Publication:
Automatic detection of attachment style in married couples through conversation analysis

dc.contributor.authorKoçak, Tuğçe Melike
dc.contributor.authorDibek, B. Ç.
dc.contributor.authorPolat, Esma Nafiye
dc.contributor.authorKafesçioğlu, Nilüfer
dc.contributor.authorDemiroğlu, Cenk
dc.contributor.departmentElectrical & Electronics Engineering
dc.contributor.departmentPsychology
dc.contributor.ozuauthorKAFESCİOĞLU, Nilüfer
dc.contributor.ozuauthorDEMİROĞLU, Cenk
dc.contributor.ozugradstudentKoçak, Tuğçe Melike
dc.contributor.ozugradstudentPolat, Esma Nafiye
dc.date.accessioned2023-08-11T07:51:35Z
dc.date.available2023-08-11T07:51:35Z
dc.date.issued2023-05-31
dc.description.abstractAnalysis of couple interactions using speech processing techniques is an increasingly active multi-disciplinary field that poses challenges such as automatic relationship quality assessment and behavioral coding. Here, we focused on the prediction of individuals’ attachment style using interactions of recently married (1–15 months) couples. For low-level acoustic feature extraction, in addition to the frame-based acoustic features such as mel-frequency cepstral coefficients (MFCCs) and pitch, we used the turn-based i-vector features that are the commonly used in speaker verification systems. Sentiments, positive and negative, of the dialog turns were also automatically generated from transcribed text and used as features. Feature and score fusion algorithms were used for low-level acoustic features and text features. Even though score and feature fusion algorithms performed similar, predictions with score fusion were more consistent when couples have known each other for a longer period of time.
dc.description.sponsorshipTÜBİTAK
dc.identifier.doi10.1186/s13636-023-00291-w
dc.identifier.issn1687-4714
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85160943068
dc.identifier.urihttp://hdl.handle.net/10679/8628
dc.identifier.urihttps://doi.org/10.1186/s13636-023-00291-w
dc.identifier.volume2023
dc.identifier.wos000998467900001
dc.language.isoeng
dc.publicationstatusPublished
dc.publisherSpringer
dc.relation.ispartofEurasip Journal on Audio, Speech, and Music Processing
dc.relation.projectinfo:eu-repo/grantAgreement/TUBITAK/1001 - Bilimsel ve Teknolojik Araştırma Projelerini Destekleme Programı/113K538
dc.rightsAttribution 4.0 International
dc.rightsopenAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.keywordsAcoustic features
dc.subject.keywordsAttachment style
dc.subject.keywordsCouple interaction
dc.subject.keywordsI-vectors
dc.titleAutomatic detection of attachment style in married couples through conversation analysis
dc.typereview
dspace.entity.typePublication
relation.isOrgUnitOfPublication7b58c5c4-dccc-40a3-aaf2-9b209113b763
relation.isOrgUnitOfPublicationeb613b06-2aad-4fc0-baba-a9a816d9132e
relation.isOrgUnitOfPublication.latestForDiscovery7b58c5c4-dccc-40a3-aaf2-9b209113b763

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