Abstract
This paper deals with the CLEAR 2007 evaluation on the detection of acoustic events which happen during seminars. The proposed system first converts an audio sequence in a stream of MFCC features, then a detecting/classifying block identifies an acoustic event with time stamps and assign to it a label among all possible event labels. Identification and classification are based on Hidden Markov Models (HMM). The results, measured in terms of two metrics (accuracy and error rate) are obtained applying the implemented system on the interactive seminars collected under the CHIL project. Final not very good results highlight the task complexity.
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Zieger, C. (2008). An HMM Based System for Acoustic Event Detection. 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_32
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DOI: https://doi.org/10.1007/978-3-540-68585-2_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68584-5
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