The CHIL Audiovisual Corpus for Lecture and Meeting Analysis inside Smart Rooms

• Published in: Language Resources and Evaluation Vol. 41; no. 3/4; pp. 389 - 407
• Main Authors: Mostefa, Djamel, Moreau, Nicolas, Choukri, Khalid, Potamianos, Gerasimos, Chu, Stephen M., Tyagi, Ambrish, Casas, Josep R., Turmo, Jordi, Cristoforetti, Luca, Tobia, Francesco, Pnevmatikakis, Aristodemos, Mylonakis, Vassilis, Talantzis, Fotios, Burger, Susanne, Stiefelhagen, Rainer, Bernardin, Keni, Rochet, Cedrick
• Format: Journal Article
• Language: English
• Published: Dordrect Springer 01.12.2007; Springer Nature B.V
• Subjects: Annotations; Cameras; Communication research; Computerized corpora; Consortia; Corpus analysis; Datasets; Human behavior; Interpersonal communication; Lectures; Meetings; Microphones; Multimedia communications; Orthography; Product labeling; Recording; Sensors; Social interaction; Space; Technological change; Technology; Technology assessment; Transcription; Video data; Websites; United States > US; Italy; Germany
• ISSN: 1574-020X; 1572-8412; 1574-0218
• DOI: 10.1007/s10579-007-9054-4

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 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 proving numerous synchronized audio and video streams of real lectures and meetings, captured in multiple recording sites over the past 4 years. It particulary 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 mantual 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 of 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 evaluations of the CHIL consortium, as well as at the recent international CLEAR and Rich Transcription evaluations. The CHIL corpus is publicly available to the research community.