Utilize este identificador para referenciar este registo:
https://hdl.handle.net/10316/95162
Campo DC | Valor | Idioma |
---|---|---|
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 | 2021-07-04T17:25:17Z | - |
dc.date.available | 2021-07-04T17:25:17Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | https://hdl.handle.net/10316/95162 | - |
dc.description.abstract | This research addresses the role of audio and lyrics in the music emo- tion recognition. Each dimension (e.g., audio) was separately studied, as well as in a context of bimodal analysis. We perform classification by quadrant catego- ries (4 classes). Our approach is based on several audio and lyrics state-of-the-art features, as well as novel lyric features. To evaluate our approach we create a ground-truth dataset. The main conclusions show that unlike most of the similar works, lyrics performed better than audio. This suggests the importance of the new proposed lyric features and that bimodal analysis is always better than each dimension. | 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.rights | openAccess | pt |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt |
dc.subject | bimodal analysis | pt |
dc.subject | music emotion recognition | pt |
dc.title | Bi-Modal Music Emotion Recognition: Novel Lyrical Features and Dataset | pt |
dc.type | conferenceObject | pt |
degois.publication.location | Riva del Garda, Italy | pt |
degois.publication.title | 9th International Workshop on Music and Machine Learning – MML 2016 – in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECML/PKDD 2016 | pt |
dc.peerreviewed | yes | pt |
dc.date.embargo | 2016-01-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.openairetype | conferenceObject | - |
item.languageiso639-1 | en | - |
item.fulltext | Com Texto completo | - |
item.cerifentitytype | Publications | - |
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 | - |
Aparece nas coleções: | I&D CISUC - Artigos em Livros de Actas |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
Malheiro et al. - 2016 - Bi-Modal Music Emotion Recognition: Novel Lyrical Features and Dataset.pdf | 50.61 kB | Adobe PDF | Ver/Abrir |
Visualizações de página
248
Visto em 27/ago/2024
Downloads
112
Visto em 27/ago/2024
Google ScholarTM
Verificar
Este registo está protegido por Licença Creative Commons