That’s the point. They’re hallucination engines. They pattern match and fill holes by design. It doesn’t matter if the match isn’t perfect, it will patch it over with nonsense instead.
Same, I’d say it’s way better than most other transcription tools I’ve used, but it does need to be monitored to catch when it starts going off the rails.
How can it be that bad?
I’ve used zoom’s ai transcriptions, for far less mission critical stuff, and it’s generally fine, (I still wouldn’t trust it for medical purposes)
Zoom ai transcriptions also make things up.
That’s the point. They’re hallucination engines. They pattern match and fill holes by design. It doesn’t matter if the match isn’t perfect, it will patch it over with nonsense instead.
Whisper has been known to hallucinate during long moments of silence. Most of their examples though are most likely due to bad audio quality.
I use whisper quite a bit and it will fumble a word here or there but never to the extent that is being shown in the article.
Same, I’d say it’s way better than most other transcription tools I’ve used, but it does need to be monitored to catch when it starts going off the rails.
It’s not the transcripts that are the issue here. It’s that the transcripts are being interpreted by the model to give information.