Browsing School of Electronic Engineering and Computer Science by Author "Vahidi, C"
Now showing items 1-10 of 10
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AI (r)evolution – where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning
Bindi, G; Demerlé, N; Diaz, R; Genova, D; Golvet, A; Hayes, B; Huang, J; Liu, L; Martos, V; Nabi, S (Institut de Recherche et Coordination Acoustique/Musique (IRCAM), 2023-10-31) -
Differentiable Time-Frequency Scattering in Kymatio
Vahidi, C; Muradeli, J; Wang, C; Han, H; Lostanlen, V; Lagrange, M; Fazekas, G; arXiv -
DMRN+16: Digital Music Research Network One-day Workshop 2021
Grechin, S; Banar, B; Hayes, B; Welham, C; Pelinski, T; Poliakov, E; Li, Y; Zhang, H; Lobbers, S; Liang, J (Centre for Digital Music (C4DM), 2021-12-17)DMRN+16: Digital Music Research Network One-day Workshop 2021 Queen Mary University of London Tuesday 21st December 2021 Keynote speakers Keynote 1. Prof. Sophie Scott -Director, Institute of Cognitive Neuroscience, UCL. ... -
DMRN+17: Digital Music Research Network One-day Workshop 2022
Miller, J; Lewis, D; Guo, Z; Li, Y; Ma, Y; Vahidi, C; Boon, H; Wolstanholme, L; Gil Panal, JM; Hayes, B (Centre for Digital Music - C4DM, 2022-12-20)DMRN+17: Digital Music Research Network One-day Workshop 2022 Queen Mary University of London - Tuesday 20th December 2022. The Digital Music Research Network (DMRN) aims to promote research in the area of Digital Music, ... -
Hearing from Within a Sound: A Series of Techniques for Deconstructing and Spatialising Timbre
Wolstanholme, L; Vahidi, C; Mcpherson, A; International Conference on Spatial and Immersive Audio (AES) (Audio Engineering Society, 2023-08-23)We present a series of compositional techniques for deconstructing and spatialsing timbre in an immersive audio environment. These techniques aim to engulf a spectator within a given abstract timbre, by highlighting said ... -
Kymatio: Deep Learning meets Wavelet Theory for Music Signal Processing
Vahidi, C; Mitcheltree, C; Lostanlen, V (2023-11-05)We present a tutorial on MIR with the open-source Kymatio (Andreux et al., 2020) toolkit for analysis and synthesis of music signals and timbre with differentiable computing. Kymatio is a Python package for applications ... -
Mesostructures: Beyond Spectrogram Loss in Differentiable Time–Frequency Analysis
Vahidi, C; Han, H; Wang, C; Fazekas, G; LAGRANGE, M; LOSTANLEN, VComputer musicians refer to mesostructures as the intermediate levels of articulation between the microstructure of waveshapes and the macrostructure of musical forms. Examples of mesostructures include melody, arpeggios, ... -
A Modulation Front-End for Music Audio Tagging
Vahidi, C; Fazekas, G; Saitis, C; The International Joint Conference on Neural NetworksConvolutional Neural Networks have been extensively explored in the task of automatic music tagging. The problem can be approached by using either engineered time-frequency features or raw audio as input. Modulation filter ... -
Perceptual musical similarity metric learning with graph neural networks
Vahidi, C; Singh, S; Benetos, E; Phan, QH; Stowell, D; Fazekas, G; Lagrange, M; IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) (IEEE, 2023-10-22)Sound retrieval for assisted music composition depends on evaluating similarity between musical instrument sounds, which is partly influenced by playing techniques. Previous methods utilizing Euclidean nearest neighbours ... -
Timbre Space Representation of a Subtractive Synthesizer
Vahidi, C; Fazekas, G; Saitis, C; Palladini, A; International Conference on Timbre (Timbre 2020) (2020-09-03)