Gan-audioAnimal vocalizations will be synthesised using various artificial intelligence techniques to interrogate how computation enables new sonic experiences of 'nature' in the contexts of conservation and ecologically-inspired musical composition.
Principal investigatorSergio Renteria Aguilar firstname.lastname@example.org
Area of science
Applications usedAudio generative models for PyTorch
To generate high-fidelity synthetic animal vocalizations and soundscapes from wildlife sound archives and create a software to manipulate them according to musical principles.
A machine learning technique (variational autoencoder) capable of generating high-fidelity audio from publicly available sound libraries.
By speeding up the training process through NVIDIA V100 GPUs.