Machine Learning For Multimodal Interaction


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Machine Learning for Multimodal Interaction


Machine Learning for Multimodal Interaction

Author: Steve Renals

language: en

Publisher: Springer

Release Date: 2007-01-23


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This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Machine Learning for Multimodal Interaction, MLMI 2006, held in Bethesda, MD, USA, in May 2006. The papers are organized in topical sections on multimodal processing, image and video processing, HCI and applications, discourse and dialogue, speech and audio processing, and NIST meeting recognition evaluation.

Machine Learning for Multimodal Interaction


Machine Learning for Multimodal Interaction

Author: Samy Bengio

language: en

Publisher: Springer

Release Date: 2005-01-17


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This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Machine Learning for Multimodal Interaction, MLMI 2004, held in Martigny, Switzerland in June 2004. The 30 revised full papers presented were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on HCI and applications, structuring and interaction, multimodal processing, speech processing, dialogue management, and vision and emotion.

Machine Learning for Multimodal Interaction


Machine Learning for Multimodal Interaction

Author: Andrei Popescu-Belis

language: en

Publisher: Springer

Release Date: 2008-02-22


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This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2007, held in Brno, Czech Republic, in June 2007. The 25 revised full papers presented together with 1 invited paper were carefully selected during two rounds of reviewing and revision from 60 workshop presentations. The papers are organized in topical sections on multimodal processing, HCI, user studies and applications, image and video processing, discourse and dialogue processing, speech and audio processing, as well as the PASCAL speech separation challenge.