Periodic signal modeling for the octave problem in music transcription

A. Schutz, D. Slock
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引用次数: 5

Abstract

Precise automatic music transcription requires accurate modeling and identification of the spectral content of the audio signal. Whereas a deterministic model in terms of modulated periodic signals allows to distinguish different notes, the presence of multiple notes separated by octaves poses a big problem since they share the same periodicity, and hence completely overlapping spectral content. In this paper we propose the introduction of a spectral model to allow distinction of such mixtures of spectral content at various octaves. Cyclic correlations are estimated at its pitch and decomposed into even and odd parts, corresponding to even and odd harmonics.
音乐转录中八度问题的周期信号建模
精确的自动音乐转录需要对音频信号的频谱内容进行准确的建模和识别。然而,在调制周期信号方面的确定性模型允许区分不同的音符,由八度分隔的多个音符的存在带来了一个大问题,因为它们具有相同的周期性,因此完全重叠的频谱内容。在本文中,我们提出了一个光谱模型的引入,以允许在不同的八度区分这种混合的光谱内容。在其基音处估计循环相关,并将其分解为偶次和奇次,对应于偶次和奇次谐波。
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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