3 papers
eess.AS2025
Listen to Extract: Onset-Prompted Target Speaker Extraction
Pengjie Shen, Kangrui Chen, Shulin He +5
We propose listen to extract (LExt), a highly-effective while extremely-simple algorithm for monaural target speaker extraction (TSE). Given an enrollment utterance of a target spe…
eess.AS2025
MC-LExt: Multi-Channel Target Speaker Extraction with Onset-Prompted Speaker Conditioning Mechanism
Tongtao Ling, Shulin He, Pengjie Shen +1
Multi-channel target speaker extraction (MC-TSE) aims to extract a target speaker's voice from multi-speaker signals captured by multiple microphones. Existing methods often rely o…
eess.AS2025
ARiSE: Auto-Regressive Multi-Channel Speech Enhancement
Pengjie Shen, Xueliang Zhang, Zhong-Qiu Wang
We propose ARiSE, an auto-regressive algorithm for multi-channel speech enhancement. ARiSE improves existing deep neural network (DNN) based frame-online multi-channel speech enhan…