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Communication Dans Un Congrès Année : 2010

Transcription-based video genre classification

Stanislas Oger
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Georges Linarès

Résumé

In this paper, we present a new method for video genre identification based on the linguistic content analysis. This approach relies on the analysis of the most frequent words in the video transcriptions provided by an automatic speech recognition system. Experiments are conducted on a corpus composed of cartoons, movies, news, commercials, documentary , sport and music. On this 7-genre identification task, the proposed transcription-based method obtains up to 80% of correct identification. Finally, this rate is increased to 95% by combining the proposed linguistic-level features with low-level acoustic features. Index Terms— video genre classification, audio-based video processing, linguistic feature extraction
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Dates et versions

hal-01319884 , version 1 (23-05-2016)

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Citer

Stanislas Oger, Mickael Rouvier, Georges Linarès. Transcription-based video genre classification. IEEE International Conference on Acoustics, Speech and Signal Processing , Mar 2010, Dallas, United States. ⟨10.1109/ICASSP.2010.5495042⟩. ⟨hal-01319884⟩

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