Music Emotion Recognition from Lyrics: A Comparative Study

Bibliographic Details
Main Author: Malheiro, Ricardo
Publication Date: 2013
Other Authors: Panda, Renato, Gomes, Paulo J. S., Paiva, Rui Pedro
Format: Other
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/10316/95165
Summary: 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).
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spelling Music Emotion Recognition from Lyrics: A Comparative Studylanguage processinglyricsmachine learningmulti-modal fusionmusic emotion recognitionnatural language processingmachine learningWe 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.2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/otherhttps://hdl.handle.net/10316/95165https://hdl.handle.net/10316/95165engMalheiro, RicardoPanda, RenatoGomes, Paulo J. S.Paiva, Rui Pedroinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2022-05-25T02:38:35Zoai:estudogeral.uc.pt:10316/95165Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:43:15.797902Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Music Emotion Recognition from Lyrics: A Comparative Study
title Music Emotion Recognition from Lyrics: A Comparative Study
spellingShingle Music Emotion Recognition from Lyrics: A Comparative Study
Malheiro, Ricardo
language processing
lyrics
machine learning
multi-modal fusion
music emotion recognition
natural language processing
machine learning
title_short Music Emotion Recognition from Lyrics: A Comparative Study
title_full Music Emotion Recognition from Lyrics: A Comparative Study
title_fullStr Music Emotion Recognition from Lyrics: A Comparative Study
title_full_unstemmed Music Emotion Recognition from Lyrics: A Comparative Study
title_sort Music Emotion Recognition from Lyrics: A Comparative Study
author Malheiro, Ricardo
author_facet Malheiro, Ricardo
Panda, Renato
Gomes, Paulo J. S.
Paiva, Rui Pedro
author_role author
author2 Panda, Renato
Gomes, Paulo J. S.
Paiva, Rui Pedro
author2_role author
author
author
dc.contributor.author.fl_str_mv Malheiro, Ricardo
Panda, Renato
Gomes, Paulo J. S.
Paiva, Rui Pedro
dc.subject.por.fl_str_mv language processing
lyrics
machine learning
multi-modal fusion
music emotion recognition
natural language processing
machine learning
topic language processing
lyrics
machine learning
multi-modal fusion
music emotion recognition
natural language processing
machine learning
description 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).
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/other
format other
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10316/95165
https://hdl.handle.net/10316/95165
url https://hdl.handle.net/10316/95165
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833602450531024896

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