#!/usr/bin/python3
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer
import os
if not os.path.exists("model-en"):
print ("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model' in the current folder.")
if not os.path.exists("model"):
print ("Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as 'model' in the current folder.")
exit (1)
import pyaudio
model = Model("model")
rec = KaldiRecognizer(model, 16000)
p = pyaudio.PyAudio()
stream = p.open(format=pyaudio.paInt16, channels=1, rate=16000, input=True, frames_per_buffer=8000)
stream.start_stream()
model = Model("model-en")
rec = KaldiRecognizer(model, 16000)
while True:
data = stream.read(2000)
data = stream.read(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
+8 -6
View File
@@ -1,12 +1,14 @@
#!/usr/bin/python3
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer
from vosk import Model, KaldiRecognizer, SetLogLevel
import sys
import os
import wave
if not os.path.exists("model-en"):
print ("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model-en' in the current folder.")
SetLogLevel(0)
if not os.path.exists("model"):
print ("Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as 'model' in the current folder.")
exit (1)
wf = wave.open(sys.argv[1], "rb")
@@ -14,11 +16,11 @@ 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("model-en")
model = Model("model")
rec = KaldiRecognizer(model, wf.getframerate())
while True:
data = wf.readframes(1000)
data = wf.readframes(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
+7 -6
View File
@@ -1,4 +1,4 @@
#!/usr/bin/python3
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer, SpkModel
import sys
@@ -7,15 +7,15 @@ import json
import os
import numpy as np
model_path = "model-en"
model_path = "model"
spk_model_path = "model-spk"
if not os.path.exists(model_path):
print ("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as {} in the current folder.".format(model_path))
print ("Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as {} in the current folder.".format(model_path))
exit (1)
if not os.path.exists(spk_model_path):
print ("Please download the speaker model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as {} in the current folder.".format(spk_model_path))
print ("Please download the speaker model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as {} in the current folder.".format(spk_model_path))
exit (1)
wf = wave.open(sys.argv[1], "rb")
@@ -30,7 +30,7 @@ rec = KaldiRecognizer(model, spk_model, wf.getframerate())
# We compare speakers with cosine distance. We can keep one or several fingerprints for the speaker in a database
# to distingusih among users.
spk_sig = [5.64308, 4.23898, 1.119433, -0.810904, 2.115443, 2.328436, 6.135152, 1.348195, 2.60771, 1.020717, 4.324225, -0.873012, 6.123375, 4.903791, 0.064803, 4.66212, 3.502724, 2.535861, 5.452417, 7.081769, -0.823969, -5.167974, 8.568919, 4.159035, 5.314441, 3.688272, 5.730379, 4.463213, 7.227232, 3.538961, 3.316218, 1.269628, -1.902378, 3.512679, -1.947611, -1.520158, 3.80928, -2.721601, 5.359588, 2.942463, -7.474174, 3.788054, 0.303426, 4.951366, 1.72281, -1.867125, -3.574615, 3.622509, 4.803109, 2.829714, 1.528521, 6.408293, 0.820131, 5.066522, 2.836125, 2.867029, 3.725267, 0.505927, 1.462984, 5.001863, -3.838309, -2.45902, 3.992581, 4.451616, 2.865211, -1.148313, 4.996399, -3.473454, 2.876967, 3.940124, 7.553079, 0.373356, 1.396561, 2.686691, 2.094895, 0.913796, -0.286909, 3.540179, 4.904687, 0.84554, 7.585956, 1.017081, 0.168355, 6.672327, 4.092033, -4.240158, -2.017081, -0.813043, 6.468298, 4.115041, 2.231936, 2.370055, 4.972295, 5.58382, 6.022872, 2.706988, 5.248096, -1.918003, 8.259204, -0.900911, 1.961962, 2.349709, 3.290093, 3.344172, 3.307027, 4.203372, -0.315103, 5.61919, -3.229496, 3.777309, 4.328595, 1.461014, 2.622894, 0.315525, 5.447259, 5.407609, 5.339016, 1.604555, 5.359932, 0.090242, 0.535306, 4.724705, 4.692502, 0.5783, -5.436688, -4.915511, 1.959807, 2.825248]
spk_sig = [4.658117, 1.277387, 3.346158, -1.473036, -2.15727, 2.461757, 3.76756, -1.241252, 2.333765, 0.642588, -2.848165, 1.229534, 3.907015, 1.726496, -1.188692, 1.16322, -0.668811, -0.623309, 4.628018, 0.407197, 0.089955, 0.920438, 1.47237, -0.311365, -0.437051, -0.531738, -1.591781, 3.095415, 0.439524, -0.274787, 4.03165, 2.665864, 4.815553, 1.581063, 1.078242, 5.017717, -0.089395, -3.123428, 5.34038, 0.456982, 2.465727, 2.131833, 4.056272, 1.178392, -2.075712, -1.568503, 0.847139, 0.409214, 1.84727, 0.986758, 4.222116, 2.235512, 1.369377, 4.283126, 2.278125, -1.467577, -0.999971, 3.070041, 1.462214, 0.423204, 2.143578, 0.567174, -2.294655, 1.864723, 4.307356, 2.610872, -1.238721, 0.551861, 2.861954, 0.59613, -0.715396, -1.395357, 2.706177, -2.004444, 2.055255, 0.458283, 1.231968, 3.48234, 2.993858, 0.402819, 0.940885, 0.360162, -2.173674, -2.504609, 0.329541, 3.653913, 3.638025, -1.406409, 2.14059, 1.662765, -0.991323, 0.770921, 0.010094, 3.775469, 1.847511, 2.074432, -1.928593, 0.807414, 2.964505, 0.128597, 1.297962, 2.645227, 0.136405, -2.543087, 0.932246, 2.405783, -2.122267, 3.044013, 0.486728, 4.395338, 0.474267, 0.781297, 1.694144, -0.831078, -0.462362, -0.964715, 3.187863, 6.008708, 1.725954, 3.667886, -1.467623, 3.370667, 2.72555, -0.796541, 2.416543, 0.675401, -0.737634, -1.709676]
def cosine_dist(x, y):
nx = np.array(x)
@@ -38,12 +38,13 @@ def cosine_dist(x, y):
return 1 - np.dot(nx, ny) / np.linalg.norm(nx) / np.linalg.norm(ny)
while True:
data = wf.readframes(1000)
data = wf.readframes(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
res = json.loads(rec.Result())
print ("Text:", res['text'])
print ("X-vector:", res['spk'])
print ("Speaker distance:", cosine_dist(spk_sig, res['spk']))
res = json.loads(rec.FinalResult())
+5 -5
View File
@@ -1,16 +1,16 @@
#!/usr/bin/python3
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer
import sys
import json
import os
if not os.path.exists("model-en"):
print ("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model-en' in the current folder.")
if not os.path.exists("model"):
print ("Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as 'model' in the current folder.")
exit (1)
model = Model("model-en")
model = Model("model")
# Large vocabulary free form recognition
rec = KaldiRecognizer(model, 16000)
@@ -22,7 +22,7 @@ wf = open(sys.argv[1], "rb")
wf.read(44) # skip header
while True:
data = wf.read(2000)
data = wf.read(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
+5 -5
View File
@@ -1,12 +1,12 @@
#!/usr/bin/python3
#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer
import sys
import os
import wave
if not os.path.exists("model-en"):
print ("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack as 'model-en' in the current folder.")
if not os.path.exists("model"):
print ("Please download the model from https://github.com/alphacep/vosk-api/blob/master/doc/models.md and unpack as 'model' in the current folder.")
