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音乐、身体与机器:人机音乐互动中基于手势的同步

Music, body, and machine: gesture-based synchronization in human-robot musical interaction.

作者信息

Gao Xuedan, Rogel Amit, Sankaranarayanan Raghavasimhan, Dowling Brody, Weinberg Gil

机构信息

Robotic Musicianship Lab, Center for Music Technology, Georgia Institute of Technology, Atlanta, GA, United States.

出版信息

Front Robot AI. 2024 Dec 5;11:1461615. doi: 10.3389/frobt.2024.1461615. eCollection 2024.

Abstract

Musical performance relies on nonverbal cues for conveying information among musicians. Human musicians use bodily gestures to communicate their interpretation and intentions to their collaborators, from mood and expression to anticipatory cues regarding structure and tempo. Robotic Musicians can use their physical bodies in a similar way when interacting with fellow musicians. The paper presents a new theoretical framework to classify musical gestures and a study evaluating the effect of robotic gestures on synchronization between human musicians and Shimon - a robotic marimba player developed at Georgia Tech. Shimon utilizes head and arm movements to signify musical information such as expected notes, tempo, and beat. The study, in which piano players were asked to play along with Shimon, assessed the effectiveness of these gestures on human-robot synchronization. Subjects were evaluated for their ability to synchronize with unknown tempo changes as communicated by Shimon's ancillary and social gestures. The results demonstrate the significant contribution of non-instrumental gestures to human-robot synchronization, highlighting the importance of non-music-making gestures for anticipation and coordination in human-robot musical collaboration. Subjects also indicated more positive feelings when interacting with the robot's ancillary and social gestures, indicating the role of these gestures in supporting engaging and enjoyable musical experiences.

摘要

音乐表演依赖于非语言线索在音乐家之间传递信息。人类音乐家通过身体手势向合作者传达自己的诠释和意图,从情绪和表情到关于结构和节奏的预期线索。机器人音乐家在与其他音乐家互动时也可以以类似的方式运用它们的身体。本文提出了一个对音乐手势进行分类的新理论框架,并开展了一项研究,评估机器人手势对人类音乐家与“西蒙”(佐治亚理工学院研发的一款机器人马林巴琴演奏者)之间同步性的影响。西蒙利用头部和手臂动作来表示音乐信息,如预期音符、节奏和节拍。该研究要求钢琴演奏者与西蒙一起演奏,评估这些手势对人机同步的有效性。研究对象被评估与西蒙通过辅助和社交手势传达的未知节奏变化同步的能力。结果表明非乐器手势对人机同步有显著贡献,突出了非音乐制作手势在人机音乐协作中的预期和协调作用。研究对象在与机器人的辅助和社交手势互动时也表示有更积极的感受,表明这些手势在支持引人入胜且愉悦的音乐体验方面的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9494/11655300/7f390a014131/frobt-11-1461615-g001.jpg

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