What song now? Personalized Rhythm Guitar Learning in Western Popular Music

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Zakaria Hassein-Bey, Yohann Abbou, Alexandre D'Hooge, Mathieu Giraud, Gilles Guillemain, Aurélien Jeanneau

Published: 2025, Last Modified: 23 Mar 2026ISMIR 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: The guitar is one of the most popular musical instruments, and numerous pedagogical tools have been developed to support learners. They rely on vast collections of songs, sheet music, and tablatures, making it challenging for guitarists to navigate and identify pieces that are both pedagogically relevant and aligned with their musical interests. We introduce a simple multi-criteria rule-based model to assess both the difficulty of learning a piece and the skill level of a guitarist, taking into account musical and technical factors. The model provides personalized recommendations that help learners progress efficiently, considering parts within songs, but also multiple versions of the same part, accounting for simplified adaptations or different playing styles, and finally exercises used to progressively learn each part version. We implement and evaluate this approach in the context of accompaniment guitar in popular music, using a dataset designed for the proprietary application [REDACTED]. Expert evaluation of 90 recommendation for 8 user profiles of varying levels indicate that in 86% of cases, the model provides relevant recommendations. While the full dataset remains proprietary, we release under open licenses the code along with a sub-corpus containing annotated difficulties for 337 versions of 111 parts from 41 songs.