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Yeah. So if we if we can live with the latency or cut the latencies elsewhere , then then that would be a , uh , good thing.
|
Yeah. Yeah.
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Um , anybody has anybody you guys or or Naren , uh , somebody , tried the , uh , um , second th second stream thing ? Uh.
|
Oh , I just I just h put the second stream in place and , uh ran one experiment , but just like just to know that everything is fine.
| false |
QMSum_194
|
Yeah. Yeah.
|
Um , anybody has anybody you guys or or Naren , uh , somebody , tried the , uh , um , second th second stream thing ? Uh.
|
Oh , I just I just h put the second stream in place and , uh ran one experiment , but just like just to know that everything is fine.
|
Uh - huh.
| false |
QMSum_194
|
Um , anybody has anybody you guys or or Naren , uh , somebody , tried the , uh , um , second th second stream thing ? Uh.
|
Oh , I just I just h put the second stream in place and , uh ran one experiment , but just like just to know that everything is fine.
|
Uh - huh.
|
So it was like , uh , forty - five cepstrum plus twenty - three mel log mel.
| false |
QMSum_194
|
Oh , I just I just h put the second stream in place and , uh ran one experiment , but just like just to know that everything is fine.
|
Uh - huh.
|
So it was like , uh , forty - five cepstrum plus twenty - three mel log mel.
|
Yeah.
| false |
QMSum_194
|
Uh - huh.
|
So it was like , uh , forty - five cepstrum plus twenty - three mel log mel.
|
Yeah.
|
And and , just , like , it gave me the baseline performance of the Aurora , which is like zero improvement.
| false |
QMSum_194
|
So it was like , uh , forty - five cepstrum plus twenty - three mel log mel.
|
Yeah.
|
And and , just , like , it gave me the baseline performance of the Aurora , which is like zero improvement.
|
Yeah. Yeah.
| false |
QMSum_194
|
Yeah.
|
And and , just , like , it gave me the baseline performance of the Aurora , which is like zero improvement.
|
Yeah. Yeah.
|
So I just tried it on Italian just to know that everything is But I I didn't export anything out of it because it was , like , a weird feature set.
| false |
QMSum_194
|
And and , just , like , it gave me the baseline performance of the Aurora , which is like zero improvement.
|
Yeah. Yeah.
|
So I just tried it on Italian just to know that everything is But I I didn't export anything out of it because it was , like , a weird feature set.
|
Yeah.
| false |
QMSum_194
|
Yeah. Yeah.
|
So I just tried it on Italian just to know that everything is But I I didn't export anything out of it because it was , like , a weird feature set.
|
Yeah.
|
So.
| false |
QMSum_194
|
So I just tried it on Italian just to know that everything is But I I didn't export anything out of it because it was , like , a weird feature set.
|
Yeah.
|
So.
|
Yeah. Well , what I think , you know , would be more what you 'd want to do is is is , uh , put it into another neural net. Right ?
| false |
QMSum_194
|
Yeah.
|
So.
|
Yeah. Well , what I think , you know , would be more what you 'd want to do is is is , uh , put it into another neural net. Right ?
|
Mm - hmm.
| false |
QMSum_194
|
So.
|
Yeah. Well , what I think , you know , would be more what you 'd want to do is is is , uh , put it into another neural net. Right ?
|
Mm - hmm.
|
Yeah , yeah , yeah , yeah.
| false |
QMSum_194
|
Yeah. Well , what I think , you know , would be more what you 'd want to do is is is , uh , put it into another neural net. Right ?
|
Mm - hmm.
|
Yeah , yeah , yeah , yeah.
|
And then But , yeah , we 're we 're not quite there yet. So we have to figure out the neural nets , I guess.
| false |
QMSum_194
|
Mm - hmm.
|
Yeah , yeah , yeah , yeah.
|
And then But , yeah , we 're we 're not quite there yet. So we have to figure out the neural nets , I guess.
|
Yeah.
| false |
QMSum_194
|
Yeah , yeah , yeah , yeah.
|
And then But , yeah , we 're we 're not quite there yet. So we have to figure out the neural nets , I guess.
|
Yeah.
|
The uh , other thing I was wondering was , um , if the neural net , um , has any because of the different noise con unseen noise conditions for the neural net , where , like , you train it on those four noise conditions , while you are feeding it with , like , a additional some four plus some f few more conditions which it hasn't seen , actually ,
| false |
QMSum_194
|
And then But , yeah , we 're we 're not quite there yet. So we have to figure out the neural nets , I guess.
