3 papers
eess.AS2026
Discrete Token Modeling for Multi-Stem Music Source Separation with Language Models
Pengbo Lyu, Xiangyu Zhao, Chengwei Liu +4
We propose a generative framework for multi-track music source separation (MSS) that reformulates the task as conditional discrete token generation. Unlike conventional approaches…
eess.AS2025
USE: A Unified Model for Universal Sound Separation and Extraction
Hongyu Wang, Chenda Li, Xin Zhou +2
Sound separation (SS) and target sound extraction (TSE) are fundamental techniques for addressing complex acoustic scenarios. While existing SS methods struggle with determining th…
eess.AS2025
MeanSE: Efficient Generative Speech Enhancement with Mean Flows
Jiahe Wang, Hongyu Wang, Wei Wang +5
Speech enhancement (SE) improves degraded speech's quality, with generative models like flow matching gaining attention for their outstanding perceptual quality. However, the flow-…