I'm trying to make a neural audio codec using a variety of misguided methods. One I am using ESNs wrong spreading leak rates in a logarithmic fashion acting like a digital cochlea. The other is trying to do the same with a complex mass-spring-damper system to simulate the various hairs of the cochlea as well. Both approaches make super interesting visuals and appear to cluster reasonably well, but I am still learning about RVQ and audio loss (involves GANs and spectral loss). I kinda wanna beat SNAC if I can.