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Paragraph level multi-perspective context modeling for question generation

  • Beihang University
  • Ping An Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Proper understanding of paragraph is essential for question generation task since the semantic interaction is complicated among sentences. How to integrate long text paragraph information into question generation is still a challenge. In this research, we proposed a multi-perspective paragraph context modeling mechanism, which firstly encodes the contextualized representation of input paragraph, and then utilize multi-head self-attention and Rezero network to further enhance paragraph-level feature extraction and context modeling. Finally, attention-based decoder with copy mechanism generates question according to encoded hidden states. Experimental study on widely used SQuAD dataset has shown the proposed method's potential.

源语言英语
主期刊名2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
7418-7422
页数5
ISBN(电子版)9781728176055
DOI
出版状态已出版 - 2021
活动2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, 加拿大
期限: 6 6月 202111 6月 2021

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2021-June
ISSN(印刷版)1520-6149

会议

会议2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
国家/地区加拿大
Virtual, Toronto
时期6/06/2111/06/21

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