kaldi-active-grammar VS realworld

https://github.com/dictation-toolbox/dragonfly

https://github.com/daanzu/kaldi-active-grammar

With an open system/engine, you can train your own personal speech model. For kaldi-active-grammar (https://github.com/daanzu/kaldi-active-grammar), you can do so without all that much difficulty, although the process/documentation could certainly use improvement.

I bootstrapped my personal speech model by retaining the commands from me using WSR. My voice is quite abnormal, and it took only 10 hours of speech data to train a model orders of magnitude more accurate than any generic model I've ever used. And of course, I retain much of my usage now with Kaldi, so my model improves more and more over time. A virtuous flywheel!

I have been coding entirely by voice for approximately 10 years now (by hand long before that). Most of that time I have been using the Dragonfly (https://github.com/dictation-toolbox/dragonfly) library to construct my own customized voice coding system. The library is highly flexible and open source, allowing you to easily customize everything to suit what you need to be productive. It is perhaps the power user analogue to Dragon Naturally Speaking. With it, you can certainly be highly productive coding by voice. In fact, I develop kaldi-active-grammar (https://github.com/daanzu/kaldi-active-grammar), a free and open source speech recognition backend usable by Dragonfly, itself entirely by voice. There's also a community of voice coders using Dragonfly and other tools that build on top of it, such as Caster (https://github.com/dictation-toolbox/Caster).

- Demo: https://www.youtube.com/watch?v=Qk1mGbIJx3s / Software: https://github.com/daanzu/kaldi-active-grammar

Far field audio is usually harder for any speech system to get correct, so having a good quality mic and using it nearby will _usually_ help with the transcription quality. As a long time Linux user, I would love to see it get some more powerful voice tools - really hope that this opens up over the next few years. Feel free to drop me an email (on my profile) happy to help with setup on any of the above.

kaldi repo: https://github.com/daanzu/kaldi-active-grammar

In light of all this, it became exceedingly clear that someone else needed to step in and help. Why not me? Well, it can be me. And, after 3 months of development, I am happy to announce (again) dwayne/elm-conduit (demo), an open-source Elm SPA for RealWorld's Medium.com clone.

https://github.com/gothinkster/realworld

It's just for web app (a Todo app). Your GIS AND CLI ideas are interesting, I haven't seen anything similar to realworld for those.

View on GitHub

So what would be a better benchmark? Perhaps a "standard" "real world" app, like https://github.com/gothinkster/realworld

Or something simpler?

RealWorld example app is a full-stack application called "Conduit" that consists of a backend that serves JSON API and a frontend UI. There are numerous implementations for different languages and frameworks, but in this tutorial you will be using the Spring backend and the React frontend.

Github has millions of projects, some large fraction with more than 100 stars, so it doesn't seem like you are searching very hard. But more importantly, why "100 stars"? Stars are meaningless and arbitrary. Many developers use stars like bookmarks. I just did a quick search and noticed a project like realworld (just a demo for learning, 65 contributors) has have more stars than Bitcoin (900+ developers, perhaps you have heard of it?)

I feel you, context API sometimes overcomplicates everything. Let me introduce to you RealWorld. It is a great project that uses composition to make its structure scalable. It is actually a codebase that implements various fragments of a larger scale project such as Medium or Twitter. Check it out here: https://github.com/gothinkster/realworld. I hope this helps!