activity
20222025
most citedX-SepFormer: End-to-end Speaker Extraction Network with Explicit Optimization on Speaker Confusion

3 citations · 3 across the 9 of their papers we have counts for

collaborators

9 papers

eess.AS2025

SCDiar: a streaming diarization system based on speaker change detection and speech recognition

Naijun Zheng, Xucheng Wan, Kai Liu +1

In hours-long meeting scenarios, real-time speech stream often struggles with achieving accurate speaker diarization, commonly leading to speaker identification and speaker count e…

cs.SD2025

CAMEL: Cross-Attention Enhanced Mixture-of-Experts and Language Bias for Code-Switching Speech Recognition

He Wang, Xucheng Wan, Naijun Zheng +4

Code-switching automatic speech recognition (ASR) aims to transcribe speech that contains two or more languages accurately. To better capture language-specific speech representatio…

cs.CL2024

XCB: an effective contextual biasing approach to bias cross-lingual phrases in speech recognition

Xucheng Wan, Naijun Zheng, Kai Liu +1

Contextualized ASR models have been demonstrated to effectively improve the recognition accuracy of uncommon phrases when a predefined phrase list is available. However, these mode…

cs.SD2024

An efficient text augmentation approach for contextualized Mandarin speech recognition

Naijun Zheng, Xucheng Wan, Kai Liu +2

Although contextualized automatic speech recognition (ASR) systems are commonly used to improve the recognition of uncommon words, their effectiveness is hindered by the inherent l…

eess.AS2023

Pyramid Multi-branch Fusion DCNN with Multi-Head Self-Attention for Mandarin Speech Recognition

Kai Liu, Hailiang Xiong, Gangqiang Yang +3

As one of the major branches of automatic speech recognition, attention-based models greatly improves the feature representation ability of the model. In particular, the multi-head…

eess.AS2023★ 3 cited

X-SepFormer: End-to-end Speaker Extraction Network with Explicit Optimization on Speaker Confusion

Kai Liu, Ziqing Du, Xucheng Wan +1

Target speech extraction (TSE) systems are designed to extract target speech from a multi-talker mixture. The popular training objective for most prior TSE networks is to enhance r…

cs.SD2023

Improving Target Speaker Extraction with Sparse LDA-transformed Speaker Embeddings

Kai Liu, Xucheng Wan, Ziqing Du +1

As a practical alternative of speech separation, target speaker extraction (TSE) aims to extract the speech from the desired speaker using additional speaker cue extracted from the…

cs.SD2022

Joint Speech Activity and Overlap Detection with Multi-Exit Architecture

Ziqing Du, Kai Liu, Xucheng Wan +1

Overlapped speech detection (OSD) is critical for speech applications in scenario of multi-party conversion. Despite numerous research efforts and progresses, comparing with speech…

cs.SD2022

Speech Enhancement with Perceptually-motivated Optimization and Dual Transformations

Xucheng Wan, Kai Liu, Ziqing Du +1

To address the monaural speech enhancement problem, numerous research studies have been conducted to enhance speech via operations either in time-domain on the inner-domain learned…