NMF-based multiple pitch estimation using sparseness and inter-frame continuity constraints

Takanori Fujisawa, Ikuo Degawa, M. Ikehara
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引用次数: 2

Abstract

This paper proposes NMF-based (non-negative matrix factorization) multiple pitch estimation algorithm. The approach of NMF-based multiple pitch estimation is to decompose input magnitude spectrogram into sum of basis spectra representing individual pitches. In decomposing music signals, the amplitude of basis spectra should have sparseness, and the shape of amplitude should be continuous between neighbor temporal frames. We introduce the constraint using matrix norm to enforce these characteristic at once and propose new NMF algorithm for spectral decomposition with this constraint. The evaluation of solo piano music shows this algorithm can implement more robust pitch estimation in the place which input spectrum has certain different shape from basis spectra or the shape of input spectrum has temporal change.
使用稀疏性和帧间连续性约束的基于nmf的多基音估计
提出了一种基于非负矩阵分解(nmf)的多基音估计算法。基于nmf的多基音估计方法是将输入的幅度谱图分解为代表单个基音的基谱和。在对音乐信号进行分解时,基谱的幅值应具有稀疏性,在相邻的时间帧之间,幅值的形状应是连续的。我们利用矩阵范数引入约束来强制这些特征,并提出了一种新的NMF谱分解算法。对钢琴独奏音乐的评价表明,在输入谱与基谱形状存在一定差异或输入谱形状有时间变化的情况下,该算法能实现更强的鲁棒性音高估计。
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