|
Yeah.
|
The uh , other thing I was wondering was , um , if the neural net , um , has any because of the different noise con unseen noise conditions for the neural net , where , like , you train it on those four noise conditions , while you are feeding it with , like , a additional some four plus some f few more conditions which it hasn't seen , actually ,
|
Mm - hmm.
| false |
QMSum_194
|
Yeah.
|
The uh , other thing I was wondering was , um , if the neural net , um , has any because of the different noise con unseen noise conditions for the neural net , where , like , you train it on those four noise conditions , while you are feeding it with , like , a additional some four plus some f few more conditions which it hasn't seen , actually ,
|
Mm - hmm.
|
from the f f while testing.
| false |
QMSum_194
|
The uh , other thing I was wondering was , um , if the neural net , um , has any because of the different noise con unseen noise conditions for the neural net , where , like , you train it on those four noise conditions , while you are feeding it with , like , a additional some four plus some f few more conditions which it hasn't seen , actually ,
|
Mm - hmm.
|
from the f f while testing.
|
Yeah , yeah. Right.
| false |
QMSum_194
|
Mm - hmm.
|
from the f f while testing.
|
Yeah , yeah. Right.
|
Um instead of just h having c uh , those cleaned up t cepstrum , sh should we feed some additional information , like The the We have the VAD flag. I mean , should we f feed the VAD flag , also , at the input so that it it has some additional discriminating information at the input ?
| false |
QMSum_194
|
from the f f while testing.
|
Yeah , yeah. Right.
|
Um instead of just h having c uh , those cleaned up t cepstrum , sh should we feed some additional information , like The the We have the VAD flag. I mean , should we f feed the VAD flag , also , at the input so that it it has some additional discriminating information at the input ?
|
Hmm - hmm ! Um
| false |
QMSum_194
|
Yeah , yeah. Right.
|
Um instead of just h having c uh , those cleaned up t cepstrum , sh should we feed some additional information , like The the We have the VAD flag. I mean , should we f feed the VAD flag , also , at the input so that it it has some additional discriminating information at the input ?
|
Hmm - hmm ! Um
|
Wh - uh , the the VAD what ?
| false |
QMSum_194
|
Um instead of just h having c uh , those cleaned up t cepstrum , sh should we feed some additional information , like The the We have the VAD flag. I mean , should we f feed the VAD flag , also , at the input so that it it has some additional discriminating information at the input ?
|
Hmm - hmm ! Um
|
Wh - uh , the the VAD what ?
|
We have the VAD information also available at the back - end.
| false |
QMSum_194
|
Hmm - hmm ! Um
|
Wh - uh , the the VAD what ?
|
We have the VAD information also available at the back - end.
|
Uh - huh.
| false |
QMSum_194
|
Wh - uh , the the VAD what ?
|
We have the VAD information also available at the back - end.
|
Uh - huh.
|
So if it is something the neural net is not able to discriminate the classes
| false |
QMSum_194
|
We have the VAD information also available at the back - end.
|
Uh - huh.
|
So if it is something the neural net is not able to discriminate the classes
|
Yeah.
| false |
QMSum_194
|
Uh - huh.
|
So if it is something the neural net is not able to discriminate the classes
|
Yeah.
|
I mean Because most of it is sil I mean , we have dropped some silence f We have dropped so silence frames ?
| false |
QMSum_194
|
So if it is something the neural net is not able to discriminate the classes
|
Yeah.
|
I mean Because most of it is sil I mean , we have dropped some silence f We have dropped so silence frames ?
|
Mm - hmm.
| false |
QMSum_194
|
Yeah.
|
I mean Because most of it is sil I mean , we have dropped some silence f We have dropped so silence frames ?
|
Mm - hmm.
|
No , we haven't dropped silence frames still.
| false |
QMSum_194
|
I mean Because most of it is sil I mean , we have dropped some silence f We have dropped so silence frames ?
|
Mm - hmm.
|
No , we haven't dropped silence frames still.
|
Uh , still not. Yeah.
| false |
QMSum_194
|
Mm - hmm.
|
No , we haven't dropped silence frames still.
|
Uh , still not. Yeah.
|
Yeah. So
| false |
QMSum_194
|
No , we haven't dropped silence frames still.
|
Uh , still not. Yeah.
