自动声乐片段检测在流行音乐

2013 Ninth International Conference on Computational Intelligence and Security Pub Date : 2013-12-14 DOI:10.1109/CIS.2013.80

Liming Song, Ming Li, Yonghong Yan

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引用次数: 7

摘要

提出了一种声学复调音乐信号中人声片段的自动检测技术。我们使用歌唱声音特定的几个特征的组合作为特征，并使用高斯混合模型(GMM)分类器进行声乐和非声乐分类。我们采用了光谱白化预处理，并在RWC流行音乐数据集上存档了81.3%的性能。

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Automatic Vocal Segments Detection in Popular Music

We propose a technique for the automatic vocal segments detection in an acoustical polyphonic music signal. We use a combination of several characteristics specific to singing voice as the feature and employ a Gaussian Mixture Model (GMM) classifier for vocal and non-vocal classification. We have employed a pre-processing of spectral whitening and archived a performance of 81.3% over the RWC popular music dataset.

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2013 Ninth International Conference on Computational Intelligence and Security

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