From the 2 of 7 linked papers with an AI index.
4 papers · 1 filter
WeSep: A Modular and Cue-Composable Framework for Target Speaker Extraction
Ke Zhang, Xiaoyang Yu, Haoyu Li +3
WeSep is a modular framework that treats target speaker extraction as a cue‑conditioned learning problem, separating cue modules from the separator backbone to flexibly incorporate…
SLT 2026 REAL-TSE Challenge: Real-world Target Speaker Extraction from Conversational Recordings
Shuai Wang, Zihan Qian, Ke Zhang +9
The paper presents the REAL‑TSE Challenge, a benchmark for extracting a target speaker’s voice from real conversational recordings in Mandarin and English, with both online low‑lat…
Interpolating Speaker Identities in Embedding Space for Data Expansion
Tianchi Liu, Ruijie Tao, Qiongqiong Wang +5
The success of deep learning-based speaker verification systems is largely attributed to access to large-scale and diverse speaker identity data. However, collecting data from more…
WeSep: A Scalable and Flexible Toolkit Towards Generalizable Target Speaker Extraction
Shuai Wang, Ke Zhang, Shaoxiong Lin +6
Target speaker extraction (TSE) focuses on isolating the speech of a specific target speaker from overlapped multi-talker speech, which is a typical setup in the cocktail party pro…