MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and Content

Yang Shi, Chris Bryan, Sridatt Bhamidipati, Ying Zhao, Yaoxue Zhang, Kwan Liu Ma

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

In team-based workplaces, reviewing and reflecting on the content from a previously held meeting can lead to better planning and preparation. However, ineffective meeting summaries can impair this process, especially when participants have difficulty remembering what was said and what its context was. To assist with this process, we introduce MeetingVis, a visual narrative-based approach to meeting summarization. MeetingVis is composed of two primary components: (1) a data pipeline that processes the spoken audio from a group discussion, and (2) a visual-based interface that efficiently displays the summarized content. To design MeetingVis, we create a taxonomy of relevant meeting data points, identifying salient elements to promote recall and reflection. These are mapped to an augmented storyline visualization, which combines the display of participant activities, topic evolutions, and task assignments. For evaluation, we conduct a qualitative user study with five groups. Feedback from the study indicates that MeetingVis effectively triggers the recall of subtle details from prior meetings: all study participants were able to remember new details, points, and tasks compared to an unaided, memory-only baseline. This visual-based approaches can also potentially enhance the productivity of both individuals and the whole team.

Original languageEnglish (US)
Pages (from-to)1918-1929
Number of pages12
JournalIEEE Transactions on Visualization and Computer Graphics
Volume24
Issue number6
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

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Keywords

  • Design study
  • information visualization
  • meeting summarization
  • natural language processing
  • visual narrative
  • voice recognition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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