135 citations · 148 across the 4 of their papers we have counts for
7 papers
MTCRNN: A multi-scale RNN for directed audio texture synthesis
M. Huzaifah, L. Wyse
Audio textures are a subset of environmental sounds, often defined as having stable statistical characteristics within an adequately large window of time but may be unstructured lo…
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…
Mechanisms of Artistic Creativity in Deep Learning Neural Networks
Lonce Wyse
The generative capabilities of deep learning neural networks (DNNs) have been attracting increasing attention for both the remarkable artifacts they produce, but also because of th…
Conditioning a Recurrent Neural Network to synthesize musical instrument transients
Lonce Wyse, Muhammad Huzaifah
A recurrent Neural Network (RNN) is trained to predict sound samples based on audio input augmented by control parameter information for pitch, volume, and instrument identificatio…
Applying Visual Domain Style Transfer and Texture Synthesis Techniques to Audio - Insights and Challenges
M. Huzaifah, L. Wyse
Style transfer is a technique for combining two images based on the activations and feature statistics in a deep learning neural network architecture. This paper studies the analog…
Real-valued parametric conditioning of an RNN for interactive sound synthesis
Lonce Wyse
A Recurrent Neural Network (RNN) for audio synthesis is trained by augmenting the audio input with information about signal characteristics such as pitch, amplitude, and instrument…