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Wavelet ridges for musical instrument classification

机译:用于乐器分类的小波脊

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摘要

The time-varying frequency structure of musical signals have been analyzed using wavelets by either extracting the instantaneous frequency of signals or building features from the energies of sub-band coefficients. We propose to benefit from a combination of these two approaches and use the time-frequency domain energy localization curves, called as wavelet ridges, in order to build features for classification of musical instrument sounds. We evaluated the representative capability of our feature in different musical instrument classification problems using support vector machine classifiers. The comparison with the features based on parameterizing the wavelet sub-band energies confirmed the effectiveness of the proposed feature.
机译:音乐信号的时变频率结构已通过使用小波进行了分析,方法是从子带系数的能量中提取信号的瞬时频率或建立特征。我们建议受益于这两种方法的组合,并使用称为小波脊的时频域能量定位曲线,以建立乐器声音分类的特征。我们使用支持向量机分类器评估了我们的功能在不同乐器分类问题中的代表性能力。与基于参数化小波子带能量的特征的比较证实了所提出特征的有效性。

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