exit (1)
wf = wave.open(sys.argv[1], "rb")
@@ -14,12 +14,12 @@ 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("model-en")
model = Model("model")
# You can also specify the possible word list
rec = KaldiRecognizer(model, wf.getframerate(), "zero oh one two three four five six seven eight nine")
while True:
data = wf.readframes(1000)
data = wf.readframes(4000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
+71 -5
View File
@@ -1,13 +1,79 @@
import os
import sys
import setuptools
from cmake import *
from setuptools import Extension
from setuptools.command.build_py import build_py as _build_py
import distutils.dir_util
import distutils.log
class build_py(_build_py):
def run(self):
self.run_command("build_ext")
return super().run()
kaldi_root = os.getenv('KALDI_ROOT')
kaldi_mkl = os.getenv('KALDI_MKL')
source_path = os.getenv("VOSK_SOURCE", os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(__file__)), "../src")))
if kaldi_root == None:
print("Define KALDI_ROOT")
exit(1)
distutils.log.set_verbosity(distutils.log.DEBUG)
distutils.dir_util.copy_tree(
source_path,
"vosk",
update=1,
verbose=1)
with open("README.md", "r") as fh:
long_description = fh.read()
kaldi_static_libs = ['src/online2/kaldi-online2.a',
'src/decoder/kaldi-decoder.a',
'src/ivector/kaldi-ivector.a',
'src/gmm/kaldi-gmm.a',
'src/nnet3/kaldi-nnet3.a',
'src/tree/kaldi-tree.a',
'src/feat/kaldi-feat.a',
'src/lat/kaldi-lat.a',
'src/lm/kaldi-lm.a',
'src/hmm/kaldi-hmm.a',
'src/transform/kaldi-transform.a',
'src/cudamatrix/kaldi-cudamatrix.a',
'src/matrix/kaldi-matrix.a',
'src/fstext/kaldi-fstext.a',
'src/util/kaldi-util.a',
'src/base/kaldi-base.a',
'tools/openfst/lib/libfst.a',
'tools/openfst/lib/libfstngram.a']
kaldi_link_args = ['-s']
kaldi_libraries = []
if sys.platform.startswith('darwin'):
kaldi_link_args.extend(['-Wl,-undefined,dynamic_lookup', '-framework', 'Accelerate'])
elif kaldi_mkl != None:
kaldi_link_args.extend(['-L/opt/intel/mkl/lib/intel64', '-Wl,-rpath=/opt/intel/mkl/lib/intel64'])
kaldi_libraries.extend(['mkl_rt', 'mkl_intel_lp64', 'mkl_core', 'mkl_sequential'])
else:
kaldi_static_libs.append('tools/OpenBLAS/libopenblas.a')
kaldi_libraries.append('gfortran')
sources = ['kaldi_recognizer.cc', 'model.cc', 'spk_model.cc', 'vosk_api.cc', 'vosk.i']
vosk_ext = Extension('vosk._vosk',
define_macros = [('FST_NO_DYNAMIC_LINKING', '1')],
include_dirs = [kaldi_root + '/src', kaldi_root + '/tools/openfst/include', 'vosk'],
swig_opts=['-outdir', 'vosk', '-c++'],
libraries = kaldi_libraries,
extra_objects = [kaldi_root + '/' + x for x in kaldi_static_libs],
sources = ['vosk/' + x for x in sources],
extra_link_args = kaldi_link_args,
extra_compile_args = ['-std=c++11', '-Wno-sign-compare', '-Wno-unused-variable', '-Wno-unused-local-typedefs'])
setuptools.setup(
name="vosk", # Replace with your own username
version="0.3.3",
version="0.3.9",
author="Alpha Cephei Inc",
author_email="contact@alphacephei.com",
description="API for Kaldi and Vosk",
@@ -15,8 +81,8 @@ setuptools.setup(
long_description_content_type="text/markdown",
url="https://github.com/alphacep/vosk-api",
packages=setuptools.find_packages(),
ext_modules=[CMakeExtension('_vosk', 'vosk')],
cmdclass={'build_ext': CMakeBuildExt, 'build_py' : CMakeBuildExtFirst},
ext_modules=[vosk_ext],
cmdclass = {'build_py' : build_py},
classifiers=[
'Programming Language :: Python :: 3',
'License :: OSI Approved :: Apache Software License',
@@ -25,5 +91,5 @@ setuptools.setup(
'Operating System :: MacOS :: MacOS X',
'Topic :: Software Development :: Libraries :: Python Modules'
],
python_requires='>=3.4',
python_requires='>=3.5',
)
+35
View File
@@ -0,0 +1,35 @@
#!/usr/bin/env python3
from multiprocessing.dummy import Pool
from vosk import Model, KaldiRecognizer
import sys
import os
import wave
import json
model = Model("model")
def recognize(line):
uid, fn = line.split()
wf = wave.open(fn, "rb")
rec = KaldiRecognizer(model, wf.getframerate())
text = ""
while True:
data = wf.readframes(1000)
if len(data) == 0:
break
if rec.AcceptWaveform(data):
jres = json.loads(rec.Result())
text = text + " " + jres['text']
jres = json.loads(rec.FinalResult())
text = text + " " + jres['text']
return (uid + text)
def main():
p = Pool(8)
texts = p.map(recognize, open(sys.argv[1]).readlines())
print ("\n".join(texts))
main()
+2 -1
View File
@@ -1 +1,2 @@
from .vosk import KaldiRecognizer, Model, SpkModel
from .vosk import KaldiRecognizer, Model, SpkModel, SetLogLevel
+219 -97
View File
@@ -1,4 +1,4 @@
// Copyright 2019 Alpha Cephei Inc.
// Copyright 2019-2020 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.
@@ -20,120 +20,186 @@
using namespace fst;
using namespace kaldi::nnet3;
KaldiRecognizer::KaldiRecognizer(Model &model, float sample_frequency) : model_(model), spk_model_(0), sample_frequency_(sample_frequency) {
KaldiRecognizer::KaldiRecognizer(Model *model, float sample_frequency) : model_(model), spk_model_(0), sample_frequency_(sample_frequency) {
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_.feature_info_);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_.trans_model_, model_.feature_info_.silence_weighting_config, 3);
model_->Ref();
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_->feature_info_);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_->trans_model_, model_->feature_info_.silence_weighting_config, 3);
g_fst_ = NULL;
decode_fst_ = NULL;
if (!model_.hclg_fst_) {
if (model_.hcl_fst_ && model_.g_fst_) {
decode_fst_ = LookaheadComposeFst(*model_.hcl_fst_, *model_.g_fst_, model_.disambig_);
if (!model_->hclg_fst_) {
if (model_->hcl_fst_ && model_->g_fst_) {
decode_fst_ = LookaheadComposeFst(*model_->hcl_fst_, *model_->g_fst_, model_->disambig_);
} else {
KALDI_ERR << "Can't create decoding graph";
}
}
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_.nnet3_decoding_config_,
*model_.trans_model_,
*model_.decodable_info_,
model_.hclg_fst_ ? *model.hclg_fst_ : *decode_fst_,
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_->nnet3_decoding_config_,
*model_->trans_model_,
*model_->decodable_info_,
model_->hclg_fst_ ? *model_->hclg_fst_ : *decode_fst_,
feature_pipeline_);
frame_offset_ = 0;
input_finalized_ = false;
spk_feature_ = NULL;
InitState();
InitRescoring();
}
KaldiRecognizer::KaldiRecognizer(Model &model, float sample_frequency, char const *grammar) : model_(model), spk_model_(0), sample_frequency_(sample_frequency)
KaldiRecognizer::KaldiRecognizer(Model *model, float sample_frequency, char const *grammar) : model_(model), spk_model_(0), sample_frequency_(sample_frequency)
{
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_.feature_info_);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_.trans_model_, model_.feature_info_.silence_weighting_config, 3);
model_->Ref();
if (model_.hcl_fst_) {
g_fst_.AddState();
g_fst_.SetStart(0);
g_fst_.AddState();
g_fst_.SetFinal(1, fst::TropicalWeight::One());
g_fst_.AddArc(1, StdArc(0, 0, fst::TropicalWeight::One(), 0));
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_->feature_info_);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_->trans_model_, model_->feature_info_.silence_weighting_config, 3);
g_fst_ = new StdVectorFst();
if (model_->hcl_fst_) {
g_fst_->AddState();
g_fst_->SetStart(0);
g_fst_->AddState();
g_fst_->SetFinal(1, fst::TropicalWeight::One());
g_fst_->AddArc(1, StdArc(0, 0, fst::TropicalWeight::One(), 0));
// Create simple word loop FST
std::stringstream ss(grammar);
std::string token;
stringstream ss(grammar);
string token;
while (std::getline(ss, token, ' ')) {
int32 id = model_.word_syms_->Find(token);
g_fst_.AddArc(0, StdArc(id, id, fst::TropicalWeight::One(), 1));
while (getline(ss, token, ' ')) {
int32 id = model_->word_syms_->Find(token);
g_fst_->AddArc(0, StdArc(id, id, fst::TropicalWeight::One(), 1));
}
ArcSort(&g_fst_, ILabelCompare<StdArc>());
ArcSort(g_fst_, ILabelCompare<StdArc>());
decode_fst_ = LookaheadComposeFst(*model_.hcl_fst_, g_fst_, model_.disambig_);
decode_fst_ = LookaheadComposeFst(*model_->hcl_fst_, *g_fst_, model_->disambig_);
} else {
decode_fst_ = NULL;
KALDI_ERR << "Can't create decoding graph";
}
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_.nnet3_decoding_config_,
*model_.trans_model_,
*model_.decodable_info_,
model_.hclg_fst_ ? *model.hclg_fst_ : *decode_fst_,
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_->nnet3_decoding_config_,
*model_->trans_model_,
*model_->decodable_info_,
model_->hclg_fst_ ? *model_->hclg_fst_ : *decode_fst_,
feature_pipeline_);
frame_offset_ = 0;
input_finalized_ = false;
spk_feature_ = NULL;
InitState();
InitRescoring();
}
KaldiRecognizer::KaldiRecognizer(Model *model, SpkModel *spk_model, float sample_frequency) : model_(model), spk_model_(spk_model), sample_frequency_(sample_frequency) {
KaldiRecognizer::KaldiRecognizer(Model &model, SpkModel *spk_model, float sample_frequency) : model_(model), spk_model_(spk_model), sample_frequency_(sample_frequency) {
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_.feature_info_);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_.trans_model_, model_.feature_info_.silence_weighting_config, 3);
model_->Ref();
spk_model->Ref();
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_->feature_info_);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_->trans_model_, model_->feature_info_.silence_weighting_config, 3);
decode_fst_ = NULL;
g_fst_ = NULL;
if (!model_.hclg_fst_) {
if (model_.hcl_fst_ && model_.g_fst_) {
decode_fst_ = LookaheadComposeFst(*model_.hcl_fst_, *model_.g_fst_, model_.disambig_);
if (!model_->hclg_fst_) {
if (model_->hcl_fst_ && model_->g_fst_) {
decode_fst_ = LookaheadComposeFst(*model_->hcl_fst_, *model_->g_fst_, model_->disambig_);
} else {
KALDI_ERR << "Can't create decoding graph";
}
}
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_.nnet3_decoding_config_,
*model_.trans_model_,
*model_.decodable_info_,
model_.hclg_fst_ ? *model.hclg_fst_ : *decode_fst_,
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_->nnet3_decoding_config_,
*model_->trans_model_,
*model_->decodable_info_,
model_->hclg_fst_ ? *model_->hclg_fst_ : *decode_fst_,
feature_pipeline_);
frame_offset_ = 0;
input_finalized_ = false;
spk_feature_ = new OnlineMfcc(spk_model_->spkvector_mfcc_opts);
InitState();
InitRescoring();
}
KaldiRecognizer::~KaldiRecognizer() {
delete feature_pipeline_;
delete silence_weighting_;
delete decoder_;
delete g_fst_;
delete decode_fst_;
delete spk_feature_;
delete lm_fst_;
model_->Unref();
if (spk_model_)
spk_model_->Unref();
}
void KaldiRecognizer::InitState()
{
frame_offset_ = 0;
samples_processed_ = 0;
samples_round_start_ = 0;
state_ = RECOGNIZER_INITIALIZED;
}
void KaldiRecognizer::InitRescoring()
{
if (model_->std_lm_fst_) {
fst::CacheOptions cache_opts(true, 50000);
fst::MapFstOptions mapfst_opts(cache_opts);
fst::StdToLatticeMapper<kaldi::BaseFloat> mapper;
lm_fst_ = new fst::MapFst<fst::StdArc, kaldi::LatticeArc, fst::StdToLatticeMapper<kaldi::BaseFloat> >(*model_->std_lm_fst_, mapper, mapfst_opts);
} else {
lm_fst_ = NULL;
}
}
void KaldiRecognizer::CleanUp()
{
delete silence_weighting_;
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_.trans_model_, model_.feature_info_.silence_weighting_config, 3);
silence_weighting_ = new kaldi::OnlineSilenceWeighting(*model_->trans_model_, model_->feature_info_.silence_weighting_config, 3);
if (spk_feature_) {
delete spk_feature_;
spk_feature_ = new OnlineMfcc(spk_model_->spkvector_mfcc_opts);
}
frame_offset_ += decoder_->NumFramesDecoded();
decoder_->InitDecoding(frame_offset_);
// Each 10 minutes we drop the pipeline to save frontend memory in continuous processing
// here we drop few frames remaining in the feature pipeline but hope it will not
// cause a huge accuracy drop since it happens not very frequently.
