10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Robust Audio-Based Classification of Video Genre

Mickael Rouvier, Georges Linarès, Driss Matrouf

LIA, France

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%.

Full Paper

Bibliographic reference.  Rouvier, Mickael / Linarès, Georges / Matrouf, Driss (2009): "Robust audio-based classification of video genre", In INTERSPEECH-2009, 1159-1162.