A Systematic Review on Multimodal Emotion Recognition
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Publication Date: | 2024 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10362/180009 |
Summary: | Publisher Copyright: © 2013 IEEE. |
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A Systematic Review on Multimodal Emotion RecognitionBuilding Blocks, Current State, Applications, and Challengesaffective computingartificial intelligencedeep learningemotion expressionemotion recognitionmachine learningMultimodal emotion recognitionComputer Science(all)Materials Science(all)Engineering(all)Publisher Copyright: © 2013 IEEE.Emotion recognition involves accurately interpreting human emotions from various sources and modalities, including questionnaires, verbal, and physiological signals. With its broad applications in affective computing, computational creativity, human-robot interactions, and market research, the field has seen a surge in interest in recent years. This paper presents a systematic review of multimodal emotion recognition (MER) techniques developed from 2014 to 2024, encompassing verbal, physiological signals, facial, body gesture, and speech as well as emerging methods like sketches emotion recognition. The review explores various emotion models, distinguishing between emotions, feelings, sentiments, and moods, along with human emotional expression, categorized in both artistic and non-verbal ways. It also discusses the background of automated emotion recognition systems and introduces seven criteria for evaluating modalities alongside a current state analysis of MER, drawn from the human-centric perspective of this field. By selecting the PRISMA guidelines and carefully analyzing 45 selected articles, this review provides comprehensive perspectives into existing studies, datasets, technical approaches, identified gaps, and future directions in MER. It also highlights existing challenges and current applications of the MER.DEE - Departamento de Engenharia Electrotécnica e de ComputadoresCTS - Centro de Tecnologia e SistemasUNINOVA-Instituto de Desenvolvimento de Novas TecnologiasRUNKalateh, SepidehEstrada-Jimenez, Luis A.Nikghadam-Hojjati, SanazBarata, Jose2025-02-28T22:19:58Z20242024-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article44application/pdfhttp://hdl.handle.net/10362/180009eng2169-3536PURE: 106889230https://doi.org/10.1109/ACCESS.2024.3430850info: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:RCAAP2025-03-10T01:33:56Zoai:run.unl.pt:10362/180009Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:07:11.167085Repositórios 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 |
A Systematic Review on Multimodal Emotion Recognition Building Blocks, Current State, Applications, and Challenges |
title |
A Systematic Review on Multimodal Emotion Recognition |
spellingShingle |
A Systematic Review on Multimodal Emotion Recognition Kalateh, Sepideh affective computing artificial intelligence deep learning emotion expression emotion recognition machine learning Multimodal emotion recognition Computer Science(all) Materials Science(all) Engineering(all) |
title_short |
A Systematic Review on Multimodal Emotion Recognition |
title_full |
A Systematic Review on Multimodal Emotion Recognition |
title_fullStr |
A Systematic Review on Multimodal Emotion Recognition |
title_full_unstemmed |
A Systematic Review on Multimodal Emotion Recognition |
title_sort |
A Systematic Review on Multimodal Emotion Recognition |
author |
Kalateh, Sepideh |
author_facet |
Kalateh, Sepideh Estrada-Jimenez, Luis A. Nikghadam-Hojjati, Sanaz Barata, Jose |
author_role |
author |
author2 |
Estrada-Jimenez, Luis A. Nikghadam-Hojjati, Sanaz Barata, Jose |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
DEE - Departamento de Engenharia Electrotécnica e de Computadores CTS - Centro de Tecnologia e Sistemas UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias RUN |
dc.contributor.author.fl_str_mv |
Kalateh, Sepideh Estrada-Jimenez, Luis A. Nikghadam-Hojjati, Sanaz Barata, Jose |
dc.subject.por.fl_str_mv |
affective computing artificial intelligence deep learning emotion expression emotion recognition machine learning Multimodal emotion recognition Computer Science(all) Materials Science(all) Engineering(all) |
topic |
affective computing artificial intelligence deep learning emotion expression emotion recognition machine learning Multimodal emotion recognition Computer Science(all) Materials Science(all) Engineering(all) |
description |
Publisher Copyright: © 2013 IEEE. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024 2024-01-01T00:00:00Z 2025-02-28T22:19:58Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/180009 |
url |
http://hdl.handle.net/10362/180009 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2169-3536 PURE: 106889230 https://doi.org/10.1109/ACCESS.2024.3430850 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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44 application/pdf |
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