// Also restart if we retrieved final result already
if (frame_offset_ > 20000 || state_ == RECOGNIZER_FINALIZED) {
samples_round_start_ += samples_processed_;
frame_offset_ = 0;
delete decoder_;
delete feature_pipeline_;
feature_pipeline_ = new kaldi::OnlineNnet2FeaturePipeline (model_->feature_info_);
decoder_ = new kaldi::SingleUtteranceNnet3Decoder(model_->nnet3_decoding_config_,
*model_->trans_model_,
*model_->decodable_info_,
model_->hclg_fst_ ? *model_->hclg_fst_ : *decode_fst_,
feature_pipeline_);
} else {
decoder_->InitDecoding(frame_offset_);
}
}
void KaldiRecognizer::UpdateSilenceWeights()
{
if (silence_weighting_->Active() && feature_pipeline_->NumFramesReady() > 0 &&
feature_pipeline_->IvectorFeature() != NULL) {
std::vector<std::pair<int32, BaseFloat> > delta_weights;
vector<pair<int32, BaseFloat> > delta_weights;
silence_weighting_->ComputeCurrentTraceback(decoder_->Decoder());
silence_weighting_->GetDeltaWeights(feature_pipeline_->NumFramesReady(),
frame_offset_ * 3,
@@ -171,27 +237,32 @@ bool KaldiRecognizer::AcceptWaveform(const float *fdata, int len)
bool KaldiRecognizer::AcceptWaveform(Vector<BaseFloat> &wdata)
{
if (input_finalized_) {
// Cleanup if we finalized previous utterance or the whole feature pipeline
if (!(state_ == RECOGNIZER_RUNNING || state_ == RECOGNIZER_INITIALIZED)) {
CleanUp();
input_finalized_ = false;
}
state_ = RECOGNIZER_RUNNING;
feature_pipeline_->AcceptWaveform(sample_frequency_, wdata);
UpdateSilenceWeights();
decoder_->AdvanceDecoding();
int step = static_cast<int>(sample_frequency_ * 0.2);
for (int i = 0; i < wdata.Dim(); i+= step) {
SubVector<BaseFloat> r = wdata.Range(i, std::min(step, wdata.Dim() - i));
feature_pipeline_->AcceptWaveform(sample_frequency_, r);
UpdateSilenceWeights();
decoder_->AdvanceDecoding();
}
samples_processed_ += wdata.Dim();
if (spk_feature_) {
spk_feature_->AcceptWaveform(sample_frequency_, wdata);
}
if (decoder_->EndpointDetected(model_.endpoint_config_)) {
if (decoder_->EndpointDetected(model_->endpoint_config_)) {
return true;
}
return false;
}
// Computes an xvector from a chunk of speech features.
static void RunNnetComputation(const MatrixBase<BaseFloat> &features,
const nnet3::Nnet &nnet, nnet3::CachingOptimizingCompiler *compiler,
@@ -208,7 +279,7 @@ static void RunNnetComputation(const MatrixBase<BaseFloat> &features,
output_spec.indexes.resize(1);
request.outputs.resize(1);
request.outputs[0].Swap(&output_spec);
std::shared_ptr<const nnet3::NnetComputation> computation = compiler->Compile(request);
shared_ptr<const nnet3::NnetComputation> computation = compiler->Compile(request);
nnet3::Nnet *nnet_to_update = NULL; // we're not doing any update.
nnet3::NnetComputer computer(nnet3::NnetComputeOptions(), *computation,
nnet, nnet_to_update);
@@ -221,14 +292,24 @@ static void RunNnetComputation(const MatrixBase<BaseFloat> &features,
xvector->CopyFromVec(cu_output.Row(0));
}
void KaldiRecognizer::GetSpkVector(Vector<BaseFloat> &xvector)
{
int num_frames = spk_feature_->NumFramesReady() - frame_offset_ * 3;
vector<int32> nonsilence_frames;
if (silence_weighting_->Active() && feature_pipeline_->NumFramesReady() > 0) {
silence_weighting_->ComputeCurrentTraceback(decoder_->Decoder(), true);
silence_weighting_->GetNonsilenceFrames(feature_pipeline_->NumFramesReady(),
frame_offset_ * 3,
&nonsilence_frames);
}
int num_frames = spk_feature_->NumFramesReady();
Matrix<BaseFloat> mfcc(num_frames, spk_feature_->Dim());
for (int i = 0; i < num_frames; ++i) {
if (std::find(nonsilence_frames.begin(),
nonsilence_frames.end(), i % 3) == nonsilence_frames.end())
continue;
Vector<BaseFloat> feat(spk_feature_->Dim());
spk_feature_->GetFrame(i + frame_offset_ * 3, &feat);
spk_feature_->GetFrame(i, &feat);
mfcc.CopyRowFromVec(feat, i);
}
SlidingWindowCmnOptions cmvn_opts;
@@ -242,54 +323,70 @@ void KaldiRecognizer::GetSpkVector(Vector<BaseFloat> &xvector)
RunNnetComputation(features, spk_model_->speaker_nnet, &compiler, &xvector);
}
std::string KaldiRecognizer::Result()
const char* KaldiRecognizer::GetResult()
{
if (!input_finalized_) {
decoder_->FinalizeDecoding();
input_finalized_ = true;
}
if (decoder_->NumFramesDecoded() == 0) {
return "{\"text\": \"\"}";
return StoreReturn("{\"text\": \"\"}");
}
kaldi::CompactLattice clat;
decoder_->GetLattice(true, &clat);
fst::ScaleLattice(fst::LatticeScale(8.0, 10.0), &clat);
if (model_->std_lm_fst_) {
Lattice lat1;
ConvertLattice(clat, &lat1);
fst::ScaleLattice(fst::GraphLatticeScale(-1.0), &lat1);
fst::ArcSort(&lat1, fst::OLabelCompare<kaldi::LatticeArc>());
kaldi::Lattice composed_lat;
fst::Compose(lat1, *lm_fst_, &composed_lat);
fst::Invert(&composed_lat);
kaldi::CompactLattice determinized_lat;
DeterminizeLattice(composed_lat, &determinized_lat);
fst::ScaleLattice(fst::GraphLatticeScale(-1), &determinized_lat);
fst::ArcSort(&determinized_lat, fst::OLabelCompare<kaldi::CompactLatticeArc>());
kaldi::ConstArpaLmDeterministicFst const_arpa_fst(model_->const_arpa_);
kaldi::CompactLattice composed_clat;
kaldi::ComposeCompactLatticeDeterministic(determinized_lat, &const_arpa_fst, &composed_clat);
kaldi::Lattice composed_lat1;
ConvertLattice(composed_clat, &composed_lat1);
fst::Invert(&composed_lat1);
DeterminizeLattice(composed_lat1, &clat);
}
fst::ScaleLattice(fst::LatticeScale(9.0, 10.0), &clat);
CompactLattice aligned_lat;
if (model_.winfo_) {
WordAlignLattice(clat, *model_.trans_model_, *model_.winfo_, 0, &aligned_lat);
if (model_->winfo_) {
WordAlignLattice(clat, *model_->trans_model_, *model_->winfo_, 0, &aligned_lat);
} else {
aligned_lat = clat;
}
MinimumBayesRisk mbr(aligned_lat);
const std::vector<BaseFloat> &conf = mbr.GetOneBestConfidences();
const std::vector<int32> &words = mbr.GetOneBest();
const std::vector<std::pair<BaseFloat, BaseFloat> > &times =
const vector<BaseFloat> &conf = mbr.GetOneBestConfidences();
const vector<int32> &words = mbr.GetOneBest();
const vector<pair<BaseFloat, BaseFloat> > &times =
mbr.GetOneBestTimes();
int size = words.size();
json::JSON obj;
std::stringstream text;
stringstream text;
// Create JSON object
for (int i = 0; i < size; i++) {
json::JSON word;
word["word"] = model_.word_syms_->Find(words[i]);
word["start"] = (frame_offset_ + times[i].first) * 0.03;
word["end"] = (frame_offset_ + times[i].second) * 0.03;
word["word"] = model_->word_syms_->Find(words[i]);
word["start"] = samples_round_start_ / sample_frequency_ + (frame_offset_ + times[i].first) * 0.03;
