Ontology-Based Classifier for Audio Scenes in Telemedicine

  • Cong Phuong Nguyen
  • Ngoc Yen Pham
  • Eric Castelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)


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.


Sound Effect Concept Property Audio Content Audio Object Sound Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Istrate, D., Vacher, M., Castelli, E., Sérignat, J.F.: Distress situation identifcation though sound processing. An application to medical telemonitoring. In: European Conference on Computational Biology, Paris (2003)Google Scholar
  2. Nguyen, C.P., Pham, N.Y., Castelli, E.: Toward a sound analysis system for telemedicine. In: 2nd International Conference on Fuzzy Systems and Knowledge Discovery, Chansha China (2005)Google Scholar
  3. Nakatani, T., Okuno, H.G.: Sound ontology for computational auditory scene analysis. In: Proc. AAAI 1998, vol. 1, pp. 30–35 (1998)Google Scholar
  4. Khan, L., McLeod, D.: Audio Structuring and Personalized Retrieval Using Ontologies. In: Proc. of IEEE Advances in Digital Libraries, Library of Congress, Washington, DC, pp. 116–126 (2000)Google Scholar
  5. Casey, M.: MPEG-7 sound-recognition tools. IEEE Transaction on Circuits and Systems for Video Technology 11(6) (2001)Google Scholar
  6. Amatriain, X., Herrera, P.: Transmitting audio contents as sound objects. In: Proceedings of AES22 International Conference on Virtual, Synthetic and Entertainment Audio, Espoo, Finland (2002)Google Scholar
  7. Cano, P., Koppenberger, M., Celma, O., Herrera, P., Tarasov, V.: Sound effects taxonomy management in production environments. In: AES 25th International Conference, UK (2004)Google Scholar
  8. Hatala, M., Kalantari, L., Wakkary, R., Newby, K.: Ontology and rule based retrieval of sound objects in augmented audio reality system for museum visitors. In: Proceedings of the 2004 ACM symposium on Applied computing, Nicosia, Cyprus, pp. 1045–1050 (2004)Google Scholar
  9. Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar
  10. Breen, C., Khan, L., Kumar, A., Wang, L.: Ontology-based image classification using neural networks. In: Proc. SPIE, vol. 4862, pp. 198–208 (2002)Google Scholar
  11. Prabowo, R., Jackson, M., Burden, P., Knoell, H.D.: Ontology-based automatic classification for the web pages: design, implimentation and evaluation. In: The 3rd International Conference on Web Information Systems Engineering, Singapore (2002)Google Scholar
  12. Mezaris, V., Kompatsiaris, I., Strintzis, M.G.: An Ontology Approach to Object-Based Image Retrieval. In: IEEE Intl. Conf. on Image Processing (2003)Google Scholar
  13. Noh, S., Seo, H., Choi, J., Choi, K., Jung, G.: Classifying Web Pages Using Adaptive Ontology. In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Washington, DC, pp. 2144–2149 (2003)Google Scholar
  14. Taghva, K., Borsack, J., Coombs, J., Condit, A., Lumos, S., Nartker, T.: Ontology-based classification of email. In: International Conference on Information Technology: Computers and Communications, Las Vegas, Nevada (2003)Google Scholar
  15. Wu, S.H., Tsai, T.H., Hsu, W.L.: Text Categorization Using Automatically Acquired Domain Ontology. In: The Sixth International Workshop on Information Retrieval with Asian Languages (IRAL 2003), Sapporo, Japan, pp. 138–145 (2003)Google Scholar
  16. Maillot, N., Thonnat, M., Hudelot, C.: Ontology based object learning and recognition: application to image retrieval. In: ICTAI (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Cong Phuong Nguyen
    • 1
  • Ngoc Yen Pham
    • 1
  • Eric Castelli
    • 1
  1. 1.International Research Center MICA, HUT – CNRS/UMI2954 – INPGrenobleHanoiVietnam

Personalised recommendations