Author(s): Panda, Renato ; Paiva, Rui Pedro
Date: 2012
Persistent ID: https://hdl.handle.net/10316/95167
Origin: Estudo Geral - Universidade de Coimbra
Project/scholarship: info:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT ;
Author(s): Panda, Renato ; Paiva, Rui Pedro
Date: 2012
Persistent ID: https://hdl.handle.net/10316/95167
Origin: Estudo Geral - Universidade de Coimbra
Project/scholarship: info:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT ;
Short paper describing our MIREX 2012 Audio Mood Classification Task submission (1st place).
In this work, three audio frameworks – Marsyas, MIR Toolbox and PsySound3, were used to extract audio features from the audio samples. These features are then used to train several classification models, resulting in the different versions submitted to MIREX 2012 mood classification task.
This work was supported by the MOODetector project (PTDC/EIA-EIA/102185/2008), financed by the Fundação para Ciência e a Tecnologia (FCT) and Programa Operacional Temático Factores de Competitividade (COMPETE) – Portugal.