On Musical Onset Detection via the S-Transform
Abstract
Musical onset detection is a key component in any beat tracking system. Existing onset detection methods are based on temporal/spectral analysis, or methods that integrate temporal and spectral information together with statistical estimation and machine learning models. In this paper, we propose a method to localize onset components in music by using the S-transform, and thus, the method is purely based on temporal/spectral data. Unlike the other methods based on temporal/spectral data, which usually rely short time Fourier transform (STFT), our method enables effective isolation of crucial frequency subbands due to the frequency dependent resolution of S-transform. Moreover, numerical results show, even with less computationally intensive steps, the proposed method can closely resemble the performance of more resource intensive statistical estimation based approaches.
Cite
@article{arxiv.1712.02567,
title = {On Musical Onset Detection via the S-Transform},
author = {Nishal Silva and Chathuranga Weeraddana and Carlo Fischione},
journal= {arXiv preprint arXiv:1712.02567},
year = {2018}
}