High-quality interviews that follow best-practice guidelines are the best means available to frontline child protective service (CPS) workers and specially trained police officers to investigate and detect abuse and maltreatment. In Norway, the CPS and police are trained in the same interview method. In the current quantitative study, we investigate sixty-five interviews conducted by the CPS of children ages 4–8 years and seventy-two interviews conducted by the police of children ages 3–6 years. Our analysis shows that the CPS workers presented more open-ended invitations and fewer suggestive questions than the police officers. However, the CPS also asked more option-posing questions. Still, this finding may indicate that CPS workers come closer than police officers to follow best practice guidelines when they conduct child interviews. It should be noted that the police are also trained in an extended interview method, unlike the CPS workers. The number of open-ended invitations was sparse in both samples. Differences in the span of children’s ages in the two samples and different legal frameworks may have affected the findings. Implications for interview training are discussed.

When responding to allegations of child sexual, physical, and psychological abuse, Child Protection Service (CPS) workers and police personnel need to elicit detailed and accurate accounts of the abuse to assist in decision-making and prosecution. Current research emphasizes the importance of the interviewer’s ability to follow empirically based guidelines. In doing so, it is essential to implement economical and scientific training courses for interviewers. Due to recent advances in artificial intelligence, we propose to generate a realistic and interactive child avatar, aiming to mimic a child. Our ongoing research involves the integration and interaction of different components with each other, including how to handle the language, auditory, emotional, and visual components of the avatar. This paper presents three subjective studies that investigate and compare various state-of-the-art methods for implementing multiple aspects of the child avatar. The first user study evaluates the whole system and shows that the system is well received by the expert and highlights the importance of its realism. The second user study investigates the emotional component and how it can be integrated with video and audio, and the third user study investigates realism in the auditory and visual components of the avatar created by different methods. The insights and feedback from these studies have contributed to the refined and improved architecture of the child avatar system which we present here.

In this article, we present our ongoing work in the field of training police officers who conduct interviews with abused children. The objectives in this context are to protect vulnerable children from abuse, facilitate prosecution of offenders, and ensure that innocent adults are not accused of criminal acts. There is therefore a need for more data that can be used for improved interviewer training to equip police with the skills to conduct high-quality interviews. To support this important task, we propose to research a training program that utilizes different system components and multimodal data from the field of artificial intelligence such as chatbots, generation of visual content, text-to-speech, and speech-to-text. This program will be able to generate an almost unlimited amount of interview and also training data. The goal of combining all these different technologies and datatypes is to create an immersive and interactive child avatar that responds in a realistic way, to help to support the training of police interviewers, but can also produce synthetic data of interview situations that can be used to solve different problems in the same domain.

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