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Oh , oh. I see.
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Mm - hmm.
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if it gets an unambiguous result then you 're definitely in a in a in a voice in a , uh , s region with speech. Uh.
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So there 's this assumption that the v the voice activity detector can only use the MFCC ?
| false |
QMSum_120
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Mm - hmm.
|
if it gets an unambiguous result then you 're definitely in a in a in a voice in a , uh , s region with speech. Uh.
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So there 's this assumption that the v the voice activity detector can only use the MFCC ?
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That 's not clear , but this e
| false |
QMSum_120
|
if it gets an unambiguous result then you 're definitely in a in a in a voice in a , uh , s region with speech. Uh.
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So there 's this assumption that the v the voice activity detector can only use the MFCC ?
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That 's not clear , but this e
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Well , for the baseline.
| false |
QMSum_120
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So there 's this assumption that the v the voice activity detector can only use the MFCC ?
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That 's not clear , but this e
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Well , for the baseline.
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Yeah.
| false |
QMSum_120
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That 's not clear , but this e
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Well , for the baseline.
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Yeah.
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So so if you use other features then y But it 's just a question of what is your baseline. Right ? What is it that you 're supposed to do better than ?
| false |
QMSum_120
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Well , for the baseline.
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Yeah.
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So so if you use other features then y But it 's just a question of what is your baseline. Right ? What is it that you 're supposed to do better than ?
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I g Yeah.
| false |
QMSum_120
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Yeah.
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So so if you use other features then y But it 's just a question of what is your baseline. Right ? What is it that you 're supposed to do better than ?
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I g Yeah.
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And so having the baseline be the MFCC 's means that people could choose to pour their ener their effort into trying to do a really good VAD
| false |
QMSum_120
|
So so if you use other features then y But it 's just a question of what is your baseline. Right ? What is it that you 're supposed to do better than ?
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I g Yeah.
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And so having the baseline be the MFCC 's means that people could choose to pour their ener their effort into trying to do a really good VAD
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I don't s But they seem like two separate issues.
| false |
QMSum_120
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I g Yeah.
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And so having the baseline be the MFCC 's means that people could choose to pour their ener their effort into trying to do a really good VAD
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I don't s But they seem like two separate issues.
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or tryi They 're sort of separate.
| false |
QMSum_120
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And so having the baseline be the MFCC 's means that people could choose to pour their ener their effort into trying to do a really good VAD
|
I don't s But they seem like two separate issues.
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or tryi They 're sort of separate.
|
Right ? I mean
| false |
QMSum_120
|
I don't s But they seem like two separate issues.
|
or tryi They 're sort of separate.
|
Right ? I mean
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Unfortunately there 's coupling between them , which is part of what I think Stephane is getting to , is that you can choose your features in such a way as to improve the VAD.
| false |
QMSum_120
|
or tryi They 're sort of separate.
|
Right ? I mean
|
Unfortunately there 's coupling between them , which is part of what I think Stephane is getting to , is that you can choose your features in such a way as to improve the VAD.
|
Yeah.
| false |
QMSum_120
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Right ? I mean
|
Unfortunately there 's coupling between them , which is part of what I think Stephane is getting to , is that you can choose your features in such a way as to improve the VAD.
|
Yeah.
|
And you also can choose your features in such a way as to prove improve recognition. They may not be the same thing.
| false |
QMSum_120
|
Unfortunately there 's coupling between them , which is part of what I think Stephane is getting to , is that you can choose your features in such a way as to improve the VAD.
|
Yeah.
|
And you also can choose your features in such a way as to prove improve recognition. They may not be the same thing.
|
But it seems like you should do both.
| false |
QMSum_120
|
Yeah.
|
And you also can choose your features in such a way as to prove improve recognition. They may not be the same thing.
|
But it seems like you should do both.
|
You should do both
| false |
QMSum_120
|
And you also can choose your features in such a way as to prove improve recognition. They may not be the same thing.
