权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Innovating Sema: Community-building of Live Coding Language Design and Performance with Machine Learning

创新 Sema：通过机器学习进行实时编码语言设计和性能的社区建设

基本信息

批准号：
AH/V005154/1
负责人：
Thor Magnusson
金额：
$ 10.27万
依托单位：
University of Sussex
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=AH%2FV005154%2F1
关键词：
Innovating Sema Community building Live

项目摘要

The Innovating Sema project will secure the long-term existence and use of our innovative live coding platform for machine learning. After an intense development process during the MIMIC grant (AH/R002657/1) we have developed a potential paradigm-shifting system that empowers users of programming languages for artistic expression to design their own languages for interfacing with machine learning. This has not been done before and through our user studies and workshops we are confident that our system works. Our project has the potential to demystify machine learning through hands-on use, thus generating understanding and trust in modern AI. It enables non-expert users to engage with creative AI. Now is the time to secure the longevity and wide use of the Sema system promoting understanding of computing through the two pillars of language design and machine learning.The MIMIC project is a direct response to significant changes taking place in the domain of computing and the arts. Recent developments in Artificial Intelligence and Machine Learning lead to a revolution in how music and art is being created. However, these are early days concerning the integration of this new technology into software aimed at creatives. Due to the complexities of machine learning, and the lack of usable tools, such approaches have only been usable by experts. In order to study how we might bring these new fruitful technologies of new art making to the people, we created new, user-friendly technologies. They enable laypeople, both composers as well as amateur musicians, to understand and apply these new computational techniques in their own creative work.The unexpected potential for impact we discovered during the development of Sema is twofold: 1) We were going to create a high level live coding language for machine learning. However, responding to survey feedback, we decided to generalise and scale our approach by creating a system for *other people to design their own* live coding languages, using our language grammar compilation technology. This makes artists equally the creators of their own tools as well as the creators of artistic work with those tools. By designing and installing our system online and building a community that contributes to its development, we are effectively collaborating with users in filling a musical toolbox with tools and instruments. 2) During the development of Sema, we become attuned to how distant machine learning is to the general public. People do not easily understand new AI and this technology is often seen as a negative force in society (from automation anxiety, filter bubbles, bias, and algorithms pushing people to the political extremes). Our project enables people to explore machine learning, and thereby gain an understanding of how machine learning and artificial neural networks are designed and trained, through hands-on experience. Music is an ideal platform to give people an understanding of machine learning as it is a collaborative, fun and risk-free environment for experimentation (unlike self driving cars or stock market algorithms).By creating an online resource with our software (including language generator, live coding environment, machine learning architectures and models, and user contributed mini-languages) together with solid documentation and tutorials, we will secure the longevity and impact of our Sema project. Through an extensive user-engagement plan, we will create the conditions for an international community of users to grow independently of our own practice and research. This community will be initially formed by our own workshops, mailing lists, media appearances, social media communication, and dissemination through our own networks of colleagues who teach computer music internationally.

创新的SEMA项目将确保我们创新的机器学习实时编码平台的长期存在和使用。经过模拟拨款(AH/R002657/1)期间的紧张开发过程，我们开发了一个潜在的范式转换系统，使艺术表达编程语言的用户能够设计自己的语言，以便与机器学习交互。在我们的用户研究和研讨会之前并没有做到这一点，我们相信我们的系统是有效的。我们的项目有可能通过动手使用来揭开机器学习的神秘面纱，从而在现代人工智能中产生理解和信任。它使非专家用户能够参与创造性的人工智能。现在是确保SEMA系统的长寿和广泛使用的时候了，通过语言设计和机器学习这两个支柱来促进对计算的理解。MIMIC项目是对计算和艺术领域发生的重大变化的直接回应。人工智能和机器学习的最新发展导致了音乐和艺术创作方式的革命。然而，关于将这项新技术整合到针对创意的软件中，目前还处于早期阶段。由于机器学习的复杂性，以及缺乏可用的工具，这种方法只能由专家使用。为了研究如何将这些新的、富有成效的新艺术制作技术带给人们，我们创造了新的、用户友好的技术。它们使普通人，无论是作曲家还是业余音乐家，都能理解和应用这些新的计算技术在他们自己的创作工作中。在Sema的开发过程中，我们发现了意想不到的潜在影响：1)我们将为机器学习创建一种高级实时编码语言。然而，为了回应调查反馈，我们决定推广和扩大我们的方法，创建一个系统，让*其他人使用我们的语言语法编译技术来设计他们自己的*实时编码语言。这使得艺术家既是他们自己工具的创造者，也是使用这些工具的艺术作品的创造者。通过在线设计和安装我们的系统，并建立一个有助于其发展的社区，我们正在有效地与用户合作，将工具和乐器装满音乐工具箱。2)在SEMA的开发过程中，我们逐渐适应了机器学习与普通公众的距离。人们不容易理解新的人工智能，这项技术经常被视为社会上的一股负面力量(从自动化焦虑、过滤泡沫、偏见和将人们推向政治极端的算法)。我们的项目使人们能够探索机器学习，从而通过实践经验了解机器学习和人工神经网络是如何设计和训练的。音乐是一个让人们了解机器学习的理想平台，因为它是一个协作、有趣和无风险的实验环境(不同于自动驾驶汽车或股票市场算法)。通过使用我们的软件(包括语言生成器、实时编码环境、机器学习架构和模型以及用户贡献的小语言)以及坚实的文档和教程创建在线资源，我们将确保我们的SEMA项目的寿命和影响力。通过广泛的用户参与计划，我们将为国际用户社区的发展创造条件，使其独立于我们自己的实践和研究。这个社区最初将由我们自己的研讨会、邮件列表、媒体露面、社交媒体交流和传播组成，通过我们自己的同事网络在国际上教授计算机音乐。