171–180 of 354 posts
The same happens with whisper-large-v3 on Chinese transcription: silence is transcribed to something like "please upvote, share and favourite this video". I suspect they trained the model on some random YouTube video without carefully picking really useful data.
Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?
Earlier quoted context omitted.
Looks like they used more official sources for German - there, silence is apparently hallucinated as "Untertitelung des ZDF für funk, 2017" according to one of the comments on the issue. Which makes sense, as the public broadcasters' "Mediathek" is probably the largest freely available resource of subtitled videos in Germany. I wonder if the ZDF gave its approval for it being used for LLM training though?
A more appropriate output might be ``4'33" -- John Cage, 1952``
The same happens with whisper-large-v3 on Chinese transcription: silence is transcribed to something like "please upvote, share and favourite this video". I suspect they trained the model on some random YouTube video without carefully picking really useful data.
They trained the model on every YouTube video they could, and hoped the aggregate was useful data.
Earlier quoted context omitted.
> Indeed, the captioning is copyrighted work and you are not legally allowed to copy and redistribute it. Unless you qualify for one of the many exceptions, such as fair use
It’s not clear that training is fair use. That’s being contested in court I think.
Using copyrighted materials and then meaningfully transforming it isn’t infringement. LLMs only recreate original work in the same way I am when I wrote the first sentence of this paragraph because it probably exists word for word somewhere else too
The same happens with whisper-large-v3 on Chinese transcription: silence is transcribed to something like "please upvote, share and favourite this video". I suspect they trained the model on some random YouTube video without carefully picking really useful data.
In Chinese, it always added something like "For study/research purpose only. Please delete after 48 hours." This is what those volunteers added in subtitles of (pirated) movies/shows.
Little did you all know, this is just being mechanical turked by Nancy Qunqar. Way to go Nancy! Keep up the good work, ya crazy bastard!
Earlier quoted context omitted.
How is this evidence of that fact? Honest question. I can see how this might show that subtitles from online sub communities are used, or that maybe even original subtitles from e.g. DVDs are used. But isn't it already known and admitted (and allowed?) that AI uses all sorts of copyrighted material to train models?
> I can see how this might show that subtitles from online sub communities are used, or that maybe even original subtitles from e.g. DVDs are used. Indeed, the captioning is copyrighted work and you are not legally allowed to copy and redistribute it. > But isn't it already known and admitted (and allowed?) No, and I don't see where you got that from. Meta [1], OpenAI [2] and everybody else is being sued as we speak.…
It’s been determined by the judge in the Meta case that training on the material is fair use. The suit in that case is ongoing to determine the extent of the copyright damages from downloading the material. I would not be surprised if there is an appeal to the fair use ruling but that hasn’t happened yet, as far as I know. Just saying that there is good reason for them to think it’s been allowed because it kind of has; that can be reversed but it happened.
In Italian as well there are random hallucination when parsing silence, something like: “Thank you for watching”, “Subtitles by…”
I wouldn't be surprised if "like share and subscribe" also shows up at some point.
in romanian, i’ve noticed multiple instances where the transcripts ends with “nu uitati sa da-ti like si subscribe” which, as you might easily infer , translates to “don’t forget to like and subscribe”.
Earlier quoted context omitted.
That is not the case here - I never encountered this with whisper-large-v3 or similar ASR models. Part of the reason, I guess, is that those subs are burnt into the movie, which makes them hard to extract. Standalone subs need the corresponding video resource to match the audio and text. So nothing is better than YouTube videos which are already aligned.
At least for English, those "fansubs" aren't typically burnt into the movie*, but ride along in the video container (MP4/MKV) as subtitle streams. They can typically be extracted as SRT files (plain text with sentence level timestamps). *Although it used to be more common for AVI files in the olden days.