Detecting Attempts at Humor in Multiparty Meetings

Abstract—Systems designed for the automatic summarization of meetings have considered the propositional content of contributions by each speaker, but not the explicit techniques that speakers use to downgrade the perceived seriousness of those contributions. We analyze one such technique, namely attempts at humor. We find that speech spent on attempts at humor is rare by time but that it correlates strongly with laughter, which is more frequent. Contextual features describing the temporal and multiparticipant distribution of manually transcribed laughter yield error rates for the detection of attempts at humor which are 4 times lower than those obtained using oracle lexical information. Furthermore, we show that similar performance can be achieved by considering only the speaker’s laughter, indicating that meeting participants explicitly signal their attempts at humor by laughing themselves. Finally, we present evidence which suggests that, on small time scales, the production of ...

• Type: Conference
• Year: 2009
• Where: SEMCO
• Authors: Kornel Laskowski
• Keywords: Automatic Summarization, Humor, Laughter Yield Error, Semantic Computing, SEMCO 2009