现场表演创作中的紧密耦合代理

William Marley, Nicholas Ward
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引用次数: 2

摘要

我们考虑人工智能在数字乐器中的应用如何最大限度地支持对演奏声音的探索。人工智能和机器学习的现场表演应用往往侧重于分数跟踪和机器合作者的发展。在我们的工作中,我们感兴趣的是探索系统的发展,在此系统中,人类表演者在创造单个声音输出时与反应性和创造性代理相互作用。其目的是设计能够促进探索的系统,并为偶然的音乐相遇提供更多机会(而不是使用原声乐器)。首先概述了基于姿态重塑方案的自主机构整合的初步方法。然后,我们描述了一个基于《吃豆人》中的非玩家角色的简单平台,作为指导进一步讨论这一级别的音乐机器协作可能需要的测试平台。概述了这两个系统的试点研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tightly Coupled Agents in Live Performance Metacreations
We consider how the application of AI in digital musical instruments might maximally support exploration of sound in performance. Live performance applications of AI and machine learning have tended to focus on score following and the development of machine collaborators. In our work we are interested in exploring the development of systems whereby the human performer interacts with a reactive and creative agent in the creation of a single sonic output. The intention is to design systems that foster exploration and allow for greater (than with acoustic instruments) opportunities for serendipitous musical encounters. An initial approach to the integration of autonomous agency, based on gesture reshaping schemes within the Reactable performance system, is first outlined. We then describe a simple platform based on the non-player characters within Pacman, which serves as a test bed for guiding further discussion on what musical machine collaboration at this level may entail. Pilot studies for both systems are outlined.
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