this post was submitted on 20 Jul 2025
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[–] antifuchs@awful.systems 19 points 1 day ago (3 children)

This incredible banger of a bug against whisper, the OpenAI speech to text engine:

Complete silence is always hallucinated as "ترجمة نانسي قنقر" in Arabic which translates as "Translation by Nancy Qunqar"

[–] nightsky@awful.systems 5 points 6 hours ago (1 children)

Similar case from 2 years ago with Whisper when transcribing German.

I'm confused by this. Didn't we have pretty decent speech-to-text already, before LLMs? It wasn't perfect but at least didn't hallucinate random things into the text? Why the heck was that replaced with this stuff??

[–] dgerard@awful.systems 3 points 3 hours ago (1 children)

Transformers do way better transcription, buuuuuut yeah you gotta check it

[–] nightsky@awful.systems 2 points 1 hour ago

I'm just confused because I remember using Dragon Naturally Speaking for Windows 98 in the 90s and it worked pretty accurately already back then for dictation and sometimes it feels as if all of that never happened.

[–] BlueMonday1984@awful.systems 4 points 1 day ago* (last edited 18 hours ago) (1 children)

Discovered some commentary from Baldur Bjarnason about this:

Somebody linked to the discussion about this on hacker news (boo hiss) and the examples that are cropping up there are amazing

This highlights another issue with generative models that some people have been trying to draw attention to for a while: as bad as they are in English, they are much more error-prone in other languages

(Also IMO Google translate declined substantially when they integrated more LLM-based tech)

On a personal sidenote, I can see non-English text/audio becoming a form of low-background media in and of itself, for two main reasons:

  • First, LLMs' poor performance in languages other than English will make non-English AI slop easier to identify - and, by extension, easier to avoid

  • Second, non-English datasets will (likely) contain less AI slop in general than English datasets - between English being widely used across the world, the tech corps behind this bubble being largely American, and LLM userbases being largely English-speaking, chances are AI slop will be primarily generated in English, with non-English AI slop being a relative rarity.

By extension, knowing a second language will become more valuable as well, as it would allow you to access (and translate) low-background sources that your English-only counterparts cannot.

[–] froztbyte@awful.systems 6 points 1 day ago (1 children)

On a personal sidenote

do you keep count/track? the moleskine must be getting full!

[–] BlueMonday1984@awful.systems 6 points 23 hours ago

I don't keep track, I just put these together when I've got an interesting tangent to go on.

[–] BurgersMcSlopshot@awful.systems 9 points 1 day ago (1 children)

Lol, training data must have included videos where there was silence but on screen was a credit for translation. Silence in audio shouldn't require special "workarounds".

[–] antifuchs@awful.systems 10 points 1 day ago

The whisper model has always been pretty crappy at these things: I use a speech to text system as an assistive input method when my RSI gets bad and it has support for whisper (because that supports more languages than the developer could train on their own infrastructure/time) since maybe 2022 or so: every time someone tries to use it, they run into hallucinated inputs in pauses - even with very good silence detection and noise filtering.

This is just not a use case of interest to the people making whisper, imagine that.