2 citations · 4 across the 12 of their papers we have counts for
6 papers · 1 filter
An Effective Context-Balanced Adaptation Approach for Long-Tailed Speech Recognition
Yi-Cheng Wang, Li-Ting Pai, Bi-Cheng Yan +3
End-to-end (E2E) automatic speech recognition (ASR) models have become standard practice for various commercial applications. However, in real-world scenarios, the long-tailed natu…
DANCER: Entity Description Augmented Named Entity Corrector for Automatic Speech Recognition
Yi-Cheng Wang, Hsin-Wei Wang, Bi-Cheng Yan +2
End-to-end automatic speech recognition (E2E ASR) systems often suffer from mistranscription of domain-specific phrases, such as named entities, sometimes leading to catastrophic f…
An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement
Tzu-Ting Yang, Hsin-Wei Wang, Yi-Cheng Wang +2
With the massive developments of end-to-end (E2E) neural networks, recent years have witnessed unprecedented breakthroughs in automatic speech recognition (ASR). However, the codes…
Leveraging Language ID to Calculate Intermediate CTC Loss for Enhanced Code-Switching Speech Recognition
Tzu-Ting Yang, Hsin-Wei Wang, Berlin Chen
In recent years, end-to-end speech recognition has emerged as a technology that integrates the acoustic, pronunciation dictionary, and language model components of the traditional…
Effective Cross-Utterance Language Modeling for Conversational Speech Recognition
Bi-Cheng Yan, Hsin-Wei Wang, Shih-Hsuan Chiu +2
Conversational speech normally is embodied with loose syntactic structures at the utterance level but simultaneously exhibits topical coherence relations across consecutive utteran…
Exploring Non-Autoregressive End-To-End Neural Modeling For English Mispronunciation Detection And Diagnosis
Hsin-Wei Wang, Bi-Cheng Yan, Hsuan-Sheng Chiu +2
End-to-end (E2E) neural modeling has emerged as one predominant school of thought to develop computer-assisted language training (CAPT) systems, showing competitive performance to…