135 citations · 148 across the 8 of their papers we have counts for
Showing eess.ASShow all
3 papers · 1 filter
eess.AS2023
Example-Based Framework for Perceptually Guided Audio Texture Generation
Purnima Kamath, Chitralekha Gupta, Lonce Wyse +1
Controllable generation using StyleGANs is usually achieved by training the model using labeled data. For audio textures, however, there is currently a lack of large semantically l…
eess.AS2023
Towards Controllable Audio Texture Morphing
Chitralekha Gupta, Purnima Kamath, Yize Wei +3
In this paper, we propose a data-driven approach to train a Generative Adversarial Network (GAN) conditioned on "soft-labels" distilled from the penultimate layer of an audio class…
eess.AS2020
Deep generative models for musical audio synthesis
M. Huzaifah, L. Wyse
Sound modelling is the process of developing algorithms that generate sound under parametric control. There are a few distinct approaches that have been developed historically incl…