First Steps to an Audio Ontology-Based Classifier for 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 on sound analysis. If such a situation is detected, an alarm will be automatically sent to the medical centre. In this paper we present our works on building domain ontology 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 classifier uses outputs of networks to identify classes of audio scenes. The system is tested with a database extracted from films.

@InternationalConference{NPC06,
  author       = {NGUYEN, C. and PHAM, T. and CASTELLI, E.},
  title        = {First Steps to an Audio Ontology-Based Classifier for Telemedicine},
  booktitle    = {Advanced Data Mining and Applications, Lecture Notes  in Artificial Intelligence, vol. 4093},
  year         = {2006},
  url          = {/2006/NPC06},
}