Evidence map›Paper›PMID 42325339›Full record

ArticleFrontiers in psychology2026

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

Yoonseo Lee, Seho Maeng, Yujin Kim, Mirae Hong, Seohyun Kang, Jinyoung Park, Haeun Chu, Jooyoung Lee

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yoonseo LeeDongduk Women's University, Seoul, Republic of Korea.
Seho MaengDongduk Women's University, Seoul, Republic of Korea.
Yujin KimDongduk Women's University, Seoul, Republic of Korea.
Mirae HongDongduk Women's University, Seoul, Republic of Korea.
Seohyun KangDongduk Women's University, Seoul, Republic of Korea.
Jinyoung ParkDongduk Women's University, Seoul, Republic of Korea.
Haeun ChuDongduk Women's University, Seoul, Republic of Korea.
Jooyoung LeeDongduk Women's University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remote forensic interviews may restrict access to children's nonverbal cues, potentially constraining affective assessment. This exploratory study examined whether children's emotional states during forensic interviews could be identified using an artificial intelligence (AI)-assisted system that analyzes vocal emotional biomarkers, and whether AI-derived affective indices differ between an AI-assisted interview condition featuring real-time monitoring of children's emotion and a traditional face-to-face interview condition. Fifty-nine children aged 4-8 years participated in simulated forensic interviews, yielding 2,084 utterances. Acoustic features were analyzed

Indexed as

AI-assisted interview toolartificial intelligencechild forensic interviewemotion recognitionforensic interviewingvocal emotion analysis

Identifiers

PMID42325339
PMCPMC13278917

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.