Communicative interactivity: a multimodal communicative situation classification approach

Authors:
Tomasz M. Rutkowski;Danilo Mandic
Affiliations:
Brain Science Institute RIKEN, Saitama, Japan and Academic Center for Computing and Media Studies, Kyoto University, Kyoto, Japan;Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

The problem of modality detection in so called Communicative Interactivity is addressed. Multiple audio and video recordings of human communication are analyzed within this framework, based on fusion of the extracted features. At the decision level, Support Vector Machines (SVM) are utilized to segregate between the communication modalities. The proposed approach is verified through simulations on real world recordings.