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Predicting Depression and Emotions in the Cross-Roads of Cultures, Para-Linguistics, and Non-Linguistics

dc.authorscopusid 36241785000
dc.authorscopusid 57195680712
dc.authorscopusid 57209850146
dc.authorscopusid 57195218979
dc.authorscopusid 57209202409
dc.authorscopusid 57210791723
dc.authorscopusid 57219469958
dc.contributor.author Kaya, Hüsamettin
dc.contributor.author Fedotov, D.
dc.contributor.author Dresvyanskiy, D.
dc.contributor.author Doyran, M.
dc.contributor.author Mamontov, D.
dc.contributor.author Markitantov, M.
dc.contributor.author Salah, A.A.
dc.contributor.other Department of Basic Islamic Sciences / Temel İslam Bilimleri Bölümü
dc.date.accessioned 2025-02-15T19:38:16Z
dc.date.available 2025-02-15T19:38:16Z
dc.date.issued 2019
dc.department Artuklu University en_US
dc.department-temp Kaya H., Namik Kemal University, Çorlu, Turkey; Fedotov D., Ulm University, Ulm, Germany, Sehir University, Istanbul, Turkey; Dresvyanskiy D., Ulm University, Ulm, Germany; Doyran M., Utrecht University, Utrecht, Netherlands; Mamontov D., Ulm University, Ulm, Germany; Markitantov M., SPIIRAS, St. Petersburg, Russian Federation; Salah A.A.A., Utrecht University, Utrecht, Netherlands, Sehir University, Istanbul, Turkey; Kavcar E., Mardin Artuklu University, Mardin, Turkey, ITMO University, St. Petersburg, Russian Federation; Karpov A., SPIIRAS, St. Petersburg, Russian Federation; Salah A.A., Utrecht University, Utrecht, Netherlands, Boǧaziçi University, Istanbul, Turkey en_US
dc.description ACM SIGMM en_US
dc.description.abstract Cross-language, cross-cultural emotion recognition and accurate prediction of affective disorders are two of the major challenges in affective computing today. In this work, we compare several systems for Detecting Depression with AI Sub-challenge (DDS) and Cross-cultural Emotion Sub-challenge (CES) that are published as part of the Audio-Visual Emotion Challenge (AVEC) 2019. For both sub-challenges, we benefit from the baselines, while introducing our own features and regression models. For the DDS challenge, where ASR transcripts are provided by the organizers, we propose simple linguistic and word-duration features. These ASR transcriptbased features are shown to outperform the state of the art audio visual features for this task, reaching a test set Concordance Correlation Coefficient (CCC) performance of 0.344 in comparison to a challenge baseline of 0.120. Our results show that non-verbal parts of the signal are important for detection of depression, and combining this with linguistic information produces the best results. For CES, the proposed systems using unsupervised feature adaptation outperform the challenge baselines on emotional primitives, reaching test set CCC performances of 0.466 and 0.499 for arousal and valence, respectively. © 2019 Association for Computing Machinery. en_US
dc.description.sponsorship Russian Science Foundation, RSF, (18-11-00145) en_US
dc.identifier.citationcount 34
dc.identifier.doi 10.1145/3347320.3357691
dc.identifier.endpage 35 en_US
dc.identifier.isbn 9781450369138
dc.identifier.scopus 2-s2.0-85074945276
dc.identifier.scopusquality N/A
dc.identifier.startpage 27 en_US
dc.identifier.uri https://doi.org/10.1145/3347320.3357691
dc.identifier.uri https://hdl.handle.net/20.500.12514/6217
dc.identifier.wosquality N/A
dc.language.iso en en_US
dc.publisher Association for Computing Machinery, Inc en_US
dc.relation.ispartof AVEC 2019 - Proceedings of the 9th International Audio/Visual Emotion Challenge and Workshop, co-located with MM 2019 -- 9th International Audio/Visual Emotion Challenge and Workshop, AVEC 2019, held in conjunction with the ACM Multimedia 2019 -- 21 October 2019 -- Nice -- 153196 en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 36
dc.subject Affective Computing en_US
dc.subject Cross-Cultural Emotion Recognition en_US
dc.subject Depression Severity Prediction en_US
dc.subject Ptsd en_US
dc.title Predicting Depression and Emotions in the Cross-Roads of Cultures, Para-Linguistics, and Non-Linguistics en_US
dc.type Conference Object en_US
dspace.entity.type Publication
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