Emotion, age, and gender classification in children's speech by humans and machines

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dc.authorid0000-0002-6073-0393
dc.authorid0000-0001-6342-428X
dc.authorid0000-0003-3424-652X
dc.authorid0000-0001-6342-428X
dc.authorid0000-0002-1565-6921
dc.authorid0000-0001-7947-5508
dc.authorscopusid36241785000
dc.authorscopusid7006556254
dc.authorscopusid57219469958
dc.authorscopusid8521676200
dc.authorscopusid55873665200
dc.authorscopusid24468656100
dc.authorwosidLyakso, Elena/H-9904-2013
dc.authorwosidSalah, Albert Ali/ABH-5561-2020
dc.authorwosidSalah, Albert Ali/E-5820-2013
dc.authorwosidKarpov, Alexey A/A-8905-2012
dc.authorwosidGrigorev, Aleksey/Q-4953-2018
dc.contributor.authorKaya, Heysem
dc.contributor.authorSalah, Albert Ali
dc.contributor.authorKarpov, Alexey A.
dc.contributor.authorFrolova, Olga
dc.contributor.authorGrigorev, Aleksey
dc.contributor.authorLyakso, Elena
dc.date.accessioned2022-05-11T14:15:50Z
dc.date.available2022-05-11T14:15:50Z
dc.date.issued2017
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractIn this article, we present the first child emotional speech corpus in Russian, called EmoChildRu, collected from 3 to 7 years old children. The base corpus includes over 20 K recordings (approx. 30 h), collected from 120 children. Audio recordings are carried out in three controlled settings by creating different emotional states for children: playing with a standard set of toys; repetition of words from a toy-parrot in a game store setting; watching a cartoon and retelling of the story, respectively. This corpus is designed to study the reflection of the emotional state in the characteristics of voice and speech and for studies of the formation of emotional states in ontogenesis. A portion of the corpus is annotated for three emotional states (comfort, discomfort, neutral). Additional data include the results of the adult listeners' analysis of child speech, questionnaires, as well as annotation for gender and age in months. We also provide several baselines, comparing human and machine estimation on this corpus for prediction of age, gender and comfort state. While in age estimation, the acoustics-based automatic systems show higher performance, they do not reach human perception levels in comfort state and gender classification. The comparative results indicate the importance and necessity of developing further linguistic models for discrimination. (C) 2017 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipRussian Foundation for Basic ResearchRussian Foundation for Basic Research (RFBR) [10-00-000.24, 15-06-07852, 16-37-60100]; Russian Foundation for Basic Research DHSS [17-06-00503]; Government of Russia [074-U01]; Bogazici UniversityBogazici University [BAP 16A01P4]; BAGEP Award of the Science Academy; [MD-254.2017.8]
dc.description.sponsorshipThe work was supported by the Russian Foundation for Basic Research (grant nos. 10-00-000.24, 15-06-07852, and 16-37-60100), Russian Foundation for Basic Research DHSS (grant No 17-06-00503), by the grant of the President of Russia (project No MD-254.2017.8), by the Government of Russia (grant No 074-U01), by Bogazici University (project BAP 16A01P4) and by the BAGEP Award of the Science Academy.
dc.identifier.doi10.1016/j.csl.2017.06.002
dc.identifier.endpage283
dc.identifier.issn0885-2308
dc.identifier.issn1095-8363
dc.identifier.scopus2-s2.0-85021761471
dc.identifier.scopusqualityQ2
dc.identifier.startpage268
dc.identifier.urihttps://doi.org/10.1016/j.csl.2017.06.002
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6092
dc.identifier.volume46
dc.identifier.wosWOS:000407609600016
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorKaya, Heysem
dc.language.isoen
dc.publisherAcademic Press Ltd- Elsevier Science Ltd
dc.relation.ispartofComputer Speech and Language
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectEmotional child speech
dc.subjectPerception experiments
dc.subjectSpectrographic analysis
dc.subjectEmotional states
dc.subjectAge recognition
dc.subjectGender recognition
dc.subjectComputational paralinguistics
dc.subjectRecognition
dc.titleEmotion, age, and gender classification in children's speech by humans and machines
dc.typeArticle

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