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cs.CL2022
Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems
Xiaoqiang Wang, Yanqing Liu, Jinyu Li +3
Contextual biasing is an important and challenging task for end-to-end automatic speech recognition (ASR) systems, which aims to achieve better recognition performance by biasing t…
cs.CL2021★ 1 cited
A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems
Xiaoqiang Wang, Yanqing Liu, Sheng Zhao +1
It's challenging to customize transducer-based automatic speech recognition (ASR) system with context information which is dynamic and unavailable during model training. In this wo…