A Pytorch implementation of GoogleBrain's SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
SpecAugment is a SOTA-achieving data augmentation approach on speech recognition. The paper's authors did not publish code that I could find and their implementation was in TensorFlow.
- run
install.sh
(I recommend to use a uniqueconda
env for the project) - Check out SpecAugment.ipynb (a Jupyter notebook) for the functions.
-
Time Warp (Coming Soon) This augmentation relies on a lot of functionality not yet in Pytorch, so I have to write it from scratch. I am working on it.
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Time Mask (DONE!)
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Frequency Mask (DONE!)
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