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Comment by userbinator | Hacker News Reader

I don't know of any way to go smaller than that with software. I tried, but it seems like a fundamental limit for English.

If you include "robotic" speech, then there's https://en.wikipedia.org/wiki/Software_Automatic_Mouth in a few tens of KB, and the demoscene has done similar in around 1/10th that. All formant synths, of course, not the sample-based ones that you're referring to.

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SAM is awful but at the same time tantalisingly close (one of the demos of it apparently draws on a great reverse engineered version by Sebastian Macke and refactoring efforts by a couple of others including me - I spent too many hours listening to SAM output...) - especially when comparing to the still awful Festival/Flite models -, that I keep wanting to see what a better generic formant synth used as constraint on an ML model would produce.

That is, instead of allowing a generic machine learning model to output unconstrained audio, train it on the basis of letting it produce low bitrate input/control values for a formant synth instead, and see just how small you can push the model.

Me as a blind dude that is listening to a sinth all the time I don't cair about the size of the thing I just want good SQ.

That's fair, but those two are in constant tension. We can do very good speech if we ship gigs of samples. Better quality smaller models make it easier to get better quality speech in more places.

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