基于小波包分解的音乐类型分类时频分析

Chih-Hsun Chou, Jun-Han Shi
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引用次数: 0

摘要

本文研究了音乐歌曲类型分类中的时频分析方法。考虑到多分辨率分析的优势,本文提出的方法首先采用小波包分解(WPD)从音乐歌曲的谱图中获取候选特征。然后利用奇异值分解(SVD)的降维能力提取所需特征;实验采用知名数据库ISMIR2004。为了检验所提方法的性能,将所提方法的实验结果与基于MFCC的方法的实验结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-Frequency Analysis for Music Genre Classification by using Wavelet Package Decompositions
In this paper, time-frequency analysis method was studied in the genre classification of music songs. Due to the benefits of multi-resolution analysis, the proposed methods first adopted the wavelet package decomposition (WPD) to obtain candidate features from the spectrograms of music songs. Then the singular value decomposition (SVD) was used to extract the desired features because of its dimension reduction ability. In the experiments, well-known database named ISMIR2004 was applied. To examine the performance of the proposed methods, the experimental results of the proposed methods were compared with the results of the MFCC based methods.
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