|
Yeah. So
|
Th
| false |
QMSum_194
|
Uh , still not. Yeah.
|
Yeah. So
|
Th
|
the b b biggest classification would be the speech and silence. So , by having an additional , uh , feature which says " this is speech and this is nonspeech " , I mean , it certainly helps in some unseen noise conditions for the neural net.
| false |
QMSum_194
|
Yeah. So
|
Th
|
the b b biggest classification would be the speech and silence. So , by having an additional , uh , feature which says " this is speech and this is nonspeech " , I mean , it certainly helps in some unseen noise conditions for the neural net.
|
What Do y do you have that feature available for the test data ?
| false |
QMSum_194
|
Th
|
the b b biggest classification would be the speech and silence. So , by having an additional , uh , feature which says " this is speech and this is nonspeech " , I mean , it certainly helps in some unseen noise conditions for the neural net.
|
What Do y do you have that feature available for the test data ?
|
Well , I mean , we have we are transferring the VAD to the back - end feature to the back - end. Because we are dropping it at the back - end after everything all the features are computed.
| false |
QMSum_194
|
the b b biggest classification would be the speech and silence. So , by having an additional , uh , feature which says " this is speech and this is nonspeech " , I mean , it certainly helps in some unseen noise conditions for the neural net.
|
What Do y do you have that feature available for the test data ?
|
Well , I mean , we have we are transferring the VAD to the back - end feature to the back - end. Because we are dropping it at the back - end after everything all the features are computed.
|
Oh , oh , I see.
| false |
QMSum_194
|
What Do y do you have that feature available for the test data ?
|
Well , I mean , we have we are transferring the VAD to the back - end feature to the back - end. Because we are dropping it at the back - end after everything all the features are computed.
|
Oh , oh , I see.
|
So
| false |
QMSum_194
|
Well , I mean , we have we are transferring the VAD to the back - end feature to the back - end. Because we are dropping it at the back - end after everything all the features are computed.
|
Oh , oh , I see.
|
So
|
I see.
| false |
QMSum_194
|
Oh , oh , I see.
|
So
|
I see.
|
so the neural so that is coming from a separate neural net or some VAD.
| false |
QMSum_194
|
So
|
I see.
|
so the neural so that is coming from a separate neural net or some VAD.
|
OK. OK.
| false |
QMSum_194
|
I see.
|
so the neural so that is coming from a separate neural net or some VAD.
|
OK. OK.
|
Which is which is certainly giving a
| false |
QMSum_194
|
so the neural so that is coming from a separate neural net or some VAD.
|
OK. OK.
|
Which is which is certainly giving a
|
So you 're saying , feed that , also , into the neural net.
| false |
QMSum_194
|
OK. OK.
|
Which is which is certainly giving a
|
So you 're saying , feed that , also , into the neural net.
|
to Yeah. So it it 's an additional discriminating information.
| false |
QMSum_194
|
Which is which is certainly giving a
|
So you 're saying , feed that , also , into the neural net.
|
to Yeah. So it it 's an additional discriminating information.
|
Yeah. Yeah. Right.
| false |
QMSum_194
|
So you 're saying , feed that , also , into the neural net.
|
to Yeah. So it it 's an additional discriminating information.
|
Yeah. Yeah. Right.
|
So that
| false |
QMSum_194
|
to Yeah. So it it 's an additional discriminating information.
|
Yeah. Yeah. Right.
|
So that
|
You could feed it into the neural net. The other thing you could do is just , um , p modify the , uh , output probabilities of the of the , uh , uh , um , neural net , tandem neural net , based on the fact that you have a silence probability.
| false |
QMSum_194
|
Yeah. Yeah. Right.
|
So that
|
You could feed it into the neural net. The other thing you could do is just , um , p modify the , uh , output probabilities of the of the , uh , uh , um , neural net , tandem neural net , based on the fact that you have a silence probability.
|
Mm - hmm.
| false |
QMSum_194
|
So that
|
You could feed it into the neural net. The other thing you could do is just , um , p modify the , uh , output probabilities of the of the , uh , uh , um , neural net , tandem neural net , based on the fact that you have a silence probability.
|
Mm - hmm.
|
Right ?
| false |
QMSum_194
|
You could feed it into the neural net. The other thing you could do is just , um , p modify the , uh , output probabilities of the of the , uh , uh , um , neural net , tandem neural net , based on the fact that you have a silence probability.
|
Mm - hmm.
|
Right ?
