mlsanityData to 14 Oct 2026

Incorporating Structure and Chord Constraints in Symbolic Transformer-based Melodic Harmonization

arXiv 2512.07627 ↗First posted 8 Dec 2025cs.SD cs.AI cs.SCcited by 2

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Abstract (arXiv)

Transformer architectures offer significant advantages regarding the generation of symbolic music; their capabilities for incorporating user preferences toward what they generate is being studied under many aspects. This paper studies the inclusion of predefined chord constraints in melodic harmonization, i.e., where a desired chord at a specific location is provided along with the melody as inputs and the autoregressive transformer model needs to incorporate the chord in the harmonization that it generates. The peculiarities of involving such constraints is discussed and an algorithm is proposed for tackling this task. This algorithm is called B* and it combines aspects of beam search and A* along with backtracking to force pretrained transformers to satisfy the chord constraints, at the correct onset position within the correct bar. The algorithm is brute-force and has exponential complexity in the worst case; however, this paper is a first attempt to highlight the difficulties of the problem and proposes an algorithm that offers many possibilities for improvements since it accommodates the involvement of heuristics.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 23 of its 41 references that are in the map. First posted on arXiv 8 Dec 2025.

Builds on

23 of 41 references.

References · 23

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11 more
  1. 2020Directed Beam Search: Plug-and-Play Lexically Constrained Language Generationcited by 12
  2. 2024MelodyT5: A Unified Score-to-Score Transformer for Symbolic Music Processingcited by 12
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  5. 2020Melody Harmonization Using Orderless NADE, Chord Balancing, and Blocked Gibbs Samplingcited by 7
  6. 2021Generating Chord Progression from Melody with Flexible Harmonic Rhythm and Controllable Harmonic Densitycited by 5
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Citing papers per year: 2026: 2.

2 papers.