@article {42995,
	title = {Live Streaming Technology and Online Child Sexual Exploitation and Abuse - A Scoping Review},
	journal = {Trauma, Violence, \& Abuse},
	year = {2023},
	publisher = { SAGE Publications},
	abstract = {Livestreaming of child sexual abuse is an established form of online child sexual exploitationand abuse. However, only a limited body of research has examined this issue. The Covid-19pandemic has accelerated internet use and user knowledge of livestreaming servicesemphasising the importance of understanding this crime. In this scoping review, existingliterature was brought together through an iterative search of eight databases containing peer-reviewed journal articles, as well as grey literature. Records were eligible for inclusion if theprimary focus was on livestream technology and online child sexual exploitation and abuse,the child being defined as eighteen years or younger. Fourteen of the 2,218 records wereselected. The data were charted and divided into four categories: victims, offenders,legislation, and technology. Limited research, differences in terminology, study design, andpopulation inclusion criteria present a challenge to drawing general conclusions on thecurrent state of livestreaming of child sexual abuse. The records show that victims arepredominantly female. The average livestream offender was found to be older than theaverage online child sexual abuse offender. Therefore, it is unclear whether the findings arerepresentative of the global population of livestream offenders. Furthermore, there appears tobe a gap in what the records show on platforms and payment services used and current digitaltrends. The lack of a legal definition and privacy considerations pose a challenge toinvestigation, detection, and prosecution. The available data allow some insights into apotentially much larger issue.},
	author = {Catharina Sofie Rode {Drejer} and Riegler, Michael and Miriam Sinkerud {Johnson} and Halvorsen, P{\r a}l and Gunn Astrid {Baugerud}}
}
@inproceedings {43064,
	title = {A Comparative Study of Interactive Environments for Investigative Interview of A Virtual Child Avatar},
	journal = {IEEE international symposium on multimedia (ISM)},
	year = {2022},
	pages = {194-201},
	publisher = {IEEE},
	doi = {10.1109/ISM55400.2022.00043},
	author = {Syed Zohaib {Hassan} and Saeed Shafiee {Sabet} and Salehi, Pegah and Ko, Hayley and Riiser, Ingvild and Miriam Sinkerud {Johnson} and Gunn Astrid {Baugerud} and Riegler, Michael and Halvorsen, P{\r a}l}
}
@article {42991,
	title = {Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children},
	journal = {Big Data and Cognitive Computing},
	volume = {6},
	year = {2022},
	month = {Jan-06-2022},
	pages = {62},
	publisher = {MDPI},
	doi = {10.3390/bdcc6020062},
	url = {https://www.mdpi.com/2504-2289/6/2/62https://www.mdpi.com/2504-2289/6/2/62/pdf},
	author = {Salehi, Pegah and Syed Zohaib {Hassan} and Lammerse, Myrthe and Saeed Shafiee {Sabet} and Riiser, Ingvild and Ragnhild Klingenber {R{\o}ed} and Miriam S. {Johnson} and Thambawita, Vajira and Hicks, Steven and Powell, Martine and Michael E. {Lamb} and Gunn Astrid {Baugerud} and Halvorsen, P{\r a}l and Riegler, Michael}
}
@inproceedings {42595,
	title = {Towards an AI-driven talking avatar in virtual reality for investigative interviews of children},
	journal = {GameSys {\textquoteright}22: Proceedings of the 2nd Workshop on Games Systems},
	year = {2022},
	pages = {9-15},
	publisher = {ACM},
	address = {New York, NY, USA},
	isbn = {9781450393812},
	doi = {10.1145/353408510.1145/3534085.3534340},
	url = {https://dl.acm.org/doi/10.1145/3534085.3534340},
	author = {Syed Zohaib {Hassan} and Salehi, Pegah and Ragnhild Klingenber {R{\o}ed} and Halvorsen, P{\r a}l and Gunn Astrid {Baugerud} and Miriam Sinkerud {Johnson} and Lison, Pierre and Riegler, Michael and Michael E. {Lamb} and Griwodz, Carsten and Saeed Shafiee {Sabet}},
	editor = {Claypool, Mark and Eg, Ragnhild}
}
@inproceedings {28008,
	title = {Multimodal Virtual Avatars for Investigative Interviews with Children},
	journal = {Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR {\textquoteright}21)},
	year = {2021},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {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.},
	isbn = {9781450385299},
	doi = {10.1145/346394410.1145/3463944.3469269},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3463944},
	author = {Gunn Astrid {Baugerud} and Miriam S. {Johnson} and Ragnhild Klingenber {R{\o}ed} and Michael E. {Lamb} and Powell, Martine and Thambawita, Vajira and Hicks, Steven and Salehi, Pegah and Syed Zohaib {Hassan} and Halvorsen, P{\r a}l and Riegler, Michael},
	editor = {Dao, Minh-Son and Dang-Nguyen, Duc-Tien and Riegler, Michael}
}
