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Musical instrument classification using higher order spectra

机译:使用高阶谱对乐器进行分类

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This paper presents classification and recognition of monophonic isolated musical instrument sounds using higher order spectra such as Bispectrum and Trispectrum. Experimental results on a widely used dataset shows that higher order spectra based features improve the recognition accuracy, when combined with conventional features such as Mel Frequency Cepstral Coefficient (MFCC), Cepstral, Spectral and Temporal features. Nineteen western musical instruments covering four families with full pitch range have been used for experimentation.
机译:本文介绍了使用高阶频谱(例如双频谱和三频谱)对单音孤立乐器声音的分类和识别。在广泛使用的数据集上的实验结果表明,与常规特征(如梅尔频率倒谱系数(MFCC),倒谱,频谱和时间特征)结合使用时,基于高阶谱的特征可提高识别精度。涵盖四个音高范围的19个西方乐器已用于实验。

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