Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras
Sound
2017-06-20 v1 Machine Learning
Multimedia
Abstract
We introduce Kapre, Keras layers for audio and music signal preprocessing. Music research using deep neural networks requires a heavy and tedious preprocessing stage, for which audio processing parameters are often ignored in parameter optimisation. To solve this problem, Kapre implements time-frequency conversions, normalisation, and data augmentation as Keras layers. We report simple benchmark results, showing real-time on-GPU preprocessing adds a reasonable amount of computation.
Cite
@article{arxiv.1706.05781,
title = {Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras},
author = {Keunwoo Choi and Deokjin Joo and Juho Kim},
journal= {arXiv preprint arXiv:1706.05781},
year = {2017}
}
Comments
ICML 2017 machine learning for music discovery