Date
Publisher
arXiv
Recent AI-driven step-function advances in several longstanding problems in music technology are opening up new avenues to create the next generation of music education tools. Creating personalized, engaging, and effective learning experiences are continuously evolving challenges in music education. Here we present two case studies using such advances in music technology to address these challenges. In our first case study we showcase an application that uses Automatic Chord Recognition to generate personalized exercises from audio tracks, connecting traditional ear training with real-world musical contexts. In the second case study we prototype adaptive piano method books that use Automatic Music Transcription to generate exercises at different skill levels while retaining a close connection to musical interests. These applications demonstrate how recent AI developments can democratize access to high-quality music education and promote rich interaction with music in the age of generative AI. We hope this work inspires other efforts in the community, aimed at removing barriers to access to high-quality music education and fostering human participation in musical expression.
Study at a glance
- Question: How can artificial intelligence be used to create personalized and engaging music learning tools?
- Setting and data: Not stated in the abstract
- Method: Two case studies prototyping music education tools
Why it matters
Creating personalized, engaging, and effective learning experiences is a continuously evolving challenge in music education. Barriers also limit access to high-quality music education and human participation in musical expression.
Key findings
- In music education, an automated chord recognition tool can generate personalized exercises from audio tracks, connecting ear training with real-world musical contexts.
- Adaptive piano prototypes using automated transcription can generate exercises for different skill levels while reflecting learners' musical interests.
- Recent artificial intelligence tools can expand access to high-quality music education and promote rich interaction with music.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
