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I dunno, that article is paywalled. ES-HyperNEAT uses what's referred to an an evolvable substrate, which is the internal architecture of the ANN being involved. This provides for arbitrary neuronal wiring which is interesting and a departure from conventional GPU-based training architectures based on layers. For classifying audio stuff typically spectrogram analysis with CNNs are used, to pick up on latent features from a visual perspective. Probably getting your audio sources into an appropriate format would be the challenging part of it. Maybe experiment with the output from Aubio to get it into a representable format that an ES-HyperNEAT ANN could consume.
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