43 citations
- Fraunhofer Institute for Manufacturing Engineering and AutomationDE2 papers
- GESIS - Leibniz Institute for the Social SciencesDE2 papers
- University of Duisburg-EssenDE2 papers
- University of MannheimDE2 papers
- University of StuttgartDE2 papers
- Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-InstitutDE1 paper
- Fraunhofer Institute for Transportation and Infrastructure SystemsDE1 paper
- Fraunhofer Institute of Optronics, System Technologies and Image ExploitationDE1 paper
- Institute of Science TokyoJP1 paper
- Karlsruhe Institute of TechnologyDE1 paper
- Technische Hochschule MannheimDE1 paper
- The University of TokyoJP1 paper
6 papers · 1 filter
More-than-Human Storytelling: Designing Longitudinal Narrative Engagements with Generative AI
Émilie Fabre, Katie Seaborn, Shuta Koiwai +2
Longitudinal engagement with generative AI (GenAI) storytelling agents is a timely but less charted domain. We explored multi-generational experiences with "Dreamsmithy," a daily d…
Evaluating ASR Confidence Scores for Automated Error Detection in User-Assisted Correction Interfaces
Korbinian Kuhn, Verena Kersken, Gottfried Zimmermann
Despite advances in Automatic Speech Recognition (ASR), transcription errors persist and require manual correction. Confidence scores, which indicate the certainty of ASR results,…
Communication Access Real-Time Translation Through Collaborative Correction of Automatic Speech Recognition
Korbinian Kuhn, Verena Kersken, Gottfried Zimmermann
Communication access real-time translation (CART) is an essential accessibility service for d/Deaf and hard of hearing (DHH) individuals, but the cost and scarcity of trained perso…
It might be balanced, but is it actually good? An Empirical Evaluation of Game Level Balancing
Florian Rupp, Alessandro Puddu, Christian Becker-Asano +1
Achieving optimal balance in games is essential to their success, yet reliant on extensive manual work and playtesting. To facilitate this process, the Procedural Content Generatio…
Know What Not To Know: Users' Perception of Abstaining Classifiers
Andrea Papenmeier, Daniel Hienert, Yvonne Kammerer +2
Machine learning systems can help humans to make decisions by providing decision suggestions (i.e., a label for a datapoint). However, individual datapoints do not always provide e…
How Accurate Does It Feel? -- Human Perception of Different Types of Classification Mistakes
Andrea Papenmeier, Dagmar Kern, Daniel Hienert +2
Supervised machine learning utilizes large datasets, often with ground truth labels annotated by humans. While some data points are easy to classify, others are hard to classify, w…