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AI-assisted vocal emotion analysis in forensic interview with children: an exploratory study.

Yoonseo Lee¹, Seho Maeng¹, Yujin Kim¹

¹Dongduk Women's University, Seoul, Republic of Korea.

Frontiers in Psychology

|June 22, 2026

Summary

Artificial intelligence (AI) can analyze children's vocal biomarkers during forensic interviews to assess emotions. AI-assisted interviews showed higher anger indicators but did not increase overall child distress.

Keywords:

AI-assisted interview tool artificial intelligence child forensic interview emotion recognition forensic interviewing vocal emotion analysis

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Area of Science:

Forensic Psychology
Artificial Intelligence
Child Development

Background:

Remote forensic interviews may limit nonverbal cues, impacting children's affective assessment.
Artificial intelligence (AI) offers potential for analyzing vocal emotional biomarkers.
Evaluating AI's role in assessing children's emotions during interviews is crucial.

Purpose of the Study:

To determine if AI can identify children's emotional states via vocal biomarkers in forensic interviews.
To compare AI-derived affective indices between AI-assisted and traditional interview settings.
To assess the impact of AI-assisted interviews on children's emotional states.

Main Methods:

Fifty-nine children (4-8 years) participated in simulated forensic interviews.
AI analyzed vocal acoustic features from 2,084 recorded utterances post hoc.
Speech emotion models estimated probabilities for happiness, anger, sadness, and neutral emotions.

Main Results:

Anger probabilities and anger-to-sadness ratios were significantly higher in the AI-assisted condition.
No significant increase in overall distress was observed in the AI-assisted group.
Dominant happiness levels did not significantly differ between interview conditions.

Conclusions:

AI-based vocal affect analysis can supplement observational tools in forensic interviews.
AI-assisted interview conditions appear emotionally valid for children.
AI offers a structured method for monitoring affective changes, especially when visual cues are limited.