StreamMUSE v0
Real-Time Language Model Jamming: A Case Study for Live Music Accompaniment Generation
This work was accepted by RTAS 2026.
v0
Version Summary
What this version contributes to the StreamMUSE project.
Frames the task as real-time accompaniment generation conditioned on an external musical stream.
Uses a client-server architecture where the client sends high-frequency requests and schedules returned accompaniment.
Studies the interaction between inference interval, generation length, round-trip latency, and music quality.
Recorded demos
Real-time
A human performer plays the melody, while the system generates accompaniment in real time.
Real-time demo 2
Real-time demo 3
Real-time demo 4
Playable assets
MIDI Examples
MIDI examples can be played directly in the browser or downloaded.
v0 MIDI accompaniment example
Playable placeholder MIDI for validating in-page playback and download.
Publication
Paper Information
Real-Time Language Model Jamming: A Case Study for Live Music Accompaniment Generation
2026 IEEE 32nd Real-Time and Embedded Technology and Applications Symposium (RTAS)
Bowen Zheng, Andrew H. Yang, Jiaqi Ruan, Jia He, Xinyue Li, Yuan-Hsin Chen, Ziyu Wang, Xiaosong Ma
DOI: 10.1109/RTAS68450.2026.00032
@inproceedings{zheng2026realtime,
title = {Real-Time Language Model Jamming: A Case Study for Live Music Accompaniment Generation},
author = {Zheng, Bowen and Yang, Andrew H. and Ruan, Jiaqi and He, Jia and Li, Xinyue and Chen, Yuan-Hsin and Wang, Ziyu and Ma, Xiaosong},
booktitle = {2026 IEEE 32nd Real-Time and Embedded Technology and Applications Symposium (RTAS)},
year = {2026},
doi = {10.1109/RTAS68450.2026.00032}
}