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.
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Heittola, T., Klapuri, A. (2008). TUT Acoustic Event Detection System 2007. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds) Multimodal Technologies for Perception of Humans. RT CLEAR 2007 2007. Lecture Notes in Computer Science, vol 4625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68585-2_35
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DOI: https://doi.org/10.1007/978-3-540-68585-2_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68584-5
Online ISBN: 978-3-540-68585-2
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