# Structure-Aware Piano Accompaniment via Style Planning and Dataset-Aligned Pattern Retrieval

arXiv: https://arxiv.org/abs/2602.15074 · HTML: https://mlsanity.com/paper/2602.15074/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 23 references that are in the map.
- First posted on arXiv 16 Feb 2026.

## Builds on (most cited first, 15 of 15)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Music Transformer](https://mlsanity.com/paper/1809.04281/) (2018)
- [POP909: A Pop-song Dataset for Music Arrangement Generation](https://mlsanity.com/paper/2008.07142/) (2020)
- [This Time with Feeling: Learning Expressive Musical Performance](https://mlsanity.com/paper/1808.03715/) (2018)
- [Anticipatory Music Transformer](https://mlsanity.com/paper/2306.08620/) (2023)
- [Polyffusion: A Diffusion Model for Polyphonic Score Generation with Internal and External Controls](https://mlsanity.com/paper/2307.10304/) (2023)
- [All-In-One Metrical And Functional Structure Analysis With Neighborhood Attentions on Demixed Audio](https://mlsanity.com/paper/2307.16425/) (2023)
- [Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models](https://mlsanity.com/paper/2405.09901/) (2024)
- [AccoMontage: Accompaniment Arrangement via Phrase Selection and Style Transfer](https://mlsanity.com/paper/2108.11213/) (2021)
- [Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling](https://mlsanity.com/paper/2310.16334/) (2023)
- [AccoMontage2: A Complete Harmonization and Accompaniment Arrangement System](https://mlsanity.com/paper/2209.00353/) (2022)
- [PiCoGen: Generate Piano Covers with a Two-stage Approach](https://mlsanity.com/paper/2407.20883/) (2024)
- [Emotion-Driven Melody Harmonization via Melodic Variation and Functional Representation](https://mlsanity.com/paper/2407.20176/) (2024)
- [METEOR: Melody-aware Texture-controllable Symbolic Orchestral Music Generation via Transformer VAE](https://mlsanity.com/paper/2409.11753/) (2024)

## Abstract (arXiv)

We introduce a structure-aware approach for symbolic piano accompaniment that decouples high-level planning from note-level realization. A lightweight transformer predicts an interpretable, per-measure style plan conditioned on section/phrase structure and functional harmony, and a retriever then selects and reharmonizes human-performed piano patterns from a corpus. We formulate retrieval as pattern matching under an explicit energy with terms for harmonic feasibility, structural-role compatibility, voice-leading continuity, style preferences, and repetition control. Given a structured lead sheet and optional keyword prompts, the system generates piano-accompaniment MIDI. In our experiments, transformer style-planner-guided retrieval produces diverse long-form accompaniments with strong style realization. We further analyze planner ablations and quantify inter-style isolation. Experimental results demonstrate the effectiveness of our inference-time approach for piano accompaniment generation.