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Structuration automatique de flux télévisuels

Camille Guinaudeau 1
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 requires the implementation of automatic structuring techniques that can facilitate access to the information contained in documents, while being generic enough to be able to structure different kinds of videos. For this, we develop two kinds of thematic structuring of TV shows, linear or hierarchical, based on the automatic transcripts of the speech pronounced in the programs. These transcripts, independent of the type of documents considered, are used thanks to natural language processing (NLP) methods. The two structuring techniques, as well as the topic segmentation phase on which they rely, has led to several original contributions. First, the topic segmentation technique employed, originally developed for text, is adapted to the peculiarities of professional videos transcripts - transcription errors, limited number of repetition. The lexical cohesion criterion on which the segmentation step is based is, indeed, sensitive to these characteristics, which severely penalizes the algorithm performances. This adaptation is implemented, on the one hand by taking into account, during the lexical cohesion computation, linguistic knowledge and automatic speech recognition and signal information (semantic relations, prosody, confidence measures), and on the other hand on language model interpolation techniques. From this topic segmentation step, we propose a method for linear thematic structuring that is able to connect segments addressing similar topic. The method, based on a technique from the information retrieval domain, is adapted to the audiovisual data through prosodic cues, that help to promote prominent words in the speech, and semantic relations. Finally, we propose an exploratory work that studies different ways to adapt a linear topic segmentation algorithm to a hierarchical topic segmentation task. For this, the linear topic segmentation algorithm is modified - adjustement of the lexical cohesion computation, use of lexical chains - to reflect the distribution of the vocabulary in the document to be segmented. Experiments conducted on three corpora composed of broadcast news and reports on current affairs, manually and automatically transcribed, show that the proposed adjustments lead to improved performance of the structuring methods developed.
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Contributor : Pascale Sébillot <>
Submitted on : Wednesday, November 30, 2011 - 10:38:01 AM
Last modification on : Thursday, January 7, 2021 - 4:20:18 PM
Long-term archiving on: : Thursday, March 1, 2012 - 2:26:04 AM


  • HAL Id : tel-00646522, version 1


Camille Guinaudeau. Structuration automatique de flux télévisuels. Multimédia [cs.MM]. INSA de Rennes, 2011. Français. ⟨tel-00646522⟩



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