G: OK .
F: Test .
B: Let 's see , I should be
E: As close to your mouth as you can get it .
B: Two .
D: Up high D: high as you can get .
B: La
H: Channel one one one .
G: Yeah , on your upper lip .
B: Is this channel one ?
B: Gee , OK .
B: Yes .
B: OK .
E: OK , so for for For people wearing the wireless mikes , like like this one , I find the easiest way to wear it is sorta this this sorta like that .
H: This is chan channel channel one one two three
F: Channel five , channel five .
B: Yeah .
E: It 's actually a lot more comfortable then if you try to put it over your temples ,
B: Mm - hmm . What do you do ,
F: Test , test test .
E: so B: you do it higher ?
B: Mm - hmm .
D: Adam 's just trying to generate good uh data for the recognizer there .
G: Yeah , I think we 're supposed to G: that 's right .
E: And then also , for for all of them , if your boom is adjustable , the boom should be towards the corner of your mouth ,
F: Test test .
A: By the way , there was a bug .
A: Yeah , i it wasn't using the proper
D: Oh it was .
E: and about a uh a thumb to a thumb and a half distance away from your mouth ,
A: basically it wasn't adapting anything .
D: Oh .
E: so about like I 'm wearing it now .
D: Oh that 's interesting .
D: So why didn't you get the same results and the unadapted ?
H: It 's not always possible .
E: so so Jane , you could actually do even a little closer to your mouth ,
A: Hmm ?
G: I could can this be adjuste like this ?
D: Why didn't you get the same results and the unadapted ?
E: but A: Oh , because when it estimates the transformer pro produces like a single matrix or something .
E: Yep .
G: Is that @ @ ? OK ,
G: thank you .
F: Adam , I 'm not F: uh , looks kinda low on channel five D: O Oh oh I see .
D: I see , I see .
F: no ?
B: OK .
E: Channel five , s speak again .
G: Hello .
F: Maybe not .
A: Basically there were no counts
E: Yeah , that 's alright .
F: Hello ?
H: Yeah .
F: It 's OK ?
E: I mean , we could we could up the gain slightly if you wanted to .
F: Is this OK ?
H: OK .
D: I see what you mean .
C: Who 's channel B ?
E: but E: Uh , channel B is probably Liz .
C: Uh oh .
H: Uh channel B I am channel B .
B: You wanna close this ,
G: Channel eight , eight .
B: or
C: No I
E: Thank you .
H: No , channel B .
C: yeah ,
A: Hello , hello .
C: yeah , you 're channel B .
H: Yeah , yeah .
C: So can you talk a bit ?
C: I thought it might be too
H: OK , yeah ,
H: channel B , one two three four five .
C: OK .
E: Yeah , it 's alright .
E: So , the gain isn't real good .
B: We 're recording ,
C: OK .
E: OK ,
E: so we are recording .
H: Ah .
B: right ?
B: Yeah .
F: Oh .
E: Um everyone should have at least two forms possibly three in front of you depending on who you are .
A: OK .
E: Um we we 're doing a new speaker form and you only have to spea fill out the speaker form once
E: but everyone does need to do it .
E: And so that 's the name , sex , email , et cetera .
H: Mm - hmm .
E: We we had a lot of discussion about the variety of English and so on
E: so if you don't know what to put just leave it blank .
E: Um I I designed the form and I don't know what to put for my own region ,
E: so
A: Mmm .
D: California .
A: I think E: California .
H: California .
A: Um may I make one suggestion ?
A: Instead of age put date of uh year of birth
E: Sure .
A: because age will change , but The year of birth changes , you know , stays the same , usually .
E: Oh .
E: Birth year ?
C: A actually , wait a minute ,
G: Although on A: Yeah .
C: shouldn't it be the other way around ?
D: Not for me .
G: course on the other on the other hand you could you view it as the age at the time of the C: On the other side ,
C: yeah .
A: Well the thing is , if ten years from now you look at this form knowing that G: Yes , but what we care about is the age at at the recording date rather than the D: But there 's no other date on the form .
C: O yeah .
C: W we don't care how they old they really are .
A: Well well I don't know .
G: Yes . Unless we wanna send them a card .
E: Well I guess it depends on how long the corpus is gonna be collected for .
G: Yeah , that 's true .
A: Anyway .
C: I still don't see the problem .
E: Either way
E: yeah I think I think age is alright
E: and then um there will be attached to this a point or two these forms uh so that you 'll be able to extract the date off that
A: OK .
A: Mm - hmm .
E: so , anyway .
E: And so then you also have a digits form which needs to be filled out every time , the speaker form only once , the digit form every time
E: even if you don't read the digits you have to fill out the digits form so that we know that you were at the meeting .
E: OK ?
E: And then also if you haven't filled one out already you do have to fill out a consent form .
