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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.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…
cs.SD2023
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…