|
But it seems like you should do both.
|
You should do both
|
Right ?
| false |
QMSum_120
|
But it seems like you should do both.
|
You should do both
|
Right ?
|
and and I I think that this still makes I still think this makes sense as a baseline. It 's just saying , as a baseline , we know
| false |
QMSum_120
|
You should do both
|
Right ?
|
and and I I think that this still makes I still think this makes sense as a baseline. It 's just saying , as a baseline , we know
|
Mmm.
| false |
QMSum_120
|
Right ?
|
and and I I think that this still makes I still think this makes sense as a baseline. It 's just saying , as a baseline , we know
|
Mmm.
|
you know , we had the MFCC 's before , lots of people have done voice activity detectors ,
| false |
QMSum_120
|
and and I I think that this still makes I still think this makes sense as a baseline. It 's just saying , as a baseline , we know
|
Mmm.
|
you know , we had the MFCC 's before , lots of people have done voice activity detectors ,
|
Mm - hmm.
| false |
QMSum_120
|
Mmm.
|
you know , we had the MFCC 's before , lots of people have done voice activity detectors ,
|
Mm - hmm.
|
you might as well pick some voice activity detector and make that the baseline , just like you picked some version of HTK and made that the baseline.
| false |
QMSum_120
|
you know , we had the MFCC 's before , lots of people have done voice activity detectors ,
|
Mm - hmm.
|
you might as well pick some voice activity detector and make that the baseline , just like you picked some version of HTK and made that the baseline.
|
Yeah. Right.
| false |
QMSum_120
|
Mm - hmm.
|
you might as well pick some voice activity detector and make that the baseline , just like you picked some version of HTK and made that the baseline.
|
Yeah. Right.
|
And then let 's try and make everything better. Um , and if one of the ways you make it better is by having your features be better features for the VAD then that 's so be it.
| false |
QMSum_120
|
you might as well pick some voice activity detector and make that the baseline , just like you picked some version of HTK and made that the baseline.
|
Yeah. Right.
|
And then let 's try and make everything better. Um , and if one of the ways you make it better is by having your features be better features for the VAD then that 's so be it.
|
Mm - hmm.
| false |
QMSum_120
|
Yeah. Right.
|
And then let 's try and make everything better. Um , and if one of the ways you make it better is by having your features be better features for the VAD then that 's so be it.
|
Mm - hmm.
|
But , uh , uh , uh , at least you have a starting point that 's um , cuz i i some of the some of the people didn't have a VAD at all , I guess. Right ? And and
| false |
QMSum_120
|
And then let 's try and make everything better. Um , and if one of the ways you make it better is by having your features be better features for the VAD then that 's so be it.
|
Mm - hmm.
|
But , uh , uh , uh , at least you have a starting point that 's um , cuz i i some of the some of the people didn't have a VAD at all , I guess. Right ? And and
|
Yeah.
| false |
QMSum_120
|
Mm - hmm.
|
But , uh , uh , uh , at least you have a starting point that 's um , cuz i i some of the some of the people didn't have a VAD at all , I guess. Right ? And and
|
Yeah.
|
then they they looked pretty bad and and in fact what they were doing wasn't so bad at all.
| false |
QMSum_120
|
But , uh , uh , uh , at least you have a starting point that 's um , cuz i i some of the some of the people didn't have a VAD at all , I guess. Right ? And and
|
Yeah.
|
then they they looked pretty bad and and in fact what they were doing wasn't so bad at all.
|
Mm - hmm. Mm - hmm.
| false |
QMSum_120
|
Yeah.
|
then they they looked pretty bad and and in fact what they were doing wasn't so bad at all.
|
Mm - hmm. Mm - hmm.
|
But , um.
| false |
QMSum_120
|
then they they looked pretty bad and and in fact what they were doing wasn't so bad at all.
|
Mm - hmm. Mm - hmm.