word["end"] = samples_round_start_ / sample_frequency_ + (frame_offset_ + times[i].second) * 0.03;
word["conf"] = conf[i];
obj["result"].append(word);
if (i) {
text << " ";
}
text << model_.word_syms_->Find(words[i]);
text << model_->word_syms_->Find(words[i]);
}
obj["text"] = text.str();
@@ -301,43 +398,68 @@ std::string KaldiRecognizer::Result()
}
}
return obj.dump();
return StoreReturn(obj.dump());
}
std::string KaldiRecognizer::PartialResult()
const char* KaldiRecognizer::PartialResult()
{
if (state_ != RECOGNIZER_RUNNING) {
return StoreReturn("{\"text\": \"\"}");
}
json::JSON res;
if (decoder_->NumFramesDecoded() == 0) {
res["partial"] = "";
return res.dump();
return StoreReturn(res.dump());
}
kaldi::Lattice lat;
decoder_->GetBestPath(false, &lat);
std::vector<kaldi::int32> alignment, words;
vector<kaldi::int32> alignment, words;
LatticeWeight weight;
GetLinearSymbolSequence(lat, &alignment, &words, &weight);
std::ostringstream text;
ostringstream text;
for (size_t i = 0; i < words.size(); i++) {
if (i) {
text << " ";
}
text << model_.word_syms_->Find(words[i]);
text << model_->word_syms_->Find(words[i]);
}
res["partial"] = text.str();
return res.dump();
return StoreReturn(res.dump());
}
std::string KaldiRecognizer::FinalResult()
const char* KaldiRecognizer::Result()
{
if (!input_finalized_) {
feature_pipeline_->InputFinished();
UpdateSilenceWeights();
decoder_->AdvanceDecoding();
decoder_->FinalizeDecoding();
input_finalized_ = true;
if (state_ != RECOGNIZER_RUNNING) {
return StoreReturn("{\"text\": \"\"}");
}
return Result();
decoder_->FinalizeDecoding();
state_ = RECOGNIZER_ENDPOINT;
return GetResult();
}
const char* KaldiRecognizer::FinalResult()
{
if (state_ != RECOGNIZER_RUNNING) {
return StoreReturn("{\"text\": \"\"}");
}
feature_pipeline_->InputFinished();
UpdateSilenceWeights();
decoder_->AdvanceDecoding();
decoder_->FinalizeDecoding();
state_ = RECOGNIZER_FINALIZED;
return GetResult();
}
// Store result in recognizer and return as const string
const char *KaldiRecognizer::StoreReturn(const string &res)
{
last_result_ = res;
return last_result_.c_str();
}
+27 -9
View File
@@ -29,36 +29,54 @@
using namespace kaldi;
enum KaldiRecognizerState {
RECOGNIZER_INITIALIZED,
RECOGNIZER_RUNNING,
RECOGNIZER_ENDPOINT,
RECOGNIZER_FINALIZED
};
class KaldiRecognizer {
public:
KaldiRecognizer(Model &model, float sample_frequency);
KaldiRecognizer(Model &model, SpkModel *spk_model, float sample_frequency);
KaldiRecognizer(Model &model, float sample_frequency, char const *grammar);
KaldiRecognizer(Model *model, float sample_frequency);
KaldiRecognizer(Model *model, SpkModel *spk_model, float sample_frequency);
KaldiRecognizer(Model *model, float sample_frequency, char const *grammar);
~KaldiRecognizer();
bool AcceptWaveform(const char *data, int len);
bool AcceptWaveform(const short *sdata, int len);
bool AcceptWaveform(const float *fdata, int len);
std::string Result();
std::string FinalResult();
std::string PartialResult();
const char* Result();
const char* FinalResult();
const char* PartialResult();
private:
void InitState();
void InitRescoring();
void CleanUp();
void UpdateSilenceWeights();
bool AcceptWaveform(Vector<BaseFloat> &wdata);
void GetSpkVector(Vector<BaseFloat> &xvector);
const char *GetResult();
const char *StoreReturn(const string &res);
Model &model_;
Model *model_;
SingleUtteranceNnet3Decoder *decoder_;
fst::LookaheadFst<fst::StdArc, int32> *decode_fst_;
fst::StdVectorFst g_fst_; // dynamically constructed grammar
fst::StdVectorFst *g_fst_; // dynamically constructed grammar
OnlineNnet2FeaturePipeline *feature_pipeline_;
OnlineSilenceWeighting *silence_weighting_;
SpkModel *spk_model_;
OnlineBaseFeature *spk_feature_;
fst::MapFst<fst::StdArc, kaldi::LatticeArc, fst::StdToLatticeMapper<kaldi::BaseFloat> > *lm_fst_;
float sample_frequency_;
int32 frame_offset_;
bool input_finalized_;
int64 samples_processed_;
int64 samples_round_start_;
KaldiRecognizerState state_;
string last_result_;
};
+187 -57
View File
@@ -14,19 +14,7 @@
//
// Possible model layout:
//
// * Default kaldi model with HCLG.fst
//
// * Lookahead model with const G.fst
//
// * Lookahead model with ngram G.fst
//
// * File disambig_tid.int required only for lookadhead models
//
// * File word_boundary.int is required if we want to have precise word timing information
// otherwise we don't do any word alignment. Optionally lexicon alignment can be done
// with corresponding C++ code inside kaldi recognizer.
// For details of possible model layout see doc/models.md section model-structure
#include "model.h"
@@ -45,24 +33,101 @@ static FstRegisterer<NGramFst<StdArc>> NGramFst_StdArc_registerer;
#ifdef __ANDROID__
#include <android/log.h>
static void AndroidLogHandler(const LogMessageEnvelope &env, const char *message)
static void KaldiLogHandler(const LogMessageEnvelope &env, const char *message)
{
__android_log_print(ANDROID_LOG_VERBOSE, "KaldiDemo", message, 1);
int priority;
if (env.severity > GetVerboseLevel())
return;
if (env.severity > LogMessageEnvelope::kInfo) {
priority = ANDROID_LOG_VERBOSE;
} else {
switch (env.severity) {
case LogMessageEnvelope::kInfo:
priority = ANDROID_LOG_INFO;
break;
case LogMessageEnvelope::kWarning:
priority = ANDROID_LOG_WARN;
break;
case LogMessageEnvelope::kAssertFailed:
priority = ANDROID_LOG_FATAL;
break;
case LogMessageEnvelope::kError:
default: // If not the ERROR, it still an error!
priority = ANDROID_LOG_ERROR;
break;
}
}
std::stringstream full_message;
full_message << env.func << "():" << env.file << ':'
<< env.line << ") " << message;
__android_log_print(priority, "VoskAPI", "%s", full_message.str().c_str());
}
#else
static void KaldiLogHandler(const LogMessageEnvelope &env, const char *message)
{
if (env.severity > GetVerboseLevel())
return;
// Modified default Kaldi logging so we can disable LOG messages.
std::stringstream full_message;
if (env.severity > LogMessageEnvelope::kInfo) {
full_message << "VLOG[" << env.severity << "] (";
} else {
switch (env.severity) {
case LogMessageEnvelope::kInfo:
full_message << "LOG (";
break;
case LogMessageEnvelope::kWarning:
full_message << "WARNING (";
break;
case LogMessageEnvelope::kAssertFailed:
full_message << "ASSERTION_FAILED (";
break;
case LogMessageEnvelope::kError:
default: // If not the ERROR, it still an error!
full_message << "ERROR (";
break;
}
}
// Add other info from the envelope and the message text.
