Author(s): Malheiro, Ricardo ; Panda, Renato ; Gomes, Paulo J. S. ; Paiva, Rui Pedro
Date: 2013
Persistent ID: https://hdl.handle.net/10316/95165
Origin: Estudo Geral - Universidade de Coimbra
Project/scholarship: info:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT ;
Subject(s): language processing; lyrics; machine learning; multi-modal fusion; music emotion recognition; natural language processing; machine learning
We present a study on music emotion recognition from lyrics. We start from a dataset of 764 samples (audio+lyrics) and perform feature extraction using several natural language processing techniques. Our goal is to build classifiers for the different datasets, comparing different algorithms and using feature selection. The best results (44.2% F-measure) were attained with SVMs. We also perform a bi-modal analysis that combines the best feature sets of audio and lyrics.The combination of the best audio and lyrics features achieved better results than the best feature set from audio only (63.9% F- Measure against 62.4% F-Measure).
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.
