ISCA Archive Interspeech 2009
ISCA Archive Interspeech 2009

Robust audio-based classification of video genre

Mickael Rouvier, Georges Linarès, Driss Matrouf

Video genre classification is a challenging task in a global context of fast growing video collections available on the Internet. This paper presents a new method for video genre identification by audio analysis. Our approach relies on the combination of low and high level audio features. We investigate the discriminative capacity of features related to acoustic instability, speaker interactivity, speech quality and acoustic space characterization. The genre identification is performed on these features by using a SVM classifier. Experiments are conducted on a corpus composed from cartoons, movies, news, commercials and musics on which we obtain an identification rate of 91%.

doi: 10.21437/Interspeech.2009-337

Cite as: Rouvier, M., Linarès, G., Matrouf, D. (2009) Robust audio-based classification of video genre. Proc. Interspeech 2009, 1159-1162, doi: 10.21437/Interspeech.2009-337

  author={Mickael Rouvier and Georges Linarès and Driss Matrouf},
  title={{Robust audio-based classification of video genre}},
  booktitle={Proc. Interspeech 2009},