mlsanityData to 7 Oct 2026

Learning Interpretable Representation for Controllable Polyphonic Music Generation

arXiv 2008.07122 ↗First posted 17 Aug 2020cs.SD cs.CL cs.LGcited by 40

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Abstract (arXiv)

While deep generative models have become the leading methods for algorithmic composition, it remains a challenging problem to control the generation process because the latent variables of most deep-learning models lack good interpretability. Inspired by the content-style disentanglement idea, we design a novel architecture, under the VAE framework, that effectively learns two interpretable latent factors of polyphonic music: chord and texture. The current model focuses on learning 8-beat long piano composition segments. We show that such chord-texture disentanglement provides a controllable generation pathway leading to a wide spectrum of applications, including compositional style transfer, texture variation, and accompaniment arrangement. Both objective and subjective evaluations show that our method achieves a successful disentanglement and high quality controlled music generation.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 6; 2023: 12; 2024: 7; 2025: 6; 2026: 4.

40 papers.

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  1. 2023MuseCoco: Generating Symbolic Music from Textcited by 50
  2. 2023Polyffusion: A Diffusion Model for Polyphonic Score Generation with Internal and External Controlscited by 35
  3. 2024MuPT: A Generative Symbolic Music Pretrained Transformercited by 32
  4. 2021Controllable deep melody generation via hierarchical music structure representationcited by 30
  5. 2024Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Modelscited by 24
  6. 2022Controllable Data Generation by Deep Learning: A Reviewcited by 20
  7. 2023The Ethical Implications of Generative Audio Models: A Systematic Literature Reviewcited by 18
  8. 2023Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editingcited by 15
  9. 2021Self-Supervised VQ-VAE for One-Shot Music Style Transfercited by 13
  10. 2021Music Composition with Deep Learning: A Reviewcited by 12
  11. 2022Symbolic music generation conditioned on continuous-valued emotionscited by 12
  12. 2021Structure-Enhanced Pop Music Generation via Harmony-Aware Learningcited by 11
28 more
  1. 2023GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformerscited by 11
  2. 2023Structured Multi-Track Accompaniment Arrangement via Style Prior Modellingcited by 9
  3. 2021Audio-to-symbolic Arrangement via Cross-modal Music Representation Learningcited by 6
  4. 2022Learning long-term music representations via hierarchical contextual constraintscited by 5
  5. 2022Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generationcited by 4
  6. 2024The NES Video-Music Database: A Dataset of Symbolic Video Game Music Paired with Gameplay Videoscited by 4
  7. 2022A Survey on Artificial Intelligence for Music Generation: Agents, Domains and Perspectivescited by 3
  8. 2023IteraTTA: An interface for exploring both text prompts and audio priors in generating music with text-to-audio modelscited by 3
  9. 2025Mamba-Diffusion Model with Learnable Wavelet for Controllable Symbolic Music Generationcited by 3
  10. 2023From Words to Music: A Study of Subword Tokenization Techniques in Symbolic Music Generationcited by 2
  11. 2023Controllable Lyrics-to-Melody Generationcited by 2
  12. 2023Automatic Time Signature Determination for New Scores Using Lyrics for Latent Rhythmic Structurecited by 2
  13. 2023MusER: Musical Element-Based Regularization for Generating Symbolic Music with Emotioncited by 2
  14. 2024A Survey of Music Generation in the Context of Interactioncited by 2
  15. 2024Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraintscited by 2
  16. 2025Incorporating Structure and Chord Constraints in Symbolic Transformer-based Melodic Harmonizationcited by 2
  17. 2023Motif-Centric Representation Learning for Symbolic Musiccited by 1
  18. 2024The Interpretation Gap in Text-to-Music Generation Modelscited by 1
  19. 2024Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generationcited by 1
  20. 2025MuseTok: Symbolic Music Tokenization for Generation and Semantic Understandingcited by 1
  21. 2026ViTex: Visual Texture Control for Multi-Track Symbolic Music Generation via Discrete Diffusion Modelscited by 1
  22. 2022Relating Human Perception of Musicality to Prediction in a Predictive Coding Modelcited by 0
  23. 2025Are Inherently Interpretable Models More Robust? A Study In Music Emotion Recognitioncited by 0
  24. 2025Encoding of musical structures in hidden units of restricted Boltzmann machinescited by 0
  25. 2025Disentangling Score Content and Performance Style for Joint Piano Rendering and Transcriptioncited by 0
  26. 2026D3PIA: A Discrete Denoising Diffusion Model for Piano Accompaniment Generation From Lead sheetcited by 0
  27. 2026Learning Music Style for Piano Arrangement Through Cross-Modal Bootstrappingcited by 0
  28. 2026MI-MIDI: Mechanistic Interpretability of Text-to-MIDI Generation Models via Probing, Lenses and Steeringcited by 0