So , the next point , yeah , we 've had some discussion with Steve and Shawn , um , about their um , uh , articulatory stuff , um. So we 'll perhaps start something next week.
Mm - hmm.
Um , discussion with Hynek , Sunil and Pratibha for trying to plug in their our  our networks with their  within their block diagram , uh , where to plug in the  the network , uh , after the  the feature , before as um a as a plugin or as a anoth another path , discussion about multi - band and TRAPS , um , actually Hynek would like to see , perhaps if you remember the block diagram there is , uh , temporal LDA followed b by a spectral LDA for each uh critical band. And he would like to replace these by a network which would , uh , make the system look like a TRAP. Well , basically , it would be a TRAP system. Basically , this is a TRAP system  kind of TRAP system , I mean , but where the neural network are replaced by LDA. Hmm.  Um , yeah , and about multi - band , uh , I started multi - band MLP trainings , um mmh  Actually , I w I w hhh  prefer to do exactly what I did when I was in Belgium. So I take exactly the same configurations , seven bands with nine frames of context , and we just train on TIMIT , and on the large database , so , with SPINE and everything. And , mmm , I 'm starting to train also , networks with larger contexts. So , this would  would be something between TRAPS and multi - band because we still have quite large bands , and  but with a lot of context also. So Um Yeah , we still have to work on Finnish , um , basically , to make a decision on which MLP can be the best across the different languages. For the moment it 's the TIMIT network , and perhaps the network trained on everything. So. Now we can test these two networks on  with  with delta and large networks. Well , test them also on Finnish
Mmm.