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Abstract

This paper describes a system used in acoustic event detection task of the CLEAR 2007 evaluation. The objective of the task is to detect acoustic events (door slam, steps, paper wrapping etc.) using acoustic data from a multiple microphone set up in the meeting room environment. A system based on hidden Markov models and multi-channel audio data was implemented. Mel-Frequency Cepstral Coefficients are used to represent the power spectrum of the acoustic signal. Fully-connected three-state hidden Markov models are trained for 12 acoustic events and one-state models are trained for speech, silence, and unknown events.

Keywords

Hide Markov Model Acoustic Event Meeting Room Reference Event Observation Probability 
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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References

  1. 1.
    Temko, A., Malkin, R., Zieger, C., Macho, D., Nadeu, C., Omologo, M.: CLEAR Evaluation of Acoustic Event Detection and Classification Systems. In: Stiefelhagen, R., Garofolo, J.S. (eds.) CLEAR 2006. LNCS, vol. 4122, pp. 311–322. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Temko, A., Nadeu, C.: Classification of acoustic events using SVM-based clustering schemes. Pattern Recognition 39(4), 682–694 (2006)zbMATHCrossRefGoogle Scholar
  3. 3.
    Gaunard, P., Mubikangiey, C., Couvreur, C., Fontaine, V.: Automatic Classification of Environmental Noise Events by Hidden Markov Models. Applied Acoustics 54(3), 187–206 (1998)CrossRefGoogle Scholar
  4. 4.
    Eronen, A., Tuomi, J., Klapuri, A., Fagerlund, S., Sorsa, T., Lorho, G., Huopaniemi, J.: Audio-based context recognition. IEEE Transactions on Audio, Speech, and Language Processing 14(1), 321–329 (2006)CrossRefGoogle Scholar
  5. 5.
    Rabiner, L., Juang, B.H.: Fundamentals of Speech Recognition. PTR Prentice-Hall Inc, New Jersey (1993)Google Scholar
  6. 6.
  7. 7.
    NIST: Spring (RT-05S) Rich Transcription Meeting Recognition Evaluation Plan (2005), http://nist.gov/speech/tests/rt/rt2005/spring/rt05smeetingeval-plan-V1.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Toni Heittola
    • 1
  • Anssi Klapuri
    • 1
  1. 1.Tampere University of TechnologyTampereFinland

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