hub / github.com/SymbioticLab/Oort / spec_augment

Function spec_augment

training/utils/spec_augment.py:68–115 · view source on GitHub ↗

Spec augmentation Calculation Function. 'SpecAugment' have 3 steps for audio data augmentation. first step is time warping using Tensorflow's image_sparse_warp function. Second step is frequency masking, last step is time masking. # Arguments: mel_spectrogram(numpy array): audi

(mel_spectrogram, time_warping_para=40, frequency_masking_para=27,
                 time_masking_para=70, frequency_mask_num=1, time_mask_num=1)

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Callers 1

parse_audioMethod · 0.90

Calls 1

time_warpFunction · 0.70

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