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Chi-Han Lin

2 accepted papers

2024

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

ICASSP 2024accepted

With the massive developments of end-to-end (E2E) neural networks, recent years have witnessed unprecedented breakthroughs in automatic speech recognition (ASR). However, the code-switching phenomenon remains a major obstacle that hinders ASR from perfection, as the lack of labeled data and the vari…

Cited by 0SourceScholar
2024

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

COLING 2024main

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. A family of fast and lightweight named entity correction (NEC) models for ASR have recently…