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. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Nguyen, C. P., Pham, N. Y., & Castelli, E. (2006). Ontology-based classifier for audio scenes in telemedicine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4224 LNCS, pp. 1382–1389). Springer Verlag. https://doi.org/10.1007/11875581_164
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