|
Mm - hmm.
| false |
QMSum_194
|
Mm - hmm.
|
Right ?
|
Mm - hmm.
|
So you have an independent estimator of what the silence probability is , and you could multiply the two things , and renormalize.
| false |
QMSum_194
|
Right ?
|
Mm - hmm.
|
So you have an independent estimator of what the silence probability is , and you could multiply the two things , and renormalize.
|
Yeah.
| false |
QMSum_194
|
Mm - hmm.
|
So you have an independent estimator of what the silence probability is , and you could multiply the two things , and renormalize.
|
Yeah.
|
Uh , I mean , you 'd have to do the nonlinearity part and deal with that. Uh , I mean , go backwards from what the nonlinearity would , you know would be.
| false |
QMSum_194
|
So you have an independent estimator of what the silence probability is , and you could multiply the two things , and renormalize.
|
Yeah.
|
Uh , I mean , you 'd have to do the nonlinearity part and deal with that. Uh , I mean , go backwards from what the nonlinearity would , you know would be.
|
Through t to the soft max.
| false |
QMSum_194
|
Yeah.
|
Uh , I mean , you 'd have to do the nonlinearity part and deal with that. Uh , I mean , go backwards from what the nonlinearity would , you know would be.
|
Through t to the soft max.
|
But but , uh
| false |
QMSum_194
|
Uh , I mean , you 'd have to do the nonlinearity part and deal with that. Uh , I mean , go backwards from what the nonlinearity would , you know would be.
|
Through t to the soft max.
|
But but , uh
|
Yeah , so maybe , yeah , when
| false |
QMSum_194
|
Through t to the soft max.
|
But but , uh
|
Yeah , so maybe , yeah , when
|
But in principle wouldn't it be better to feed it in ? And let the net do that ?
| false |
QMSum_194
|
But but , uh
|
Yeah , so maybe , yeah , when
|
But in principle wouldn't it be better to feed it in ? And let the net do that ?
|
Well , u Not sure.
| false |
QMSum_194
|
Yeah , so maybe , yeah , when
|
But in principle wouldn't it be better to feed it in ? And let the net do that ?
|
Well , u Not sure.
|
Hmm.
| false |
QMSum_194
|
But in principle wouldn't it be better to feed it in ? And let the net do that ?
|
Well , u Not sure.
|
Hmm.
|
I mean , let 's put it this way. I mean , y you you have this complicated system with thousands and thousand parameters
| false |
QMSum_194
|
Well , u Not sure.
|
Hmm.
|
I mean , let 's put it this way. I mean , y you you have this complicated system with thousands and thousand parameters
|
Yeah.
| false |
QMSum_194
|
Hmm.
|
I mean , let 's put it this way. I mean , y you you have this complicated system with thousands and thousand parameters
|
Yeah.
|
and you can tell it , uh , " Learn this thing. " Or you can say , " It 's silence ! Go away ! " I mean , I mean , i Doesn't ? I think I think the second one sounds a lot more direct.
| false |
QMSum_194
|
I mean , let 's put it this way. I mean , y you you have this complicated system with thousands and thousand parameters
|
Yeah.
|
and you can tell it , uh , " Learn this thing. " Or you can say , " It 's silence ! Go away ! " I mean , I mean , i Doesn't ? I think I think the second one sounds a lot more direct.
|
What what if you
| false |
QMSum_194
|
Yeah.
|
and you can tell it , uh , " Learn this thing. " Or you can say , " It 's silence ! Go away ! " I mean , I mean , i Doesn't ? I think I think the second one sounds a lot more direct.
|
What what if you
|
Uh.
| false |
QMSum_194
|
and you can tell it , uh , " Learn this thing. " Or you can say , " It 's silence ! Go away ! " I mean , I mean , i Doesn't ? I think I think the second one sounds a lot more direct.
|
What what if you
|
Uh.
|
Right. So , what if you then , uh since you know this , what if you only use the neural net on the speech portions ?
| false |
QMSum_194
|
What what if you
|
Uh.
|
Right. So , what if you then , uh since you know this , what if you only use the neural net on the speech portions ?
|
Well , uh ,
| false |
QMSum_194
|
Uh.
|
Right. So , what if you then , uh since you know this , what if you only use the neural net on the speech portions ?
|
Well , uh ,
|
That 's what
| false |
QMSum_194
|
Right. So , what if you then , uh since you know this , what if you only use the neural net on the speech portions ?
