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Dissonance Spectrum explicitly models perceptual frequency interactions for better music understanding

arXiv 2608.25621 ↗First posted 26 Aug 2026cs.SD cs.AIcited by 0

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Abstract (arXiv)

Conventional music representations describe acoustic energy over time and frequency but do not explicitly expose relations among simultaneous frequency components. We introduce the Dissonance Spectrum (DS), a nonnegative time--frequency representation that applies a tolerance-based rational pitch-relation kernel with logarithmic harmonic distance to a constant-Q spectrum and attributes aggregate pairwise interactions back to individual frequency bins. Controlled music-theory tests show strong ordinal agreement for intervals, harmonic-function connections, and church modes, and weaker but significant agreement across diverse chord voicings. DS is then encoded by a lightweight parallel branch whose zero-initialized residual projection preserves the baseline function at initialization. Across six paired training seeds in open-ended music question answering and categorical and dimensional music emotion recognition, DS obtains the highest mean on every reported endpoint relative to the unchanged baseline, a parameter-matched Gaussian-input branch, and an architecture-matched magnitude-CQT branch. These results support DS as an interpretable, complementary representation, while listener-specific perception and broader task coverage remain open problems.

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References · 13

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
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  6. 2023A Foundation Model for Music Informaticscited by 45
  7. 2021SpecTNT: a Time-Frequency Transformer for Music Audiocited by 15
  8. 2019Towards Explainable Music Emotion Recognition: The Route via Mid-level Featurescited by 10
  9. 2016Feature Learning for Chord Recognition: The Deep Chroma Extractorcited by 8
  10. 2025Towards Unified Music Emotion Recognition across Dimensional and Categorical Modelscited by 7
  11. 2013Harmony Perception by Periodicity Detectioncited by 3
  12. 2025From Discord to Harmony: Decomposed Consonance-based Training for Improved Audio Chord Estimationcited by 2
1 more
  1. 2025Psychoacoustic study of simple-tone dyads: frequency ratio and pitchcited by 1

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