224 citations · 673 across the 26 of their papers we have counts for
11 papers · 1 filter
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…
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.…
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…
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…
Learning music audio representations via weak language supervision
Ilaria Manco, Emmanouil Benetos, Elio Quinton +1
Audio representations for music information retrieval are typically learned via supervised learning in a task-specific fashion. Although effective at producing state-of-the-art res…
Performer Identification From Symbolic Representation of Music Using Statistical Models
Syed Rifat Mahmud Rafee, Gyorgy Fazekas, Geraint A. ~Wiggins
Music Performers have their own idiosyncratic way of interpreting a musical piece. A group of skilled performers playing the same piece of music would likely to inject their unique…
Neural Waveshaping Synthesis
Ben Hayes, Charalampos Saitis, György Fazekas
We present the Neural Waveshaping Unit (NEWT): a novel, lightweight, fully causal approach to neural audio synthesis which operates directly in the waveform domain, with an accompa…
A Modulation Front-End for Music Audio Tagging
Cyrus Vahidi, Charalampos Saitis, György Fazekas
Convolutional Neural Networks have been extensively explored in the task of automatic music tagging. The problem can be approached by using either engineered time-frequency feature…
MusCaps: Generating Captions for Music Audio
Ilaria Manco, Emmanouil Benetos, Elio Quinton +1
Content-based music information retrieval has seen rapid progress with the adoption of deep learning. Current approaches to high-level music description typically make use of class…
Transfer Learning for Piano Sustain-Pedal Detection
Beici Liang, György Fazekas, Mark Sandler
Detecting piano pedalling techniques in polyphonic music remains a challenging task in music information retrieval. While other piano-related tasks, such as pitch estimation and on…
Automatic tagging using deep convolutional neural networks
Keunwoo Choi, George Fazekas, Mark Sandler
We present a content-based automatic music tagging algorithm using fully convolutional neural networks (FCNs). We evaluate different architectures consisting of 2D convolutional la…