Yeah.
And the other one is for the distant microphone
Ah , OK.
which has more noise so , it 's logical that  it performs worse. So as I was saying , the miss rate is quite important uh , which means that we tend to label speech as  as a silence. And , uh , I didn't analyze further yet , but  I think it 's  it may be due to the fricative sounds which may be  in noisy condition maybe label  labelled as silence. And it may also be due to the alignment because  well , the reference alignment. Because right now I just use an alignment obtained from  from a system trained on channel zero. And I checked it a little bit but there might be alignment errors. Um , yeah , e like the fact that   the  the models tend to align their first state on silence and their last state o on silence also. So the reference  reference alignment would label as speech some silence frame before speech and after speech. This is something that we already noticed before when  mmm , So this cus this could also explain , uh , the high miss rate maybe. Uh