Hmm.
Uh , but  Yeah. Mmm  Yep. So the next thing is um , I have the spreadsheet for three different system. But for this you only have to look right now on the SpeechDat - Car performance uh , because I didn't test  so  I didn't test the spectral subtraction on TI - digits yet. Uh , so you have three she sheets. One is the um proposal - one system. Actually , it 's not exe exactly proposal - one. It 's the system that Sunil just described. Um , but with uh , Wiener filtering from um , France Telecom included. Um , so this gives like fifty - seven point seven percent , uh , s uh , error rate reduction on the SpeechDat - Car data. Mmm , and then I have two sheets where it 's for a system where  uh , so it 's again the same system. But in this case we have spectral subtraction with a maximum overestimation factor of two point five. Uh , there is smoothing of the gain trajectory with some kind of uh , low - pass filter , which has forty milliseconds latency. And then , after subtraction um , I add a constant to the energies and I have two cases d where  The first case is where the constant is twenty - five DB below the mean speech energy and the other is thirty DB below. Um , and for these s two system we have like fifty - five point , uh , five - percent improvement , and fifty - eight point one. So again , it 's around fifty - six , fifty - seven. Uh
Cuz I notice the TI - digits number is exactly the same for these last two ?
Yeah , because I didn't  For the France Telecom uh , spectral subtraction included in the  our system , the TI - digits number are the right one , but not for the other system because I didn't test it yet  this system , including  with spectral subtraction on the TI - digits data. I just tested it on SpeechDat - Car.