马来语，印地语，泰米尔语和中国音乐的数据集和分类模型
A dataset and classification model for Malay, Hindi, Tamil and Chinese music
摘要：
在本文中，我们提出了一个新的数据集，音乐例外，从三个主要民族在新加坡：中国，马来人和印度（印地语和泰米尔语）。我们使用这个新的数据集来训练不同的分类模型，以区分这些民族的音乐起源。通过探索使用不同的音乐特征作为输入来优化分类模型。这两个高级特征，即，音乐上有意义的特征，以及低级特征，即，从音频文件中提取基于频谱图的特征，以优化不同分类模型的性能。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
