Genre Controlled Music Generation via Activation Steering
Sound
2026-05-27 v2 Artificial Intelligence
Audio and Speech Processing
Abstract
Computational Music Generation is evolving towards non-conventional styles, demanding methods that enable precise and controllable blending of diverse music elements. In this work, we present a method for fine grained control using inference-time interventions on an autoregressive generative transformer, MusicGen. Through our approach, we achieve genre control by steering the residual stream using weights of a linear probe on it. By framing activation steering as a human-controllable interaction, our work highlights how interpretable model behaviors can empower in co-creative music generation.Audio samples demonstrating our method are available on our demo page.
Cite
@article{arxiv.2506.10225,
title = {Genre Controlled Music Generation via Activation Steering},
author = {Swathi Narashiman and Pranay Mathur and Dipanshu Panda and Jayden Koshy Joe and Harshith M R and Anish Veerakumar and Aniruddh Krishna and Keerthiharan A},
journal= {arXiv preprint arXiv:2506.10225},
year = {2026}
}