They use all kinds of languages with all kinds of accents and and ticks.
In my experience, and from the time I did a bit of NLP the situations is often along the line of. It works for mostly accent free simple English. Fails to get anywhere usable on most other languages and or accents. Sure that is to some degree because of missing training data. But for a consumer this doesn't change that for very many consumers this features work terrible bad.
Just out interest I tried out the youtube auto generated subtitle for a german video, but even at the parts where the text was super clear and well pronounced the result was hardly differentiable from randomly picking arbitrary words. It wasn't even that the algorithm choose similar sounding word. They where completely different words in many case. I think in a sentence of ~10 words in average 1 or 2 where correct. And that was at the parts where the text was unusually clear understandable. At other parts it wasn't even able to recognize that there where words...
Just imagine all the idioms they have to account for in these voice algorithms. I know in German they also handle "halb neun" correctly as 8:30.
Although it does have a problem with hours over 20 (“22 o’clock” becomes 20:02 for some reason, possibly because of my thick Italian accent).
Again, whether I would understand them or not, no one to my knowledge speaks like that in U. S. English. It is a great example to use to show the quirks of language. It is a bad example to use to show that Siri "doesn't even support 24 hour time - at least in English".
And in any case i said eighteen not eight a m.