4 citations · 7 across the 10 of their papers we have counts for
4 papers · 1 filter
The Role of Large Language Models in Musicology: Are We Ready to Trust the Machines?
Pedro Ramoneda, Emilia Parada-Cabaleiro, Benno Weck +1
In this work, we explore the use and reliability of Large Language Models (LLMs) in musicology. From a discussion with experts and students, we assess the current acceptance and co…
Towards Explainable and Interpretable Musical Difficulty Estimation: A Parameter-efficient Approach
Pedro Ramoneda, Vsevolod Eremenko, Alexandre D'Hooge +2
Estimating music piece difficulty is important for organizing educational music collections. This process could be partially automatized to facilitate the educator's role. Neverthe…
Music Proofreading with RefinPaint: Where and How to Modify Compositions given Context
Pedro Ramoneda, Martin Rocamora, Taketo Akama
Autoregressive generative transformers are key in music generation, producing coherent compositions but facing challenges in human-machine collaboration. We propose RefinPaint, an…
Can Audio Reveal Music Performance Difficulty? Insights from the Piano Syllabus Dataset
Pedro Ramoneda, Minhee Lee, Dasaem Jeong +2
Automatically estimating the performance difficulty of a music piece represents a key process in music education to create tailored curricula according to the individual needs of t…