Implemented over 150 GAN architectures for instrument & sound effect sample generation, for exhaustive granular controlled experimental comparison, representing the largest multivariate analysis of structural model variations in this domain to date. This included the structurally novel PrismGAN & SBIGAN models, which both quantifiably succeed at eliminating spectral artifacts in inference. Analysis was performed along 79 metrics, including several novel spectral comparison methods for audio inference evaluation.
