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Feb, 2022
RescoreBERT:利用BERT进行具有区分性的语音识别重评分
RescoreBERT: Discriminative Speech Recognition Rescoring with BERT
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Liyan Xu, Yile Gu, Jari Kolehmainen, Haidar Khan, Ankur Gandhe...
TL;DR
本文介绍了如何利用BERT模型及MWER loss设计一种用于ASR系统的rescoring模型,该模型可将WER降低6.6%/3.4%相对值,并对来自对话代理的内部数据集进行了验证,在该数据集中,该模型将延迟和WER均降低了3至8%的相对值。
Abstract
second-pass rescoring
is an important component in
automatic speech recognition
(ASR) systems that is used to improve the outputs from a first-pass decoder by implementing a lattice rescoring or $n$-best re-ranki
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