DemisEom/SpecAugment
A Implementation of SpecAugment with Tensorflow & Pytorch, introduced by Google Brain
Applies time warping and frequency/time masking directly to mel-spectrograms for robust speech augmentation across both TensorFlow and PyTorch backends. The implementation accepts pre-computed spectrograms via librosa and modifies them through temporal warping, consecutive frequency channel masking, and utterance-level time masking. Includes test utilities with LibriSpeech dataset examples for validation.
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Language
Python
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Apache-2.0
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Last pushed
Apr 05, 2022
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