Meeting Summarization
12 papers with code • 2 benchmarks • 5 datasets
Generating a summary from meeting transcriptions.
A survey for this task: Abstractive Meeting Summarization: A Survey
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
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.
Abstractive Meeting Summarization: A Survey
A system that could reliably identify and sum up the most important points of a conversation would be valuable in a wide variety of real-world contexts, from business meetings to medical consultations to customer service calls.
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
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
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
Lastly, we compare the performance of our baseline models with BART, a state-of-the-art language model that is effective for summarization.
Query-Utterance Attention with Joint modeling for Query-Focused Meeting Summarization
Previous works typically concatenate the query with meeting transcripts and implicitly model the query relevance only at the token level with attention mechanism.