I don't know about much better, but I like Whisper's ability to subtitle foreign language content on YouTube that (somehow) doesn't have auto-generated subs. For example some relatively obscure comedy sketches from Germany where I'm not quite fluent enough to go by ear.

10 years ago you'd be searching through random databases to see if someone had synchronized subtitles for the exact copy of the video that you had. Or older lecture videos that don't have transcripts. Many courses had to, in order to comply with federal funding, but not all. And lots of international courses don't have this requirement at all (for example some great introductory CS/maths courses from German + Swiss institutions). Also think about taking this auto generated output and then generating summaries for lecture notes, reading recommendations - this sort of stuff is what LLMs are great at.

You can do some clever things like take the foreign sub, have Whisper also transcribe it and then ask a big model like Gemini to go line by line and check the translation to English. This can include accounting for common transcription errors or idiomatic difference between langauges. I do it in Cursor to keep track of what the model has changed and for easy rollback. It's often good enough to correct mis-heard words that would be garbled through a cheaper model. And you can even query the model to ask about why a particular translation was made and what would be a more natural way to say the same thing. Sometimes it even figures out jokes. It's not a fast or fully automatic process, but the quality can be extremely good if you put some time into reviewing.

Having 90% of this be possible offline/open access is also very impressive. I've not tried newer OSS models like Qwen3 but I imagine it'd do a decent job of the cleanup.