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Oh , oh. I see. | 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. | So there 's this assumption that the v the voice activity detector can only use the MFCC ? | false | QMSum_120 |
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. | So there 's this assumption that the v the voice activity detector can only use the MFCC ? | 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. | So there 's this assumption that the v the voice activity detector can only use the MFCC ? | That 's not clear , but this e | Well , for the baseline. | false | QMSum_120 |
So there 's this assumption that the v the voice activity detector can only use the MFCC ? | That 's not clear , but this e | Well , for the baseline. | Yeah. | false | QMSum_120 |
That 's not clear , but this e | Well , for the baseline. | Yeah. | 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 |
Well , for the baseline. | Yeah. | 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 ? | I g Yeah. | false | QMSum_120 |
Yeah. | 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 ? | I g Yeah. | 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 ? | I g Yeah. | 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. | false | QMSum_120 |
I g Yeah. | 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. | or tryi They 're sort of separate. | false | QMSum_120 |
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. | 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 | 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 |
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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