STT for TorchScript is a port of Coqui STT based on DeepSpeech to PyTorch.

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Text Data & NLPst3
Overview

st3

STT for TorchScript is a port of Coqui STT based on DeepSpeech to PyTorch.

Currently it supports converting pbmm models to pt scripts with integrated beam search.

Check out the first pre-release: https://github.com/proger/st3/releases

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Releases(english1)

  • english1(Sep 13, 2021)

    This is a conversion of Coqui English STT v0.9.3 model to TorchScript, allowing to deploy a speech recognizer as a single file. The TorchScript bundle is self-contained and runs DeepSpeech frontend and beam search returning 10 best results. LM Scorer is not supported at the moment.

    To run, download the pt file and save the following code to recognize.py and make sure you have torchaudio installed using pip3 install torchaudio:

    import torch, torchaudio, sys

waveform, sr = torchaudio.load(sys.argv[1], normalize=True)
assert sr == 16000
model = torch.jit.load('coqui-stt-0.9.3-models.pt')
for transcript, scores in model(waveform.squeeze()):
    print(transcript, scores)

    Now you can run the model on English recordings like below. Any format supported by TorchAudio backend should work.

    python3 recognize.py sample.wav
    Source code(tar.gz)
    Source code(zip)
    coqui-stt-0.9.3-models.pt(180.26 MB)
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Vlad Ki
Vlad Ki
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