Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/95163
DC Field | Value | Language |
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dc.contributor.author | Malheiro, Ricardo | - |
dc.contributor.author | Panda, Renato | - |
dc.contributor.author | Gomes, Paulo J. S. | - |
dc.contributor.author | Paiva, Rui Pedro | - |
dc.date.accessioned | 2021-07-04T17:35:44Z | - |
dc.date.available | 2021-07-04T17:35:44Z | - |
dc.date.issued | 2016 | - |
dc.identifier.isbn | 978-989-758-203-5 | - |
dc.identifier.issn | 2184-3228 | - |
dc.identifier.uri | https://hdl.handle.net/10316/95163 | - |
dc.description.abstract | This research addresses the role of lyrics in the music emotion recognition process. Our approach is based on several state of the art features complemented by novel stylistic, structural and semantic features. To evaluate our approach, we created a ground truth dataset containing 180 song lyrics, according to Russell's emotion model. We conduct four types of experiments: regression and classification by quadrant, arousal and valence categories. Comparing to the state of the art features (ngrams-baseline), adding other features, including novel features, improved the F-measure from 68.2%, 79.6% and 84.2% to 77.1%, 86.3% and 89.2%, respectively for the three classification experiments. To study the relation between features and emotions (quadrants) we performed experiments to identify the best features that allow to describe and discriminate between arousal hemispheres and valence meridians. To further validate these experiments, we built a validation set comprising 771 lyrics extracted from the AllMusic platform, having achieved 73.6% Fmeasure in the classification by quadrants. Regarding regression, results show that, comparing to similar studies for audio, we achieve a similar performance for arousal and a much better performance for valence. | pt |
dc.description.sponsorship | This work was supported by CISUC (Center for Informatics and Systems of the University of Coimbra). | pt |
dc.language.iso | eng | pt |
dc.publisher | SciTePress | pt |
dc.rights | openAccess | pt |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt |
dc.subject | lyrics feature extraction | pt |
dc.subject | lyrics music classification | pt |
dc.subject | lyrics music emotion recognition | pt |
dc.subject | lyrics music regression | pt |
dc.subject | music information eetrieval | pt |
dc.title | Classification and Regression of Music Lyrics: Emotionally-Significant Features | pt |
dc.type | conferenceObject | pt |
degois.publication.location | Porto, Portugal | pt |
degois.publication.title | 8th International Conference on Knowledge Discovery and Information Retrieval – KDIR 2016 | pt |
dc.relation.publisherversion | https://www.scitepress.org/Link.aspx?doi=10.5220/0006037400450055 | pt |
dc.peerreviewed | yes | pt |
dc.identifier.doi | 10.5220/0006037400450055 | - |
dc.date.embargo | 2016-01-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.openairetype | conferenceObject | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.fulltext | Com Texto completo | - |
crisitem.author.dept | Faculty of Sciences and Technology | - |
crisitem.author.dept | Faculty of Sciences and Technology | - |
crisitem.author.parentdept | University of Coimbra | - |
crisitem.author.parentdept | University of Coimbra | - |
crisitem.author.researchunit | CISUC - Centre for Informatics and Systems of the University of Coimbra | - |
crisitem.author.researchunit | CISUC - Centre for Informatics and Systems of the University of Coimbra | - |
crisitem.author.researchunit | CISUC - Centre for Informatics and Systems of the University of Coimbra | - |
crisitem.author.parentresearchunit | Faculty of Sciences and Technology | - |
crisitem.author.parentresearchunit | Faculty of Sciences and Technology | - |
crisitem.author.parentresearchunit | Faculty of Sciences and Technology | - |
crisitem.author.orcid | 0000-0002-3010-2732 | - |
crisitem.author.orcid | 0000-0003-2539-5590 | - |
crisitem.author.orcid | 0000-0003-3215-3960 | - |
Appears in Collections: | I&D CISUC - Artigos em Livros de Actas |
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File | Description | Size | Format | |
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Malheiro et al. - 2016 - Classification and Regression of Music Lyrics Emotionally-Significant Features.pdf | 365.06 kB | Adobe PDF | View/Open |
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