|
But , um.
|
Yeah. It seems like you should try to make your baseline as good as possible. And if it turns out that you can't improve on that , well , I mean , then , you know , nobody wins and you just use MFCC. Right ?
| false |
QMSum_120
|
Mm - hmm. Mm - hmm.
|
But , um.
|
Yeah. It seems like you should try to make your baseline as good as possible. And if it turns out that you can't improve on that , well , I mean , then , you know , nobody wins and you just use MFCC. Right ?
|
Yeah. I mean , it seems like , uh , it should include sort of the current state of the art that you want are trying to improve , and MFCC 's , you know , or PLP or something it seems like reasonable baseline for the features , and anybody doing this task , uh , is gonna have some sort of voice activity detection at some level , in some way. They might use the whole recognizer to do it but rather than a separate thing , but but they 'll have it on some level. So , um.
| false |
QMSum_120
|
But , um.
|
Yeah. It seems like you should try to make your baseline as good as possible. And if it turns out that you can't improve on that , well , I mean , then , you know , nobody wins and you just use MFCC. Right ?
|
Yeah. I mean , it seems like , uh , it should include sort of the current state of the art that you want are trying to improve , and MFCC 's , you know , or PLP or something it seems like reasonable baseline for the features , and anybody doing this task , uh , is gonna have some sort of voice activity detection at some level , in some way. They might use the whole recognizer to do it but rather than a separate thing , but but they 'll have it on some level. So , um.
|
It seems like whatever they choose they shouldn't , you know , purposefully brain - damage a part of the system to make a worse baseline , or
| false |
QMSum_120
|
Yeah. It seems like you should try to make your baseline as good as possible. And if it turns out that you can't improve on that , well , I mean , then , you know , nobody wins and you just use MFCC. Right ?
|
Yeah. I mean , it seems like , uh , it should include sort of the current state of the art that you want are trying to improve , and MFCC 's , you know , or PLP or something it seems like reasonable baseline for the features , and anybody doing this task , uh , is gonna have some sort of voice activity detection at some level , in some way. They might use the whole recognizer to do it but rather than a separate thing , but but they 'll have it on some level. So , um.
|
It seems like whatever they choose they shouldn't , you know , purposefully brain - damage a part of the system to make a worse baseline , or
|
Well , I think people just had
| false |
QMSum_120
|
Yeah. I mean , it seems like , uh , it should include sort of the current state of the art that you want are trying to improve , and MFCC 's , you know , or PLP or something it seems like reasonable baseline for the features , and anybody doing this task , uh , is gonna have some sort of voice activity detection at some level , in some way. They might use the whole recognizer to do it but rather than a separate thing , but but they 'll have it on some level. So , um.
|
It seems like whatever they choose they shouldn't , you know , purposefully brain - damage a part of the system to make a worse baseline , or
|
Well , I think people just had
|
You know ?
| false |
QMSum_120
|
It seems like whatever they choose they shouldn't , you know , purposefully brain - damage a part of the system to make a worse baseline , or
|
Well , I think people just had
|
You know ?
|
it wasn't that they purposely brain - damaged it. I think people hadn't really thought through about the , uh the VAD issue.
| false |
QMSum_120
|
Well , I think people just had
|
You know ?
|
it wasn't that they purposely brain - damaged it. I think people hadn't really thought through about the , uh the VAD issue.
|
Mmm.
| false |
QMSum_120
|
You know ?
|
it wasn't that they purposely brain - damaged it. I think people hadn't really thought through about the , uh the VAD issue.
|
Mmm.
|
Mm - hmm.
| false |
QMSum_120
|
it wasn't that they purposely brain - damaged it. I think people hadn't really thought through about the , uh the VAD issue.
|
Mmm.
|
Mm - hmm.
|
And and then when the the the proposals actually came in and half of them had V A Ds and half of them didn't , and the half that did did well and the half that didn't did poorly.
