(Disclaimer: I also work in the field.) I would disagree with most of your points. The provided scripts are available for a huge number of datasets. Many of t

(Disclaimer: I also work in the field.) I would disagree with most of your points. The provided scripts are available for a huge number of datasets. Many of the datasets are also useful for use in production. And it's very simple to adapt the provided scripts for further data. Kaldi is complex and big, yes. But you don't have to use all of it. And it is that way because doing STT properly simply is complex. At least for the conventional standard hybrid HMM/NN models. You could surely go some of the end-to-end ways but that will lead to other problems in production. And once you need to deal with these problems, it might become even more complicated. (This is a whole topic on its own...) Kaldi is used in research as well as in production. It can be easily deployed. Kaldi is very well documented. Just check the homepage of it. In addition to it, there is a huge community (both academia and industry).