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I personally use Whisper to transcribe painfully long meetings (2+ hours). The transcripts are then segmented and, you guessed it, entered right into GPT-4 for
by StanAngeloff 3y ago
I personally use Whisper to transcribe painfully long meetings (2+ hours). The transcripts are then segmented and, you guessed it, entered right into GPT-4 for clean up, summarisation, minutes, etc. So in a sense it's a great way to get more people to use their other products?
- throw03172019 3y agoThis sounds amazing. Would you be willing to share your code? Thanks!
- StanAngeloff 3y agoI run this[0] on Google Colab. The way I have it set up is to encode the meeting minutes to .ogg, push them to Google Drive, then adjust the script to tell it how many speakers there were and the topic of conversation. The `initial_prompt` really helps the model especially if you are talking about brand names, etc. that it may not know how to correctly transcribe. I've added a comment at the bottom of the Gist with some of the prompts I've used in the past. I've successfully managed to produce reports on week-long meetings (~18 hours) that were essential to get the team up to speed. As a company we are currently shifting to Otter.ai[1] which gives good enough results for everyday meetings. [0]: https://gist.github.com/StanAngeloff/91480fac18a74d8aff3e4cf566cfd0ff#file-pyannote-ipynb https://gist.github.com/StanAngeloff/91480fac18a74d8aff3e4cf... [1]: https://otter.ai/ https://otter.ai/
- throw03172019 3y agoWow, thanks so much for the in depth answer. This looks really great, I can’t wait to give it a try.