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AI-Based Music Tutor

Posted by on Wednesday, June 12, 2024 in Uncategorized.

The very first concepts that a person learns when they pick up a new instrument are the names of pitches, how those pitches are annotated musically, and how to manipulate their instrument to reliably produce a pitch corresponding to each note. To date, this type of note- and pitch-based knowledge represents the extent of mainstream research in the domain of technology-aided music education. As a musician of any skill level can attest, however, being able to identify and play the correct notes on an instrument is only half the skill set needed to actually play the instrument. The other half includes learning how to read and express articulation, dynamics, phrasing, and playing styles. This project envisions using technology to make music education, specifically learning how to play an instrument, more accessible, enjoyable, and comprehensive than current techniques. While there is no substitute for human-based instruction, especially regarding creative and expressive subjects like music, there is room for productive use of technology to augment existing techniques, particularly in terms of filling the time gaps between interactions with a human instructor and addressing knowledge gaps about particular elements and genres of musical expression. This project aims to utilize recent breakthroughs in AI to bridge the gap between human- and software-based music education.

How to Get Involved

If you are interested in working with the Music Tutor project, please contact Will Hedgecock.

Music Tutor PI

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Will Hedgecock
Research Scientist, Institute for Software Integrated Systems

Music Tutor Personnel

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Pascal Le Boeuf
Assistant Professor of the Practice, Music and Technology

Funding Sources

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