Browsing ODA Open Digital Archive by Author "Salehi, Pegah"

Now showing items 1-7 of 7

    • Enhancing investigative interview training using a child avatar system: a comparative study of interactive environments 

      Zohaib Hassan, Syed; Shafiee Sabet, Saeed; Riegler, Michael Alexander; Baugerud, Gunn Astrid; Ko, Hayley Manalang; Salehi, Pegah; Røed, Ragnhild Klingenberg; Sinkerud Johnson, Miriam; Halvorsen, Pål (Peer reviewed; Journal article, 2023)
      The impact of investigative interviews by police and Child Protective Services (CPS) on abused children can be profound, making effective training vital. Quality in these interviews often falls short and current training ...

    • Enhancing questioning skills through child avatar chatbot training with feedback 

      Røed, Ragnhild Klingenberg; Baugerud, Gunn Astrid; Zohaib Hassan, Syed; Shafiee Sabet, Saeed; Salehi, Pegah; Powell, Martine B.; Riegler, Michael Alexander; Halvorsen, Pål; Sinkerud Johnson, Miriam (Peer reviewed; Journal article, 2023)
      Training child investigative interviewing skills is a specialized task. Those being trained need opportunities to practice their skills in realistic settings and receive immediate feedback. A key step in ensuring the ...

    • Impact of different type of Child Avatar Interactions on user Quality of Experience 

      Hals, Alexander William Ingvarsson (ACIT;2022, Master thesis, 2022)
      Conducting an interview and communicating with children that have experienced traumatic situations can be difficult. Norway’s Child Protective services received in 2017 over 58.580 reports about child maltreatment and ...

    • SinGAN-Seg: Synthetic training data generation for medical image segmentation 

      Thambawita, Vajira L B; Salehi, Pegah; Sheshkal, Sajad Amouei; Hicks, Steven; Hammer, Hugo Lewi; Parasa, Sravanthi; de Lange, Thomas; Halvorsen, Pål; Riegler, Michael (PLOS ONE;17(5): e0267976, Peer reviewed; Journal article, 2022-05-02)
      Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a ...

    • Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children 

      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, Michael (Big Data and Cognitive Computing;Volume 6 / Issue 2, Peer reviewed; Journal article, 2022-06-01)
      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 ...

    • A Theoretical and Empirical Analysis of 2D and 3D Virtual Environments in Training for Child Interview Skills 

      Salehi, Pegah; Hassan, Syed Zohaib; Baugerud, Gunn Astrid; Powell, Martine; Johnson, Miriam S.; Johansen, Dag; Shafiee Sabet, Saeed; Riegler, Michael; Halvorsen, Pål (Peer reviewed; Journal article, 2024)
      This paper presents a detailed study of an AI-driven platform designed for the training of child welfare and law enforcement professionals in conducting investigative interviews with maltreated children. It achieves a ...

    • Using an AI-based avatar for interviewer training at Children’s Advocacy Centers: Proof of Concept 

      Baugerud, Gunn Astrid; Johnson, Miriam S.; Dianiska, Rachel; Røed, Ragnhild Klingenberg; Powell, Martine B.; Lamb, Michael E.; Hassan, Syed Zohaib; Sabet, Saeed; Hicks, Steven Alexander; Salehi, Pegah; Riegler, Michael Alexander; Halvorsen, Pål; Quas, Jodi (Peer reviewed; Journal article, 2024)
      This proof-of- concept study focused on interviewers’ behaviors and perceptions when interacting with a dynamic AI child avatar alleging abuse. Professionals (N = 68) took part in a virtual reality (VR) study in which they ...