Quality seems to depend on the language. For languages with less online presence, you get absurd errors very frequently, especially if there are any typos or re

Quality seems to depend on the language. For languages with less online presence, you get absurd errors very frequently, especially if there are any typos or regional variation in spelling (common in phonetic languages, in an informal context). There was a thread today about LLMs' robustness to scrambled data; this seems heavily dependent on the quantity of training data. That's for text to text though, not sure if voice to voice would be better or worse in this regard.