E: And that should just be one person whose name I don't know .
E: OK ?
F: Do you want this Adam ?
E: Uh sure .
E: Thank you .
B: So uh
E: OK so should we do agenda items ?
B: Uh oh that 's a good idea .
B: I shouldn't run the meeting .
E: Uh well I have I wanna talk about new microphones and wireless stuff .
G: Mmm .
E: And I 'm sure Liz and Andreas wanna talk about recognition results .
E: Anything else ?
C: I guess what time do we have to leave ?
C: Three thirty ?
A: Yeah .
C: Yeah ,
E: Why don't you go first then .
C: so .
B: Yeah ,
B: good idea .
A: OK .
C: Um Well , I I sent out an email s couple hours ago
C: so
C: um with Andreas ' help um Andreas put together a sort of no frills recognizer
C: which is uh gender - dependent but like no adaptation , no cross - word models , no trigrams C: a bigram recognizer
C: and that 's trained on Switchboard which is telephone conversations .
C: Um and thanks to Don 's help wh who C: Don took the first meeting that Jane had transcribed
C: and um you know separated used the individual channels we segmented it in into the segments that Jane had used
C: and uh Don sampled that so so eight K
C: um and then we ran up to I guess the first twenty minutes ,
C: up to synch time of one two zero zero
C: so is that that 's twenty minutes or so ?
C: Um yeah because I guess there 's some ,
E: Or so .
C: and Don can talk to Jane about this ,
C: there 's some bug in the actual synch time file that ah uh
C: I 'm we 're not sure where it came from but stuff after that was a little messier .
C: Anyway so it 's twenty minutes and I actually
E: Hmm .
C: um
E: I E: was that did that did that recording have the glitch in the middle ?
G: I 'm puzzled by that .
G: I oh oh , I see .
C: There 's there 's a G: Oh there was a glitch somewhere .
C: yeah ,
C: so that actually
C: um
F: Was it twenty minutes in ,
G: I forgot about that .
C: if it was twenty minutes in then I don't know
F: I thought G: Well , I mean , they A: Well it was interesting ,
G: but I was able to can transcribe
E: I don't remember when it is .
A: suddenly the the overall error rate when we first ran it was like eighty percent
A: but i looking at the first sentences looked much better than that
A: and then suddenly it turned very bad
A: and then we noticed that the reference was always one off with the F: Yeah , that might be that might be that might be my fault .
C: Wel
A: it was actually recognized
E: Oh no .
G: Wow .
A: so
F: I 'm not E: Oh so that was just a parsing mismatch .
A: OK .
C: No actually it was C: yeah i it was a complicated bug
C: because they were sometimes one off and then sometimes totally random
C: so
G: Oh .
F: yeah , I was pretty certain that it worked up until that time ,
G: That 's not good .
C: um
C: Yeah
F: so
C: so that 's what we have
A: OK .
E: Alright .
G: Yeah .
C: but that that will be completely gone if this synch time problem
E: The the glitch
A: So so we have everything recognized but we scored only the first uh whatever , up to that time to
G: And the only glitch G: yeah .
E: yeah .
C: So you guys know .
B: S sorry I haven't seen the email ,
C: Yeah .
E: Th - the
G: The the well wait
C: So here 's the actual copy of the email
B: what was the score ?
G: we should say something about the glitch .
G: He he can say something about the glitch .
C: um oh OK
E: yeah .
G: Cuz it 's it 's it 's h it 's it 's very small C: so does this glitch occur at other E: There there there 's an acoustic glitch that occurs where um the channels get slightly asynchronized
G: very small .
G: Yep .
C: Oh .
C: Right .
E: so the that that problem has gone away in the original driver believe it or not when the SSH key gen ran the driver paused for a fraction of a second
A: Mmm .
F: Hmm .
B: Hmm .
E: and so the channels get a little asynchronous
E: and so if you listen to it in the middle there 's a little part where it starts doing doing click sounds .
B: So C: And is it only once that that happens ?
E: But
E: yeah
E: it C: OK .
E: right once in the middle .
C: There 's the previous page has some more information about sort of what was wrong
B: so C: but
E: Um But that shouldn't affect anything
B: so un unsurprisingly Adam is the golden voice ,
G: S
C: OK
C: so that 's actually
G: and it B: you see this here ?
E: yeah yeah
C: It y it 's E: " bah "
C: OK
C: no A: Oh , and C: What happens is it actually affects the script that Don D: Huh .
C: I mean if we know about it then I guess it could always be checked for it
E: Well the acoustic one shouldn't do anything .
C: but they
F: Yeah , I don't know exactly what affected it
G: I agree .
G: I agree .
F: but I 'll I 'll talk to you about it ,
A: I I have E: But I I do remember A: Yeah .
F: I 'll show you the point .
