How Domain Terminology Affects Meeting Summarization Performance
Jia Jin Koay, Alexander Roustai, Xiaojin Dai, Dillon Burns, and Alec Kerrigan, Fei Liu

TL;DR
This paper investigates how domain-specific terminology influences the effectiveness of meeting summarization systems, highlighting the importance of incorporating jargon knowledge for improved performance.
Contribution
It introduces a dataset with annotated domain terminology and analyzes its impact on meeting summarization accuracy, revealing significant effects.
Findings
Domain terminology substantially affects summarization performance
Annotated jargon terms are publicly released for future research
Inclusion of domain knowledge improves summarization results
Abstract
Meetings are essential to modern organizations. Numerous meetings are held and recorded daily, more than can ever be comprehended. A meeting summarization system that identifies salient utterances from the transcripts to automatically generate meeting minutes can help. It empowers users to rapidly search and sift through large meeting collections. To date, the impact of domain terminology on the performance of meeting summarization remains understudied, despite that meetings are rich with domain knowledge. In this paper, we create gold-standard annotations for domain terminology on a sizable meeting corpus; they are known as jargon terms. We then analyze the performance of a meeting summarization system with and without jargon terms. Our findings reveal that domain terminology can have a substantial impact on summarization performance. We publicly release all domain terminology to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Advanced Text Analysis Techniques
