I experimenting with sth similar actually. One small additional requirement: although I studied linguistics and took a year-long course in English phonology, s

I experimenting with sth similar actually. One small additional requirement: although I studied linguistics and took a year-long course in English phonology, speech-to-text still struggles with my accent. The approach I'm playing with atm is inspired by some advice from Simon Willis, here on HN: record audio → transcribe using whisper → clean up and format using a GPT prompt So far the results have been pretty good: the original meaning is preserved but the text is much easier to read (and the missing/"misheard" words are often corrected). What I'm experimenting at the moment: - picking the right model size, tweaking the prompts - better UX (e.g. immediate visual feedback)