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Here, we focused on the prediction of individuals\u2019 attachment style using interactions of recently married (1\u201315 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.<\/jats:p>","DOI":"10.1186\/s13636-023-00291-w","type":"journal-article","created":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T17:02:24Z","timestamp":1685552544000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Automatic detection of attachment style in married couples through conversation analysis"],"prefix":"10.1186","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8867-2263","authenticated-orcid":false,"given":"Tu\u011f\u00e7e Melike","family":"Ko\u00e7ak","sequence":"first","affiliation":[]},{"given":"B\u00fc\u015fra \u00c7ilem","family":"Dibek","sequence":"additional","affiliation":[]},{"given":"Esma Nafiye","family":"Polat","sequence":"additional","affiliation":[]},{"given":"Nil\u00fcfer","family":"Kafes\u00e7io\u011flu","sequence":"additional","affiliation":[]},{"given":"Cenk","family":"Demiro\u011flu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,31]]},"reference":[{"issue":"4","key":"291_CR1","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1111\/j.1939-0025.1982.tb01456.x","volume":"52","author":"J Bowlby","year":"1982","unstructured":"J. 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