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> Maybe I've just had a bad microphone. Yeah, I would definitely double-check your setup. At work we use Whisper to live-transcribe-and-translate all-hands mee

• s3p 1y ago
  +1 this. Whisper works insanely well. I've been using the medium model as it has yet to mis transcribe anything noticeable, and it's very lightweight. I even converted it to a coreML model so it runs accelerated on apple silicon. It doesn't run *that* much faster than before.. but it ran really fast to begin with. For anyone tinkering, ive had much success with whisper.cpp.
  • azinman2 1y ago
    What was the process of converting it like? I assume you then had to write all of the inference code as well?
    • tough 1y ago
      not the gp but found this https://github.com/ggml-org/whisper.cpp/blob/master/models/convert-whisper-to-coreml.py https://github.com/ggml-org/whisper.cpp/blob/master/models/c...
• Grimblewald 1y ago
  I'd agree with your experience. I simply sit my phone (~200 dollar motorola, cheap phone) in centre of room, split voice file into chunks using voice prints/ID's I get from a voice embedding model I trained, then feed labelled chunks through whisper, and get a nice transcript of everything said. I combine that with my handwritten notes (as image, get a VLM to transcribe) and the agenda, and I get out really nice meeting minutes as a LaTex document. Works a charm and has turned an hour or two of work per meeting into maybe 30 minutes (proofing what was written).