Vocal Biomarkers of Childhood Trauma: A Machine-Learning Approach to Speech Analysis

Key Points

• This research aims to explore the potential of vocal biomarkers for identifying childhood trauma.
• Analyzed vocal data from Arabic-speaking children
• Employed a logistic regression model for classification
• Assessed the model's performance in distinguishing trauma exposure
• The model reliably distinguished trauma exposure in children
• Demonstrated strong accuracy and potential for real-world applications
• Highlighted the need for further validation in other contexts