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Human-like conversations with Digital Personas: Conversational strategies that support mutual understanding
Kunc, Benjamín ; Šipošová, Barbora (advisor) ; Nováková Schöffelová, Miroslava (referee)
Communication is a collaborative process, and as such requires the communicators to create common ground - the assumption that they mutually understand each other on a sufficient level (Clark, 1996). The AI-powered virtual agents capable of using natural language to communicate with humans have recently attracted the attention of both the general public and experts, as the progress enables humans to give virtual agents more complex tasks in which a conversation itself is a crucial part of a task, such as in education, healthcare or mental health. While the virtual agents are getting better at understanding natural language, their ability to fulfill complex independent tasks (conducting semi-structured interviews, tutoring, coaching, etc.) is bounded by the limitations of their communication skills, and thus they perform the best at rather short, domain-specific conversations (Drouin et al., 2022). The goals of this thesis were to 1) create an experimental framework designed for a brief (5min) social voice chat between humans and virtual agents that would allow to experimentally manipulate different conversational strategies; 2) propose the first set of conversational strategies for mutual understanding and suggest appropriate self-report and behavioral metrics to measure the impact of the...
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