Abstract
The ability to automatically infer relevant aspects of human users' thoughts and feelings is crucial for technologies to intelligently adapt their behaviors in complex interactions. Research on multimodal analysis has demonstrated the potential of technology to provide such estimates for a broad range of internal states and processes. However, constructing robust approaches for deployment in real-world applications remains an open problem. The MSECP-Wild workshop series is a multidisciplinary forum to present and discuss research addressing this challenge. Submissions to this 5th iteration span efforts relevant to multimodal data collection, modeling, and applications. In addition, our workshop program builds on discussions emerging in previous iterations, highlighting ethical considerations when building and deploying technology modeling internal states in the wild. For this purpose, we host a range of relevant keynote speakers and interactive activities.
Original language | English |
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Title of host publication | ICMI 2023 |
Subtitle of host publication | Proceedings of the 25th International Conference on Multimodal Interaction |
Publisher | Association for Computing Machinery |
Pages | 828-829 |
Number of pages | 2 |
ISBN (Electronic) | 9798400700552 |
DOIs | |
Publication status | Published - Oct 2023 |
Event | 25th International Conference on Multimodal Interaction, ICMI 2023 - Paris, France Duration: 9 Oct 2023 → 13 Oct 2023 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 25th International Conference on Multimodal Interaction, ICMI 2023 |
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Country/Territory | France |
City | Paris |
Period | 9/10/23 → 13/10/23 |
Bibliographical note
Funding Information:This research was (partially) funded by the Hybrid Intelligence Center, a 10-year program funded by the Dutch Ministry of Education, Culture, and Science through the Netherlands Organisation for Scientifc Research, https://hybrid-intelligence-centre.nl, grant number 024.004.022.
Publisher Copyright:
© 2023 Owner/Author.
Keywords
- Affective Computing
- Human-centered AI
- Multimodal Modeling