In one test clip, the auto subtitles looked almost perfect. Then one auto subtitle showed gp where the speaker had actually said HP. It was one token in a long transcript, and that was exactly the problem: nothing in the editor made it look more dangerous than the clean words around it.
Disclosure: AI helped me edit and structure this article. The gp / HP mistake came from my own build, and I checked the technical details against the code and the working editor.
I ran into this while building a subtitle editor. The ASR system already returned word-level timing and confidence values, but a polished block of text made every word look equally trustworthy. The model exposed uncertainty; the interface hid it.
That led me to a narrower engineering conclusion:
Auto subtitles are drafts. An accuracy score describes a model result; it does not define a finished review workflow.
