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Excitation signature extraction for pitched musical instrument timbre analysis using Higher Order Statistics

机译:使用高阶统计量进行音高乐器音色分析的激励特征提取

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The timber of pitched musical instruments is analyzed through the excitation signature by means of Higher Order Statistics (HOS) and subspace analysis. To describe the features of instrument sounding mechanism, the excitation signature is proposed, which decisively characterizes the musical instrument category rather than the difference within one kind of instrument family. Subspace analysis is applied to get more efficient timbre representations for musical instrument classification. Experimental results show that HOS based features provide more significant timbre patterns in both time and frequency domain in comparison with the 2nd order statistics features. Dimensional reduction of excitation signature is also considered for the efficiency of musical instrument classification.
机译:通过高阶统计量(HOS)和子空间分析,通过激励签名来分析音高乐器的木材。为了描述乐器发声机制的特点,提出了激励签名,它能决定性地描述乐器的种类,而不是一种乐器家族之间的差异。子空间分析用于获得更有效的乐器分类音色表示。实验结果表明,与2 顺序统计功能相比,基于HOS的功能在时域和频域均提供了更显着的音色模式。还考虑了激励特征的降维以提高乐器分类的效率。

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