Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/95165
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dc.contributor.authorMalheiro, Ricardo-
dc.contributor.authorPanda, Renato-
dc.contributor.authorGomes, Paulo J. S.-
dc.contributor.authorPaiva, Rui Pedro-
dc.date.accessioned2021-07-04T18:13:28Z-
dc.date.available2021-07-04T18:13:28Z-
dc.date.issued2013-
dc.identifier.urihttps://hdl.handle.net/10316/95165-
dc.description.abstractWe 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).pt
dc.description.sponsorshipThis 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.pt
dc.language.isoengpt
dc.relationinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT/MOODetector - A System for Mood-based Classification and Retrieval of Audio Musicpt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectlanguage processingpt
dc.subjectlyricspt
dc.subjectmachine learningpt
dc.subjectmulti-modal fusionpt
dc.subjectmusic emotion recognitionpt
dc.subjectnatural language processingpt
dc.subjectmachine learningpt
dc.titleMusic Emotion Recognition from Lyrics: A Comparative Studypt
dc.typeconferenceObjectpt
degois.publication.locationPrague, Czech Republicpt
degois.publication.title6th International Workshop on Music and Machine Learning – MML 2013 – in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECML/PKDD 2013pt
dc.peerreviewedyespt
dc.date.embargo2013-01-01*
uc.date.periodoEmbargo0pt
item.openairetypeconferenceObject-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.fulltextCom Texto completo-
crisitem.author.deptFaculty of Sciences and Technology-
crisitem.author.deptFaculty of Sciences and Technology-
crisitem.author.parentdeptUniversity of Coimbra-
crisitem.author.parentdeptUniversity of Coimbra-
crisitem.author.researchunitCISUC - Centre for Informatics and Systems of the University of Coimbra-
crisitem.author.researchunitCISUC - Centre for Informatics and Systems of the University of Coimbra-
crisitem.author.researchunitCISUC - Centre for Informatics and Systems of the University of Coimbra-
crisitem.author.parentresearchunitFaculty of Sciences and Technology-
crisitem.author.parentresearchunitFaculty of Sciences and Technology-
crisitem.author.parentresearchunitFaculty of Sciences and Technology-
crisitem.author.orcid0000-0002-3010-2732-
crisitem.author.orcid0000-0003-2539-5590-
crisitem.author.orcid0000-0003-3215-3960-
crisitem.project.grantnoinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/102185/PT/MOODetector - A System for Mood-based Classification and Retrieval of Audio Music-
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