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Lecture Notes in Computer Science Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen
Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos New York University, NY, USA Doug Tygar University of California, Berkeley, CA, USA Moshe Y. Vardi Rice University, Houston, TX, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany
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Samy Bengio Hervé Bourlard (Eds.)
Machine Learning for Multimodal Interaction First International Workshop, MLMI 2004 Martigny, Switzerland, June 21-23, 2004 Revised Selected Papers
Springer
eBook ISBN: Print ISBN:
3-540-30568-8 3-540-24509-X
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Preface
This book contains a selection of refereed papers presented at the 1st Workshop on Machine Learning for Multimodal Interaction (MLMI 2004), held at the “Centre du Parc,” Martigny, Switzerland, during June 21–23, 2004. The workshop was organized and sponsored jointly by three European projects, AMI, Augmented Multiparty Interaction, http://www.amiproject.org PASCAL, Pattern Analysis, Statistical Modeling and Computational Learning, http://www.pascal-network.org M4, Multi-modal Meeting Manager, http://www.m4project.org as well as the Swiss National Centre of Competence in Research (NCCR): IM2: Interactive Multimodal Information Management, http://www.im2.ch MLMI 2004 was thus sponsored by the European Commission and the Swiss National Science Foundation. Given the multiple links between the above projects and several related research areas, it was decided to organize a joint workshop bringing together researchers from the different communities working around the common theme of advanced machine learning algorithms for processing and structuring multimodal human interaction in meetings. The motivation for creating such a forum, which could be perceived as a number of papers from different research disciplines, evolved from a real need that arose from these projects and the strong motivation of their partners for such a multidisciplinary workshop. This assessment was indeed confirmed by the success of this first MLMI workshop, which attracted more than 200 participants. The conference program featured invited talks, full papers (subject to careful peer review, by at least three reviewers), and posters (accepted on the basis of abstracts) covering a wide range of areas related to machine learning applied to multimodal interaction—and more specifically to multimodal meeting processing, as addressed by the M4, AMI and IM2 projects. These areas included: human-human communication modeling speech and visual processing multimodal processing, fusion and fission multimodal dialog modeling human-human interaction modeling multimodal data structuring and presenta