Learning how to teach from “Videolectures”: automatic prediction of lecture ratings based on teacher's nonverbal behavior

Cognitive Infocommunications(2012)

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摘要
Large repositories of presentation recordings (e.g., “Videolectures” and “Academic Earth”) often provide their users with rating facilities. The rating of a presentation certainly depends on the content, but the way the content is delivered is likely to play a role as well. This paper focuses on the latter aspect and shows that nonverbal behavior (in particular arms movement and prosody) allows one to predict whether a presentation is rated as low or high in terms of quality. The experiments have been performed over 100 presentations collected from “Videolectures” and the accuracy is up to 66% depending on the techniques adopted. In other words, nonverbal communication actually influences the ratings assigned to a presentation.
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关键词
accuracy,media,optical imaging,support vector machines,vectors,estimation,feature extraction
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