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Fusion multi-niveaux par boosting pour le tagging automatique

Abstract : Tags constitute a very useful tool for multimedia document indexing. This PhD thesis deals with automatic tagging, which consists in associating a set of tags to each song automatically, using an algorithm. We use boosting techniques to design a learning which better considers the complexity of the information expressed by music. A boosting algorithm is proposed, which can jointly use song descriptions associated to excerpts of different durations. This algorithm is used to fuse new descriptions, which belong to different abstraction levels. Finally, a new learning framework is proposed for automatic tagging, which better leverages the subtlety ofthe information expressed by music.
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Submitted on : Thursday, April 28, 2016 - 3:28:08 AM
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  • HAL Id : tel-01308527, version 1



Rémi Foucard. Fusion multi-niveaux par boosting pour le tagging automatique. Traitement du signal et de l'image [eess.SP]. Télécom ParisTech, 2013. Français. ⟨NNT : 2013ENST0093⟩. ⟨tel-01308527⟩



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