BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Talks.cam//talks.cam.ac.uk// X-WR-CALNAME:Talks.cam BEGIN:VEVENT SUMMARY:Audiovisual Discrimination Between Laughter and Speech - Stavros P etridis\, Imperial College London DTSTART:20081204T141500Z DTEND:20081204T151500Z UID:TALK15122@talks.cam.ac.uk CONTACT:Laurel D. Riek DESCRIPTION:In human - human interaction\, information is communicated bet ween the parties through various channels. Speech is usually the dominant channel but other cues like facial e xpressions\, head gestures\, hand gestures and non-linguistic vocalizations play an important role in communic ation as well. One of the most important non-linguistic vocalizations is l aughter\, which is reported to be the most frequently annotated non-verbal behaviour in meeting corpora. Laughter is a powerful affective and social signal since people very often express their emotion and regulate convers ations by laughing. Although there are a few works on automatic laughter d etection the focus of past research has mainly been on audio-based detecti on. \n

\nInspired by the results in audiovisual speech recognition and audiovisual affect recognition\, this talk presents an audiovisual approac h to distinguishing spontaneous episodes of laughter from speech. Informat ion is extracted simultaneously from the audio and visual channel and fuse d using decision and feature level fusion leading to improved performance over single- modal approaches. The first part of the talk investigates the pe rformance of different combinations of audio/visual cues\, facial expressi ons and head movements for video and spectral and prosodic features for au dio. Once the most informative cues are found then\, in the second part\, two types of features are compared\, static features extracted on an audio /video frame basis and temporal features extracted over a temporal window\ , describing the evolution of static features over time. This is followed by a comparison of the two different fusion levels\, decision- and feature -level fusion. Finally\, initial results on recognizing two types of laugh ter are presented. LOCATION:SS03 END:VEVENT END:VCALENDAR