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Comment by kenarsa | Hacker News Reader

For speech-to-text right? I provided the quote for voice control engine: https://picovoice.ai/#wake-word-detection

The voice control comes in two variations standard and tiny. The tiny one consumes even fewer resources. I provided metrics for the standard one. You can check the benchmark repo on benchmark it yourself as well :) https://github.com/Picovoice/wakeword-benchmark

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Yep! I see the difference now. I'll give this a try. Thanks.

you are welcome!

So I had a quick poke around on the wake word github repo but it looks like you cant generate custom keywords for the raspberry pi. Is that correct? So you have to use the pre-built ones in the resources directory? There seem to be a lot files in there but how do I know what each one does?

I suggest doing a quick read on one of the demos (Python for example) that should clear things up. If not you can always open an issue...

Yeh I think I understand now. The filename of each file in the resources folder represents the hot-word that's detected. When you specify multiple files it'll give the index corresponding to the file and hence the word that was detected. So the problem is that since you don't support generating your own hot-words for raspberry pi, you are stuck with the small random set of words in the repo. That's kind of a huge limitation. So while I'm sure this is a great project for use with x86 and mac, it's a non-starter for me. Presumably proper support for raspberry pi is coming at some point so I'll be sure to check back.

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