|
Well , uh ,
|
That 's what
|
Well , I guess that 's the same. Uh , that 's similar.
| false |
QMSum_194
|
Well , uh ,
|
That 's what
|
Well , I guess that 's the same. Uh , that 's similar.
|
Yeah , I mean , y you 'd have to actually run it continuously ,
| false |
QMSum_194
|
That 's what
|
Well , I guess that 's the same. Uh , that 's similar.
|
Yeah , I mean , y you 'd have to actually run it continuously ,
|
But I mean I mean , train the net only on
| false |
QMSum_194
|
Well , I guess that 's the same. Uh , that 's similar.
|
Yeah , I mean , y you 'd have to actually run it continuously ,
|
But I mean I mean , train the net only on
|
but it 's @ @ Well , no , you want to train on on the nonspeech also , because that 's part of what you 're learning in it , to to to generate , that it 's it has to distinguish between.
| false |
QMSum_194
|
Yeah , I mean , y you 'd have to actually run it continuously ,
|
But I mean I mean , train the net only on
|
but it 's @ @ Well , no , you want to train on on the nonspeech also , because that 's part of what you 're learning in it , to to to generate , that it 's it has to distinguish between.
|
Speech.
| false |
QMSum_194
|
But I mean I mean , train the net only on
|
but it 's @ @ Well , no , you want to train on on the nonspeech also , because that 's part of what you 're learning in it , to to to generate , that it 's it has to distinguish between.
|
Speech.
|
But I mean , if you 're gonna if you 're going to multiply the output of the net by this other decision , uh , would then you don't care about whether the net makes that distinction , right ?
| false |
QMSum_194
|
but it 's @ @ Well , no , you want to train on on the nonspeech also , because that 's part of what you 're learning in it , to to to generate , that it 's it has to distinguish between.
|
Speech.
|
But I mean , if you 're gonna if you 're going to multiply the output of the net by this other decision , uh , would then you don't care about whether the net makes that distinction , right ?
|
Well , yeah. But this other thing isn't perfect.
| false |
QMSum_194
|
Speech.
|
But I mean , if you 're gonna if you 're going to multiply the output of the net by this other decision , uh , would then you don't care about whether the net makes that distinction , right ?
|
Well , yeah. But this other thing isn't perfect.
|
Ah.
| false |
QMSum_194
|
But I mean , if you 're gonna if you 're going to multiply the output of the net by this other decision , uh , would then you don't care about whether the net makes that distinction , right ?
|
Well , yeah. But this other thing isn't perfect.
|
Ah.
|
So that you bring in some information from the net itself.
| false |
QMSum_194
|
Well , yeah. But this other thing isn't perfect.
|
Ah.
|
So that you bring in some information from the net itself.
|
Right , OK. That 's a good point.
| false |
QMSum_194
|
Ah.
|
So that you bring in some information from the net itself.
|
Right , OK. That 's a good point.
|
Yeah. Now the only thing that that bothers me about all this is that I I I The the fact i i It 's sort of bothersome that you 're getting more deletions.
| false |
QMSum_194
|
So that you bring in some information from the net itself.
|
Right , OK. That 's a good point.
|
Yeah. Now the only thing that that bothers me about all this is that I I I The the fact i i It 's sort of bothersome that you 're getting more deletions.
|
Yeah. But So I might maybe look at , is it due to the fact that um , the probability of the silence at the output of the network , is , uh ,
| false |
QMSum_194
|
Right , OK. That 's a good point.
|
Yeah. Now the only thing that that bothers me about all this is that I I I The the fact i i It 's sort of bothersome that you 're getting more deletions.
|
Yeah. But So I might maybe look at , is it due to the fact that um , the probability of the silence at the output of the network , is , uh ,
|
Is too high.
| false |
QMSum_194
|
Yeah. Now the only thing that that bothers me about all this is that I I I The the fact i i It 's sort of bothersome that you 're getting more deletions.
|
Yeah. But So I might maybe look at , is it due to the fact that um , the probability of the silence at the output of the network , is , uh ,
|
Is too high.
|
too too high or
| false |
QMSum_194
|
Yeah. But So I might maybe look at , is it due to the fact that um , the probability of the silence at the output of the network , is , uh ,
|
Is too high.
|
too too high or
|
Yeah. So maybe So
| false |
QMSum_194
|
Is too high.
|
too too high or
|
Yeah. So maybe So
|
If it 's the case , then multiplying it again by i by something ?
