Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/114653
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Panda, Renato | - |
dc.contributor.author | Malheiro, Ricardo | - |
dc.contributor.author | Paiva, Rui Pedro | - |
dc.date.accessioned | 2024-04-04T08:26:26Z | - |
dc.date.available | 2024-04-04T08:26:26Z | - |
dc.date.issued | 2023 | - |
dc.identifier.issn | 1949-3045 | pt |
dc.identifier.issn | 2371-9850 | pt |
dc.identifier.uri | https://hdl.handle.net/10316/114653 | - |
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 article 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. Previous MER surveys offered broad reviews, covering topics such as emotion paradigms, approaches for the collection of ground-truth data, types of MER problems and overviewing different MER systems. On the contrary, our approach is to offer a deep and specific review on one key MER problem: the design of emotionally-relevant audio features. | pt |
dc.language.iso | eng | pt |
dc.publisher | IEEE | pt |
dc.relation | MERGE project financed by Fundação para Ciência e a Tecnologia (FCT) | pt |
dc.rights | openAccess | 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 | 68 | pt |
degois.publication.lastPage | 88 | pt |
degois.publication.issue | 1 | pt |
degois.publication.title | IEEE Transactions on Affective Computing | pt |
dc.peerreviewed | yes | pt |
dc.identifier.doi | 10.1109/TAFFC.2020.3032373 | pt |
degois.publication.volume | 14 | pt |
dc.date.embargo | 2023-01-01 | * |
uc.date.periodoEmbargo | 0 | pt |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.fulltext | Com Texto completo | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
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 | |
---|---|---|---|---|
Audio_Features_for_Music_Emotion_Recognition_A_Survey.pdf | 3.94 MB | Adobe PDF | View/Open |
Page view(s)
54
checked on Jul 3, 2024
Download(s)
30
checked on Jul 3, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.