| false |
QMSum_120
|
Mmm.
|
Mm - hmm.
|
And and then when the the the proposals actually came in and half of them had V A Ds and half of them didn't , and the half that did did well and the half that didn't did poorly.
|
Mm - hmm.
| false |
QMSum_120
|
Mm - hmm.
|
And and then when the the the proposals actually came in and half of them had V A Ds and half of them didn't , and the half that did did well and the half that didn't did poorly.
|
Mm - hmm.
|
So it 's
| false |
QMSum_120
|
And and then when the the the proposals actually came in and half of them had V A Ds and half of them didn't , and the half that did did well and the half that didn't did poorly.
|
Mm - hmm.
|
So it 's
|
Mm - hmm. Um.
| false |
QMSum_120
|
Mm - hmm.
|
So it 's
|
Mm - hmm. Um.
|
Uh.
| false |
QMSum_120
|
So it 's
|
Mm - hmm. Um.
|
Uh.
|
Yeah. So we 'll see what happen with this. And Yeah. So what happened since , um , last week is well , from OGI , these experiments on putting VAD on the baseline. And these experiments also are using , uh , some kind of noise compensation , so spectral subtraction , and putting on - line normalization , um , just after this. So I think spectral subtraction , LDA filtering , and on - line normalization , so which is similar to the pro proposal - one , but with spectral subtraction in addition , and it seems that on - line normalization doesn't help further when you have spectral subtraction.
| false |
QMSum_120
|
Mm - hmm. Um.
|
Uh.
|
Yeah. So we 'll see what happen with this. And Yeah. So what happened since , um , last week is well , from OGI , these experiments on putting VAD on the baseline. And these experiments also are using , uh , some kind of noise compensation , so spectral subtraction , and putting on - line normalization , um , just after this. So I think spectral subtraction , LDA filtering , and on - line normalization , so which is similar to the pro proposal - one , but with spectral subtraction in addition , and it seems that on - line normalization doesn't help further when you have spectral subtraction.
|
Is this related to the issue that you brought up a couple of meetings ago with the the musical tones
| false |
QMSum_120
|
Uh.
|
Yeah. So we 'll see what happen with this. And Yeah. So what happened since , um , last week is well , from OGI , these experiments on putting VAD on the baseline. And these experiments also are using , uh , some kind of noise compensation , so spectral subtraction , and putting on - line normalization , um , just after this. So I think spectral subtraction , LDA filtering , and on - line normalization , so which is similar to the pro proposal - one , but with spectral subtraction in addition , and it seems that on - line normalization doesn't help further when you have spectral subtraction.
|
Is this related to the issue that you brought up a couple of meetings ago with the the musical tones
|
and ?
| false |
QMSum_120
|
Yeah. So we 'll see what happen with this. And Yeah. So what happened since , um , last week is well , from OGI , these experiments on putting VAD on the baseline. And these experiments also are using , uh , some kind of noise compensation , so spectral subtraction , and putting on - line normalization , um , just after this. So I think spectral subtraction , LDA filtering , and on - line normalization , so which is similar to the pro proposal - one , but with spectral subtraction in addition , and it seems that on - line normalization doesn't help further when you have spectral subtraction.
|
Is this related to the issue that you brought up a couple of meetings ago with the the musical tones
|
and ?
|
I have no idea , because the issue I brought up was with a very simple spectral subtraction approach ,
| false |
QMSum_120
|
Is this related to the issue that you brought up a couple of meetings ago with the the musical tones
|
and ?
|
I have no idea , because the issue I brought up was with a very simple spectral subtraction approach ,
|
Mmm.
| false |
QMSum_120
|
and ?
|
I have no idea , because the issue I brought up was with a very simple spectral subtraction approach ,
|
Mmm.
