But the error happens in 'audio to text' part, so text prompt won't solve it. The way to fix it is probably fine-tuning the underlying audio to text model.
Doing audio-to-text requires having a statistical model for what word or phrase a piece of sound is most likely to be. Without context, you can't do better than ranking the most likely candidates where a common word is more likely than an uncommon one. Having a task-specific dictionary at that point would help.
One could also imagine doing it at the summary step where the AI could simply be asked to do phonetic analysis. "Here is a transcription of a meeting. Here is a list of terms/names/participants etc. Given the transcription, the meeting context/topics and assuming the transcriptor has made errors, replace similarly sounding words and terms with more likely ones from the context"
One could also imagine doing it at the summary step where the AI could simply be asked to do phonetic analysis. "Here is a transcription of a meeting. Here is a list of terms/names/participants etc. Given the transcription, the meeting context/topics and assuming the transcriptor has made errors, replace similarly sounding words and terms with more likely ones from the context"