arXiv Notify me• Jul 24, 2026paper

Music-JEPA: Learning a World Model of Sound from Action

Yann LeCun(guest)

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Executive Summary

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World Models for Audio Action-Conditioned Predictive Learning

3 quotes

Concerns Raised

The model is currently limited to piano music and may not generalize easily to more complex instruments or full orchestral pieces.
The approach depends on the availability of paired audio-pianoroll data, which can be scarce for many instruments and genres.
The scalability and computational cost of training such world models for more complex audio environments remain open questions.

Opportunities Identified

The action-conditioned framework can be extended to other instruments like guitar, drums, or even the human voice.
This technology could power a new generation of intelligent music production tools for composition, arrangement, and sound design.
The learned representations could be used to significantly improve related audio tasks like source separation, audio restoration, and realistic instrument synthesis.

Key Themes

Research Findings5

The Music-JEPA model learns a world model of piano sound by framing music as an action-conditioned system where audio is the state and the pianoroll is the instrument action.

The Music-JEPA model predicts a future audio state based on a given current audio state and a pianoroll action.

Experiments with Music-JEPA demonstrate that the model learns the relationships between musical actions and their resulting sound.

The latent representations learned by Music-JEPA can be used for downstream tasks such as beat tracking, composer identification, and key estimation.

The Music-JEPA model enables piano transcription through a planning process that searches for the actions that best explain a target sound.

Topics

AI Machine Learning Self-Supervised Learning World Models Joint Embedding Predictive Architecture (JEPA)Music Information Retrieval (MIR)Audio Generation Audio Analysis Piano Transcription Representation Learning Deep Learning Computational Musicology Yann LeCun Action-Conditioned Models Predictive Learning

Processed Jul 28, 2026Daily intelligence brief → yt-dlp + mlx-whisper + Gemini

Music-JEPA: Learning a World Model of Sound from Action

Continue your research

Concerns Raised

Opportunities Identified

Key Themes

World Models for Audio

Action-Conditioned Predictive Learning

Advancements in Self-Supervised Learning (JEPA)

From Foundational Research to Practical Application

Research Findings5

Topics