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Yeah. Uh , maybe I should write it on the board. So , there 's four rounds of training. Um , I g I g I guess you could say iterations. The first one is three , then seven , seven , and seven. And what these numbers refer to is the number of times that the , uh , HMM re - estimation is run. It 's this program called H E
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But in HTK , what 's the difference between , uh , a an inner loop and an outer loop in these iterations ?
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OK. So what happens is , um , at each one of these points , you increase the number of Gaussians in the model.
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Yeah. Oh , right ! This was the mix up stuff.
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Yeah. The mix up.
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That 's right.
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Right.
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I remember now.
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And so , in the final one here , you end up with , uh for all of the the digit words , you end up with , uh , three mixtures per state ,
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Yeah.
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eh , in the final thing. So I had done some experiments where I was I I want to play with the number of mixtures.
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Mm - hmm.
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But , um , uh , I wanted to first test to see if we actually need to do this many iterations early on.
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Uh , one , two ,
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Mm - hmm.
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And so , um , I I ran a couple of experiments where I reduced that to l to be three , two , two , uh , five , I think , and I got almost the exact same results.
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Mm - hmm.
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And but it runs much much faster. So , um , I I think m it only took something like , uh , three or four hours to do the full training ,
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As opposed to ?
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Good.
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as opposed to wh what , sixteen hours or something like that ? I mean , it takes you have to do an overnight basically , the way it is set up now.
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Yeah. It depends.
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Mm - hmm.
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Mm - hmm.
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So , uh , even we don't do anything else , doing something like this could allow us to turn experiments around a lot faster.
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And then when you have your final thing , do a full one , so it 's
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And when you have your final thing , we go back to this.
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Yeah.
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So , um , and it 's a real simple change to make. I mean , it 's like one little text file you edit and change those numbers , and you don't do anything else.
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Oh , this is a
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Mm - hmm.
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And then you just run.
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OK.
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So it 's a very simple change to make and it doesn't seem to hurt all that much.
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So you you run with three , two , two , five ? That 's a
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So I Uh , I I have to look to see what the exact numbers were.
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Yeah.
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I I thought was , like , three , two , two , five ,
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Mm - hmm.
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but I I 'll I 'll double check. It was over a week ago that I did it ,
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OK. Mm - hmm.
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so I can't remember exactly.
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Oh.
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But , uh
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Mm - hmm.
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um , but it 's so much faster. I it makes a big difference.
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Hmm.
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So we could do a lot more experiments and throw a lot more stuff in there.
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Yeah.
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That 's great.
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Um. Oh , the other thing that I did was , um , I compiled the HTK stuff for the Linux boxes. So we have this big thing that we got from IBM , which is a five - processor machine. Really fast , but it 's running Linux. So , you can now run your experiments on that machine and you can run five at a time and it runs , uh , as fast as , you know , uh , five different machines.
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Mm - hmm.
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Mm - hmm.
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So , um , I 've forgotten now what the name of that machine is but I can I can send email around about it.
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Yeah.
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And so we 've got it now HTK 's compiled for both the Linux and for , um , the Sparcs. Um , you have to make you have to make sure that in your dot CSHRC , um , it detects whether you 're running on the Linux or a a Sparc and points to the right executables. Uh , and you may not have had that in your dot CSHRC before , if you were always just running the Sparc. So , um ,
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Mm - hmm.
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uh , I can I can tell you exactly what you need to do to get all of that to work. But it 'll it really increases what we can run on.
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Hmm. Cool.
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So , together with the fact that we 've got these faster Linux boxes and that it takes less time to do these , um , we should be able to crank through a lot more experiments.
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Mm - hmm.
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So.
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Hmm.
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So after I did that , then what I wanted to do was try increasing the number of mixtures , just to see , um see how how that affects performance.
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Yeah.
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So.
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Yeah. In fact , you could do something like keep exactly the same procedure and then add a fifth thing onto it
|
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Mm - hmm.
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that had more.
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Exactly.
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Yeah.
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Right. Right.
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So at at the middle o where the arrows are showing , that 's you 're adding one more mixture per state ,
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Uh - huh. Uh ,
|
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or ?
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let 's see , uh. It goes from this uh , try to go it backwards this at this point it 's two mixtures per state. So this just adds one. Except that , uh , actually for the silence model , it 's six mixtures per state.
|
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Mm - hmm.
|
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Uh , so it goes to two.
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OK.
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Um. And I think what happens here is
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Might be between , uh , shared , uh shared variances or something ,
|
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Yeah. I think that 's what it is.
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or
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Uh , yeah. It 's , uh Shoot. I I I can't remember now what happens at that first one. Uh , I have to look it up and see.
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Oh , OK.
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Um , there because they start off with , uh , an initial model which is just this global model , and then they split it to the individuals. And so , it may be that that 's what 's happening here. I I I have to look it up and see. I I don't exactly remember.
|
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OK.
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OK.
|
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So. That 's it.
|
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Alright. So what else ?
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Um. Yeah. There was a conference call this Tuesday. Um. I don't know yet the what happened Tuesday , but the points that they were supposed to discuss is still , uh , things like the weights , uh
|
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Oh , this is a conference call for , uh , uh , Aurora participant sort of thing.
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For
|
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Yeah. Yeah.
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I see.
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Mmm.
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Do you know who was who was since we weren't in on it , uh , do you know who was in from OGI ? Was was was Hynek involved or was it Sunil
|
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I have no idea.
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or ?
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Mmm , I just
|
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