DANCER: Entity Description Augmented Named Entity Corrector for Automatic Speech Recognition

no code implementations • 26 Mar 2024 • Yi-Cheng Wang, Hsin-Wei Wang, Bi-Cheng Yan, Chi-Han Lin, Berlin Chen

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 failures in downstream tasks.

Automatic Speech Recognition Language Modelling +2

An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement

no code implementations • 27 Feb 2024 • Tzu-Ting Yang, Hsin-Wei Wang, Yi-Cheng Wang, Chi-Han Lin, Berlin Chen

With the massive developments of end-to-end (E2E) neural networks, recent years have witnessed unprecedented breakthroughs in automatic speech recognition (ASR).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Preserving Phonemic Distinctions for Ordinal Regression: A Novel Loss Function for Automatic Pronunciation Assessment

no code implementations • 3 Oct 2023 • Bi-Cheng Yan, Hsin-Wei Wang, Yi-Cheng Wang, Jiun-Ting Li, Chi-Han Lin, Berlin Chen

Automatic pronunciation assessment (APA) manages to quantify the pronunciation proficiency of a second language (L2) learner in a language.

regression