There is a pull request for precise with a newer version of tensorflow, I have tried it but training does not work well at all and half the scripts are broken. I tried for a day to use it and the best I could do was 50% false-negatives for my wakeword and training was slow. The current version of precise at least trains well and I had only one false-negative with the same training data in 1/100 of the time. And that one was excusable since it was pretty bad quality wise.
I don’t see a big problem with training a model myself, so far i have not have any good experience with any pre-trained model. The only thing that I could get to work was pocketsphinx and that basically reacted to anything I said (and any noise) . The next best results I had was raven, but that still reacted to way to much so now I am training precise. I got it up to roughly the same as raven was, and I only used a pretty small set of samples for wakewords (less than 50) and next to no not wakewords recorded by the same mic rhasspy uses. I only played around with it properly for 3 hours as of yet, thought I spent nearly a week getting a system up and running to even train properly. Once I have more non wakeword data in there, I am pretty sure I can get it to run properly for me.
The problem here is, that few ppl have the knowledge, time and motivation to write something like that. And if something working exists, it happens often enough that it is bought out by some company wanting to play with voice assistants. Precise is not bad, it is just outdated and there is no working version for python 3.8 because of them using an outdated tensorflow library. If they would update that could produce pretty good model.
Another part of the problem is where ppl run their voice assistants. From what I read here, quite a few ppl use anything from a raspberry pi zero to a raspberry pi 4, with a few ppl using it in a vm on their nas. The ppl that have a small server, or anything with more power than a pi4 are rare exceptions, so most systems are geared to run on lower end systems. If it has to run on a potato, there is next to no way it will be perfectly accurate. And if there is a system that is accurate but does not run on the most used hardware, what good is it then?