B: And more are supposed to come soon
B: and there 's only a moderate amount of dat of memory .
B: So I don't think anybody has been sufficiently excited by it to spend much time uh with it ,
B: but uh Hopefully , they 'll get us some more parts , soon
B: and B: Uh , yeah , I think that 'll be B: once we get it populated , that 'll be a nice machine .
B: I mean we will ultimately get eight processors in there .
B: And uh and uh a nice amount of memory .
B: Uh so it 'll be a pr pretty fast Linux machine .
G: And if we can do things on Linux , some of the machines we have going already , like Swede ?
B: Mm - hmm .
G: Um It seems pretty fast .
B: Mm - hmm .
G: But I think Fudge is pretty fast too .
B: Yeah , I mean you can check with uh Dave Johnson .
B: I mean , it it 's  I think the machine is just sitting there .
B: And it does have two processors ,
B: you know
B: and  Somebody could do  you know , uh , check out uh the multi - threading libraries .
B: And I mean i it 's possible that the B: I mean , I guess the prudent thing to do would be for somebody to do the work on  on getting our code running on that machine with two processors even though there aren't five or eight .
B: There 's there 's there 's gonna be debugging hassles
B: and then we 'd be set for when we did have five or eight , to have it really be useful .
B: But . Notice how I said somebody
B: and turned my head your direction .
B: That 's one thing you don't get in these recordings .
B: You don't get the  don't get the visuals
B: but G: I is it um mostly um the neural network trainings that are um slowing us down or the HTK runs that are slowing us down ?
B: Uh , I think yes .
B: Uh , Isn't that right ?
B: I mean I think you 're you 're sort of held up by both ,
B: right ?
B: If the if the neural net trainings were a hundred times faster you still wouldn't be anything B: running through these a hundred times faster
B: because you 'd be stuck by the HTK trainings ,
D: Mmm .
D: Yeah .
B: right ?
B: But if the HTK B: I mean I think they 're both It sounded like they were roughly equal ?
B: Is that about right ?
D: Yeah .
B: Yeah .
G: Because , um I think that 'll be running Linux ,
G: and Sw - Swede and Fudge are already running Linux
G: so , um I could try to get um the train the neural network trainings or the HTK stuff running under Linux , and to start with I 'm wondering which one I should pick first .
B: Uh , probably the neural net
B: cuz it 's probably it it 's  it 's um B: Well , I I don't know .
B: They both B: HTK we use for um this Aurora stuff
B: Um Um , I think It 's not clear yet what we 're gonna use for trainings
B: uh B: Well , there 's the trainings
B: uh is it the training that takes the time , or the decoding ?
B: Uh , is it about equal between the two ?
B: For for Aurora ?
D: For HTK ?
B: For B: Yeah . For the Aurora ?
D: Uh Training is longer .
B: OK .
D: Yeah .
B: OK .
B: Well , I don't know how we can B: I don't know how to B: Do we have HTK source ?
B: Is that D: Mmm .
B: Yeah .
B: You would think that would fairly trivially B: the training would , anyway ,
B: th the testing uh I don't I don't think would parallelize all that well .
B: But I think that you could certainly do d um , distributed , sort of  Ah ,
B: no , it 's the  each individual sentence
B: is pretty tricky to parallelize .
B: But you could split up the sentences in a test set .
A: They have a they have a thing for doing that
A: and th they have for awhile , in H T
B: Yeah ?
A: And you can parallelize the training .
A: And run it on several machines
B: Aha !
A: and it just basically keeps counts .
A: And there 's something  a final thing that you run
A: and it accumulates all the counts together .
D: Mmm .
B: I see .
A: I don't what their scripts are set up to do for the Aurora stuff ,
A: but D: Yeah .
B: Something that we haven't really settled on yet is other than this Aurora stuff , uh what do we do , large vocabulary training slash testing for uh tandem systems .
B: Cuz we hadn't really done much with tandem systems for larger stuff .
B: Cuz we had this one collaboration with CMU and we used SPHINX .
B: Uh , we 're also gonna be collaborating with SRI
B: and we have their have theirs .
B: Um So I don't know
B: Um . So I I think the the advantage of going with the neural net thing is that we 're gonna use the neural net trainings , no matter what ,
G: OK .
B: for a lot of the things we 're doing ,
B: whereas , w exactly which HMM Gaussian - mixture - based HMM thing we use is gonna depend uh
B: So with that , maybe we should uh go to our <nonvocalsound> digit recitation task .
B: And , it 's about eleven fifty .
B: Canned .
B: Uh , I can I can start over here .
B: Great ,
B: uh , could you give Adam a call .
B: Tell him to
F: Oh .
B: He 's at two nine seven seven .
B: OK .
B: I think we can @ @ You know Herve 's coming tomorrow ,
B: right ?
B: Herve will be giving a talk , yeah , talk at eleven .
B: Did uh , did everybody sign these consent Er everybody Has everyone signed a consent form before , on previous meetings ?
B: You don't have to do it again each time
B: Yes .
B: microphones off