改进音高估计方法，让机器更懂音乐的和谐感。
Pitch Estimation With Mean Averaging Smoothed Product Spectrum And Musical Consonance Evaluation Using MASP
- 用全局均值平滑增强频谱，解决漏泛音导致的音高误判
- 在有无泛音情况下均保持与人耳感知一致的音高估计
- 首次将音高机制延伸至和声和谐度评估，契合音乐理论
本文提出均值平滑乘积谱（MASP）算法，作为谐波乘积谱（HPS）的改进版本，旨在提升对存在缺失泛音等复杂频谱的音高估计鲁棒性，适用于谐波与非谐波情形。通过引入全局均值平滑处理，MASP有效降低了传统HPS对缺失泛音的敏感性，使音高估计结果更符合听觉感知。基于音高与和谐度之间存在周期性关联的观察，该方法进一步扩展为一种谐波度度量（H），用于评估二音与三音组合的音乐和谐性，所得和谐度层级与音乐理论及人类感知高度一致。研究暗示音高感知与和谐感知可能共享依赖于频谱结构的共同神经机制。
原文摘要 · Abstract (English)
This study introduces Mean Averaging Smoothed Product (MASP) Spectrum, which is a modified version of the Harmonic Product Spectrum, designed to enhance pitch estimation for many algorithm-wise deceptive frequency spectra that still lead clear pitches, for both harmonic and inharmonic cases. By introducing a global mean based smoothing for spectrum, the MASP algorithm diminishes the unwanted sensitivity of HPS for spectra with missing partials. The method exhibited robust pitch estimations consistent with perceptual expectations. Motivated upon the strong correlation between consonance and periodicity, the same algorithm is extended and, with the proposition of a harmonicity measure (H), used to evaluate musical consonance for two and three tones; yielding consonance hierarchies that align with perception and practice of music theory. These findings suggest that perception of pitch and consonance may share a similar underlying mechanism that depend on spectrum.
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