Link to my project for those interested: https://github.com/osprey-voice/osprey. It's still kind of a work in progress but it's been working for me.
Right now it’s about 5 hours total, which isn’t a ton for actually training on, which is why I haven’t prioritized releasing it and haven’t even trained on it myself yet. I’ve been mostly using it for evaluation so far.
If someone approaches me and says “I have a compelling need for a bit of training data in the form of your prompts” I’ll probably prioritize a release higher.
As another perspective, a majority of the people at this point submitting their voice are already using Talon and just want the engine to be more robust.
https://github.com/jaxcore/deepspeech-plugin
It's not quite there yet, but I'm working on it.
It can type numbers and symbols reasonably well, I need to do some additional work like build a custom language model to be able to type letters and plug some other gaps in Mozilla's CommonVoice model.
Here's the number typing example: https://github.com/jaxcore/deepspeech-plugin/tree/master/exa...
There'd be some back and forth regarding it's suitability for coding over there. Much better support than I expected apparently...
Still as a general solution I do believe it has drawbacks, noisy environments etc.
As a generalization, you seem to be coming up with reasons you _think_ voice coding won’t work well, while ignoring the fact it already does. For example, noisy environments have several very good solutions, such as using microphones designed for them, leaving the environment, or software to reduce noise like Krisp.
The biggest realistic drawback from my perspective is the fact it’s not very quick at mousing, which is why I’ve done a bunch of research on fused eye/head mousing as well.
[1] http://tbf-rnd.life/blog/2019/05/21/hello-world/#comment-25
Now that I am a mac user I finally have the chance to take a look at your solution. I do think that I have a lot to learn and do not think that the areas of research are in conflict at all.
All the best and good luck!
Along with benchmarks for testing the performance and in a more or less sciency fashion compare them to each other. An overlap would also exist in other areas such as word prediction and probably many more.
This isn’t quite accurate. To my knowledge the options are: you are either using it in Talon and it just works, or you want to use it outside Talon and you will need to write entirely new glue code to add support for it in your project of choice.
Is anyone working on decent speech recognition for Mac/Linux or know good resources for that? The ideal output is a stream of what could have been said, as well as some alternatives, each with a confidence.
Every alternative I've tried has not been as effective as the version of Dragon I used from 2011. I think the focus on accents and training is a big thing here -- I'm happy to spend a couple hours training it for better results.