Multimodal Corpora [[electronic resource] ] : From Models of Natural Interaction to Systems and Applications / / edited by Michael Kipp, Jean-Claude Martin, Patrizia Paggio, Dirk Heylen

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009
• Edizione: 1st ed. 2009.
• Descrizione fisica: 1 online resource (X, 223 p.)
• Disciplina: 410.1/88
• Soggetto topico: Optical data processing; Natural language processing (Computer science); Computer graphics; Pattern recognition; Biometrics (Biology); Computer Imaging, Vision, Pattern Recognition and Graphics; Natural Language Processing (NLP); Image Processing and Computer Vision; Computer Graphics; Pattern Recognition; Biometrics
• Persona (resp. second.): KippMichael; MartinJean-Claude; PaggioPatrizia; HeylenDirk
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Collecting and Distributing Multimodal Corpora -- The SmartWeb Corpora: Multimodal Access to the Web in Natural Environments -- Promoting free Dialog Video Corpora: The IFADV Corpus Example -- Coding and Analyzing Multimodal Corpora -- Creating and Exploiting Multimodal Annotated Corpora: The ToMA Project -- Multi-track Annotation of Child Language and Gestures -- Gesture, Gaze and Persuasive Strategies in Political Discourse -- Unsupervised Clustering in Multimodal Multiparty Meeting Analysis -- Validating Multimodal Corpora -- Multimodal Corpora Annotation: Validation Methods to Assess Coding Scheme Reliability -- On the Contextual Analysis of Agreement Scores -- The Intercultural Dimension of Multimodal Corpora -- Creating Standardized Video Recordings of Multimodal Interactions across Cultures -- Multimodal Intercultural Information and Communication Technology – A Framework for Designing and Evaluating Multimodal Intercultural Communicators -- Tools for Browsing, Coding and Exchanging Data in Multimodal Corpora -- Tools and Resources for Visualising Conversational-Speech Interaction -- Accessing a Large Multimodal Corpus Using an Automatic Content Linking Device -- An Exchange Format for Multimodal Annotations.
• Sommario/riassunto: Empirically based research in multimodality starts with the collection of video data relevant for a specific research question. This data must then be enriched by human coders, who annotate the corpus and who also explore the potential interconnections between modalities (e.g., face, gesture, speech, posture, etc.). The data must then be validated for consistency using quantitative measures -- systematic analysis of the observed multimodal behaviors is the central characteristic of multimodal corpora. For analysis and modeling tasks, exploratory qualitative and quantitative analysis tools are needed for browsing, viewing, extraction, and modeling. At the same time, the intercultural dimension must be taken into account, since multimodal interaction is always embedded in a social setting. This state-of-the-art survey documents the scientific outcome of the International Workshop on "Multimodal Corpora: From Models of Natural Interaction to Systems and Applications", held in conjunction with the 6th International Conference for Language Resources and Evaluation (LREC), on May 27, 2008, in Marrakech, Morocco. It presents current research from fields as diverse as psychology, artificial intelligence, robotics, signal processing, computational linguistics, and human-computer interaction. The 6 selected workshop contributions are complemented by 7 invited research articles, including contributions from major international multimodal corpus projects like AMI and SmartWeb. All papers underwent a special review process for this volume, resulting in significant revisions and extensions based on the experts' advice.
• Titolo autorizzato: Multimodal Corpora
• ISBN: 3-642-04793-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996465335103316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Artificial Intelligence ; ; 5509