3 papers
cs.SD2026
AnyEdit: A Unified Framework for Speech and Singing Voice Editing with Real-World Environmental Consistency
Yunjia Zhang, Junan Zhang, Jing Yang +3
We present AnyEdit, a unified, separation-free framework for speech and singing voice editing that preserves real-world acoustic environments, including noise, reverberation, and b…
cs.SD2025
SingVERSE: A Diverse, Real-World Benchmark for Singing Voice Enhancement
Shaohan Jiang, Junan Zhang, Yunjia Zhang +3
This paper presents a benchmark for singing voice enhancement. The development of singing voice enhancement is limited by the lack of realistic evaluation data. To address this gap…
cs.SD2025
AnyAccomp: Generalizable Accompaniment Generation via Quantized Melodic Bottleneck
Junan Zhang, Yunjia Zhang, Xueyao Zhang +1
Singing Accompaniment Generation (SAG) is the process of generating instrumental music for a given clean vocal input. However, existing SAG techniques use source-separated vocals a…