Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts

Tan, Haochen, Wu, Han, Shao, Wei, Zhang, Xinyun, Zhan, Mingjie, Hou, Zhaohui, Liang, Ding, Song, Linqi

arXiv.org Artificial Intelligence 

Based on this understanding, Although numerous achievements have been made we propose a two-step meeting summarization in the well-structured text abstractive summarization framework, Reconstrcut before Summarize(RbS), (Zhang et al., 2020a; Liu* et al., 2018; Lewis to address the challenge of scattered et al., 2020), the research on meeting summarization information in meetings. RbS adopts a reconstructor is still stretched in limit. There are some outstanding to reconstruct the responses in the meeting, it challenges in this field, including 1) much also synchronically traces out which texts in the noise brought from automated speech recognition meeting drove the responses and marks them as models; 2) lengthy meeting transcripts consisting essential contents. Therefore, salient information of casual conversations, content redundancy, and is captured and annotated as anchor tokens in RbS.

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