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: 2222369
• 负责人: Bryan Pardo
• 金额: $ 38.61万
• 依托单位: Northwestern University
• 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=2222369&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）工具来创作，表演和传播他们的音乐，同时也加速了音频AI研究。这涉及创建一个开放访问的软件框架，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工具进行音乐创作，以及一系列举措，使大量音乐家能够以变革的方式使用这些工具。 音乐家们有望使用这些工具来制作成本更低、质量更高的音乐产品，以满足对视频、网站、广告、录音和其他新媒体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，有可能增加能够以艺术谋生的音乐天才的人数，特别是来自目前代表性不足的人口。为了使成长中的音乐家能够充分利用人工智能工具，将为有音乐兴趣的学生开发一套创新的学习体验，并在为期两个学期的课程中进行实地测试，并为大学前代表性不足的青年举办“夏令营”，同时沿着创建在线教学材料，以支持各种环境中的特定学习体验。 该项目团队拥有音乐，音频工程，人工智能，学习科学/教育，商业/创业，道德和包容性方面的互补学科专业知识。这些技能将用于开发常用的免费和开源数字音频平台的框架，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;以及，B）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的音乐家，以便他们可以改进他们的模型。我们还将对不同的音乐家进行采访和调查，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，以及流行病的影响和音乐制作中代表性不足的人群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变革性使用人工智能的因素，这种理解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，为设计有效的教育干预措施提供信息，以更好地为未来的音乐家和其他领域专家做好准备，利用技术。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。