I think another important difference is that humans won't get stuck in a loop asking you for clarification the same way several times, after 2 or 3 times they'll typically change behaviors. Eg they'll ask you to spell the word or respond with the not-understood word with a questioning tone to signal that they don't understand what that word means.

This could be implemented though. Based on the part of the sentence that is understood, figure out most likely words for the missing part and ask a specific question about it to fill the gap.

See, it's not about hard coding such behavior. I would say that it reaches human level of understanding if it automatically learns these ways of solving the problem. Asking relevant questions can be hard coded, but it doesn't equal "understanding" the problem.

I think the chinese room experiment overlooks this part of "understanding"

Exactly, when SR has a low confidence level it needs to ask for you to repeat yourself. Not just choose the highest confidence match and hope for the best.

Siri underlines words its not sure about. Then if you click it, it gives you a menu of potential other candidates.

Seems like a good approach.

That's a good start but a probably the wrong interface for it, "non-native" in the context, a command initialized by voice should present the options by voice.

It's a valid HCI solution to a technical failure mode. Once the software has advanced to the point where the AI is truly conversational, it is a watershed moment.

That's fine for dictation but of little use when driving or other eyes free scenarios.

Also. When. People. Talk. To. Siri. They. Speak. Very. Distinctly. With. Clear. Separation. Between. Words.

Or that is my observation, anyway. I don't use it myself.

I bet Siri's great at understanding what William Shatner says.