This paper gives the final results of the ESTER evaluation campaign which started in 2003 and ended in January 2005. The aim of this campaign was to evaluate automatic broadcast news rich transcription systems for the French language. The evaluation tasks were divided into three main categories: orthographic transcription, event detection and tracking (e.g. speech vs. music, speaker tracking), and information extraction. The last one, limited to named entity detection in this evaluation, was a preliminary test. The paper reports on protocols and gives the results obtained in the campaign.
The analysis of lectures and meetings inside smart rooms has recently attracted much interest in the literature, being the focus of international projects and technology evaluations. A key enabler for progress in this area is the availability of Ambrish Tyagi has contributed to this work during two summer internships with the IBM T.appropriate multimodal and multi-sensory corpora, annotated with rich human activity information during lectures and meetings. This paper is devoted to exactly such a corpus, developed in the framework of the European project CHIL, ''Computers in the Human Interaction Loop''. The resulting data set has the potential to drastically advance the state-of-the-art, by providing numerous synchronized audio and video streams of real lectures and meetings, captured in multiple recording sites over the past 4 years. It particularly overcomes typical shortcomings of other existing databases that may contain limited sensory or monomodal data, exhibit constrained human behavior and interaction patterns, or lack data variability. The CHIL corpus is accompanied by rich manual annotations of both its audio and visual modalities. These provide a detailed multi-channel verbatim orthographic transcription that includes speaker turns and identities, acoustic condition information, and named entities, as well as video labels in multiple camera views that provide multi-person 3D head and 2D facial feature location information. Over the past 3 years, the corpus has been crucial to the evaluation of a multitude of audiovisual perception technologies for human activity analysis in lecture and meeting scenarios, demonstrating its utility during internal J. Turmo
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