CLASS-PHSDPOP-PHMar 22, 2012

Entropy-based Tuning of Musical Instruments

arXiv:1203.5101v218 citations
Originality Synthesis-oriented
AI Analysis

This addresses tuning for musical instruments like pianos, offering a computational method that mimics expert aural tuning, but it is incremental as it builds on existing entropy concepts.

The paper tackles the problem of tuning musical instruments by proposing to minimize the Shannon entropy of preprocessed Fourier spectra, which reproduces the correct stretch curve and similar pitch fluctuations as high-quality aural tuning.

The human sense of hearing perceives a combination of sounds 'in tune' if the corresponding harmonic spectra are correlated, meaning that the neuronal excitation pattern in the inner ear exhibits some kind of order. Based on this observation it is suggested that musical instruments such as pianos can be tuned by minimizing the Shannon entropy of suitably preprocessed Fourier spectra. This method reproduces not only the correct stretch curve but also similar pitch fluctuations as in the case of high-quality aural tuning.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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