Soundhound programmer here: We just haven't developed that domain of knowledge yet. The natural language part of things can absolutely understand that, but the underlying base of understanding hasn't been developed.
For example, we haven't done movie show times yet either. Doesn't mean the natural language parsing isn't advanced ;)
Re:Hound voice search NLP demo [video]
by chinpokomon on Friday June 05, 2015 @06:41AM
(#9664767)
It seems like you've turned some things off. One if the demo videos had a question like "What is the population if the capitol of the main that has the Space Needle?" When I tried that question tonight, it returned a Wikipedia link for Washington DC and second answer was strangely Pyongyang. Asking directly about the population of Washington DC, it gave that answer. Who is the President of the United States, returned a Wikipedia article about the (office of the) POTUS. I intended to follow that question with "How tall is he?" -- a question Google demonstrated at Google I/O 3 years ago.
"How is the weather tomorrow?" "How about Saturday?" "And Sunday?" That line of questioning worked surprisingly well.
So that indicates that the natural language parsing isn't super advanced.
"Traditional"-style dependency parsing should be able to solve that, and some of the Facebook AI group's recent work indicates that neural-network based parsing should be able to handle it too.
My toy QA system can handle the second case, without even doing dependency parsing.
It's not clear to me if this is a problem or not. If their voice recognition is as good as it seems that's pretty significant technology.