| # 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 |
| A[Hydra Overrides + Config Dataclass] --> B{Config} |
| B --> |Init| C[Model] |
| B --> |Init| D[Trainer] |
| C & D --> E[Set trainer] |
| E --> |Optional| F[Change Transducer Decoding Strategy] |
| F --> H[Load Manifest] |
| E --> |Skip| H |
| H --> I["model.transcribe(...)"] |
| I --> J[Write output manifest] |
| K[Ground Truth Manifest] |
| 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)`. |
