Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History—Findings From a Machine Learning Analysis of Speech Data

Voice data suggests that mothers with ED history might be emotionally stronger involved throughout child feeding. This indicates that there are differences in communication between women with and without ED history and highlights the importance of research into maternal communication in affected families. ML approaches are promising tools as they can detect more subtle nuances compared to questionnaires.

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Publication Details

Journal
European Eating Disorders Review
Published
2025-10-03
DOI
https://doi.org/10.1002/erv.70038
Primary Topic
Eating Disorders and Behaviors
Type
article
Field-Weighted Citation Impact
0.00
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article

Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History—Findings From a Machine Learning Analysis of Speech Data

Katrin Elisabeth Giel, Andreas Triantafyllopoulos, Jana Katharina Throm, Manuel Milling et al.
European Eating Disorders Review
Eating Disorders and Behaviors
article

Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History—Findings From a Machine Learning Analysis of Speech Data

Katrin Elisabeth Giel, Andreas Triantafyllopoulos, Jana Katharina Throm, Manuel Milling, Annica Franziska Dörsam, Björn W. Schuller, Alexander Kathan, Johanna Löchner
article en

Abstract

Voice data suggests that mothers with ED history might be emotionally stronger involved throughout child feeding. This indicates that there are differences in communication between women with and without ED history and highlights the importance of research into maternal communication in affected families. ML approaches are promising tools as they can detect more subtle nuances compared to questionnaires.

European Eating Disorders ReviewVol. 34(2)
University of Augsburg (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Munich Center for Quantum Science and Technology (DE), Data:Lab Munich (Germany) (DE), German Center for Diabetes Research (DE), Imperial College London (GB), Technical University of Munich (DE)
Openalex Percentile: Top 61%
Eating Disorders and Behaviors
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Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History—Findings From a Machine Learning Analysis of Speech Data — Katrin Elisabeth Giel, Andreas Triantafyllopoulos, et al. · European Eating Disorders Review (2025) | TGRS Research Map | TGRS