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For my sci-fi story (alpha readers wanted; see profile), I used Whisper to transcribe an interview of a Malawian President. From there, I created a vocabulary c
by thangalin 4y ago
For my sci-fi story (alpha readers wanted; see profile), I used Whisper to transcribe an interview of a Malawian President. From there, I created a vocabulary comprised of only the president's words, which I used almost exclusively when writing his speech.
The results from Whisper are incredible, with very few mistakes. Though it did get Nelson Mandela's first name wrong (transcribed as Nesson). What's more, Whisper finished transcribing a 60-minute audio stream in 20 minutes on commodity hardware (T1000 G8 NVIDIA GPU). Broadly, here are the steps I used:
* Download and install podman.
* Download and install git.
* Download and install curl.
* Open a command prompt.
* Run the following commands to containerize Whisper:
git clone https://github.com/lablab-ai/whisper-api-flask whisper
cd whisper
mv Dockerfile Containerfile
podman build --network="host" -t whisper .
podman run --network="host" -p 5000:5000 whisper
* Download MP3 file (e.g., filename.mp3).
* Run the following command to produce a transcription:
curl -F "file=@filename.mp3" http://localhost:5000/whisper
- 101008 4y agoWhisper is great. You can get faster results running the tiny model. I used it for podcast transcription and it is much faster and the quality is not worse than the medium model - there are some podcast episodes that the transcription is the same.
- alach11 4y agoIf speed is important, you're much better off using a larger model and whisper.cpp.
- pantalaimon 4y agoWow thank you! That's a nice speedup indeed, with whisper I get 33,53s user 2,05s system 443% cpu 8,023 total with the 'tiny.en' model whereas whisper.cpp gives me 22,71s user 0,12s system 745% cpu 3,062 total with the 'base.en' model for a 15s audio clip on an i7-3770 (8 threads).
- alach11 4y agoAwesome! Thanks for posting the stats. In my workflows I've found rare but noticeable quality differences between the model sizes. So when practical I try to use the larger ones.
- hodanli 4y agothank you for this
- malborodog 4y agowhy not just run whisper from the command line directly? Why put it into a docker container??
- ec109685 4y agoWhy not keep everything tightly contained?
- kerpotgh 4y ago[dead]
- malborodog 4y agoHm, I'm on Mac so it takes up a bunch of ram and I'm not used to this workflow. good point though.
- ec109685 4y agoUnless you actually use the memory (e.g. allocate it), it won’t impact system performance, but yeah, it definitely is overhead.
- pdntspa 4y agosome people just love making their environments needlessly complicated.
- jazzyjackson 4y agocomplexity is in the eye of the beholder, some people just get docker enough that it's not a friction Now installing the dependencies of every git repo I want to try on my host system, that's how an environment becoming needlessly complicated
- deleted 4y ago[deleted]