Towards automatic personalization of speech dialog for enhanced user experience

As intelligent virtual agents (IVAs) become increasingly integrated into healthcare, their ability to communicate empathetically and adapting to client-specific needs is critical. Yet most current systems rely on generic, neutral language that may limit user engagement, especially in sensitive or emotionally charged contexts. This paper proposes a research agenda toward automatic personalization of speech dialog as one important factor of IVAs — the dynamic adaptation of language style and tone to the individual user — as one important factor of IVAs to improve user experience (UX) and acceptance. We outline a conceptual framework for dialog personalization, identify core challenges, and propose a concept for system architecture and its evaluation. We ground our vision in relevant literature across human-computer interaction, natural language processing, and health communication. To support the feasibility of this direction, we present results from a proof-of-concept study suggesting that personalized speech dialog can significantly enhance user-perceived system response quality of a task-oriented system to fill out medical surveys. This work lays the foundation for developing more effective and personalized voice communication with IVAs in healthcare applications.