论文标题
马来，印地语，泰米尔语和中文音乐的数据集和分类模型
A dataset and classification model for Malay, Hindi, Tamil and Chinese music
论文作者
论文摘要
在本文中，我们介绍了一个新的数据集，其中有来自新加坡三个主要种族的音乐剧除外：中国，马来和印度人（印地语和泰米尔语）。我们使用这个新数据集来训练不同的分类模型，以这些种族群体来区分音乐的起源。通过探索使用不同的音乐功能作为输入来优化分类模型。从音频文件中提取了两个高级功能，即音乐上有意义的功能以及低级功能，即基于频谱图的功能，以优化不同的分类模型的性能。
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.
