A Real-Time Sound Recognition System in an Assisted Environment

  • Héctor Lozano
  • Inmaculada Hernáez
  • Javier Camarena
  • Ibai Díez
  • Eva Navas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7383)

Abstract

This article focuses on the development of detection and classification system of environmental sounds in real-time in a typical home for persons with disabilities. Based on the extraction of acoustic characteristics (Mel Frequency Cepstral Coefficients, Zero Crossing Rate, Roll Off Point and Spectral Centroid) and using a probabilistic classifier (Gaussian Mixture Model), preliminary results show an accuracy rate greater than 93% in the detection and 98% in the classification task

Keywords

Gaussian Mixture Model Acoustic Characteristic Zero Crossing Rate Spectral Centroid Audio Classification 
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.
This is a preview of subscription content, log in to check access

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lozano, H., Hernáez, I., Picón, A., Camarena, J., Navas, E.: Audio Classification Techniques in Home Environments for Elderly/Dependant People. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2010. LNCS, vol. 6179, pp. 320–323. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Lozano, H., Hernáez, I., Navas, E., et al.: Non-Speech Sounds Classification for People with Hearing Disabilities. In: AAATE, pp. 276–280 (2007)Google Scholar
  3. 3.
    Cowling, M.: Non-Speech Environmental Sound Classification System for Autonomous Surveillance. Phd Thesis. Griffith University (2004)Google Scholar
  4. 4.
    Temko, A.: Acoustic Event Detection and Classification. Phd Thesis. Universitat Politècnica de Catalunya (2007)Google Scholar
  5. 5.
    Clavel, C., Ehrette, T., Richard, G.: Events Detection for an Audio-Based Surveillance System. In: Proc. of the IEEE Int. Conf. on Multimedia and Expo., ICME, pp. 1306–1309 (2005)Google Scholar
  6. 6.
    Atrey, K., Maddage, C., Kankanhalli, S.: Audio Based Event Detection for Multimedia Surveillance. In: IEEE International Conference ICCASP, pp. 813–816 (2006)Google Scholar
  7. 7.
    Vacher, M., Istrate, D., Besacier, L., Serignat, J.F.: Life Sounds Extraction and Classification in Noisy Environment. In: IASTED’SIP, Honolulu, Hawaii, USA (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Héctor Lozano
    • 1
  • Inmaculada Hernáez
    • 2
  • Javier Camarena
    • 1
  • Ibai Díez
    • 1
  • Eva Navas
    • 2
  1. 1.Tecnalia, Health and Quality of Life Unit, Parque TecnológicoZamudioSpain
  2. 2.Department of Electronics and TelecommunicationsUniversity of the Basque CountryBilbaoSpain

Personalised recommendations