A dataset and classification model for Malay, Hindi, Tamil and Chinese music
Sound
2020-09-16 v2 Machine Learning
Audio and Speech Processing
Abstract
In this paper we present a new dataset, with musical excepts from the three main ethnic groups in Singapore: Chinese, Malay and Indian (both Hindi and Tamil). We use this new dataset to train different classification models to distinguish the origin of the music in terms of these ethnic groups. The classification models were optimized by exploring the use of different musical features as the input. Both high level features, i.e., musically meaningful features, as well as low level features, i.e., spectrogram based features, were extracted from the audio files so as to optimize the performance of the different classification models.
Keywords
Cite
@article{arxiv.2009.04459,
title = {A dataset and classification model for Malay, Hindi, Tamil and Chinese music},
author = {Fajilatun Nahar and Kat Agres and Balamurali BT and Dorien Herremans},
journal= {arXiv preprint arXiv:2009.04459},
year = {2020}
}
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4 pages