Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/95171
Title: MOODetector: A Prototype Software Tool for Mood-based Playlist Generation
Authors: Cardoso, Luís
Panda, Renato 
Paiva, Rui Pedro 
Keywords: classification; feature extraction; music emotion recognition; music information retrieval; playlist generation; regression
Issue Date: 2011
Project: info:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT/MOODetector - A System for Mood-based Classification and Retrieval of Audio Music 
Serial title, monograph or event: 3º Simpósio de Informática - INForum 2011
Place of publication or event: Coimbra, Portugal
Abstract: We propose a prototype software tool for the automatic generation of mood-based playlists. The tool works as typical music player, extended with mechanisms for automatic estimation of arousal and valence values in the Thayer plane (TP). Playlists are generated based on one seed song or a desired mood trajectory path drawn by the user, according to the distance to the seed(s) in the TP. Besides playlist generation, a mood tracking visualization tool is also implemented, where individual songs are segmented and classified according to the quadrants in the TP. Additionally, the methodology for music emotion recognition, tackled in this paper as a regression and classification problem, is described, along with the process for feature extraction and selection. Experimental results for mood regression are slightly higher than the state of the art, indicating the viability of the followed strategy (in terms of R2 statistics, arousal and valence estimation accuracy reached 63% and 35.6%, respectively).
URI: http://hdl.handle.net/10316/95171
Rights: openAccess
Appears in Collections:I&D CISUC - Artigos em Livros de Actas

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