this post was submitted on 09 Jan 2025
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Hopefully better than YouTube's, those are often pretty bad, especially for non-English videos.
They are terrible.
They're awful for English videos too, IMO. Anyone with any kind of accent(read literally anyone except those with similar accents to the team that developed the auto-caption) it makes egregious errors, it's exceptionally bad with Australian, New Zealand, English, Irish, Scottish, Southern US, and North Eastern US. I'm my experience "using" it i find it nigh unusable.
ELEVUHN
ELEVUHN
Youtube's removal of community captions was the first time I really started to hate youtube's management, they removed an accessibility feature for no good reason, making my experience with it significantly worse. I still haven't found a replacement for it (at least, one that actually works)
and if you are forced to use the auto-generated ones remember no [__] swearing either! as we all know disabled people are small children who need to be coddled!
Same here. It kick-started my hatred of YouTube, and they continued to make poor decision after poor decision.
I've been working on something similar-ish on and off.
There are three (good) solutions involving open-source models that I came across:
Vosk has the best models. But they are large. You can't use the gigaspeech model for example (which is useful even with non-US english) to live-generate subs on many devices, because of the memory requirements. So my guess would be, whatever VLC will provide will probably suck to an extent, because it will have to be fast/lightweight enough.
What also sets vosk-api apart is that you can ask it to provide multiple alternatives (10 is usually used).
One core idea in my tool is to combine all alternatives into one text. So suppose the model predicts text to be either "... still he ..." or "... silly ...". My tool can give you "... (still he|silly) ..." instead of 50/50 chancing it.
@neme @TheImpressiveX [Music]