full_message << "VoskAPI" << ':'
<< env.func << "():" << env.file << ':'
<< env.line << ") " << message;
// Print the complete message to stderr.
full_message << "\n";
std::cerr << full_message.str();
}
#endif
Model::Model(const char *model_path) {
Model::Model(const char *model_path) : model_path_str_(model_path) {
#ifdef __ANDROID__
SetLogHandler(AndroidLogHandler);
#endif
SetLogHandler(KaldiLogHandler);
const char *usage = "Read the docs";
struct stat buffer;
string am_path = model_path_str_ + "/am/final.mdl";
if (stat(am_path.c_str(), &buffer) == 0) {
ConfigureV2();
} else {
ConfigureV1();
}
ReadDataFiles();
ref_cnt_ = 1;
}
// Old model layout without model configuration file
void Model::ConfigureV1()
{
const char *extra_args[] = {
"--min-active=200",
"--max-active=3000",
"--beam=10.0",
"--lattice-beam=2.0",
"--max-active=7000",
"--beam=13.0",
"--lattice-beam=6.0",
"--acoustic-scale=1.0",
"--frame-subsampling-factor=3",
@@ -71,49 +136,70 @@ Model::Model(const char *model_path) {
"--endpoint.rule2.min-trailing-silence=0.5",
"--endpoint.rule3.min-trailing-silence=1.0",
"--endpoint.rule4.min-trailing-silence=2.0",
};
std::string model_path_str(model_path);
kaldi::ParseOptions po(usage);
"--print-args=false",
};
kaldi::ParseOptions po("");
nnet3_decoding_config_.Register(&po);
endpoint_config_.Register(&po);
decodable_opts_.Register(&po);
std::vector<const char*> args;
vector<const char*> args;
args.push_back("vosk");
args.insert(args.end(), extra_args, extra_args + sizeof(extra_args) / sizeof(extra_args[0]));
po.Read(args.size(), args.data());
nnet3_rxfilename_ = model_path_str_ + "/final.mdl";
hclg_fst_rxfilename_ = model_path_str_ + "/HCLG.fst";
hcl_fst_rxfilename_ = model_path_str_ + "/HCLr.fst";
g_fst_rxfilename_ = model_path_str_ + "/Gr.fst";
disambig_rxfilename_ = model_path_str_ + "/disambig_tid.int";
word_syms_rxfilename_ = model_path_str_ + "/words.txt";
winfo_rxfilename_ = model_path_str_ + "/word_boundary.int";
carpa_rxfilename_ = model_path_str_ + "/rescore/G.carpa";
std_fst_rxfilename_ = model_path_str_ + "/rescore/G.fst";
final_ie_rxfilename_ = model_path_str_ + "/ivector/final.ie";
mfcc_conf_rxfilename_ = model_path_str_ + "/mfcc.conf";
}
void Model::ConfigureV2()
{
kaldi::ParseOptions po("something");
nnet3_decoding_config_.Register(&po);
endpoint_config_.Register(&po);
decodable_opts_.Register(&po);
po.ReadConfigFile(model_path_str_ + "/conf/model.conf");
nnet3_rxfilename_ = model_path_str_ + "/am/final.mdl";
hclg_fst_rxfilename_ = model_path_str_ + "/graph/HCLG.fst";
hcl_fst_rxfilename_ = model_path_str_ + "/graph/HCLr.fst";
g_fst_rxfilename_ = model_path_str_ + "/graph/Gr.fst";
disambig_rxfilename_ = model_path_str_ + "/graph/disambig_tid.int";
word_syms_rxfilename_ = model_path_str_ + "/graph/words.txt";
winfo_rxfilename_ = model_path_str_ + "/graph/phones/word_boundary.int";
carpa_rxfilename_ = model_path_str_ + "/rescore/G.carpa";
std_fst_rxfilename_ = model_path_str_ + "/rescore/G.fst";
final_ie_rxfilename_ = model_path_str_ + "/ivector/final.ie";
mfcc_conf_rxfilename_ = model_path_str_ + "/conf/mfcc.conf";
}
void Model::ReadDataFiles()
{
struct stat buffer;
KALDI_LOG << "Decoding params beam=" << nnet3_decoding_config_.beam <<
" max-active=" << nnet3_decoding_config_.max_active <<
" lattice-beam=" << nnet3_decoding_config_.lattice_beam;
KALDI_LOG << "Silence phones " << endpoint_config_.silence_phones;
feature_info_.feature_type = "mfcc";
ReadConfigFromFile(model_path_str + "/mfcc.conf", &feature_info_.mfcc_opts);
ReadConfigFromFile(mfcc_conf_rxfilename_, &feature_info_.mfcc_opts);
feature_info_.mfcc_opts.frame_opts.allow_downsample = true; // It is safe to downsample
feature_info_.silence_weighting_config.silence_weight = 1e-3;
feature_info_.silence_weighting_config.silence_phones_str = "1:2:3:4:5:6:7:8:9:10";
OnlineIvectorExtractionConfig ivector_extraction_opts;
ivector_extraction_opts.splice_config_rxfilename = model_path_str + "/ivector/splice.conf";
ivector_extraction_opts.cmvn_config_rxfilename = model_path_str + "/ivector/online_cmvn.conf";
ivector_extraction_opts.lda_mat_rxfilename = model_path_str + "/ivector/final.mat";
ivector_extraction_opts.global_cmvn_stats_rxfilename = model_path_str + "/ivector/global_cmvn.stats";
ivector_extraction_opts.diag_ubm_rxfilename = model_path_str + "/ivector/final.dubm";
ivector_extraction_opts.ivector_extractor_rxfilename = model_path_str + "/ivector/final.ie";
ivector_extraction_opts.num_gselect = 5;
ivector_extraction_opts.min_post = 0.025;
ivector_extraction_opts.posterior_scale = 0.1;
ivector_extraction_opts.max_remembered_frames = 1000;
ivector_extraction_opts.max_count = 100;
ivector_extraction_opts.ivector_period = 200;
feature_info_.use_ivectors = true;
feature_info_.ivector_extractor_info.Init(ivector_extraction_opts);
nnet3_rxfilename_ = model_path_str + "/final.mdl";
hclg_fst_rxfilename_ = model_path_str + "/HCLG.fst";
hcl_fst_rxfilename_ = model_path_str + "/HCLr.fst";
g_fst_rxfilename_ = model_path_str + "/Gr.fst";
disambig_rxfilename_ = model_path_str + "/disambig_tid.int";
word_syms_rxfilename_ = model_path_str + "/words.txt";
winfo_rxfilename_ = model_path_str + "/word_boundary.int";
feature_info_.silence_weighting_config.silence_phones_str = endpoint_config_.silence_phones;
trans_model_ = new kaldi::TransitionModel();
nnet_ = new kaldi::nnet3::AmNnetSimple();
@@ -126,19 +212,35 @@ Model::Model(const char *model_path) {
SetDropoutTestMode(true, &(nnet_->GetNnet()));
nnet3::CollapseModel(nnet3::CollapseModelConfig(), &(nnet_->GetNnet()));
}
decodable_info_ = new nnet3::DecodableNnetSimpleLoopedInfo(decodable_opts_,
nnet_);
struct stat buffer;
if (stat(final_ie_rxfilename_.c_str(), &buffer) == 0) {
KALDI_LOG << "Loading i-vector extractor from " << final_ie_rxfilename_;
OnlineIvectorExtractionConfig ivector_extraction_opts;
ivector_extraction_opts.splice_config_rxfilename = model_path_str_ + "/ivector/splice.conf";
ivector_extraction_opts.cmvn_config_rxfilename = model_path_str_ + "/ivector/online_cmvn.conf";
ivector_extraction_opts.lda_mat_rxfilename = model_path_str_ + "/ivector/final.mat";
ivector_extraction_opts.global_cmvn_stats_rxfilename = model_path_str_ + "/ivector/global_cmvn.stats";
ivector_extraction_opts.diag_ubm_rxfilename = model_path_str_ + "/ivector/final.dubm";
ivector_extraction_opts.ivector_extractor_rxfilename = model_path_str_ + "/ivector/final.ie";
feature_info_.use_ivectors = true;
feature_info_.ivector_extractor_info.Init(ivector_extraction_opts);
} else {
feature_info_.use_ivectors = false;
}
if (stat(hclg_fst_rxfilename_.c_str(), &buffer) == 0) {
KALDI_LOG << "Loading HCLG from " << hclg_fst_rxfilename_;
hclg_fst_ = fst::ReadFstKaldiGeneric(hclg_fst_rxfilename_);
hcl_fst_ = NULL;
g_fst_ = NULL;
} else {
KALDI_LOG << "Loading HCL and G from " << hcl_fst_rxfilename_ << " " << g_fst_rxfilename_;
hclg_fst_ = NULL;
hcl_fst_ = fst::StdFst::Read(hcl_fst_rxfilename_);
g_fst_ = fst::StdFst::Read(g_fst_rxfilename_);
