Monaural sound source separation using covariance profile of partials

Priyanka Goel, K. Ramakrishnan
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引用次数: 1

Abstract

This paper addresses the problem of separation of pitched sounds in monaural recordings. We present a novel feature for the estimation of parameters of overlapping harmonics which considers the covariance of partials of pitched sounds. Sound templates are formed from the monophonic parts of the mixture recording. A match for every note is found among these templates on the basis of covariance profile of their harmonics. The matching template for the note provides the second order characteristics for the overlapped harmonics of the note. The algorithm is tested on the RWC music database instrument sounds. The results clearly show that the covariance characteristics can be used to reconstruct overlapping harmonics effectively.
单耳声源分离利用协方差剖面的偏
本文解决了单声录音中音高分离的问题。提出了一种考虑音调偏频协方差的重叠谐波参数估计新方法。声音模板由混合录音的单音部分形成。根据其谐波的协方差分布,在这些模板中找到每个音符的匹配。音符的匹配模板为音符的重叠谐波提供了二阶特征。在RWC音乐数据库中对该算法进行了测试。结果表明,利用协方差特征可以有效地重建重叠谐波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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