Towards Embodied AI: Design Approached for Robots in Opera

Elizabeth Jochum, Chris Kiefer, Tim Hopkins, Evelyn Ficarra

Research output: Contribution to book/anthology/report/conference proceedingBook chapterResearchpeer-review

Abstract

Opera has historically been a site for developing new and emerging technologies. The recent explosion of interest in AI and machine learning tools have created numerous possibilities for generating creative content in music, poetry, and images, and opera is an ideal testing ground for exploring how these tools might contribute to novel forms of creative expression. This chapter outlines our efforts to explore the creative possibilities of embodied AI through a series of dedicated workshops and performances with an interdisciplinary research team. The goal of the ongoing Robot Opera project is to integrate diverse AI tools and explore their potential for machine performers. Our investigations focus on how emerging technologies challenge conventional understandings of voice, embodiment, and performance. We also explore how to design virtuosic and lively robot performers that do not only imitate human voices and musicality, but machines that are capable of generating their own unique sounds and musical expression. Following a brief history of robots in opera, we summarise our prior work with robot performance. We then describe our iterative design approach and summarise key insights from the workshops and performances and consider the trade-offs of working with existing robots and the possibilities for working with open, configurable systems in performance.
Original languageEnglish
Title of host publicationCultural Technologies: Robots and Artificial Intelligence in the Performing Arts
EditorsYuji Sone, Richard Savery
PublisherRoutledge Taylor & Francis Group
Publication statusSubmitted - 2024

Keywords

  • robot
  • AI
  • machine learning
  • music synthesis
  • embodied AI
  • opera
  • performance
  • puppetry

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