ReadIntegerVectorSimple(disambig_rxfilename_, &disambig_);
}
@@ -149,6 +251,7 @@ Model::Model(const char *model_path) {
word_syms_ = g_fst_->OutputSymbols();
}
if (!word_syms_) {
KALDI_LOG << "Loading words from " << word_syms_rxfilename_;
if (!(word_syms_ = fst::SymbolTable::ReadText(word_syms_rxfilename_)))
KALDI_ERR << "Could not read symbol table from file "
<< word_syms_rxfilename_;
@@ -156,11 +259,38 @@ Model::Model(const char *model_path) {
KALDI_ASSERT(word_syms_);
if (stat(winfo_rxfilename_.c_str(), &buffer) == 0) {
KALDI_LOG << "Loading winfo " << winfo_rxfilename_;
kaldi::WordBoundaryInfoNewOpts opts;
winfo_ = new kaldi::WordBoundaryInfo(opts, winfo_rxfilename_);
} else {
winfo_ = NULL;
}
if (stat(carpa_rxfilename_.c_str(), &buffer) == 0) {
KALDI_LOG << "Loading CARPA model from " << carpa_rxfilename_;
std_lm_fst_ = fst::ReadFstKaldi(std_fst_rxfilename_);
fst::Project(std_lm_fst_, fst::PROJECT_OUTPUT);
if (std_lm_fst_->Properties(fst::kILabelSorted, true) == 0) {
fst::ILabelCompare<fst::StdArc> ilabel_comp;
fst::ArcSort(std_lm_fst_, ilabel_comp);
}
ReadKaldiObject(carpa_rxfilename_, &const_arpa_);
} else {
std_lm_fst_ = NULL;
}
}
void Model::Ref()
{
ref_cnt_++;
}
void Model::Unref()
{
ref_cnt_--;
if (ref_cnt_ == 0) {
delete this;
}
}
Model::~Model() {
+26 -9
View File
@@ -32,6 +32,7 @@
#include "rnnlm/rnnlm-utils.h"
using namespace kaldi;
using namespace std;
class KaldiRecognizer;
@@ -39,18 +40,29 @@ class Model {
public:
Model(const char *model_path);
~Model();
void Ref();
void Unref();
protected:
~Model();
void ConfigureV1();
void ConfigureV2();
void ReadDataFiles();
friend class KaldiRecognizer;
std::string nnet3_rxfilename_;
std::string hclg_fst_rxfilename_;
std::string hcl_fst_rxfilename_;
std::string g_fst_rxfilename_;
std::string word_syms_rxfilename_;
std::string winfo_rxfilename_;
std::string disambig_rxfilename_;
string model_path_str_;
string nnet3_rxfilename_;
string hclg_fst_rxfilename_;
string hcl_fst_rxfilename_;
string g_fst_rxfilename_;
string disambig_rxfilename_;
string word_syms_rxfilename_;
string winfo_rxfilename_;
string carpa_rxfilename_;
string std_fst_rxfilename_;
string final_ie_rxfilename_;
string mfcc_conf_rxfilename_;
kaldi::OnlineEndpointConfig endpoint_config_;
kaldi::LatticeFasterDecoderConfig nnet3_decoding_config_;
@@ -62,11 +74,16 @@ protected:
kaldi::nnet3::AmNnetSimple *nnet_;
const fst::SymbolTable *word_syms_;
kaldi::WordBoundaryInfo *winfo_;
std::vector<int32> disambig_;
vector<int32> disambig_;
fst::Fst<fst::StdArc> *hclg_fst_;
fst::Fst<fst::StdArc> *hcl_fst_;
fst::Fst<fst::StdArc> *g_fst_;
fst::VectorFst<fst::StdArc> *std_lm_fst_;
kaldi::ConstArpaLm const_arpa_;
int ref_cnt_;
};
#endif /* MODEL_H_ */
+15
View File
@@ -24,4 +24,19 @@ SpkModel::SpkModel(const char *speaker_path) {
SetBatchnormTestMode(true, &speaker_nnet);
SetDropoutTestMode(true, &speaker_nnet);
CollapseModel(nnet3::CollapseModelConfig(), &speaker_nnet);
ref_cnt_ = 1;
}
void SpkModel::Ref()
{
ref_cnt_++;
}
void SpkModel::Unref()
{
ref_cnt_--;
if (ref_cnt_ == 0) {
delete this;
}
}
+5
View File
@@ -27,12 +27,17 @@ class SpkModel {
public:
SpkModel(const char *spk_path);
void Ref();
void Unref();
protected:
friend class KaldiRecognizer;
~SpkModel() {};
kaldi::nnet3::Nnet speaker_nnet;
MfccOptions spkvector_mfcc_opts;
int ref_cnt_;
};
#endif /* SPK_MODEL_H_ */
+96 -32
View File
@@ -1,7 +1,10 @@
%module(package="vosk") vosk
#if SWIGPYTHON
%module(package="vosk", "threads"=1) vosk
#else
%module Vosk
#endif
%include <typemaps.i>
%include <std_string.i>
#if SWIGPYTHON
%include <pybuffer.i>
@@ -11,39 +14,12 @@
%include <arrays_csharp.i>
#endif
namespace kaldi {
}
#if SWIGPYTHON
%pybuffer_binary(const char *data, int len);
%ignore KaldiRecognizer::AcceptWaveform(const short *sdata, int len);
%ignore KaldiRecognizer::AcceptWaveform(const float *fdata, int len);
%exception {
try {
$action
} catch (kaldi::KaldiFatalError &e) {
PyErr_SetString(PyExc_RuntimeError, const_cast<char*>(e.KaldiMessage()));
SWIG_fail;
} catch (std::exception &e) {
PyErr_SetString(PyExc_RuntimeError, const_cast<char*>(e.what()));
SWIG_fail;
}
}
#endif
#if SWIGJAVA
%apply char *BYTE {const char *data};
%ignore KaldiRecognizer::AcceptWaveform(const short *sdata, int len);
%ignore KaldiRecognizer::AcceptWaveform(const float *fdata, int len);
#endif
%{
#include "kaldi_recognizer.h"
#include "model.h"
#include "spk_model.h"
%}
#if SWIGJAVA
%typemap(javaimports) KaldiRecognizer %{
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
@@ -67,6 +43,94 @@ CSHARP_ARRAYS(char, byte)
%apply short INPUT[] {const short *sdata};
#endif
%include "kaldi_recognizer.h"
%include "model.h"
%include "spk_model.h"
#if SWIGJAVASCRIPT
%begin %{
#include <v8.h>
#include <node.h>
#include <node_buffer.h>
%}
#endif
%{
#include "vosk_api.h"
typedef struct VoskModel Model;
typedef struct VoskSpkModel SpkModel;
typedef struct VoskRecognizer KaldiRecognizer;
%}
typedef struct {} Model;
typedef struct {} SpkModel;
typedef struct {} KaldiRecognizer;
%extend Model {
Model(const char *model_path) {
return vosk_model_new(model_path);
}
~Model() {
vosk_model_free($self);
}
}
%extend SpkModel {
SpkModel(const char *model_path) {
return vosk_spk_model_new(model_path);
}
~SpkModel() {
vosk_spk_model_free($self);
}
}
%extend KaldiRecognizer {
KaldiRecognizer(Model *model, float sample_rate) {
return vosk_recognizer_new(model, sample_rate);
}
KaldiRecognizer(Model *model, SpkModel *spk_model, float sample_rate) {
return vosk_recognizer_new_spk(model, spk_model, sample_rate);
}
KaldiRecognizer(Model *model, float sample_rate, const char* grammar) {
return vosk_recognizer_new_grm(model, sample_rate, grammar);
}
~KaldiRecognizer() {
vosk_recognizer_free($self);
}
#if SWIGCSHARP
bool AcceptWaveform(const char *data, int len) {
return vosk_recognizer_accept_waveform($self, data, len);
}
bool AcceptWaveform(const short *sdata, int len) {
return vosk_recognizer_accept_waveform_s($self, sdata, len);
}
bool AcceptWaveform(const float *fdata, int len) {
return vosk_recognizer_accept_waveform_f($self, fdata, len);
}
#elif SWIGJAVA
bool AcceptWaveform(const char *data, int len) {
return vosk_recognizer_accept_waveform($self, data, len);
}
#elif SWIGJAVASCRIPT
bool AcceptWaveform(SWIG_Object ptr) {
char* data = (char*) node::Buffer::Data(ptr);
size_t length = node::Buffer::Length(ptr);
return vosk_recognizer_accept_waveform($self, data, length);
}
#else
int AcceptWaveform(const char *data, int len) {
return vosk_recognizer_accept_waveform($self, data, len);
}
#endif
const char* Result() {
return vosk_recognizer_result($self);
}
const char* PartialResult() {
return vosk_recognizer_partial_result($self);
}
const char* FinalResult() {
return vosk_recognizer_final_result($self);
}
}
%rename(SetLogLevel) vosk_set_log_level;
void vosk_set_log_level(int level);
+97
View File
@@ -0,0 +1,97 @@
// Copyright 2020 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.
