Design for Virtuosity: Modelling and Supporting Expertise in Digital Musical Interaction

精湛设计：数字音乐交互中的建模和支持专业知识

• 批准号: EP/N005112/1
• 负责人: Andrew McPherson
• 金额: $ 114.38万
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN005112%2F1
• 关键词: Design; Virtuosity; Modelling; Supporting; Expertise

Musical performers spend many years achieving proficiency on their instruments. Newly-created digital musical instruments (DMIs) face a significant barrier to adoption in that few performers are willing to repeat these years of training to develop expertise on an unknown instrument. Without expert players, evaluating the success of a DMI design is challenging, and establishing its place in a broader musical community is nearly impossible. As a result, while many digital instruments have been created over the past decade, few have achieved lasting impact beyond the first few performances.This fellowship proposes a new approach to DMI design which repurposes the existing skills and experience of trained musicians, providing them with a rapid path to virtuosity without years of retraining. The research programme is organised around two complementary themes: study of performer-instrument interaction and creation of new instruments which capture the full richness and subtlety of virtuosic performance.First, models will be developed of the interaction between performer and instrument. Instrumental performance can be considered a special case of human-machine interaction which is interesting both for its complexity and for the common experience that the musical instrument becomes an extension of the body: while playing, the performer is often not consciously thinking about the instrument. Controlled experiments and participatory design exercises will establish how an instrument's design affects the development of expertise, and how existing expertise can be transferred to newly-created instruments.Second, the resulting models will be applied to the DMI creation process, taking a holistic approach unifying hardware design, digital signal processing, human-computer interaction (HCI) and artistic considerations. Existing DMIs often implicitly prioritise the convenience of the computer over the experience of the human player. On acoustic instruments, the entire physical object contributes to the sound, however subtly, but the choice of sensors in a DMI typically reduces the performer's actions to just a few machine-tractable dimensions. This fellowship will create instruments which deliberately oversample the interaction, using more sensors and higher sampling rates than apparently necessary, not to create a more complicated instrument, but rather to capture the subtle nuances that experts prize. Evaluation of the new DMIs will help refine the original models of performer-instrument interaction.This project focuses on musical interaction, but the principle of repurposing expertise is widely applicable within HCI. The capabilities of human users cannot be modelled only through generic cognitive and motor processes; real people have specialist skills developed over years of practice, and new technologies which connect to those skills are far more likely to find acceptance than ones which must be learned from scratch. Music is a good test case since instrumental training is widespread and reasonably standardised, but the findings will be relevant to other expert domains.This fellowship supports the time of the PI and two postdoctoral researchers. One postdoc will focus on performer studies and interaction, the other on digital signal processing and data mapping strategies. Close collaboration with musicians throughout the research will ensure its relevance to that community. This research integrates hardware design, digital signal processing, human-computer interaction, cognitive science, musicology and arts practice. The PI, with background and professional activities in music composition, electronic engineering and HCI, is ideally placed to lead this multidisciplinary project.

音乐表演者要花很多年的时间才能熟练掌握他们的乐器。新发明的数字乐器（dmi）面临着一个重大的采用障碍，因为很少有表演者愿意重复这些年的培训来发展对未知乐器的专业知识。没有专业的玩家，评估DMI设计的成功是具有挑战性的，并且在更广泛的音乐社区中确立其地位几乎是不可能的。因此，虽然在过去的十年中创造了许多数字乐器，但很少有乐器在最初的几次演出之后取得持久的影响。该奖学金提出了一种新的DMI设计方法，重新利用训练有素的音乐家的现有技能和经验，为他们提供一条无需多年再培训即可快速达到精湛技艺的途径。研究计划围绕两个互补的主题组织：表演者与乐器互动的研究和新乐器的创造，这些新乐器捕捉了精湛演奏的全部丰富性和微妙性。首先，将建立演奏者和乐器之间相互作用的模型。乐器演奏可以被认为是人机交互的一种特殊情况，它的复杂性和乐器成为身体延伸的共同体验都很有趣：在演奏时，表演者通常不会有意识地思考乐器。对照实验和参与式设计练习将确定一种仪器的设计如何影响专门知识的发展，以及如何将现有的专门知识转移到新创建的仪器上。其次，由此产生的模型将应用于DMI创建过程，采用统一硬件设计，数字信号处理，人机交互（HCI）和艺术考虑的整体方法。现有的dmi通常含蓄地优先考虑计算机的便利性，而不是人类玩家的体验。在原声乐器上，整个物理对象对声音的贡献是微妙的，但DMI中传感器的选择通常会将表演者的动作减少到几个机器可处理的尺寸。这项研究将会创造出一些仪器，这些仪器会故意对相互作用进行过采样，使用更多的传感器和更高的采样率，而不是创造一个更复杂的仪器，而是捕捉专家们所看重的细微差别。对新dmi的评估将有助于改进表演者-乐器相互作用的原始模型。这个项目的重点是音乐互动，但重新利用专业知识的原则在HCI中广泛适用。人类用户的能力不能仅仅通过一般的认知和运动过程来建模；真人拥有经过多年实践发展起来的专业技能，与这些技能相关的新技术比必须从头开始学习的技术更容易被接受。音乐是一个很好的测试案例，因为器乐训练很普遍，而且相当标准化，但研究结果将与其他专业领域相关。该奖学金支持PI和两名博士后研究人员的时间。一名博士后将专注于表演者研究和交互，另一名博士后将专注于数字信号处理和数据映射策略。在整个研究过程中与音乐家密切合作将确保其与该社区的相关性。本研究集硬件设计、数字信号处理、人机交互、认知科学、音乐学和艺术实践于一体。PI在作曲、电子工程和HCI方面有专业背景和活动，是领导这个多学科项目的理想人选。

项目成果

The finer the musician, the smaller the details: NIMEcraft under the microscope

音乐家越优秀，细节就越小：显微镜下的 NIMEcraft

• 发表时间: 2017
• 作者: Armitage J

Bricolage in a hybrid digital lutherie context: a workshop study

混合数字制琴环境中的拼凑：研讨会研究

• 发表时间: 2019
• 作者: Armitage J

Crafting Digital Musical Instruments: An Exploratory Workshop Study

制作数字乐器：探索性研讨会研究

• 发表时间: 2018
• 作者: Armitage J

Supporting Live Craft Process in Digital Musical Instrument Design

支持数字乐器设计中的现场工艺流程

• 发表时间: 2018
• 作者: Armitage J

Guitar augmentation for Percussive Fingerstyle: Combining self-reflexive practice and user-centred design

打击乐指弹的吉他增强：结合自我反思练习和以用户为中心的设计

• 发表时间: 2021
• 作者: A Martelloni