| false |
QMSum_194
|
too too high or
|
Yeah. So maybe So
|
If it 's the case , then multiplying it again by i by something ?
|
It may not be it
| false |
QMSum_194
|
Yeah. So maybe So
|
If it 's the case , then multiplying it again by i by something ?
|
It may not be it
|
Yeah.
| false |
QMSum_194
|
If it 's the case , then multiplying it again by i by something ?
|
It may not be it
|
Yeah.
|
Mm - hmm.
| false |
QMSum_194
|
It may not be it
|
Yeah.
|
Mm - hmm.
|
Yeah , it it may be too it 's too high in a sense , like , everything is more like a , um , flat probability.
| false |
QMSum_194
|
Yeah.
|
Mm - hmm.
|
Yeah , it it may be too it 's too high in a sense , like , everything is more like a , um , flat probability.
|
Yeah.
| false |
QMSum_194
|
Mm - hmm.
|
Yeah , it it may be too it 's too high in a sense , like , everything is more like a , um , flat probability.
|
Yeah.
|
Oh - eee - hhh.
| false |
QMSum_194
|
Yeah , it it may be too it 's too high in a sense , like , everything is more like a , um , flat probability.
|
Yeah.
|
Oh - eee - hhh.
|
So , like , it 's not really doing any distinction between speech and nonspeech
| false |
QMSum_194
|
Yeah.
|
Oh - eee - hhh.
|
So , like , it 's not really doing any distinction between speech and nonspeech
|
Uh , yeah.
| false |
QMSum_194
|
Oh - eee - hhh.
|
So , like , it 's not really doing any distinction between speech and nonspeech
|
Uh , yeah.
|
or , I mean , different among classes.
| false |
QMSum_194
|
So , like , it 's not really doing any distinction between speech and nonspeech
|
Uh , yeah.
|
or , I mean , different among classes.
|
Yeah.
| false |
QMSum_194
|
Uh , yeah.
|
or , I mean , different among classes.
|
Yeah.
|
Mm - hmm.
| false |
QMSum_194
|
or , I mean , different among classes.
|
Yeah.
|
Mm - hmm.
|
Be interesting to look at the Yeah , for the I wonder if you could do this. But if you look at the , um , highly mism high mismat the output of the net on the high mismatch case and just look at , you know , the distribution versus the the other ones , do you do you see more peaks or something ?
| false |
QMSum_194
|
Yeah.
|
Mm - hmm.
|
Be interesting to look at the Yeah , for the I wonder if you could do this. But if you look at the , um , highly mism high mismat the output of the net on the high mismatch case and just look at , you know , the distribution versus the the other ones , do you do you see more peaks or something ?
|
Yeah. Yeah , like the entropy of the the output ,
| false |
QMSum_194
|
Mm - hmm.
|
Be interesting to look at the Yeah , for the I wonder if you could do this. But if you look at the , um , highly mism high mismat the output of the net on the high mismatch case and just look at , you know , the distribution versus the the other ones , do you do you see more peaks or something ?
|
Yeah. Yeah , like the entropy of the the output ,
|
Yeah.
| false |
QMSum_194
|
Be interesting to look at the Yeah , for the I wonder if you could do this. But if you look at the , um , highly mism high mismat the output of the net on the high mismatch case and just look at , you know , the distribution versus the the other ones , do you do you see more peaks or something ?
|
Yeah. Yeah , like the entropy of the the output ,
|
Yeah.
|
Yeah , for instance.
| false |
QMSum_194
|
Yeah. Yeah , like the entropy of the the output ,
|
Yeah.
|
Yeah , for instance.
|
or
| false |
QMSum_194
|
Yeah.
|
Yeah , for instance.
|
or
|
But I bu
| false |
QMSum_194
|
Yeah , for instance.
|
or
|
But I bu
|
It it seems that the VAD network doesn't Well , it doesn't drop , uh , too many frames because the dele the number of deletion is reasonable. But it 's just when we add the tandem , the final MLP , and then
| false |
QMSum_194
|
or
|
But I bu
|
It it seems that the VAD network doesn't Well , it doesn't drop , uh , too many frames because the dele the number of deletion is reasonable. But it 's just when we add the tandem , the final MLP , and then
|
Yeah. Now the only problem is you don't want to ta I guess wait for the output of the VAD before you can put something into the other system ,
| false |
QMSum_194
|
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