Meeting Summarization
8 papers with code • 0 benchmarks • 2 datasets
Generating a summary from meeting transcriptions.
Benchmarks
These leaderboards are used to track progress in Meeting Summarization
QMSum
public_meetings
Most implemented papers
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining
microsoft/HMNet
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Findings of the Association for Computational Linguistics 2020
With the abundance of automatic meeting transcripts, meeting summarization is of great interest to both participants and other parties.
Align then Summarize: Automatic Alignment Methods for Summarization Corpus Creation
We report automatic alignment and summarization performances on this corpus and show that automatic alignment is relevant for data annotation since it leads to large improvement of almost +4 on all ROUGE scores on the summarization task.
Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents
To the best of our knowledge, Summ$^N$ is the first multi-stage split-then-summarize framework for long input summarization.
How Domain Terminology Affects Meeting Summarization Performance
We then analyze the performance of a meeting summarization system with and without jargon terms.
Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization
xcfcode/DDAMS
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First, we present a Dialogue Discourse-Dware Meeting Summarizer (DDAMS) to explicitly model the interaction between utterances in a meeting by modeling different discourse relations.
QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
Yale-LILY/QMSum
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NAACL 2021
As increasing numbers of meetings are recorded and transcribed, meeting summaries have become essential to remind those who may or may not have attended the meetings about the key decisions made and the tasks to be completed.
Meeting Summarization with Pre-training and Clustering Methods
wxj77/meetingsummarization
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Lastly, we compare the performance of our baseline models with BART, a state-of-the-art language model that is effective for summarization.
