Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1445
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAkcay, Mehmet Berkehan-
dc.contributor.authorOguz, Kaya-
dc.date.accessioned2023-06-16T14:11:39Z-
dc.date.available2023-06-16T14:11:39Z-
dc.date.issued2020-
dc.identifier.issn0167-6393-
dc.identifier.issn1872-7182-
dc.identifier.urihttps://doi.org/10.1016/j.specom.2019.12.001-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/1445-
dc.description.abstractSpeech is the most natural way of expressing ourselves as humans. It is only natural then to extend this communication medium to computer applications. We define speech emotion recognition (SER) systems as a collection of methodologies that process and classify speech signals to detect the embedded emotions. SER is not a new field, it has been around for over two decades, and has regained attention thanks to the recent advancements. These novel studies make use of the advances in all fields of computing and technology, making it necessary to have an update on the current methodologies and techniques that make SER possible. We have identified and discussed distinct areas of SER, provided a detailed survey of current literature of each, and also listed the current challenges.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofSpeech Communıcatıonen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSpeech emotion recognitionen_US
dc.subjectSurveyen_US
dc.subjectSpeech featuresen_US
dc.subjectClassificationen_US
dc.subjectSpeech databasesen_US
dc.subjectVoice Qualityen_US
dc.subjectCommunicating Emotionen_US
dc.subjectSpectral Featuresen_US
dc.subjectNeural-Networksen_US
dc.subjectClassificationen_US
dc.subjectValenceen_US
dc.subjectExpressionen_US
dc.subjectArousalen_US
dc.subjectAdversarialen_US
dc.subjectAudioen_US
dc.titleSpeech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiersen_US
dc.typeReview Articleen_US
dc.identifier.doi10.1016/j.specom.2019.12.001-
dc.identifier.scopus2-s2.0-85076679231en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authoridOguz, Kaya/0000-0002-1860-9127-
dc.authoridAKCAY, Mehmet Berkehan/0000-0001-9039-5453-
dc.authorwosidOguz, Kaya/A-1812-2016-
dc.authorscopusid57196440541-
dc.authorscopusid54902980200-
dc.identifier.volume116en_US
dc.identifier.startpage56en_US
dc.identifier.endpage76en_US
dc.identifier.wosWOS:000525305700005en_US
dc.relation.publicationcategoryDiğeren_US
dc.identifier.scopusqualityQ2-
dc.identifier.wosqualityQ2-
item.grantfulltextreserved-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeReview Article-
item.fulltextWith Fulltext-
item.languageiso639-1en-
crisitem.author.dept05.05. Computer Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Files in This Item:
File SizeFormat 
492.pdf
  Restricted Access
1.16 MBAdobe PDFView/Open    Request a copy
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

486
checked on Sep 25, 2024

WEB OF SCIENCETM
Citations

303
checked on Sep 25, 2024

Page view(s)

118
checked on Sep 30, 2024

Download(s)

6
checked on Sep 30, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.