|
and the one that they use at OGI is one from from the proposed the the the Aurora prop uh , proposals , which might be much better. So , yeah. I asked Sunil for more information about that , but , uh , I don't know yet. Um. And what 's happened here is that we so we have this kind of new , um , reference system which use a nice a a clean downsampling - upsampling , which use a new filter that 's much shorter and which also cuts the frequency below sixty - four hertz ,
| false |
QMSum_120
|
I have no idea , because the issue I brought up was with a very simple spectral subtraction approach ,
|
Mmm.
|
and the one that they use at OGI is one from from the proposed the the the Aurora prop uh , proposals , which might be much better. So , yeah. I asked Sunil for more information about that , but , uh , I don't know yet. Um. And what 's happened here is that we so we have this kind of new , um , reference system which use a nice a a clean downsampling - upsampling , which use a new filter that 's much shorter and which also cuts the frequency below sixty - four hertz ,
|
Right.
| false |
QMSum_120
|
Mmm.
|
and the one that they use at OGI is one from from the proposed the the the Aurora prop uh , proposals , which might be much better. So , yeah. I asked Sunil for more information about that , but , uh , I don't know yet. Um. And what 's happened here is that we so we have this kind of new , um , reference system which use a nice a a clean downsampling - upsampling , which use a new filter that 's much shorter and which also cuts the frequency below sixty - four hertz ,
|
Right.
|
which was not done on our first proposal.
| false |
QMSum_120
|
and the one that they use at OGI is one from from the proposed the the the Aurora prop uh , proposals , which might be much better. So , yeah. I asked Sunil for more information about that , but , uh , I don't know yet. Um. And what 's happened here is that we so we have this kind of new , um , reference system which use a nice a a clean downsampling - upsampling , which use a new filter that 's much shorter and which also cuts the frequency below sixty - four hertz ,
|
Right.
|
which was not done on our first proposal.
|
When you say " we have that " , does Sunil have it now , too ,
| false |
QMSum_120
|
Right.
|
which was not done on our first proposal.
|
When you say " we have that " , does Sunil have it now , too ,
|
I No.
| false |
QMSum_120
|
which was not done on our first proposal.
|
When you say " we have that " , does Sunil have it now , too ,
|
I No.
|
or ?
| false |
QMSum_120
|
When you say " we have that " , does Sunil have it now , too ,
|
I No.
|
or ?
|
No.
| false |
QMSum_120
|
I No.
|
or ?
|
No.
|
OK.
| false |
QMSum_120
|
or ?
|
No.
|
OK.
|
Because we 're still testing. So we have the result for , uh , just the features
| false |
QMSum_120
|
No.
|
OK.
|
Because we 're still testing. So we have the result for , uh , just the features
|
OK.
| false |
QMSum_120
|
OK.
|
Because we 're still testing. So we have the result for , uh , just the features
|
OK.
|
and we are currently testing with putting the neural network in the KLT. Um , it seems to improve on the well - matched case , um , but it 's a little bit worse on the mismatch and highly - mismatched I mean when we put the neural network. And with the current weighting I think it 's sh it will be better because the well - matched case is better. Mmm.
| false |
QMSum_120
|
Because we 're still testing. So we have the result for , uh , just the features
|
OK.
|
and we are currently testing with putting the neural network in the KLT. Um , it seems to improve on the well - matched case , um , but it 's a little bit worse on the mismatch and highly - mismatched I mean when we put the neural network. And with the current weighting I think it 's sh it will be better because the well - matched case is better. Mmm.
|
But how much worse since the weighting might change how how much worse is it on the other conditions , when you say it 's a little worse ?
| false |
QMSum_120
|
OK.
|
and we are currently testing with putting the neural network in the KLT. Um , it seems to improve on the well - matched case , um , but it 's a little bit worse on the mismatch and highly - mismatched I mean when we put the neural network. And with the current weighting I think it 's sh it will be better because the well - matched case is better. Mmm.
|
But how much worse since the weighting might change how how much worse is it on the other conditions , when you say it 's a little worse ?
