D: OK .
A: Mike . Mike - one ?
B: Ah .
D: We 're on ?
D: Yes , please .
D: I mean , we 're testing noise robustness
D: but let 's not get silly .
D: OK ,
D: so , uh , you 've got some , uh , Xerox things to pass out ?
D: That are A: Yeah ,
D: Yeah .
A: um .
A: Yeah .
A: Yeah , I 'm sorry for the table ,
A: but as it grows in size , uh , it .
D: Uh , so for th the last column we use our imagination .
D: OK .
B: Ah , yeah .
D: Ah .
A: Uh , yeah .
B: Uh , do you want @ @ .
D: This one 's nice , though .
D: This has nice big font .
A: Yeah .
C: Let 's see .
C: Yeah .
D: Yeah .
C: Chop !
D: When you get older you have these different perspectives .
A: So
D: I mean , lowering the word hour rate is fine , but having big font !
A: Next time we will put colors or something .
D: That 's what 's D: Yeah . It 's mostly big font .
A: Uh .
D: OK .
D: Uh A: OK , s so there is kind of summary of what has been done D: Go ahead .
A: It 's this .
D: Oh . OK .
A: Summary of experiments since , well , since last week
A: and also since the we 've started to run work on this .
A: Um . So since last week we 've started to fill the column with um uh features w with nets trained on PLP with on - line normalization
A: but with delta also ,
A: because the column was not completely D: Mm - hmm . Mm - hmm .
A: well , it 's still not completely filled ,
A: but we have more results to compare with network using without PLP
A: and finally , hhh , <comment> um ehhh <comment> PL - uh delta seems very important .
A: Uh I don't know .
A: If you take um , let 's say , anyway Aurora - two - B ,
A: so , the next t the second , uh , part of the table ,
D: Mm - hmm .
A: uh when we use the large training set using French , Spanish , and English , you have one hundred and six without delta
A: and eighty - nine with the delta .
D: a And again all of these numbers are with a hundred percent being , uh , the baseline performance ,
A: Yeah ,
A: on the baseline , yeah .
D: but with a mel cepstra system going straight into the HTK ?
A: So A: Yeah . Yeah .
D: Yes .
A: So now we see that the gap between the different training set is much uh uh much smaller
C: It 's out of the way .
A: um A: But , actually , um , for English training on TIMIT is still better than the other languages .
A: And
A: Mmm , Yeah .
A: And f also for Italian , actually .
A: If you take the second set of experiment for Italian ,
A: so , the mismatched condition ,
D: Mm - hmm .
A: um when we use the training on TIMIT
A: so , it 's multi - English ,
A: we have a ninety - one number ,
D: Mm - hmm .
A: and training with other languages is a little bit worse .
D: Um Oh , I see .
D: Down near the bottom of this sheet .
D: Uh , <comment> yes .
A: So ,
A: yeah .
D: OK .
A: And , yeah , and here the gap is still more important between using delta and not using delta .
D: Yes .
A: If y if I take the training s the large training set , it 's we have one hundred and seventy - two ,
D: Yeah .
A: and one hundred and four when we use delta .
D: Mm - hmm .
A: Uh . Even if the contexts used is quite the same ,
A: because without delta we use seventeenths seventeen frames .
A: Uh .
A: Yeah , um , so the second point is that we have no single cross - language experiments , uh , that we did not have last week .
A: Uh , so this is training the net on French only ,
A: or on English only ,
A: and testing on Italian .
D: Mm - hmm .
A: And training the net on French only
A: and Spanish only
A: and testing on , uh TI - digits .
D: Mm - hmm .
A: And ,
A: fff <comment> um ,
A: yeah .
A: What we see is that these nets are not as good ,
A: except for the multi - English , which is always one of the best .
A: Yeah ,
A: then we started to work on a large dat database containing , uh , sentences from the French , from the Spanish , from the TIMIT , from SPINE , uh from <comment> uh English digits , and from Italian digits .
A: So this is the another line another set of lines in the table .
D: Ah , yes .
A: Uh , @ @ with SPINE
D: Mm - hmm .
A: and uh , actually we did this before knowing the result of all the data ,
A: uh , so we have to to redo the uh the experiment training the net with , uh PLP , but with delta .
D: Mm - hmm .
A: But
A: um this this net performed quite well .
A: Well ,
A: it 's it 's better than the net using French , Spanish , and English only .
A: Uh .
A: So ,
A: uh , yeah .