Publications
Proceedings, refereed
A Comparative Study of Interactive Environments for Investigative Interview of A Virtual Child Avatar
In IEEE international symposium on multimedia (ISM). IEEE, 2022.Status: Published
A Comparative Study of Interactive Environments for Investigative Interview of A Virtual Child Avatar
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | IEEE international symposium on multimedia (ISM) |
Pagination | 194-201 |
Publisher | IEEE |
DOI | 10.1109/ISM55400.2022.00043 |
Comparison of Crowdsourced and Remote Subjective User Studies: A Case Study of Investigative Child Interviews
In The 14th International Conference on Quality of Multimedia Experience. IEEE, 2022.Status: Published
Comparison of Crowdsourced and Remote Subjective User Studies: A Case Study of Investigative Child Interviews
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | The 14th International Conference on Quality of Multimedia Experience |
Publisher | IEEE |
URL | https://ieeexplore.ieee.org/document/9900900 |
DOI | 10.1109/QoMEX55416.2022.9900900 |
Human vs. GPT-3: The challenges of extracting emotions from child responses
In The 14th International Conference on Quality of Multimedia Experience. IEEE, 2022.Status: Published
Human vs. GPT-3: The challenges of extracting emotions from child responses
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | The 14th International Conference on Quality of Multimedia Experience |
Publisher | IEEE |
ISBN Number | 978-1-6654-8794-8 |
ISSN Number | 2472-7814 |
Accession Number | 22114185 |
URL | https://ieeexplore.ieee.org/document/9900885 |
DOI | 10.1109/QoMEX55416.2022.9900885 |
Investigative Interviews using a Multimodal Virtual Avatar
In American Psychology-Law Society Conference 2022. Denver USA,: American Psychology-Law Society, 2022.Status: Accepted
Investigative Interviews using a Multimodal Virtual Avatar
To meet best-practice standards, we are developing an interactive virtual avatar aiming as a training tool to raise interviewing skills of child-welfare and law-enforcement professionals. Therefore, we present the “Ilma” avatar that recognizes interviewers’ behavior during open-ended, closed and leading questions, and which can automatically respond to the conversation. We conducted a user study in which master students (N=3) and child protective workers (N=8) interviewed “Ilma” and rated their perception of the interaction. The results show that the participants valued the interaction and found the avatar useful. Thus, it has great potential to be an effective training tool.
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | American Psychology-Law Society Conference 2022 |
Publisher | American Psychology-Law Society |
Place Published | Denver USA, |
Is More Realistic Better? A Comparison of Game Engine and GAN-based Avatars for Investigative Interviews of Children
In ICDAR '22: Proceedings of the 3rd ACM Workshop on Intelligent Cross-Data Analysis and Retrieval. New York, NY, USA: ACM, 2022.Status: Published
Is More Realistic Better? A Comparison of Game Engine and GAN-based Avatars for Investigative Interviews of Children
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | ICDAR '22: Proceedings of the 3rd ACM Workshop on Intelligent Cross-Data Analysis and Retrieval |
Pagination | 41-49 |
Publisher | ACM |
Place Published | New York, NY, USA |
ISBN Number | 9781450392419 |
URL | https://dl.acm.org/doi/proceedings/10.1145/3512731 |
DOI | 10.1145/351273110.1145/3512731.3534209 |
Towards an AI-driven talking avatar in virtual reality for investigative interviews of children
In GameSys '22: Proceedings of the 2nd Workshop on Games Systems. New York, NY, USA: ACM, 2022.Status: Published
Towards an AI-driven talking avatar in virtual reality for investigative interviews of children
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | GameSys '22: Proceedings of the 2nd Workshop on Games Systems |
Pagination | 9-15 |
Publisher | ACM |
Place Published | New York, NY, USA |
ISBN Number | 9781450393812 |
URL | https://dl.acm.org/doi/10.1145/3534085.3534340 |
DOI | 10.1145/353408510.1145/3534085.3534340 |
Virtual Reality Talking Avatar for Investigative Interviews of Maltreat Children
In 19th International Conference on Content-based Multimedia Indexing. New York, NY, USA: Association for Computing Machinery (ACM), 2022.Status: Published
Virtual Reality Talking Avatar for Investigative Interviews of Maltreat Children
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2022 |
Conference Name | 19th International Conference on Content-based Multimedia Indexing |
Pagination | 201-204 |
Publisher | Association for Computing Machinery (ACM) |
Place Published | New York, NY, USA |
ISBN Number | 9781450397209 |
URL | https://doi.org/10.1145/3549555.3549572 |
DOI | 10.1145/3549555.3549572 |
Journal Article
Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children
Big Data and Cognitive Computing 6, no. 2 (2022): 62.Status: Published
Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children
Afilliation | Communication Systems, Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Journal Article |
Year of Publication | 2022 |
Journal | Big Data and Cognitive Computing |
Volume | 6 |
Issue | 2 |
Pagination | 62 |
Date Published | Jan-06-2022 |
Publisher | MDPI |
URL | https://www.mdpi.com/2504-2289/6/2/62https://www.mdpi.com/2504-2289/6/2/... |
DOI | 10.3390/bdcc6020062 |
Visual Sentiment Analysis from Disaster Images in Social Media
Sensors 22 (2022): 3628.Status: Published
Visual Sentiment Analysis from Disaster Images in Social Media
The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on visual sentiment analysis in a societally important domain, namely disaster analysis in social media. To this aim, we propose a deep visual sentiment analyzer for disaster-related images, covering different aspects of visual sentiment analysis starting from data collection, annotation, model selection, implementation, and evaluations. For data annotation and analyzing people’s sentiments towards natural disasters and associated images in social media, a crowd-sourcing study has been conducted with a large number of participants worldwide. The crowd-sourcing study resulted in a large-scale benchmark dataset with four different sets of annotations, each aiming at a separate task. The presented analysis and the associated dataset, which is made public, will provide a baseline/benchmark for future research in the domain. We believe the proposed system can contribute toward more livable communities by helping different stakeholders, such as news broadcasters, humanitarian organizations, as well as the general public.
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Journal Article |
Year of Publication | 2022 |
Journal | Sensors |
Volume | 22 |
Number | 10 |
Pagination | 3628 |
Date Published | 05/2022 |
Publisher | MDPI |
URL | https://doi.org/10.3390/s22103628 |
DOI | 10.3390/s22103628 |
Proceedings, refereed
Multimodal Virtual Avatars for Investigative Interviews with Children
In Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR '21). New York, NY, USA: ACM, 2021.Status: Published
Multimodal Virtual Avatars for Investigative Interviews with Children
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.
Afilliation | Communication Systems, Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2021 |
Conference Name | Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR '21) |
Publisher | ACM |
Place Published | New York, NY, USA |
ISBN Number | 9781450385299 |
URL | https://dl.acm.org/doi/proceedings/10.1145/3463944 |
DOI | 10.1145/346394410.1145/3463944.3469269 |
Visual Sentiment Analysis: A Natural Disaster Use-case Task at MediaEval 2021
In MediaEval 2021. Ceurws, 2021.Status: Published
Visual Sentiment Analysis: A Natural Disaster Use-case Task at MediaEval 2021
Afilliation | Machine Learning |
Project(s) | Department of Holistic Systems |
Publication Type | Proceedings, refereed |
Year of Publication | 2021 |
Conference Name | MediaEval 2021 |
Publisher | Ceurws |