A: Mm - hmm .
B: Um .
B: But I think , you know , at this point our major concern is making the performance better
B: and and , um , if , uh , something has to take a little longer in latency in order to do it that 's you know , a secondary issue .
A: Mm - hmm .
B: But if we get told otherwise then , you know , we may have to c clamp down a bit more .
D: Mmm .
C: So , the one one one difference is that was there is like we tried computing the delta and then doing the frame - dropping .
D: S
E: Mm - hmm .
C: The earlier system was do the frame - dropping and then compute the delta on the B: Uh - huh .
C: So this A: Which could be a kind of a funny delta .
A: Right ?
C: Yeah .
B: Oh ,
B: oh .
B: So that 's fixed in this .
B: Yeah , we talked about that .
C: Yeah .
E: Yeah . Uh - huh .
C: So we have no delta . And then B: Good .
C: So the frame - dropping is the last thing that we do .
C: So , yeah , what we do is we compute the silence probability ,
C: convert it to that binary flag ,
B: Uh - huh .
C: and then in the end you c up upsample it to match the final features number of E: Mm - hmm .
A: Did that help then ?
C: It seems to be helping on the well - matched condition .
C: So that 's why this improvement I got from the last result .
C: So . And it actually r reduced a little bit on the high mismatch ,
C: so in the final weightage it 's b b better
C: because the well - matched is still weighted more than B: So , @ @ I mean , you were doing a lot of changes .
B: Did you happen to notice how much , uh , the change was due to just this frame - dropping problem ?
B: What about this ?
C: Uh , y you had something on it .
C: Right ?
E: Just the frame - dropping problem .
E: Yeah . But it 's it 's difficult .
E: Sometime we we change two two things together
E: and But it 's around maybe it 's less than one percent .
B: Uh - huh .
C: Yeah .
E: It B: Well . But like we 're saying , if there 's four or five things like that then pretty sho soon you 're talking real improvement .
E: Yeah .
E: Yeah . And it E: Yeah .
E: And then we have to be careful with that also with the neural net
B: Yeah .
E: because in <comment> the proposal the neural net was also , uh , working on after frame - dropping .
B: Mm - hmm .
E: Um .
B: Oh , that 's a real good point .
E: So . Well , we 'll have to be E: to do the same kind of correction .
B: It might be hard if it 's at the server side .
B: Right ?
E: Mmm . Well , we can do the frame - dropping on the server side
E: or we can just be careful at the terminal side to send a couple of more frames before and after ,
E: and So .
E: I think it 's OK .
B: OK .
A: You have , um A: So when you A: Uh , maybe I don't quite understand how this works ,
A: but , um , couldn't you just send all of the frames , but mark the ones that are supposed to be dropped ?
A: Cuz you have a bunch more bandwidth .
A: Right ?
B: Well , you could .
B: Yeah . I mean , it it always seemed to us that it would be kind of nice to in addition to , uh , reducing insertions , actually use up less bandwidth .
A: Yeah . Yeah .
B: But nobody seems to have cared about that in this evaluation .
A: And that way the net could use B: So .
A: If the net 's on the server side then it could use all of the frames .
C: Yes , it could be .
C: It 's , like , you mean you just transferred everything
C: and then finally drop the frames after the neural net .
C: Right ?
A: Mm - hmm .
E: Mm - hmm .
C: Yeah . That 's that 's one thing which A: But you could even mark them , before they get to the server .
C: Yeah . Right now we are C: Uh , ri
C: Right now what wha what we did is , like , we just mark we just have this additional bit which goes around the features , saying it 's currently a it 's a speech or a nonspeech .
A: Oh ,
A: OK .
C: So there is no frame - dropping till the final features , like , including the deltas are computed .
A: I see .
C: And after the deltas are computed , you just pick up the ones that are marked silence and then drop them .
A: Mm - hmm .
A: I see .
B: So it would be more or less the same thing with the neural net , I guess , actually .
E: Mm - hmm .
A: I see .
C: So . Yeah , that 's what that 's what that 's what , uh , this is doing right now .
A: I see .
A: OK .
B: Yeah .
E: Mm - hmm .