Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/95975
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Panda, Renato | - |
dc.contributor.author | Malheiro, Ricardo | - |
dc.contributor.author | Paiva, Rui Pedro | - |
dc.date.accessioned | 2021-10-25T11:50:28Z | - |
dc.date.available | 2021-10-25T11:50:28Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 1949-3045 | pt |
dc.identifier.issn | 2371-9850 | pt |
dc.identifier.uri | https://hdl.handle.net/10316/95975 | - |
dc.description.abstract | The design of meaningful audio features is a key need to advance the state-of-the-art in Music Emotion Recognition (MER). This work presents a survey on the existing emotionally-relevant computational audio features, supported by the music psychology literature on the relations between eight musical dimensions (melody, harmony, rhythm, dynamics, tone color, expressivity, texture and form) and specific emotions. Based on this review, current gaps and needs are identified and strategies for future research on feature engineering for MER are proposed, namely ideas for computational audio features that capture elements of musical form, texture and expressivity that should be further researched. Finally, although the focus of this article is on classical feature engineering methodologies (based on handcrafted features), perspectives on deep learning-based approaches are discussed. | pt |
dc.description.sponsorship | This work was supported by the MERGE project (PTDC/CCI-COM/3171/2021) financed by Fundação para Ciência e a Tecnologia (FCT) - Portugal. | pt |
dc.language.iso | eng | pt |
dc.publisher | IEEE | pt |
dc.rights | openAccess | pt |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt |
dc.subject | affective computing | pt |
dc.subject | music emotion recognition | pt |
dc.subject | audio feature design | pt |
dc.subject | music information retrieval | pt |
dc.title | Audio Features for Music Emotion Recognition: a Survey | pt |
dc.type | article | - |
degois.publication.firstPage | 1 | pt |
degois.publication.lastPage | 1 | pt |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9229494 | pt |
dc.peerreviewed | yes | pt |
dc.identifier.doi | 10.1109/TAFFC.2020.3032373 | pt |
dc.date.embargo | 2020-01-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.grantfulltext | open | - |
item.fulltext | Com Texto completo | - |
item.openairetype | article | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
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 | 0000-0003-2539-5590 | - |
crisitem.author.orcid | 0000-0002-3010-2732 | - |
crisitem.author.orcid | 0000-0003-3215-3960 | - |
Appears in Collections: | FCTUC Eng.Informática - Artigos em Revistas Internacionais I&D CISUC - Artigos em Revistas Internacionais |
Files in This Item:
File | Description | Size | Format | |
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Panda, Malheiro, Paiva - 2020 - Audio Features for Music Emotion Recognition a Survey.pdf | early access version | 629.77 kB | Adobe PDF | View/Open |
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