PS4: Proxy-Supervised Joint Training for Real Target Speaker Extraction
Training target speaker extraction (TSE) models for real conversational mixtures remains challenging because large-scale training corpora and clean target speech for supervision are unavailable. We present PS4, a proxy-supervised training framework for TSE in real conversational mixtures, with two main contributions. First, we construct a large-scale corpus of 71,771 training samples derived from four public datasets, covering both Chinese and English scenarios. Each sample contains an overlapping speech mixture, per-speaker enrollment audio, a ground-truth transcript, and frame-level voice activity labels. Second, we propose a proxy-supervised joint training strategy that fine-tunes a BS...
| Authors | Wanyi Ning, Wei Zhou, Yingpeng Li et al. |
|---|---|
| Primary category | cs.SD |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
Models and datasets referencing this paper
- TaurenMountain/REAL-PS4Dataset
- tian0105/REAL-PS4Dataset
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