A Comprehensive Corpus of Biomechanically Constrained Piano Chords: Generation, Analysis, and Implications for Voicing and Psychoacoustics
arXiv:2603.29710v1 Announce Type: cross Abstract: I present the generation and analysis of the largest known open-source corpus of playable piano chords (approximately 19.3 million entries). This dataset enumerates the two-handed search space subject to biomechanical constraints (two hands, each with 1.5 octave reach) to an unprecedented extent. To demonstrate the corpus's utility, the relationship between voicing shape and psychoacoustic targets was modeled. Harmonicity proved intrinsic to pitch-class identity: voicing statistics added negligible variance ($\Delta R^2 \approx 0.014\%$, $p \approx 0.13$). Conversely, voicing significantly predicted dissonance ($\Delta R^2 \approx 6.75\%$, $p \approx 0.0008$). Crucially, skewness ($\beta \approx +0.145$) was approximately 5.8$\times$ more e
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Abstract:I present the generation and analysis of the largest known open-source corpus of playable piano chords (approximately 19.3 million entries). This dataset enumerates the two-handed search space subject to biomechanical constraints (two hands, each with 1.5 octave reach) to an unprecedented extent. To demonstrate the corpus's utility, the relationship between voicing shape and psychoacoustic targets was modeled. Harmonicity proved intrinsic to pitch-class identity: voicing statistics added negligible variance ($\Delta R^2 \approx 0.014%$, $p \approx 0.13$). Conversely, voicing significantly predicted dissonance ($\Delta R^2 \approx 6.75%$, $p \approx 0.0008$). Crucially, skewness ($\beta \approx +0.145$) was approximately 5.8$\times$ more effective than spread ($\beta \approx -0.025$) at predicting roughness. The analysis challenges the pedagogical emphasis on
spread'': skewness is a stronger predictor of dissonance than spread. This suggests that clarity inopen voicings'' is driven less by width than by negative skewness; achieving lower-register clearance by placing wide gaps at the bottom and allowing tighter clustering in the treble. The results demonstrate the corpus's ability to enable future research, especially in areas such as generative modeling, voice-leading topology, and psychoacoustic analysis.
Comments: 10 pages, 3 figures
Subjects:
Sound (cs.SD); Audio and Speech Processing (eess.AS)
MSC classes: 00A65
Cite as: arXiv:2603.29710 [cs.SD]
(or arXiv:2603.29710v1 [cs.SD] for this version)
https://doi.org/10.48550/arXiv.2603.29710
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Mahesh Ramani [view email] [v1] Tue, 31 Mar 2026 13:13:29 UTC (3,506 KB)
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