Automatic detection of attachment style in married couples through conversation analysis

Name: Automatic detection of attachment style in married couples through conversation analysis
Author: Koçak, Tuğçe Melike, Dibek, B. Ç., Polat, Esma Nafiye, Kafesçioğlu, Nilüfer, Demiroğlu, Cenk

İsim	Automatic detection of attachment style in married couples through conversation analysis
Yazar	Koçak, Tuğçe Melike, Dibek, B. Ç., Polat, Esma Nafiye, Kafesçioğlu, Nilüfer, Demiroğlu, Cenk
Basım Tarihi:	2023-05-31
Basım Yeri	- Springer
Konu	Acoustic features, Attachment style, Couple interaction, I-vectors
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1687-4714
Kayıt Numarası	29f34fe1-92bb-4b68-9edf-29bd5c19ed5c
Lokasyon	Electrical & Electronics Engineering, Psychology
Tarih	2023-05-31
Notlar	TÜBİTAK
Örnek Metin	Analysis 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.
DOI	10.1186/s13636-023-00291-w
Cilt	2023

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Automatic detection of attachment style in married couples through conversation analysis

Yazar Koçak, Tuğçe Melike, Dibek, B. Ç., Polat, Esma Nafiye, Kafesçioğlu, Nilüfer, Demiroğlu, Cenk

Basım Tarihi 2023-05-31

Basım Yeri - Springer

Konu Acoustic features, Attachment style, Couple interaction, I-vectors

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1687-4714

Kayıt Numarası 29f34fe1-92bb-4b68-9edf-29bd5c19ed5c

Lokasyon Electrical & Electronics Engineering, Psychology

Tarih 2023-05-31

Notlar TÜBİTAK

Örnek Metin Analysis 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.

DOI 10.1186/s13636-023-00291-w

Cilt 2023