Audiogmenter: a MATLAB Toolbox for Audio Data Augmentation

11 Dec 2019  ·  Gianluca Maguolo, Michelangelo Paci, Loris Nanni, Ludovico Bonan ·

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.

PDF Abstract

Datasets


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here