#include "vosk_api.h"
#include "kaldi_recognizer.h"
#include "model.h"
#include "spk_model.h"
#include <string.h>
using namespace kaldi;
VoskModel *vosk_model_new(const char *model_path)
{
return (VoskModel *)new Model(model_path);
}
void vosk_model_free(VoskModel *model)
{
((Model *)model)->Unref();
}
VoskSpkModel *vosk_spk_model_new(const char *model_path)
{
return (VoskSpkModel *)new SpkModel(model_path);
}
void vosk_spk_model_free(VoskSpkModel *model)
{
((SpkModel *)model)->Unref();
}
VoskRecognizer *vosk_recognizer_new(VoskModel *model, float sample_rate)
{
return (VoskRecognizer *)new KaldiRecognizer((Model *)model, sample_rate);
}
VoskRecognizer *vosk_recognizer_new_spk(VoskModel *model, VoskSpkModel *spk_model, float sample_rate)
{
return (VoskRecognizer *)new KaldiRecognizer((Model *)model, (SpkModel *)spk_model, sample_rate);
}
VoskRecognizer *vosk_recognizer_new_grm(VoskModel *model, float sample_rate, const char *grammar)
{
return (VoskRecognizer *)new KaldiRecognizer((Model *)model, sample_rate, grammar);
}
int vosk_recognizer_accept_waveform(VoskRecognizer *recognizer, const char *data, int length)
{
return ((KaldiRecognizer *)(recognizer))->AcceptWaveform(data, length);
}
int vosk_recognizer_accept_waveform_s(VoskRecognizer *recognizer, const short *data, int length)
{
return ((KaldiRecognizer *)(recognizer))->AcceptWaveform(data, length);
}
int vosk_recognizer_accept_waveform_f(VoskRecognizer *recognizer, const float *data, int length)
{
return ((KaldiRecognizer *)(recognizer))->AcceptWaveform(data, length);
}
const char *vosk_recognizer_result(VoskRecognizer *recognizer)
{
return ((KaldiRecognizer *)recognizer)->Result();
}
const char *vosk_recognizer_partial_result(VoskRecognizer *recognizer)
{
return ((KaldiRecognizer *)recognizer)->PartialResult();
}
const char *vosk_recognizer_final_result(VoskRecognizer *recognizer)
{
return ((KaldiRecognizer *)recognizer)->FinalResult();
}
void vosk_recognizer_free(VoskRecognizer *recognizer)
{
delete (KaldiRecognizer *)(recognizer);
}
void vosk_set_log_level(int log_level)
{
SetVerboseLevel(log_level);
}
+210
View File
@@ -0,0 +1,210 @@
// Copyright 2020 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.
/* This header contains the C API for Vosk speech recognition system */
#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 */
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);
/** 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 */
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 sample_rate The sample rate of the audio you going to feed into the recognizer
* @returns recognizer object */
VoskRecognizer *vosk_recognizer_new(VoskModel *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 spk_model speaker model for speaker identification
* @param sample_rate The sample rate of the audio you going to feed into the recognizer
* @returns recognizer object */
VoskRecognizer *vosk_recognizer_new_spk(VoskModel *model, VoskSpkModel *spk_model, float sample_rate);
/** Creates the recognizer object with the grammar
*
* Sometimes when you want to improve recognition accuracy and when you don't need
* to recognize large vocabulary you can specify a list of words 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 sample_rate The sample rate of the audio you going to feed into the recognizer
* @param grammar The string with the list of words to recognize, for example "one two three four five [unk]"
*
* @returns recognizer object */
VoskRecognizer *vosk_recognizer_new_grm(VoskModel *model, float sample_rate, const char *grammar);
/** 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 true if silence is occured and you can retrieve a new utterance with result method */
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>
* {
* "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>
*/
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);
/** 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);
#ifdef __cplusplus
}
#endif
#endif /* _VOSK_API_H_ */
+57 -15
View File
@@ -10,6 +10,9 @@ RUN apt-get update && \
libffi-dev \
libpcre3-dev \
zlib1g-dev \
automake \
autoconf \
libtool \
&& rm -rf /var/lib/apt/lists/*
RUN cd /opt \
@@ -20,21 +23,6 @@ RUN cd /opt \
&& cd .. \
&& rm -rf swig-4.0.1.tar.gz swig-4.0.1
ARG OPENBLAS_ARCH=ARMV7
RUN cd /opt \
&& export OPENFST_CONFIGURE="--enable-static --enable-shared --enable-far --enable-ngram-fsts --enable-lookahead-fsts --with-pic --disable-bin --host=${CROSS_TRIPLE} --build=x86-linux-gnu" \
&& git clone -b lookahead --single-branch https://github.com/alphacep/kaldi \
&& cd kaldi/tools \
&& git clone -b v0.3.7 --single-branch https://github.com/xianyi/OpenBLAS \
&& make PREFIX=$(pwd)/OpenBLAS/install TARGET="${OPENBLAS_ARCH}" HOSTCC=gcc USE_LOCKING=1 USE_THREAD=0 -C OpenBLAS all install \
&& sed -i 's:status=0:exit 0:g' extras/check_dependencies.sh \
&& make -j 10 openfst \
&& cd /opt/kaldi/src \
&& sed -i "s:TARGET_ARCH=\"\`uname -m\`\":TARGET_ARCH=$(echo $CROSS_TRIPLE|cut -d - -f 1):g" configure \
&& ./configure --mathlib=OPENBLAS --shared --use-cuda=no \
&& make -j 10 online2 \
&& find /opt/kaldi -name "*.o" -exec rm {} \;
RUN cd /opt \
&& wget -q https://github.com/openssl/openssl/archive/OpenSSL_1_0_2u.tar.gz \
&& tar xf OpenSSL_1_0_2u.tar.gz \
@@ -60,3 +48,57 @@ RUN cd /opt \
&& make -j $(nproc) \
&& make install \
&& rm -rf /opt/cpython-3.7.6 /opt/cpython-3.7.6-cross /opt/v3.7.6.tar.gz
RUN cd /opt \
&& wget -q https://github.com/python/cpython/archive/v3.6.10.tar.gz \
&& tar xf v3.6.10.tar.gz \
&& cp -r cpython-3.6.10 cpython-3.6.10-cross \
&& cd /opt/cpython-3.6.10 \
&& AR=/usr/bin/ar RANLIB=/usr/bin/ranlib CPP=/usr/bin/cpp CXX=/usr/bin/g++ CC=/usr/bin/gcc ./configure --prefix="/opt/python/cp3.6-cp3.6m" \
&& make -j $(nproc) \
&& make install \
&& /opt/python/cp3.6-cp3.6m/bin/pip3 install -U pip \
&& /opt/python/cp3.6-cp3.6m/bin/pip3 install -U wheel \
&& cd /opt/cpython-3.6.10-cross \
&& export PATH=/opt/python/cp3.6-cp3.6m/bin:$PATH \
&& ./configure --prefix=$CROSS_ROOT --with-openssl=$CROSS_ROOT --host=${CROSS_TRIPLE} --build=x86-linux-gnu --disable-ipv6 ac_cv_file__dev_ptmx=no ac_cv_file__dev_ptc=no ac_cv_have_long_long_format=yes \
&& make -j $(nproc) \
&& make install \
&& rm -rf /opt/cpython-3.6.10 /opt/cpython-3.6.10-cross /opt/v3.6.10.tar.gz
RUN cd /opt \
&& wget -q https://github.com/python/cpython/archive/v3.8.3.tar.gz \
&& tar xf v3.8.3.tar.gz \
&& cp -r cpython-3.8.3 cpython-3.8.3-cross \
&& cd /opt/cpython-3.8.3 \
&& AR=/usr/bin/ar RANLIB=/usr/bin/ranlib CPP=/usr/bin/cpp CXX=/usr/bin/g++ CC=/usr/bin/gcc ./configure --prefix="/opt/python/cp3.8-cp3.8m" \
&& make -j $(nproc) \
&& make install \
&& /opt/python/cp3.8-cp3.8m/bin/pip3 install -U pip \
&& /opt/python/cp3.8-cp3.8m/bin/pip3 install -U wheel \
&& cd /opt/cpython-3.8.3-cross \
&& export PATH=/opt/python/cp3.8-cp3.8m/bin:$PATH \
&& ./configure --prefix=$CROSS_ROOT --with-openssl=$CROSS_ROOT --host=${CROSS_TRIPLE} --build=x86-linux-gnu --disable-ipv6 ac_cv_file__dev_ptmx=no ac_cv_file__dev_ptc=no ac_cv_have_long_long_format=yes \
&& make -j $(nproc) \
&& make install \
