Ontology-Based Classifier for Audio Scenes in Telemedicine

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 ontologybased classifer uses outputs of networks to identify classes of audio scenes. The system is tested with a database extracted from films.

@InternationalConference{NPC06a,
  author       = {NGUYEN, C. and PHAM, T. and CASTELLI, E.},
  title        = {Ontology-Based Classifier for Audio Scenes in Telemedicine},
  booktitle    = {Intelligent Data Engineering and Automated Learning, Lecture Notes in Computer Science},
  year         = {2006},
  url          = {/2006/NPC06a},
}