Violence content classification using audio features

Authors:
Theodoros Giannakopoulos;Dimitrios Kosmopoulos;Andreas Aristidou;Sergios Theodoridis
Affiliations:
Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilissia Athens;Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos", Athens, Greece;Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilissia Athens;Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Ilissia Athens
Venue:
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Year:
2006

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Abstract

This work studies the problem of violence detection in audio data, which can be used for automated content rating. We employ some popular frame-level audio features both from the time and frequency domain. Afterwards, several statistics of the calculated feature sequences are fed as input to a Support Vector Machine classifier, which decides about the segment content with respect to violence. The presented experimental results verify the validity of the approach and exhibit a better performance than the other known approaches.