VocalParse: Towards Unified and Scalable Singing Voice Transcription with Large Audio Language Models
High-quality singing annotations are fundamental to modern Singing Voice Synthesis (SVS) systems. However, obtaining these annotations at scale through manual labeling is unrealistic due to the substantial labor and musical expertise required, making automatic annotation highly necessary. Despite their utility, current automatic transcription systems face significant challenges: they often rely on complex multi-stage pipelines, struggle to recover text-note alignments, and exhibit poor generalization to out-of-distribution (OOD) singing data. To alleviate these issues, we present VocalParse, a unified singing voice transcription (SVT) model built upon a Large Audio Language Model (LALM). ...
| Authors | Yukun Chen, Tianrui Wang, Zhaoxi Mu et al. |
|---|---|
| Primary category | cs.SD |
| Published | 6 May 2026 |
| Last updated at source | 6 May 2026 |
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