Paper Info
Title
Joke-o-mat: browsing sitcoms punchline by punchline
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.
Year
DOI
Venue
2009
10.1145/1631272.1631525
ACM Multimedia 2001
Keywords
Field
DocType
robust automatic segmentation,automatic segmentation,dialog segment,audio track,artistic production rule,speech segment,acm multimedia grand challenge,automatic segmentation method,seinfeld episode,system distinguishes laughter,sitcoms punchline,speech segmentation
Dialog box,Laughter,Computer vision,Joke,Comedy,Computer science,Segmentation,Video navigation,Narrative,Artificial intelligence,Acoustic event detection
Conference
Citations 
PageRank 
References 
11
0.90
3
Authors
3
Name
Order
Citations
PageRank
Gerald Friedland1112796.23
Luke Gottlieb2615.79
Adam Janin325034.11