And yea, Nvidia's Parakeet v3 is good enough for my own just local transcription most of the time.

When I need local transcription to be more reliable and I don't have the energy to proof read a long ramble, I still often just pop open chatGPT, dictate, cut, paste.

But we're pretty much already to the point where local transcription models can replace cloud ones for personal use. They're still a bit rough around the edges in terms of polish and latency, but plenty of people are fine with that to avoid yet another app subscription and not having to worry about wondering what's potentially happening with their data.

If I start typing and the existing text is in Spanish, then a sensible default is to select the Spanish keyboard I have installed and let me adjust otherwise.

App developers should also be allowed to supply mini-dictionaries within a context to allow autocorrect to work correctly in that context, so for example in this thread [SpeechAnalyzer, API, Whisper, Parakeet, Nemotron] should be supplied so that these terms are autocorrected.

- it implies that error could be increased n-times, but a 15x _increase_ in 9% error would be an error rate of 135%, which is nonsensical.

- a reduction from 90% error to 20% error is clearly a bigger improvement in rightness to a reduction from 9% to 2%. One is “almost all wrong to almost all right”, the other is “more right”, but they are both a 4.5x reduction in error which means that the 4.5 quantity doesn’t have a constant meaning.

The answer is something like log odds ratios, but that introduces the additional need for a reader to know what that is, and that would be unusual.