I 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 h

I 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/