Gerald Friedland
Luke Gottlieb
ABSTRACT
This paper summarizes our contribution to the Yahoo! task of the ACM Multimedia Grand Challenge. This challenge asks for the robust automatic segmentation of videos according to "narrative themes". Based on the automatic segmentation methods presented in [1] and partly [2], we describe a system to navigate Seinfeld episodes based on automatic segmentation of the audio track only. The system distinguishes laughter, music, and other noise as well as speech segments. Speech segments are identified against pre-trained speaker models of the actors. Given this segmentation and the artistic production rules that underlie the genre situation comedy and Seinfeld in particular, the system enables a user to browse an episode by scene, by punchline, and by dialog segments. The themes can be filtered by the main actors, e.g. the user can select to see only punchlines by Jerry and Kramer. Based on the length of the laughter, the top 5 punchlines are also identified and presented to the user.
- G. Friedland and O. Vinyals. Live speaker identification in conversations. In Proceedings of ACM Multimedia, pages 1017--1018. ACM, October 2008. Google Scholar
Digital Library
- G. Friedland, C. Yeo, and H. Hung. Visual speaker localization aided by acoustic models. In Proceedings of ACM Multimedia, to appear. ACM, October 2009. Google ScholarDigital Library
Index Terms
- Joke-o-mat: browsing sitcoms punchline by punchline
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