Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913347847323648 |
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| author | Branch, Boyd Mirowski, Piotr Mathewson, Kory Ppali, Sophia Covaci, Alexandra |
| author_facet | Branch, Boyd Mirowski, Piotr Mathewson, Kory Ppali, Sophia Covaci, Alexandra |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_07111 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre Branch, Boyd Mirowski, Piotr Mathewson, Kory Ppali, Sophia Covaci, Alexandra Computation and Language 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. |
| title | Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2405.07111 |