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Meeting Summarization: A Survey of the State of the Art

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arxiv 2212.08206 v1 pith:FJMXJV7N submitted 2022-12-16 cs.CL

classification cs.CL
keywords meetingsummarizationsurveysummarizerscommunicationdatainformationpeople
verification ladder T0 review T1 audit T2 compute T3 formal
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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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  1. What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection

    cs.HC 2025-05 conditional novelty 6.0 of 10

    A study with 18 employees found that a generative AI Meeting Purpose Assistant can help people clarify meeting goals, anticipate challenges, and change how they prepare, with social and technical barriers to adoption.

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