Environmental Noise Classification for Context-Aware Applications

  • Ling Ma
  • Dan Smith
  • Ben Milner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)


Context-awareness is essential to the development of adaptive information systems. Much work has been done on developing technologies and systems that are aware of absolute location in space and time; other aspects of context have been relatively neglected. We describe our approach to automatically sensing and recognising environmental noise as a contextual cue for context-aware applications. Environmental noise provides much valuable information about a user’s current context. This paper describes an approach to classifying the noise context in the typical environments of our daily life, such as the office, car and city street. In this paper we present our hidden Markov model based noise classifier. We describe the architecture of our system, the experimental results, and discuss the open issues in environmental noise classification for mobile computing.


Hide Markov Model Discrete Cosine Transform Environmental Noise Automatic Speech Recognition Sound Event 
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.


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  1. 1.
    Abowd, G.D., Atkeson, C.G., Hong, J., Long, S., Kooper, R., Pinkerton, M.: Cyberguide: A mobile context-aware tour guide. ACM Wireless Networks (1997)Google Scholar
  2. 2.
    Beigl, M.: MemoClip: A Location based Remembrance Appliance. Personal Technologies 4(4), 230–233 (2000)CrossRefGoogle Scholar
  3. 3.
    Brown, G.J., Cooke, M.P.: Computational Auditory Scene Analysis. Computer Speech and Language 8, 297–336 (1994)CrossRefGoogle Scholar
  4. 4.
    Brown P. J.: STICK-E NOTES: changing notes and contexts – the SeSensor module and the loading of notes. EP-odd (January 1996)Google Scholar
  5. 5.
    Chen G., Kotz D.: A Survey of Context-Aware Mobile Computing, Research Dept. of Computer Science, Dartmouth College (2000)Google Scholar
  6. 6.
    Clarkson, B., Sawhney, N., Pentland, A.: Auditory Context Awareness via Wearable Computing. In: Proc. of the 1998 Workshop on Perceptual User Interfaces (PUI 1998), San Francisco, CA, USA (November 1998)Google Scholar
  7. 7.
    Couvreur, C.: Environmental Sound Recognition: A Statistical Approach, PhD thesis, Faculte Polytechnique de Mons, Belgium (June 1997)Google Scholar
  8. 8.
    Dey, A.K., Salber, D., Abowd, G.D., Futakawa, M.: The Conference Assistant: Combining Context-Awareness with Wearable Computing. In: The Third International Symposium on Wearable computers (1999)Google Scholar
  9. 9.
    Dey, A.K., Abowd, G.D.: CybreMinder: A Context-Aware System for Supporting reminders. In: Proceeding of the Second International Symposium on Handheld and Ubiquitous Computing, HUC 2000 (2000)Google Scholar
  10. 10.
    Dey, A.K., Abowd, G.D.: Towards a Better Understanding of Context and Context-Awareness. In: CHI 2000 Workshop on the What, Who, Where, When, and How of Context-Awareness (2000)Google Scholar
  11. 11.
    Ellis, D.: Prediction-Driven Computational auditory Scene Analysis For Dense Sound Mixtures. In: The ESCA workshop on the Auditory Basis of Speech Perception, Keele UK (July 1996)Google Scholar
  12. 12.
    Gaunard P., Mubikangiey C. G., Couvreur C., Fontaine V.: Automatic Classification Of Environmental Noise Events By Hidden Markov Models. Applied Acoustics (1998)Google Scholar
  13. 13.
    Harter, A., Hopper, A., Steggles, P., Ward, A., Webster, P.: The Anatomy of a Context-Aware Application. ACM/IEEE Mobile Computing and Networking (2002)Google Scholar
  14. 14.
    Huang, X., Acero, A., Hon, H.: Spoken Language Processing. Prentice-Hall, Englewood Cliffs (2001)Google Scholar
  15. 15.
  16. 16.
    Pascoe, J.: The Stick-e Note Architecture: Extending the Interface Beyond the User. In: International Conference on Intelligent User Interfaces, Orlando, Florida, USA, pp. 261–264. ACM, New York (1997)CrossRefGoogle Scholar
  17. 17.
    Peltonen, V., Tuomi, J., Klapuri, A., Huopaniemi, J., Sorsa, T.: Computational Auditory Scene Recognition. In: Proc. International Conference on Acoustic, Speech and Signal Processing, Orlando, Florida (May 2002)Google Scholar
  18. 18.
    Peltonen, V.T.K., Eronen, A.J., Parviainen, M.P., Klapuri, A.P.: Recognition of Everyday Auditory Scenes: Potentials, Latencies and Cues. In: 110th Convention Audio Engineering Society (2001)Google Scholar
  19. 19.
    Rabiner, L.R.: A tutorial on hidden Markov models and selected application in speech recognition. Proc. IEEE 77(2), 257–286 (1989)CrossRefGoogle Scholar
  20. 20.
    Randell, C., Muller, H.: The Shopping Jacket: Wearable Computing for the Consumer. Personal Technologies 4(4)Google Scholar
  21. 21.
    Sawhney, N.: Situational Awareness from Environmental Sounds (1997)Google Scholar
  22. 22.
    Schilit, B., Adams, N., Want, R.: Context-Aware Computing Applications. In: IEEE Workshop on Mobile Computing Systems and Applications (1994)Google Scholar
  23. 23.
    The HTK Book Version 3.1, Cambridge University Engineering Department (December 2001),
  24. 24.
    Want, R., Hopper, A., Falcao, V., Gibbons, J.: The Active Badge Location System. ACM Transactions on Information Systems 10(1) (1992)Google Scholar
  25. 25.
    Yan, H., Selker, T.: Context-aware office assistant. In: Proceedings of the 2000 International Conference on Intelligent User Interfaces, New Orleans, LA (January 2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Ling Ma
    • 1
  • Dan Smith
    • 1
  • Ben Milner
    • 1
  1. 1.School of Computing SciencesUniversity of East AngliaNorwichUK

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