Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation
This provides a free, large toolbox for researchers and practitioners in audio classification, but it is incremental as it implements existing techniques in a new platform.
The authors tackled the need for audio data augmentation tools in MATLAB by introducing Audiogmenter, a library with 15 algorithms for raw audio and 8 for spectrograms, validated on the ESC-50 dataset.
Audio data augmentation is a key step in training deep neural networks for solving audio classification tasks. In this paper, we introduce Audiogmenter, a novel audio data augmentation library in MATLAB. We provide 15 different augmentation algorithms for raw audio data and 8 for spectrograms. We efficiently implemented several augmentation techniques whose usefulness has been extensively proved in the literature. To the best of our knowledge, this is the largest MATLAB audio data augmentation library freely available. We validate the efficiency of our algorithms evaluating them on the ESC-50 dataset. The toolbox and its documentation can be downloaded at https://github.com/LorisNanni/Audiogmenter.