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

Information

  • NSF Award
  • 2222129
Owner
  • Award Id
    2222129
  • Award Effective Date
    10/1/2022 - a year ago
  • Award Expiration Date
    9/30/2026 - 2 years from now
  • Award Amount
    $ 1,413,858.00
  • Award Instrument
    Standard Grant

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

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.<br/> <br/>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.<br/><br/>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.

  • Program Officer
    Dan Cosleydcosley@nsf.gov7032928832
  • Min Amd Letter Date
    9/12/2022 - a year ago
  • Max Amd Letter Date
    9/12/2022 - a year ago
  • ARRA Amount

Institutions

  • Name
    University of Rochester
  • City
    ROCHESTER
  • State
    NY
  • Country
    United States
  • Address
    500 JOSEPH C WILSON BLVD
  • Postal Code
    146270001
  • Phone Number
    5852754031

Investigators

  • First Name
    Raffaella
  • Last Name
    Borasi
  • Email Address
    rborasi@warner.rochester.edu
  • Start Date
    9/12/2022 12:00:00 AM
  • First Name
    Zhiyao
  • Last Name
    Duan
  • Email Address
    zhiyao.duan@rochester.edu
  • Start Date
    9/12/2022 12:00:00 AM
  • First Name
    Jonathan
  • Last Name
    Herington
  • Email Address
    jonathan.herington@rochester.edu
  • Start Date
    9/12/2022 12:00:00 AM
  • First Name
    Rachel
  • Last Name
    Roberts
  • Email Address
    rroberts@esm.rochester.edu
  • Start Date
    9/12/2022 12:00:00 AM

Program Element

  • Text
    FW-HTF Futr Wrk Hum-Tech Frntr

Program Reference

  • Text
    FW-HTF Futr Wrk Hum-Tech Frntr