Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children
Permanent lenke
https://hdl.handle.net/10037/26861Dato
2022-06-01Type
Journal articleTidsskriftartikkel
Peer reviewed
Forfatter
Salehi, Pegah; Hassan, Syed Zohaib; Lammerse, Myrthe; Shafiee Sabet, Saeed; Riiser, Ingvild; Røed, Ragnhild Klingenberg; Sinkerud Johnson, Miriam; Hicks, Steven; Thambawita, Vajira; Powell, Martine; Lamb, Michael E.; Baugerud, Gunn Astrid; Halvorsen, Pål; Riegler, MichaelSammendrag
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.
Forlag
MDPISitering
Salehi, Hassan, Lammerse, Shafiee Sabet, Riiser, Røed, Sinkerud Johnson, Hicks S, Thambawita, Powell, Lamb, Baugerud, Halvorsen, Riegler M. Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children. Big Data and Cognitive Computing. 2022;6(2)Metadata
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