# Via Score to Performance: Efficient Human-Controllable Long Song Generation with Bar-Level Symbolic Notation

arXiv: https://arxiv.org/abs/2508.01394 · HTML: https://mlsanity.com/paper/2508.01394/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 35 references that are in the map.
- First posted on arXiv 2 Aug 2025.

## Builds on (most cited first, 28 of 28)

- [Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers](https://mlsanity.com/paper/2301.02111/) (2023)
- [High Fidelity Neural Audio Compression](https://mlsanity.com/paper/2210.13438/) (2022)
- [AudioLDM: Text-to-Audio Generation with Latent Diffusion Models](https://mlsanity.com/paper/2301.12503/) (2023)
- [Jukebox: A Generative Model for Music](https://mlsanity.com/paper/2005.00341/) (2020)
- [Simple and Controllable Music Generation](https://mlsanity.com/paper/2306.05284/) (2023)
- [GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editing](https://mlsanity.com/paper/2503.10639/) (2025)
- [YuE: Scaling Open Foundation Models for Long-Form Music Generation](https://mlsanity.com/paper/2503.08638/) (2025)
- [ChatMusician: Understanding and Generating Music Intrinsically with LLM](https://mlsanity.com/paper/2402.16153/) (2024)
- [SingSong: Generating musical accompaniments from singing](https://mlsanity.com/paper/2301.12662/) (2023)
- [Sound Event Detection: A Tutorial](https://mlsanity.com/paper/2107.05463/) (2021)
- [Sparks of Large Audio Models: A Survey and Outlook](https://mlsanity.com/paper/2308.12792/) (2023)
- [MuPT: A Generative Symbolic Music Pretrained Transformer](https://mlsanity.com/paper/2404.06393/) (2024)
- [MusicMagus: Zero-Shot Text-to-Music Editing via Diffusion Models](https://mlsanity.com/paper/2402.06178/) (2024)
- [GVPO: Group Variance Policy Optimization for Large Language Model Post-Training](https://mlsanity.com/paper/2504.19599/) (2025)
- [NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms](https://mlsanity.com/paper/2502.18008/) (2025)
- [SongGen: A Single Stage Auto-regressive Transformer for Text-to-Song Generation](https://mlsanity.com/paper/2502.13128/) (2025)
- [All-In-One Metrical And Functional Structure Analysis With Neighborhood Attentions on Demixed Audio](https://mlsanity.com/paper/2307.16425/) (2023)
- [TunesFormer: Forming Irish Tunes with Control Codes by Bar Patching](https://mlsanity.com/paper/2301.02884/) (2023)
- [GETMusic: Generating Any Music Tracks with a Unified Representation and Diffusion Framework](https://mlsanity.com/paper/2305.10841/) (2023)
- [MelodyT5: A Unified Score-to-Score Transformer for Symbolic Music Processing](https://mlsanity.com/paper/2407.02277/) (2024)
- [Accompanied Singing Voice Synthesis with Fully Text-controlled Melody](https://mlsanity.com/paper/2407.02049/) (2024)
- [ByteCover3: Accurate Cover Song Identification on Short Queries](https://mlsanity.com/paper/2303.11692/) (2023)
- [Beyond the Next Token: Towards Prompt-Robust Zero-Shot Classification via Efficient Multi-Token Prediction](https://mlsanity.com/paper/2504.03159/) (2025)
- [ByteComposer: a Human-like Melody Composition Method based on Language Model Agent](https://mlsanity.com/paper/2402.17785/) (2024)
- [MeloTrans: A Text to Symbolic Music Generation Model Following Human Composition Habit](https://mlsanity.com/paper/2410.13419/) (2024)
- [Exploring Tokenization Methods for Multitrack Sheet Music Generation](https://mlsanity.com/paper/2410.17584/) (2024)
- [A Survey of Music Generation in the Context of Interaction](https://mlsanity.com/paper/2402.15294/) (2024)
- [Applications and Advances of Artificial Intelligence in Music Generation:A Review](https://mlsanity.com/paper/2409.03715/) (2024)

## Built on by (most cited first, 3 of 3)

- [TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval](https://mlsanity.com/paper/2604.21806/) (2026)
- [Efficient Long-Sequence Diffusion Modeling for Symbolic Music Generation](https://mlsanity.com/paper/2603.00576/) (2026)
- [YuE2: Unifying Symbolic and Audio Music Generation at Frontier Quality](https://mlsanity.com/paper/2609.33757/) (2026)

## Abstract (arXiv)

Song generation is regarded as the most challenging problem in music AIGC; nonetheless, existing approaches have yet to fully overcome four persistent limitations: controllability, generalizability, perceptual quality, and duration. We argue that these shortcomings stem primarily from the prevailing paradigm of attempting to learn music theory directly from raw audio, a task that remains prohibitively difficult for current models. To address this, we present Bar-level AI Composing Helper (BACH), the first model explicitly designed for song generation through human-editable symbolic scores. BACH introduces a tokenization strategy and a symbolic generative procedure tailored to hierarchical song structure. Consequently, it achieves substantial gains in the efficiency, duration, and perceptual quality of song generation. Experiments demonstrate that BACH, with a small model size, establishes a new SOTA among all publicly reported song generation systems, even surpassing commercial solutions such as Suno. Human evaluations further confirm its superiority across multiple subjective metrics.