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Help me understand Voice Recognition tech (lemm.ee)

submitted 6 months ago* (last edited 6 months ago) by [email protected] to c/[email protected]

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Help me understand Voice Recognition tech

I am interested in getting an app that would allow me to make notes via voice-to-text. I work in a field with HIPAA protections. I'm having trouble figuring out the nuances of privacy related to these apps.

First off, is this kind of software considered "AI"? How does it even recognize that a sound equals a word? Do they use LLM tech? Does the tech learn to recognize my voice better over time? Does it use my recordings to learn to understand other's voices? Is this all a black box? How can I take precautions such that no one except me hears the things I transcribe?

This is just such confusing tech! It seems like it's fairly old and common but the more I think about it in relation to current age AI, the more creeped out I get! And yet my doctor uses one regularly... I'll be asking her about it too, don't worry.

Thank you!

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[–] [email protected] 15 points 6 months ago (2 children)

It's AI and your voice won't be used for training if you use a local model.

Use Whisper stt. It run on your computer so nothing will be out. You can adapt the model size based on how powerful your computer is. The bigger the model the better at transcribing it will be.

[–] [email protected] 0 points 6 months ago (1 children)

That sounds interesting. I was hoping for something that I could use on a mobile app. I'm not sure what "adapting the model size" means so this might be more complicated than I'm looking for.

[–] [email protected] 2 points 6 months ago* (last edited 6 months ago)

I was hoping for something that I could use on a mobile app.

Record then transcribe later ? But you can try https://whisper.ggerganov.com ( this runs on your browser but nothing is sent. So works even on your Android/IOS phone.) the website owner is a trusted dev that made whisper.cpp and llama.ccp, the latter basically being the backbone of the entire LLM industry.

I'm not sure what "adapting the model size" means so this might be more complicated than I'm looking for.

A bit of complexity is generally the price to pay for freedom from the constant surveillance and data gathering. Plus, It's actually super easy. Bigger model means better transcription quality, but the smaller ones are really good already. The base.en is probably all you need anyway.

On pc, you can generally try any app from github. They basically all use the same backend.

I found a few : https://whishper.net/ https://github.com/chidiwilliams/buzz