|
It 's like , uh , fff , fff um , ten percent relative. Yeah.
| false |
QMSum_120
|
and we are currently testing with putting the neural network in the KLT. Um , it seems to improve on the well - matched case , um , but it 's a little bit worse on the mismatch and highly - mismatched I mean when we put the neural network. And with the current weighting I think it 's sh it will be better because the well - matched case is better. Mmm.
|
But how much worse since the weighting might change how how much worse is it on the other conditions , when you say it 's a little worse ?
|
It 's like , uh , fff , fff um , ten percent relative. Yeah.
|
OK. Um.
| false |
QMSum_120
|
But how much worse since the weighting might change how how much worse is it on the other conditions , when you say it 's a little worse ?
|
It 's like , uh , fff , fff um , ten percent relative. Yeah.
|
OK. Um.
|
Mm - hmm.
| false |
QMSum_120
|
It 's like , uh , fff , fff um , ten percent relative. Yeah.
|
OK. Um.
|
Mm - hmm.
|
But it has the , uh the latencies are much shorter. That 's
| false |
QMSum_120
|
OK. Um.
|
Mm - hmm.
|
But it has the , uh the latencies are much shorter. That 's
|
Uh - y w when I say it 's worse , it 's not it 's when I I uh , compare proposal - two to proposal - one , so , r uh , y putting neural network compared to n not having any neural network. I mean , this new system is is is better ,
| false |
QMSum_120
|
Mm - hmm.
|
But it has the , uh the latencies are much shorter. That 's
|
Uh - y w when I say it 's worse , it 's not it 's when I I uh , compare proposal - two to proposal - one , so , r uh , y putting neural network compared to n not having any neural network. I mean , this new system is is is better ,
|
Uh - huh.
| false |
QMSum_120
|
But it has the , uh the latencies are much shorter. That 's
|
Uh - y w when I say it 's worse , it 's not it 's when I I uh , compare proposal - two to proposal - one , so , r uh , y putting neural network compared to n not having any neural network. I mean , this new system is is is better ,
|
Uh - huh.
|
because it has um , this sixty - four hertz cut - off , uh , clean downsampling , and , um what else ? Uh , yeah , a good VAD. We put the good VAD. So. Yeah , I don't know. I I j uh , uh pr
| false |
QMSum_120
|
Uh - y w when I say it 's worse , it 's not it 's when I I uh , compare proposal - two to proposal - one , so , r uh , y putting neural network compared to n not having any neural network. I mean , this new system is is is better ,
|
Uh - huh.
|
because it has um , this sixty - four hertz cut - off , uh , clean downsampling , and , um what else ? Uh , yeah , a good VAD. We put the good VAD. So. Yeah , I don't know. I I j uh , uh pr
|
But the latencies but you 've got the latency shorter now.
| false |
QMSum_120
|
Uh - huh.
|
because it has um , this sixty - four hertz cut - off , uh , clean downsampling , and , um what else ? Uh , yeah , a good VAD. We put the good VAD. So. Yeah , I don't know. I I j uh , uh pr
|
But the latencies but you 've got the latency shorter now.
|
Latency is short is Yeah.
| false |
QMSum_120
|
because it has um , this sixty - four hertz cut - off , uh , clean downsampling , and , um what else ? Uh , yeah , a good VAD. We put the good VAD. So. Yeah , I don't know. I I j uh , uh pr
|
But the latencies but you 've got the latency shorter now.
|
Latency is short is Yeah.
|
Yeah.
| false |
QMSum_120
|
But the latencies but you 've got the latency shorter now.
|
Latency is short is Yeah.
|
Yeah.
|
Isn't it
| false |
QMSum_120
|
Latency is short is Yeah.
|
Yeah.
|
Isn't it
|
And so
| false |
QMSum_120
|
Yeah.
|
Isn't it
|
And so
|
So it 's better than the system that we had before.
