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by properbrew
47 days ago
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I fell down the rabbit hole of voice transcription about a year ago, always had a love for utilising fine tuned LLMs so have put two and two together and built https://whistle-enterprise.com. The biggest challenge being it all running on CPU with the target device being your low to mid spec office laptop that's a few years old (I5, 8gb RAM). All nicely packaged together in a single completely offline selfcontained app that you just install and run (no environment setups, packages to download, models to download etc). One of the hardest parts I've found is the diarisation (who said what) side of things. Trying to tune this and have it working in a way that doesn't absolutely grind the laptop to a halt or take forever to complete has been _hard_ but also extremely rewarding. Another part has been the fine tuning side of the Phi-4 model, I'm on version 10 now, getting that pipeline down was a journey in itself, but I've got some great results. I wrote a bit about it in a comment here - https://news.ycombinator.com/item?id=48385906#48389625 I absolutely love working on this, I still wake up and the first thing I think about is voice transcription pipelines (sad I know), but I'm excited to see how much further performance and utility I can squeeze out. |
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I also got hammered when it came to diarization... I found that the biggest pain was creating an appropriate environment for cross-compatibility of the different backends required for whisper/faster-whisper/pyannote. It's especially challenging on older systems, so major kudos for giving it a shot.
Have you gotten any traction yet from the community?