deepspeech.pytorch – Implementation of DeepSpeech2 using Baidu Warp-CTC

deepspeech.pytorch is an implementation of DeepSpeech2 using Baidu Warp-CTC. The software creates a network based on the DeepSpeech2 architecture, trained with the CTC activation function.

Features include:

  • Train DeepSpeech, configurable RNN types and architectures with multi-GPU support.
  • Language model support using kenlm (WIP currently).
  • Multiple dataset downloaders, support for AN4, TEDLIUM, Voxforge and Librispeech. Datasets can be merged, and support for custom datasets is included.
  • Noise injection (dynamic) for online training to improve noise robustness.
  • Audio augmentation to improve noise robustness. This applies small changes to the tempo and gain when loading audio to increase robustness.
  • Easy start/stop capabilities in the event of crash or hard stop during training.
  • Visdom/Tensorboard support for visualizing training graphs.

This software has the following dependencies: python-levenshtein, torch, visdom, wget, librosa, and tqdm.

The project also offers a set of pre-trained networks for evaluation usage.

Website: github.com/SeanNaren/deepspeech.pytorch
Support:
Developer: Sean Naren
License: MIT License

deepspeech.pytorch is written in Python. Learn Python with our recommended free books and free tutorials.

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