ParseJargon: Personalized Real-Time Jargon Support System for Online Meetings
Researchers have developed ParseJargon, a system that uses speech-to-text and large language models to provide personalized jargon explanations to participants during live online meetings. Unlike generic systems that define the same terms for everyone, ParseJargon builds individual user profiles to identify only the terms a specific listener is likely unfamiliar with. The system addresses a longstanding barrier in cross-disciplinary collaboration, where uneven technical vocabulary can impede understanding and engagement.
ParseJargon is a real-time jargon support system designed to reduce communication barriers in cross-disciplinary online meetings by tailoring terminology explanations to individual listeners rather than providing uniform definitions to all participants. The research team began with an initial prototype using single-sentence user profiles and conducted a controlled study demonstrating that even minimal personalization improved listeners' comprehension and engagement compared to generic support, primarily through more precise identification of which terms actually needed defining. Based on participant feedback, the system was subsequently refined with more advanced techniques, including in-session user feedback mechanisms and portable glossary-based profiles that can carry over across meetings. Evaluations using data from the controlled study simulated how personalization improves over time, showing gains in jargon identification precision. The team also conducted latency testing and a lightweight deployment to assess real-time usability. The work has been presented in portions at CHI '26 and ACL '26 venues, indicating peer engagement with the research community.
What's missing
It is also unclear how the system handles privacy concerns related to continuous audio capture and user profiling in workplace settings. The long-term effectiveness of glossary-based profiles across varied meeting contexts remains an open question.
What different sources said
- arXiv cs.CLCenter
Breaking the Curse of Knowledge: Designing Personalized Jargon Support for Real-Time Online Meetings
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