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 * Welcome
 * Research Team
 * Activities
 * Who we are
 * AI Software
 * Visualize Music
 * Contact


AI (ARTIFICIAL INTELLIGENCE) FOR MUSICIANS

This is a Research Team Studying How Musicians can Benefit from AI (Artificial
Intelligence)

This project is supported by the National Science Foundation Artificial
Intelligence Technology for Future Music Performers.


RESEARCH TEAM




ACTIVITIES

Create AI-based software for musicians. Evaluate whether the software actually
helps musicians. Educate students for AI, software, and music performance.


VERTICALLY INTEGRATED PROJECT

Artificial Intelligence in Music is an undergraduate course. Meeting time in
Spring 2024: Varies by project; email below


MULTIDISCIPLINARY RESEARCH

This project includes students and professors from Music, Engineering,
Technology, Art, and Management.


USER STUDIES

Evaluate how musicians use AI-based tools and how these tools can be improved.


PRESENTATIONS

Gives speeches and concerts about AI and music.


CONCERTS

Demonstrate the technology.


CELLO LESSONS

Learn how to play cello, from beginners to stage performers.


PROJECT DIRECTOR:

Kristen Yeon-Ji Yun is a clinical associate professor of Music.

Josh Kamphuis is a leader of the Evaluator undergraduate research team.

Tim Nadolsky is the leader of the Companion undergraduate research team.

Kareen D Patel is an undergraduate student.

Samantha Rose Sudhoff is an undergraduate student.

Haichang Li is the leader of the Mus2Vid undergraduate research team.

Brian Ng is an undergraduate student.

Victor Yingjie Chen is a professor of Computer Graphics Technology.

Yung-Hsiang Lu is a professor of Electrical and Computer Engineering.

Cheryl Zhenyu Qian is a professor of Interaction Design in Industrial Design.

Mohammad Saifur Rahman is the inaugural Daniels School Chair in Management and a
Professor of Management at the Mitchell E. Daniels, Jr. School of Business.


EVALUATOR

The Evaluator aims to improve individual practice and performance. It analyzes a
musician’s sound and compares it to digitized music scores to detect deviations
in intonation, rhythm, and dynamics and suggest better posture based on sample
performers’ recording with correct posture.

Drawing by Cecilia Ines Sanchez.


COMPANION

The Companion plays the part of one or several instruments to replace absent
musicians with matching tempo, and style of the human musicians through audio
analysis of their performance while also responding in real-time to verbal
instructions.

Drawing by Cecilia Ines Sanchez.


VISUALIZE MUSIC

This project analyzes music elements and transforms them into textual
descriptions. These descriptions are converted into visual representations
(images or videos). The visual depictions are dynamically adjusted to mirror the
music.

 * Learn more


GET IN TOUCH

We would love to hear from you.


 * ADDRESS
   
   Elliot 34, 712 3rd Street
   Purdue University, West Lafayette, IN 47907
   USA


 * EMAIL
   
   yun98@purdue.edu


 * PHONE
   
   (765) 494-0973


 * SOCIAL
   
     
   * LinkedIn

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