48 karma · joined November 25, 2018
I vibe coded a few room proof of concept MUD. I added a tools called `oracle` (aka me) that it could ask me questions to help along its way; and the ability to interject in the loop with a hint. Just as I might want an llm to stop to ask me for help instead of plodding along...
Interesting to limit the number of turns and see where it gets stuck or how quickly it can finish.
Do you have any good reading on that link? Searched just now and there's a lot to wade through to find a good article
https://www.kickstarter.com/projects/745629624/cutiepi-raspb...
https://www.jeffgeerling.com/blog/6-lessons-learned-self-pub...
tia
Do you mean you might have a specific and relatively small set of videos that you would like searched, but at a much lower price point (e.g. 10k videos at less than $10/year)?
https://groups.google.com/d/msg/common-crawl/3o2dOHpeRxo/H2O...
So does anyone in the HN crowd have a search-based itch they're willing to pay to have scratched that's not already handled by existing search products?
https://github.com/gooofy/zamia-speech/ has been training good [acoustic] models which are worth looking at (including training with robustness against noise). They've also got lots of code and docker images and documentation.
pocketsphinx isn't actually that bad to use with their latest acoustic models and small vocabularies (so its utility depends on your exact use case). But it's not generally good with far field mics/dsp processed audio, not really good with noise, and in my experiments quite not as fast as Kaldi.
Better/larger language models in my experience make a world of difference (esp in the general vocab case) for improving accuracy for either of kaldi or pocketsphinx. Nobody really seems to talk about this(?), since everyone always uses the news corpus from like the 80s as the default language model.
I haven't really ever gotten the various ~deepspeech systems working, so I can't speak to them.