Engaging three user communities with applications and outcomes of computational music creativity

近年来，机器学习和人工智能系统通过在围棋比赛和美国电视游戏节目Jeopardy！同样的技术也被应用于其他被认为是人类本质的领域，如艺术和音乐。这个项目提出了一个替代人类与机器范式的观点：这些技术可以产生有用的，有意义的，和非威胁性的共同创造的合作伙伴。这个项目促进了四个创新和创造性的活动，与三个用户社区：作曲家，表演者和听众。该项目的主要目的是让这些用户社区参与计算音乐创意的应用和成果。另一个目的是让研究人员从这些社区中协作学习非学术背景下涌现的计算音乐创造力的影响。该项目的目标之一是开发一个软件应用程序，使任何有互联网连接的人都能探索音乐共同创作。该项目还将为该应用程序和其他应用程序的用户社区开发一个在线资源，用户可以在其中分享、评论和评价提交的结果。支持这一应用的技术来自AHRC资助的未来研究项目“通过历史研究卡利普索节奏的数据科学”（DaCaRyH，AH/N504531/1）。该项目汇集了民族音乐学家，数据科学专家和作曲家，以研究如何使用计算工具来研究卡利普索音乐，以及如何使用音乐研究来为计算分析的设计提供信息。DaCaRyH的一个意想不到的结果是，这些分析工具中的一些可以被“反转”，以创建合成从未听过的音乐的系统，这是令人惊讶的好。研究人员的初步工作（以专家启发、公共研讨会和音乐会的形式）表明，听众和从业者对探索学术领域之外的计算创造力有着浓厚的兴趣。该项目将让公众参与计算共同创造力产生的音乐。它将为作曲家提供一个实践研讨会，学习使用开发的软件应用程序。此外，中心亦会为市民举办“电脑音乐创意”研讨会。该项目的结论将采用音乐会展示新的音乐与开发的应用程序创建。为了鼓励参与，该项目将组织一个比赛，以征求与应用程序创建的原创作品，由专业合奏。比赛评审团将包括音乐家，作曲家，当然还有一位使用人工智能构建的评论家。这个项目的一个特别新颖的成果是一张专业制作的“机器民谣”音乐专辑。这张专辑的音乐将完全由系统生成，并由经验丰富的音乐家编辑、编排和演奏。研究人员的初步工作发现，由优秀音乐家演奏的好音乐是计算创造力的价值和潜在用途的最佳大使。这张专辑将作为一个持久的例证，说明机器学习工具的共同创造方法的好处。这个项目直接与数字化转型主题联系在一起，通过引入最先进的数字技术，使创造性音乐制作的参与民主化。它还与“关心未来”主题有关，鼓励社区音乐实践的创新和更新，从而有助于扩大和加深听众、表演者和作曲家的参与。该项目将使DaCaRyH项目的遗产多样化。

In recent years, machine learning and artificial intelligence systems have been grabbing headlines by defeating humans at the game of Go and the American TV game-show Jeopardy! The same technology have also been applied to other domains considered essentially human, like art and music. This project proposes an alternative viewpoint to the human-vs-machine paradigm: these technologies can produce co-creative partners that are useful, meaningful, and non-threatening.This project facilitates four innovative and creative activities to engage with three user communities: Composers, Performers, and Listeners. The principal aim of this project is to engage these user communities with applications and outcomes of computational music creativity. A subsidiary aim is for the investigators to collaboratively learn from these communities about the implications of emergent computational music creativity in non-academic contexts. Among its objectives, this project will develop a software application to enable anyone with an Internet connection to explore music co-creation. The project will also develop an online resource for the user community of this application and others, where users can share, comment and rate submitted outcomes. The technology underpinning this application comes from the AHRC-funded Care for the Future research project, "Data science for the study of calypso-rhythm through history" (DaCaRyH, AH/N504531/1). That project brings together ethnomusicologists, experts in data science and a composer to investigate how computational tools can be used to study calypso music, and how the study of music can be used to inform the design of computational analyses. An unanticipated outcome of DaCaRyH is that some of these analytical tools can be "inverted" to create systems that synthesise never-before-heard music that is surprisingly good. Preliminary work by the investigators (in the form of expert elicitations, a public workshop, and music concert) show there is great interest among listeners and practitioners for exploring computational creativity outside of the academic realm.The project will engage public audiences with music arising from computational co-creativity. It will deliver a hands-on workshop for composers to learn to use the developed software application. It will also organise a symposium on computational music creativity for the general public. The conclusion of the project will feature a music concert showcasing new music created with the developed application. To motivate participation, the project will organise a competition to solicit original compositions created with the application, to be performed by a professional ensemble. The competition jury will include musicians, composers, and of course a critic built using artificial intelligence. An especially novel outcome of this project is a professionally produced album of "machine folk" music. The album will feature music generated entirely by the system and edited, arranged, and performed by experienced musicians. The preliminary work of the investigators has found that good music performed by good musicians serves as the best ambassador for the value and potential usefulness of computational creativity. This album will serve as a lasting illustration for the benefits of the co-creative approach to machine learning tools.This project links directly with the Digital Transformations theme by bringing state of the art digital technology to democratise participation in creative music making. It also relates to the Care for the Future theme by encouraging innovation and renewal in community music practice, and thus helping to broaden and deepen engagement from listeners, performers and composers. The project will serve to diversify the legacy of the DaCaRyH project.