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.
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Giannakopoulos, T., Kosmopoulos, D., Aristidou, A., Theodoridis, S. (2006). Violence Content Classification Using Audio Features. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_55
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DOI: https://doi.org/10.1007/11752912_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34117-8
Online ISBN: 978-3-540-34118-5
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