Gerald Friedland
Luke Gottlieb
ABSTRACT
The following article presents a novel method to generate indexing information for the navigation of TV content and presents an implementation that extends the Joke-O-Mat sitcom navigation system, presented in [1]. The extended system enhances Joke-o-mat's capability to browse a sitcom by scene, punchline, dialog segment, and actor with word-level keyword search. The indexing is performed based on the alignment of the multimedia content with closed captions and "found" fan-generated scripts processed with speech and speaker recognition systems. This significantly reduces the amount of manual intervention required for training new episodes, and the final narrative-theme segmentation has proven indistinguishable from expert annotation. This article describes the new Joke-o-mat system, discusses problems with using fan-generated data, and presents results on episodes from the sitcom Seinfeld, showing segmentation accuracy and user satisfaction as determined by a human-subject study.
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Digital Library
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Index Terms
- Narrative theme navigation for sitcoms supported by fan-generated scripts
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