Hi everyone!
A few days ago I released Whishper, a new version of a project I’ve been working for about a year now.
It’s a self-hosted audio transcription suite, you can transcribe audio to text, generate subtitles, translate subtitles and edit them all from one UI and 100% locally (it even works offline).
I hope you like it, check out the website for self-hosting instructions: https://whishper.net
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Would love to deploy this, but unfortunately I’m running server equipment that apparently doesn’t support MongoDB 5 (Error message MongoDB 5.0+ requires a CPU with AVX support, and your current system does not appear to have that!). Tried deploying with both 4.4.18 and 4.4.6 and can’t get it to work. If anybody has some recommendations, I’d appreciate hearing them!
Edit: Changed my proxmox environment processor to host, fixed my issue.
I’m glad you were able to solve the problem, I add the comment I made to another user with the same problem:
Didn’t know about this problem. I’ll try to add a MariaDB alternative database option soon.
How does it compare to https://github.com/guillaumekln/faster-whisper?
I’ve been using Faster Whisper for a while locally, and its worked out better than raw whisper and benchmarks really well. Just curious if there are any reasons to switch.
Whishper uses faster-whisper in the backend.
Simply put, it is a complete UI for Faster-Whisper with extra features like transcription translation, edition, download options, etc…
Even this is an good sound to text converter and a good ai transcription service
Just tried this out but couldn’t get it to work until downgrading mongo to 4.4.6 because my NAS doesn’t ha``ve AVX support. But then, mongo stays unhealthy. No idea why.
Didn’t know about this problem. I’ll try to add a MariaDB alternative database option soon to solve this.
Does this need to connect to openai or does it function fully independently? Its for offline use.
No, it’s completely independent, it does not rely on any third-party APIs or anything else. It can function entirely offline once the models have been downloaded.
how does whisper do transcribing technical documents. like for lawyers, doctors, engineers and what not? or speakers with heavy accents?
Whisper models have a very good WER (word error ratio) for languages like Spanish, English, French… if you use the english-only models it also improves. Check out this page on the docs:
https://whishper.net/reference/models/#languages-and-accuracy