| false |
QMSum_120
|
Isn't it
|
And so
|
So it 's better than the system that we had before.
|
Yeah. Mainly because of the sixty - four hertz and the good VAD.
| false |
QMSum_120
|
And so
|
So it 's better than the system that we had before.
|
Yeah. Mainly because of the sixty - four hertz and the good VAD.
|
OK.
| false |
QMSum_120
|
So it 's better than the system that we had before.
|
Yeah. Mainly because of the sixty - four hertz and the good VAD.
|
OK.
|
And then I took this system and , mmm , w uh , I p we put the old filters also. So we have this good system , with good VAD , with the short filter and with the long filter , and , um , with the short filter it 's not worse. So well , is it
| false |
QMSum_120
|
Yeah. Mainly because of the sixty - four hertz and the good VAD.
|
OK.
|
And then I took this system and , mmm , w uh , I p we put the old filters also. So we have this good system , with good VAD , with the short filter and with the long filter , and , um , with the short filter it 's not worse. So well , is it
|
OK.
| false |
QMSum_120
|
OK.
|
And then I took this system and , mmm , w uh , I p we put the old filters also. So we have this good system , with good VAD , with the short filter and with the long filter , and , um , with the short filter it 's not worse. So well , is it
|
OK.
|
it 's in
| false |
QMSum_120
|
And then I took this system and , mmm , w uh , I p we put the old filters also. So we have this good system , with good VAD , with the short filter and with the long filter , and , um , with the short filter it 's not worse. So well , is it
|
OK.
|
it 's in
|
So that 's that 's all fine.
| false |
QMSum_120
|
OK.
|
it 's in
|
So that 's that 's all fine.
|
Yes. Uh
| false |
QMSum_120
|
it 's in
|
So that 's that 's all fine.
|
Yes. Uh
|
But what you 're saying is that when you do these So let me try to understand. When when you do these same improvements to proposal - one ,
| false |
QMSum_120
|
So that 's that 's all fine.
|
Yes. Uh
|
But what you 're saying is that when you do these So let me try to understand. When when you do these same improvements to proposal - one ,
|
Mm - hmm.
| false |
QMSum_120
|
Yes. Uh
|
But what you 're saying is that when you do these So let me try to understand. When when you do these same improvements to proposal - one ,
|
Mm - hmm.
|
that , uh , on the i things are somewhat better , uh , in proposal - two for the well - matched case and somewhat worse for the other two cases.
| false |
QMSum_120
|
But what you 're saying is that when you do these So let me try to understand. When when you do these same improvements to proposal - one ,
|
Mm - hmm.
|
that , uh , on the i things are somewhat better , uh , in proposal - two for the well - matched case and somewhat worse for the other two cases.
|
Yeah.
| false |
QMSum_120
|
Mm - hmm.
|
that , uh , on the i things are somewhat better , uh , in proposal - two for the well - matched case and somewhat worse for the other two cases.
|
Yeah.
|
So does , uh when you say , uh So The th now that these other things are in there , is it the case maybe that the additions of proposal - two over proposal - one are less im important ?
| false |
QMSum_120
|
that , uh , on the i things are somewhat better , uh , in proposal - two for the well - matched case and somewhat worse for the other two cases.
|
Yeah.
|
So does , uh when you say , uh So The th now that these other things are in there , is it the case maybe that the additions of proposal - two over proposal - one are less im important ?
|
Yeah. Probably , yeah.
| false |
QMSum_120
|
Yeah.
|
So does , uh when you say , uh So The th now that these other things are in there , is it the case maybe that the additions of proposal - two over proposal - one are less im important ?
|
Yeah. Probably , yeah.
|
I get it.
| false |
QMSum_120
|
So does , uh when you say , uh So The th now that these other things are in there , is it the case maybe that the additions of proposal - two over proposal - one are less im important ?
|
Yeah. Probably , yeah.
|
I get it.
