Topic Segmentation of Recorded Meetings

Abstract

Video chapters allow videos to be more easily digestible and can be an important pre-processing step for other video-processing tasks. In many cases, the creator can easily chapter their own videos, especially for well-edited structured videos. However, some types of videos, such as recorded meetings, are more loosely structured with less obvious breaks which makes them more cumbersome to chapter and thus would highly benefit from being automated. One approach to chaptering these types of videos is through performing topic segmentation on the transcript of the video, especially if the video is rich in dialogue. Topic segmentation is the task of dividing text based on when the topic of the text changes, most commonly performed on large bodies of written text. This thesis will detail how well state-of-the-art approaches for topic segmentation performs on recorded meetings, as well as present and evaluate strategies to improve performance for recorded meetings and express shortcomings of the common metrics used for topic segmentation.