Introduction to the special issue on Machine learning for multiple modalities in interactive systems and robots

Cuayahuitl, Heriberto and Frommberger, Lutz and Dethlefs, Nina and Raux, Antoine and Marge, Mathew and Zender, Hendrik (2014) Introduction to the special issue on Machine learning for multiple modalities in interactive systems and robots. ACM Transactions on Interactive Intelligent Systems (TiiS), 4 (3). 12e. ISSN 2160-6455

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Abstract

This special issue highlights research articles that apply machine learning to robots and other systems that interact with users through more than one modality, such as speech, gestures, and vision. For example, a robot may coordinate its speech with its actions, taking into account (audio-)visual feedback during their execution. Machine learning provides interactive systems with opportunities to improve performance not only of individual components but also of the system as a whole. However, machine learning methods that encompass multiple modalities of an interactive system are still relatively hard to find. The articles in this special issue represent examples that contribute to filling this gap.

Keywords:Machine Learning, Interactive robots, Multimodal interaction, NotOAChecked
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G760 Machine Learning
G Mathematical and Computer Sciences > G710 Speech and Natural Language Processing
G Mathematical and Computer Sciences > G440 Human-computer Interaction
Divisions:College of Science > School of Computer Science
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ID Code:22212
Deposited On:13 Feb 2016 19:13

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