Accounting for Prosodic Information to Improve ASR-Based Topic Tracking for TV Broadcast News

Camille Guinaudeau 1, * Julia Hirschberg 2
* Corresponding author
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : The increasing quantity of video material available on line requires improved methods to help users navigate such data, among which are topic tracking techniques. The goal of this paper is to show that prosodic information can improve an ASR based topic tracking system for French TV Broadcast News. To this end, two kinds of prosodic information--extracted with and without a learning phase--are integrated in the system. This integration shows significant improvements in the F1-measure, by 13 and 8 points for the two techniques compared with the baseline system.
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https://hal.archives-ouvertes.fr/hal-00646626
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Submitted on : Wednesday, November 30, 2011 - 2:08:51 PM
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Camille Guinaudeau, Julia Hirschberg. Accounting for Prosodic Information to Improve ASR-Based Topic Tracking for TV Broadcast News. 12th Annual Conference of the International Speech Communication Association, Interspeech'11, Aug 2011, Florence, Italy. 4 p., 2 columns. ⟨hal-00646626⟩

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