1. Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre
- Author
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Branch, Boyd, Mirowski, Piotr, Mathewson, Kory, Ppali, Sophia, and Covaci, Alexandra
- Subjects
Computer Science - Computation and Language - Abstract
Social robotics researchers are increasingly interested in multi-party trained conversational agents. With a growing demand for real-world evaluations, our study presents Large Language Models (LLMs) deployed in a month-long live show at the Edinburgh Festival Fringe. This case study investigates human improvisers co-creating with conversational agents in a professional theatre setting. We explore the technical capabilities and constraints of on-the-spot multi-party dialogue, providing comprehensive insights from both audience and performer experiences with AI on stage. Our human-in-the-loop methodology underlines the challenges of these LLMs in generating context-relevant responses, stressing the user interface's crucial role. Audience feedback indicates an evolving interest for AI-driven live entertainment, direct human-AI interaction, and a diverse range of expectations about AI's conversational competence and utility as a creativity support tool. Human performers express immense enthusiasm, varied satisfaction, and the evolving public opinion highlights mixed emotions about AI's role in arts., Comment: 13 pages, 7 figures, accepted for publication at the International Conference on Computational Creativity 2024
- Published
- 2024