|
Um So , yeah. Uh. Yeah , but it 's a good thing anyway to have shorter delay. Then we tried , um , to do something like proposal - two but having , um , e using also MSG features. So there is this KLT part , which use just the standard features ,
| false |
QMSum_120
|
Yeah. Probably , yeah.
|
I get it.
|
Um So , yeah. Uh. Yeah , but it 's a good thing anyway to have shorter delay. Then we tried , um , to do something like proposal - two but having , um , e using also MSG features. So there is this KLT part , which use just the standard features ,
|
Mm - hmm. Right.
| false |
QMSum_120
|
I get it.
|
Um So , yeah. Uh. Yeah , but it 's a good thing anyway to have shorter delay. Then we tried , um , to do something like proposal - two but having , um , e using also MSG features. So there is this KLT part , which use just the standard features ,
|
Mm - hmm. Right.
|
and then two neura two neural networks.
| false |
QMSum_120
|
Um So , yeah. Uh. Yeah , but it 's a good thing anyway to have shorter delay. Then we tried , um , to do something like proposal - two but having , um , e using also MSG features. So there is this KLT part , which use just the standard features ,
|
Mm - hmm. Right.
|
and then two neura two neural networks.
|
Mm - hmm.
| false |
QMSum_120
|
Mm - hmm. Right.
|
and then two neura two neural networks.
|
Mm - hmm.
|
Mmm , and it doesn't seem to help. Um , however , we just have one result , which is the Italian mismatch , so. Uh. We have to wait for that to fill the whole table , but
| false |
QMSum_120
|
and then two neura two neural networks.
|
Mm - hmm.
|
Mmm , and it doesn't seem to help. Um , however , we just have one result , which is the Italian mismatch , so. Uh. We have to wait for that to fill the whole table , but
|
OK. There was a start of some effort on something related to voicing or something. Is that ?
| false |
QMSum_120
|
Mm - hmm.
|
Mmm , and it doesn't seem to help. Um , however , we just have one result , which is the Italian mismatch , so. Uh. We have to wait for that to fill the whole table , but
|
OK. There was a start of some effort on something related to voicing or something. Is that ?
|
Yeah. Um , yeah. So basically we try to , uh , find good features that could be used for voicing detection , uh , but it 's still , uh on the , um t
| true |
QMSum_120
|
Mmm , and it doesn't seem to help. Um , however , we just have one result , which is the Italian mismatch , so. Uh. We have to wait for that to fill the whole table , but
|
OK. There was a start of some effort on something related to voicing or something. Is that ?
|
Yeah. Um , yeah. So basically we try to , uh , find good features that could be used for voicing detection , uh , but it 's still , uh on the , um t
|
Oh , well , I have the picture.
| false |
QMSum_120
|
OK. There was a start of some effort on something related to voicing or something. Is that ?
|
Yeah. Um , yeah. So basically we try to , uh , find good features that could be used for voicing detection , uh , but it 's still , uh on the , um t
|
Oh , well , I have the picture.
|
we w basically we are still playing with Matlab to to look at at what happened ,
| false |
QMSum_120
|
Yeah. Um , yeah. So basically we try to , uh , find good features that could be used for voicing detection , uh , but it 's still , uh on the , um t
|
Oh , well , I have the picture.
|
we w basically we are still playing with Matlab to to look at at what happened ,
|
What sorts of
| false |
QMSum_120
|
Oh , well , I have the picture.
|
we w basically we are still playing with Matlab to to look at at what happened ,
|
What sorts of
|
Yeah.
| false |
QMSum_120
|
we w basically we are still playing with Matlab to to look at at what happened ,
|
What sorts of
|
Yeah.
|
and
| false |
QMSum_120
|
What sorts of
|
Yeah.
|
and
|
what sorts of features are you looking at ?
| false |
QMSum_120
|
Yeah.
|
and
|
what sorts of features are you looking at ?
|
We have some
| false |
QMSum_120
|
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