Collaborative Research: FW-HTF-R: Toward an Ecosystem of Artificial Intelligence-Powered Music Production (TEAMuP)

合作研究：FW-HTF-R：迈向人工智能驱动的音乐制作生态系统 (TEAMuP)

• 批准号: 2222129
• 负责人: Raffaella Borasi
• 金额: $ 141.39万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222129&HistoricalAwards=false
• 关键词: Collaborative; Research; FW; HTF; Toward

This project builds the foundations of a new ecosystem for music production to empower future musicians to better leverage Artificial Intelligence (AI) tools in the creation, performance, and dissemination of their music, while also accelerating audio AI research. This involves the creation of both an open-access software framework enabling musicians and researchers to collaborate in the development and use of ever-better AI-powered tools for music creation, and a set of initiatives to enable a critical mass of musicians to use these tools in transformative ways. Musicians are expected to use these tools to produce lower-cost, higher-quality music products, which meet growing demand for digital music content for videos, websites, advertising, audio recordings, and other new media. Enabling musicians to be more self-sufficient in their music creation has the potential to increase the number of musically talented individuals that will be able to make a living with their art, especially from currently under-represented populations. To enable growing musicians to make full use of AI tools, a set of innovative learning experiences to acquire the needed mindsets and skills will be developed and field tested in a 2-semester course for students with music interests and a “Summer Camp” for pre-college under-represented youth, along with the creation of online instructional materials to support specific learning experiences in a variety of settings. The project team possesses complementary disciplinary expertise in music, audio-engineering, AI, learning sciences/ education, business/ entrepreneurship, ethics, and inclusion. These skills will be brought to bear on developing a framework for a commonly-used free and open-source digital audio platform that will allow: (a) audio AI researchers to easily deploy their new AI models into the platform; and, b) musicians who use these AI tools to share their music productions with AI researchers so they can refine their models. Interviews and surveys will also be conducted with diverse musicians to better understand key factors that may affect their adoption of AI music production tools and how those tools may transform their work, as well as the implications of the pandemic and other barriers that may be experienced by under-represented populations in music production. Together, the project will generate a better understanding of factors that may affect musicians’ adoption and transformative use of AI in their work, understanding which could be generalized to other occupations at the human-technology frontier. Finally, the team will develop pedagogical principles and practices that can inform the design of effective educational interventions to better prepare future musicians and other domain experts to leverage technology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目为音乐制作的新生态系统奠定了基础，使未来的音乐家能够更好地利用人工智能（AI）工具进行音乐的创作、表演和传播，同时也加速了音频人工智能的研究。这既包括创建一个开放获取的软件框架，使音乐家和研究人员能够合作开发和使用更好的人工智能音乐创作工具，也包括一系列举措，使大量音乐家能够以变革的方式使用这些工具。音乐人有望利用这些工具制作成本更低、质量更高的音乐产品，以满足视频、网站、广告、录音和其他新媒体对数字音乐内容日益增长的需求。使音乐家在音乐创作中更加自给自足，有可能增加音乐天才的数量，这些人将能够以他们的艺术谋生，特别是目前代表性不足的人群。为了使成长中的音乐家能够充分利用人工智能工具，将开发一套创新的学习体验，以获得所需的心态和技能，并在面向有音乐兴趣的学生的两个学期课程和面向大学预科学生的“夏令营”中进行实地测试，同时创建在线教学材料，以支持各种环境下的特定学习体验。项目团队在音乐、音频工程、人工智能、学习科学/教育、商业/创业、伦理和包容等领域拥有互补的专业知识。这些技能将用于开发一个常用的免费开源数字音频平台框架，该平台将允许：(a)音频人工智能研究人员轻松地将他们的新人工智能模型部署到平台中；b)音乐家使用这些人工智能工具与人工智能研究人员分享他们的音乐作品，这样他们就可以完善他们的模型。还将对不同的音乐家进行访谈和调查，以更好地了解可能影响他们采用人工智能音乐制作工具的关键因素，以及这些工具如何改变他们的工作，以及疫情的影响和代表性不足的人群在音乐制作中可能遇到的其他障碍。总之，该项目将更好地了解可能影响音乐家在工作中采用和革命性地使用人工智能的因素，了解这些因素可以推广到人类技术前沿的其他职业。最后，该团队将制定教学原则和实践，为有效教育干预的设计提供信息，以更好地为未来的音乐家和其他领域的专家做好利用技术的准备。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。