&& rm -rf /opt/cpython-3.8.3 /opt/cpython-3.8.3-cross /opt/v3.8.3.tar.gz
ARG OPENBLAS_ARCH=ARMV7
ARG ARM_HARDWARE_OPTS="-mfloat-abi=hard -mfpu=neon"
RUN cd /opt \
&& git clone -b lookahead --single-branch https://github.com/alphacep/kaldi \
&& cd kaldi/tools \
&& git clone -b v0.3.7 --single-branch https://github.com/xianyi/OpenBLAS \
&& make PREFIX=$(pwd)/OpenBLAS/install TARGET="${OPENBLAS_ARCH}" HOSTCC=gcc USE_LOCKING=1 USE_THREAD=0 -C OpenBLAS all install \
&& git clone https://github.com/alphacep/openfst openfst \
&& cd openfst \
&& autoreconf -i \
&& ./configure --prefix=/opt/kaldi/tools/openfst --enable-static --enable-shared --enable-far --enable-ngram-fsts --enable-lookahead-fsts --with-pic --disable-bin --host=${CROSS_TRIPLE} --build=x86-linux-gnu \
&& make -j 10 && make install \
&& cd /opt/kaldi/src \
&& sed -i "s:TARGET_ARCH=\"\`uname -m\`\":TARGET_ARCH=$(echo $CROSS_TRIPLE|cut -d - -f 1):g" configure \
&& sed -i "s:-mfloat-abi=hard -mfpu=neon:${ARM_HARDWARE_OPTS}:g" makefiles/linux_openblas_arm.mk \
&& sed -i "s: -O1 : -O3 :g" makefiles/linux_openblas_arm.mk \
&& ./configure --mathlib=OPENBLAS --shared --use-cuda=no \
&& make -j 10 online2 lm \
&& find /opt/kaldi -name "*.o" -exec rm {} \;
+17 -21
View File
@@ -7,29 +7,11 @@ RUN yum -y update && yum -y install \
wget \
openssl-devel \
pcre-devel \
automake \
autoconf \
libtool \
&& yum clean all
RUN cd /opt \
&& wget https://github.com/Kitware/CMake/releases/download/v3.16.2/cmake-3.16.2.tar.gz \
&& tar xf cmake-3.16.2.tar.gz \
&& cd cmake-3.16.2 \
&& ./configure --prefix=/usr && make -j 10 && make install \
&& cd .. \
&& rm -rf cmake-3.16.2 cmake-3.16.2.tar.gz
RUN cd /opt \
&& export OPENFST_CONFIGURE="--enable-static --enable-shared --enable-far --enable-ngram-fsts --enable-lookahead-fsts --with-pic --disable-bin" \
&& git clone -b lookahead --single-branch https://github.com/alphacep/kaldi \
&& cd kaldi/tools \
&& git clone -b v0.3.7 --single-branch https://github.com/xianyi/OpenBLAS \
&& make PREFIX=$(pwd)/OpenBLAS/install TARGET=NEHALEM USE_LOCKING=1 USE_THREAD=0 -C OpenBLAS all install \
&& sed -i 's:status=0:exit 0:g' extras/check_dependencies.sh \
&& make -j 10 openfst \
&& cd ../src \
&& ./configure --mathlib=OPENBLAS --shared --use-cuda=no \
&& make -j 10 online2 \
&& find /opt/kaldi -name "*.o" -exec rm {} \;
RUN cd /opt \
&& wget -O swig-4.0.1.tar.gz https://sourceforge.net/projects/swig/files/swig/swig-4.0.1/swig-4.0.1.tar.gz/download \
&& tar xf swig-4.0.1.tar.gz \
@@ -38,3 +20,17 @@ RUN cd /opt \
&& cd .. \
&& rm -rf swig-4.0.1.tar.gz swig-4.0.1
RUN cd /opt \
&& git clone -b lookahead --single-branch https://github.com/alphacep/kaldi \
&& cd kaldi/tools \
&& git clone -b v0.3.7 --single-branch https://github.com/xianyi/OpenBLAS \
&& make PREFIX=$(pwd)/OpenBLAS/install TARGET=NEHALEM USE_LOCKING=1 USE_THREAD=0 -C OpenBLAS all install \
&& git clone https://github.com/alphacep/openfst openfst \
&& cd openfst \
&& autoreconf -i \
&& ./configure --prefix=/opt/kaldi/tools/openfst --enable-static --enable-shared --enable-far --enable-ngram-fsts --enable-lookahead-fsts --with-pic --disable-bin \
&& make -j 10 && make install \
&& cd /opt/kaldi/src \
&& ./configure --mathlib=OPENBLAS --shared --use-cuda=no \
&& make -j 10 online2 lm \
&& find /opt/kaldi -name "*.o" -exec rm {} \;
+5 -1
View File
@@ -4,5 +4,9 @@ set -e
set -x
docker build --build-arg="DOCKCROSS_IMAGE=linux-armv7" --build-arg="OPENBLAS_ARCH=ARMV7" --file Dockerfile.dockcross --tag alphacep/kaldi-dockcross-armv7:latest .
docker build --build-arg="DOCKCROSS_IMAGE=linux-armv6" --build-arg="OPENBLAS_ARCH=ARMV6" --file Dockerfile.dockcross --tag alphacep/kaldi-dockcross-armv6:latest .
docker build --build-arg="DOCKCROSS_IMAGE=linux-armv6" --build-arg="OPENBLAS_ARCH=ARMV6" --build-arg="ARM_HARDWARE_OPTS=" --file Dockerfile.dockcross --tag alphacep/kaldi-dockcross-armv6:latest .
docker build --build-arg="DOCKCROSS_IMAGE=linux-arm64" --build-arg="OPENBLAS_ARCH=ARMV8" --file Dockerfile.dockcross --tag alphacep/kaldi-dockcross-arm64:latest .
docker run --rm -v /home/shmyrev/travis/vosk-api/:/io alphacep/kaldi-dockcross-armv6 /io/travis/build-wheels-dockcross.sh
docker run --rm -v /home/shmyrev/travis/vosk-api/:/io alphacep/kaldi-dockcross-armv7 /io/travis/build-wheels-dockcross.sh
docker run --rm -v /home/shmyrev/travis/vosk-api/:/io alphacep/kaldi-dockcross-arm64 /io/travis/build-wheels-dockcross.sh
+1
View File
@@ -4,3 +4,4 @@ set -e
set -x
docker build --file Dockerfile.manylinux --tag alphacep/kaldi-manylinux:latest .
docker run --rm -e PLAT=manylinux2010_x86_64 -v /home/shmyrev/travis/vosk-api/:/io alphacep/kaldi-manylinux /io/travis/build-wheels.sh
+33 -16
View File
@@ -1,20 +1,37 @@
#!/bin/bash
set -e -x
export KALDI_ROOT=/opt/kaldi
export WHEEL_FLAGS=`$CROSS_ROOT/bin/python3-config --cflags`
export PATH=/opt/python/cp3.7-cp3.7m/bin:$PATH
echo $CROSS_TRIPLE
case $CROSS_TRIPLE in
*arm-*)
export _PYTHON_HOST_PLATFORM=linux-armv6l
;;
*armv7-*)
export _PYTHON_HOST_PLATFORM=linux-armv7l
;;
*aarch64-*)
export _PYTHON_HOST_PLATFORM=linux-aarch64
;;
esac
ORIG_PATH=$PATH
for pyver in 3.6 3.7 3.8; do
pip3 wheel /io/python -w /io/wheelhouse
export KALDI_ROOT=/opt/kaldi
export PATH=/opt/python/cp${pyver}-cp${pyver}m/bin:$ORIG_PATH
export VOSK_SOURCE=/io/src
# Python 3.8 somehow changed syconfig file name
sysconfig_bit="m"
if [ $pyver == "3.8" ]; then
sysconfig_bit=""
fi
case $CROSS_TRIPLE in
*arm-*)
export _PYTHON_HOST_PLATFORM=linux-armv6l
export _PYTHON_SYSCONFIGDATA_NAME=_sysconfigdata_${sysconfig_bit}_linux_arm-linux-gnueabihf
;;
*armv7-*)
export _PYTHON_HOST_PLATFORM=linux-armv7l
export _PYTHON_SYSCONFIGDATA_NAME=_sysconfigdata_${sysconfig_bit}_linux_arm-linux-gnueabihf
;;
*aarch64-*)
export _PYTHON_HOST_PLATFORM=linux-aarch64
export _PYTHON_SYSCONFIGDATA_NAME=_sysconfigdata_${sysconfig_bit}_linux_aarch64-linux-gnu
;;
esac
export PYTHONHOME=$CROSS_ROOT
export PYTHONPATH=/opt/python/cp${pyver}-cp${pyver}m/lib/python${pyver}/site-packages:/opt/python/cp${pyver}-cp${pyver}m/lib/python${pyver}/lib-dynload
rm -rf /io/python/build
pip${pyver} -v wheel /io/python -w /io/wheelhouse
done
+4 -3
View File
@@ -4,10 +4,11 @@ set -e -x
export KALDI_ROOT=/opt/kaldi
# Compile wheels
for pypath in /opt/python/cp3*; do
export WHEEL_FLAGS=`${pypath}/bin/python3-config --cflags`
for pypath in /opt/python/cp3[56789]*; do
export VOSK_SOURCE=/io/src
mkdir -p /opt/wheelhouse
"${pypath}/bin/pip" wheel /io/python -w /opt/wheelhouse
rm -rf /io/python/build
"${pypath}/bin/pip" -v wheel /io/python -w /opt/wheelhouse
done
# Bundle external shared libraries into the wheels
+3
View File
@@ -0,0 +1,3 @@
exports.printMsg = function() {
console.log("This is a message from the Vosk package");
}
+20
View File
@@ -0,0 +1,20 @@
{
"name": "vosk-js",
"version": "0.3.0",
"description": "Node binding for continuous voice recoginition through vosk-api.",
"repository": {
"type": "git",
"url": "git://github.com/alphacep/vosk-api.git"
},
"main": "index.js",
"keywords": [
"speech",
"speech recognition",
"voice"
],
"author": "Alpha Cephei Inc.",
"license": "Apache 2.0",
"engines": {
"node": ">= 12.x.x"
}
}