activity
20162024
most citedConvolutional Recurrent Neural Networks for Music Classification

58 citations · 139 across the 19 of their papers we have counts for

collaborators

26 papers

cs.SD2024★ 1 cited

Composers' Evaluations of an AI Music Tool: Insights for Human-Centred Design

Eleanor Row, György Fazekas

We present a study that explores the role of user-centred design in developing Generative AI (GenAI) tools for music composition. Through semi-structured interviews with profession…

cs.SD2023

Pianist Identification Using Convolutional Neural Networks

Jingjing Tang, Geraint Wiggins, Gyorgy Fazekas

This paper presents a comprehensive study of automatic performer identification in expressive piano performances using convolutional neural networks (CNNs) and expressive features.…

cs.HC2023

AI as mediator between composers, sound designers, and creative media producers

Sebastian Löbbers, Mathieu Barthet, György Fazekas

Musical professionals who produce material for non-musical stakeholders often face communication challenges in the early ideation stage. Expressing musical ideas can be difficult,…

eess.SP2022★ 1 cited

Sinusoidal Frequency Estimation by Gradient Descent

Ben Hayes, Charalampos Saitis, György Fazekas

Sinusoidal parameter estimation is a fundamental task in applications from spectral analysis to time-series forecasting. Estimating the sinusoidal frequency parameter by gradient d…

cs.SD2022★ 3 cited

Rigid-Body Sound Synthesis with Differentiable Modal Resonators

Rodrigo Diaz, Ben Hayes, Charalampos Saitis +2

Physical models of rigid bodies are used for sound synthesis in applications from virtual environments to music production. Traditional methods such as modal synthesis often rely o…

cs.SD2022★ 9 cited

Contrastive Audio-Language Learning for Music

Ilaria Manco, Emmanouil Benetos, Elio Quinton +1

As one of the most intuitive interfaces known to humans, natural language has the potential to mediate many tasks that involve human-computer interaction, especially in application…