3 citations · 3 across the 11 of their papers we have counts for
6 papers · 1 filter
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…
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…
BA-MoE: Boundary-Aware Mixture-of-Experts Adapter for Code-Switching Speech Recognition
Peikun Chen, Fan Yu, Yuhao Lian +5
Mixture-of-experts based models, which use language experts to extract language-specific representations effectively, have been well applied in code-switching automatic speech reco…
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…
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…
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…