A5082629529- Speech and dialogue systems
- Topic Modeling
- Natural Language Processing Techniques
- AI in Service Interactions
- Digital Communication and Language
- Radiomics and Machine Learning in Medical Imaging
- Recommender Systems and Techniques
- Knowledge Management and Sharing
- Misinformation and Its Impacts
University of Regensburg
2020-2024
The Future Conversations workshop at CHIIR'21 looked to the future of search, recommendation, and information interaction ask: where are opportunities for conversational interactions? What do we need get there? Furthermore, who stands benefit? was hands-on interactive. Rather than a series technical talks, solicited position statements on opportunities, problems, solutions in search all modalities (written, spoken, or multimodal). This paper -co-authored by organisers participants workshop-...
We present two empirical studies to investigate users’ expectations and behaviours when using digital assistants, such as Alexa Google Home, in a kitchen context: First, survey (N = 200) queries participants on their for the kinds of information that systems should be able provide. While consensus exists expecting about cooking steps processes, younger who enjoy express higher likelihood details food history or science cooking. In follow-up Wizard-of-Oz study 48), users were guided through...
Conversational Agents are increasingly integrated into our daily routines, assisting us with various tasks, from simple commands such as scheduling events to more complex conversational search interactions. Such systems traditionally evaluated word-overlap metrics F1 score and accuracy. The full-day workshop on Search-Oriented Artificial Intelligence (SCAI) at CHIIR 2024 explored the evaluation of user's perspective. This interactive included multiple panel discussions working groups focused...
As conversational search becomes more pervasive, it increasingly important to understand the users’ underlying information needs when they converse with such systems in diverse domains. We conduct an situ study arising a home cooking context as well how are verbally communicated assistant. A human experimenter plays this role our study. Based on transcriptions of utterances, we derive detailed hierarchical taxonomy occurring context, which require different levels assistance be solved. The...
Online retail has become a popular alternative to in-store shopping. However, unlike in traditional stores, users of online shops need find the right product on their own without support from expert salespersons. Conversational search could provide means compensate for shortcomings engines. To establish design guidelines such virtual assistants, we studied conversations user study (N = 24) where experts supported finding needs. We annotated concerning content and conversational structure...
With the emergence of voice assistants and large language models, conversational interaction with information has become part everyday life. The eighth edition search-oriented AI (SCAI) workshop brings together practitioners researchers from various disciplines to discuss challenges advances in search systems. This year's focuses on evaluations beyond relevance accuracy looks at user's perspective. features a shared task user-centered evaluation datasets metrics, challenging participants...
Conversational agents have become increasingly integrated into our daily lives, including assisting with cooking-related tasks. To address these issues and supplement other datasets, we introduce QookA—a unique dataset featuring spoken queries, associated information needs, answers rooted in cooking recipes. QookA overcomes shortcomings existing laying the foundation for more effective conversational tailored to This paper outlines construction process, analyzes data, explores research...
Abstract Systematic and repeatable measurement of information systems via test collections, the Cranfield model, has been mainstay Information Retrieval since 1960s. However, this may not be appropriate for newer, more interactive systems, such as Conversational Search agents. Such rely on Machine Learning technologies, which are yet sufficiently advanced to permit true human-like dialogues, so research can enabled by simulation human In work we compare dialogues obtained from two studies...
As conversational search becomes more pervasive, it increasingly important to understand the user's underlying information needs when they converse with such systems in diverse domains. We conduct an in-situ study arising a home cooking context as well how are verbally communicated assistant. A human experimenter plays this role our study. Based on transcriptions of utterances, we derive detailed hierarchical taxonomy occurring context, which require different levels assistance be solved....