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--- |
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license: apache-2.0 |
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language: |
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- ja |
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library_name: nemo |
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tags: |
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- automatic-speech-recognition |
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- NeMo |
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--- |
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# reazonspeech-nemo-v2 |
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`reazonspeech-nemo-v2` is an automatic speech recognition model trained |
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on [ReazonSpeech v2.0 corpus](https://huggingface.co/datasets/reazon-research/reazonspeech). |
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This model supports inference of long-form Japanese audio clips up to |
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several hours. |
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## Model Architecture |
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The model features an improved Conformer architecture from |
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[Fast Conformer with Linearly Scalable Attention for Efficient |
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Speech Recognition](https://arxiv.org/abs/2305.05084). |
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* Subword-based RNN-T model. The total parameter count is 619M. |
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* Encoder uses [Longformer](https://arxiv.org/abs/2004.05150) attention |
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with local context size of 256, and has a single global token. |
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* Decoder has a vocabulary space of 3000 tokens constructed by |
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[SentencePiece](https://github.com/google/sentencepiece) |
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unigram tokenizer. |
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We trained this model for 1 million steps using AdamW optimizer |
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following Noam annealing schedule. |
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## Usage |
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We recommend to use this model through our |
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[reazonspeech](https://github.com/reazon-research/reazonspeech) |
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library. |
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``` |
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from reazonspeech.nemo.asr import load_model, transcribe, audio_from_path |
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audio = audio_from_path("speech.wav") |
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model = load_model() |
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ret = transcribe(model, audio) |
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print(ret.text) |
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``` |
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## License |
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[Apaceh Licence 2.0](https://choosealicense.com/licenses/apache-2.0/) |
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