Mm - hmm.
Mmm , yeah.
It does it automatically , actually. And so , um , uh , that one really benefited from the larger set. And it was also a diverse set with different noises and so forth. Uh , so , um , that , uh  that seemed to be  So , if you have that  that better recognizer that can  that can build up more parameters , and if you , um , have the natural room , which in this case has a p a pretty bad signal - to - noise ratio , then in that case , um , the right thing to do is just do  u use speaker adaptation. And  and not bother with  with this acoustic , uh , processing. But I think that that would not be true if we did some explicit noise - processing as well as , uh , the convolutional kind of things we were doing.
Mm - hmm.