Ontology-Based classifier for audio scenes in telemedicine

Authors:
Cong Phuong Nguyen;Ngoc Yen Pham;Eric Castelli
Affiliations:
International Research Center MICA, HUT – CNRS/UMI2954 – INPGrenoble, Hanoi, Vietnam;International Research Center MICA, HUT – CNRS/UMI2954 – INPGrenoble, Hanoi, Vietnam;International Research Center MICA, HUT – CNRS/UMI2954 – INPGrenoble, Hanoi, Vietnam
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

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Abstract

Our work is within the framework of studying and implementing a sound analysis system in a telemedicine project. The task of this system is to detect situations of distress in a patient’s room based sound analysis. In this paper we present our works on building domain ontologies of such situations. They gather abstract concepts of sounds and these concepts, along with their properties and instances, are represented by a neural network. The ontology-based classifer uses outputs of networks to identify classes of audio scenes. The system is tested with a database extracted from films.