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28 lines
1.1 KiB
Markdown
28 lines
1.1 KiB
Markdown
# Automatic Speech Recognition
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This directory contains example scripts to train ASR models using various methods such as Connectionist Temporal Classification loss, RNN Transducer Loss.
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Speech pre-training via self supervised learning, voice activity detection and other sub-domains are also included as part of this domain's examples.
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# ASR Model inference execution overview
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The inference scripts in this directory execute in the following order. When preparing your own inference scripts, please follow this order for correct inference.
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```mermaid
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graph TD
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A[Hydra Overrides + Config Dataclass] --> B{Config}
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B --> |Init| C[Model]
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B --> |Init| D[Trainer]
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C & D --> E[Set trainer]
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E --> |Optional| F[Change Transducer Decoding Strategy]
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F --> H[Load Manifest]
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E --> |Skip| H
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H --> I["model.transcribe(...)"]
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I --> J[Write output manifest]
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K[Ground Truth Manifest]
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J & K --> |Optional| L[Evaluate CER/WER]
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```
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During restoration of the model, you may pass the Trainer to the restore_from / from_pretrained call, or set it after the model has been initialized by using `model.set_trainer(Trainer)`. |