Event Detection: Vuegen et al

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This submission explores Gaussian Mixture Models (GMM) estimated from Mel Frequency Cepstral Coefficients (MFCCs) for acoustic event detection and classification. To limit the impact of silence, a shared background model is used.

Related publications

L. Vuegen, B. V. D. Broeck, P. Karsmakers, J. F. Gemmeke, B. Vanrumste, and H. V. Hamme, “An MFCC-GMM approach for event detection and classification,” 2013.: [More Details] [BIBT_EX]; @techreport{lode2013a, author = {Lode Vuegen and B Van Den Broeck and P Karsmakers and Jort F Gemmeke and B Vanrumste and H Van Hamme}, title = {An MFCC-GMM approach for event detection and classification}, year = {2013} }

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Manager: Dan Stowell, Emmanouil Benetos, Mark Plumbley

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