Meeting Summarization: A Survey of the State of the Art
December 16, 2022 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: Meeting Summarization: A Survey of the State of the Art"
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Authors
Lakshmi Prasanna Kumar, Arman Kabiri
arXiv ID
2212.08206
Category
cs.CL: Computation & Language
Citations
7
Venue
arXiv.org
Last Checked
3 days ago
Abstract
Information overloading requires the need for summarizers to extract salient information from the text. Currently, there is an overload of dialogue data due to the rise of virtual communication platforms. The rise of Covid-19 has led people to rely on online communication platforms like Zoom, Slack, Microsoft Teams, Discord, etc. to conduct their company meetings. Instead of going through the entire meeting transcripts, people can use meeting summarizers to select useful data. Nevertheless, there is a lack of comprehensive surveys in the field of meeting summarizers. In this survey, we aim to cover recent meeting summarization techniques. Our survey offers a general overview of text summarization along with datasets and evaluation metrics for meeting summarization. We also provide the performance of each summarizer on a leaderboard. We conclude our survey with different challenges in this domain and potential research opportunities for future researchers.
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