Acoustic Events Detection in Dissimilarity Measurement Space

Abstract:

The paper considers the problem of detecting acoustic events in a robust manner. The dissimilarity measurement is used to measure the distance between acoustic samples. Then this distance is used as the replacement of the Euclidean distance to build the detection model with the SVM algorithm. All the well-known features are considered when we build model in a way of feature subset ensemble. Experiments are conducted to detect events under a variety of environmental sounds. The model demonstrates the robustness of the ensemble method with dissimilarity measurement. The detection model has shown to produce comparable performance as human listeners.

• Periodical: Applied Mechanics and Materials (Volumes 333-335)
• Pages: 764-768
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.333-335.764
• Online since: July 2013
• Authors: Lin Bin Jia, Lin Li, Rong Nie
• Keywords: Acoustic Event, Dissimilarity Measurement, Support Vector Machine (SVM)

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