Context-aware RNNLM Rescoring for Conversational Speech Recognition

@article{Wei2021ContextawareRR,
  title={Context-aware RNNLM Rescoring for Conversational Speech Recognition},
  author={Kun Wei and Pengcheng Guo and Hang Lv and Zhen Tu and Lei Xie},
  journal={2021 12th International Symposium on Chinese Spoken Language Processing (ISCSLP)},
  year={2021},
  pages={1-5}
}
  • Kun Wei, Pengcheng Guo, Lei Xie
  • Published 18 November 2020
  • Computer Science
  • 2021 12th International Symposium on Chinese Spoken Language Processing (ISCSLP)
Conversational speech recognition is regarded as a challenging task due to its free-style speaking and long-term contextual dependencies. Prior work has explored the modeling of long-range context through RNNLM rescoring with improved performance. To further take advantage of the persisted nature during a conversation, such as topics or speaker turn, we extend the rescoring procedure to a new context-aware manner. For RNNLM training, we capture the contextual dependencies by concatenating… 

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