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Causal indicators for assessing the truthfulness of child speech in forensic interviews
Computer Speech & Language ( IF 4.3 ) Pub Date : 2021-07-19 , DOI: 10.1016/j.csl.2021.101263
Zane Durante 1 , Victor Ardulov 1 , Manoj Kumar 1 , Jennifer Gongola 1 , Thomas Lyon 1 , Shrikanth Narayanan 1
Affiliation  

When interviewing a child who may have witnessed a crime, the interviewer must ask carefully directed questions in order to elicit a truthful statement from the child. The presented work uses Granger causal analysis to examine and represent child–interviewer interaction dynamics over such an interview. Our work demonstrates that Granger Causal analysis of psycholinguistic and acoustic signals from speech yields significant predictors of whether a child is telling the truth, as well as whether a child will disclose witnessing a transgression later in the interview. By incorporating cross-modal Granger causal features extracted from audio and transcripts of forensic interviews, we are able to substantially outperform conventional deception detection methods and a number of simulated baselines. Our results suggest that a child’s use of concreteness and imageability in their language are strong psycholinguistic indicators of truth-telling and that the coordination of child and interviewer speech signals is much more informative than the specific language used throughout the interview.



中文翻译:

评估法医面谈中儿童言语真实性的因果指标

与可能目睹犯罪的儿童面谈时,面谈者必须谨慎地提出有针对性的问题,以便从儿童那里得到如实陈述。所呈现的作品使用 Granger 因果分析来检查和表示儿童与采访者在此类采访中的互动动态。我们的工作表明,对语音中的心理语言学和声学信号进行格兰杰因果分析可以显着预测孩子是否在说真话,以及孩子是否会在面谈后期披露目睹违规行为。通过结合从音频和法医访谈记录中提取的跨模态 Granger 因果特征,我们能够大大优于传统的欺骗检测方法和许多模拟基线。

更新日期:2021-07-22
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