G: Yeah .
G: It it had no effect on my transcription ,
C: Yeah .
G: you know , I mean I I had no trouble hearing it and and having time bins
A: Mmm .
G: but there was a E: I do remember seeing once the transcriber produce an incorrect XML file where one of the synch numbers was incorrect .
G: Oh .
F: That 's what happened .
C: Well , the the synch time the synch numbers have more significant digits than they should ,
G: Oh .
H: Yeah .
F: There was E: Where where they weren't monotonic .
F: yeah , I mean C: right ?
C: There 's things that are l in smaller increments than a frame .
H: Yeah .
G: Oh , interesting .
E: Oh OK
E: so that 's
F: Hmm .
C: And so then , I mean you look at that and it 's got you know more than three significant digits in a synch time then that can't be right
G: Oh .
E: yeah sounds like a bug .
G: Yeah .
A: Mmm .
C: so anyway it 's it 's just C: that 's why we only have twenty minutes
C: but there 's a significant amount of F: Non - zero ?
F: Um there are like more cuz there 's a lot of zeros I tacked on just because of the way the script ran ,
E: The other one I saw was that it
F: I mean but there were there was a point .
E: yeah .
C: Yeah that was fine .
E: The other one I saw was non non - monotonic synch times
C: That that was OK .
F: OK .
E: and that definitely indicra indicates a bug .
F: Uh .
C: Well that would really be a problem ,
C: yeah .
C: So anyway these are just the ones that are the prebug for one meeting .
F: Yeah .
C: um and what 's which E: So that 's very encouraging .
C: this is really encouraging cuz this is free recognition ,
H: Yeah .
B: Hmm .
B: Cool .
C: there 's no I mean the language model for Switchboard is totally different
A: Mmm .
C: so you can see some like this Trent Lott which
D: Trent Lott .
C: um I mean
C: these are sort of funny ones ,
D: It 'll get those though .
C: there 's a lot of perfect ones and good ones and all the references ,
C: I mean you can read them and when we get more results you can look through and see
E: I and as I said I would like to look at the lattices
A: Mm - hmm .
C: but
C: um it 's pretty good .
E: because it sounded like even the ones it got wrong it sort of got it right ?
C: Well so I guess we can generate
E: Sounds likes ?
G: Mm - hmm .
A: There are a fair number of errors that are , you know where got the plural S wrong or the inflection on the verb wrong .
C: um
E: Yeah ,
E: and who cares ?
E: And and there were lots of of course the " uh uh " - s , " in on " - s " of uh " - s .
A: Mmm , so if C: there 's C: No those are actually
A: Yeah .
C: a lot of the errors I think are out of vocabulary ,
C: so is it like PZM is three words ,
A: Mm - hmm .
C: it 's PZM ,
A: Mm - hmm .
C: I mean there 's nothing
E: Right .
C: There 's no language model for PZM or
E: Ri - ri right .
C: um
E: Did you say there 's no language for PZM ?
C: No language model , I mean those E: Do you mean so every time someone says PZM it 's an error ?
E: Maybe we shouldn't say PZM in these meetings .
C: Well well there 's all kinds of other stuff like Jimlet
C: and I mean um anyway there E: Yeah , that 's right , Jimlet .
B: Well , we don't even know what that means ,
C: so but this is really encouraging because
E: Yeah , that 's right .
B: so I
C: so , I mean the bottom line is even though it 's not a huge amount of data um it should be uh reasonable to actually run recognition and be like within the scope of of r reasonable s you know Switchboard
C: this is like h about how well we do on Switchboard - two data with the Switchboard - one trained mostly trained recognizer
E: Right .
C: and Switchboard - two is got sort of a different population of speakers and a different topic
E: Excellent .
C: and they 're talking about things in the news that happened after Switchboard - one
C: so there was @ @ so that 's great .
B: Yeah .
B: Yeah so we 're in better shape than we were say when we did had the ninety - three workshop
C: Um
B: and we were all getting like seventy percent error on Switchboard .
A: Mm - hmm .
C: Oh yeah
C: I mean this is really ,
B: you know
A: Mmm .
C: and thanks to Andreas who , I mean this is a
A: Mmm .
E: Well especially for the very first run , I mean you B: Yeah .
C: eh um
A: Oh it 's the B: Yeah .
E: the first run I ran of Switchboard I got a hundred twenty percent word error
C: yeah
E: but
C: So and what al also this means is that
G: Right .
E: Not Switchboard ,
C: um
E: uh Broadcast News .
A: Well it 's C: I mean there 's a bunch of things in this note to various people
C: especially I guess um with Jane that that would help for C: since we have this new data now uh in order to go from the transcripts more easily to um just the words that the recognizer would use for scoring .
C: I had to deal with some of it by hand but I think a lot of it can be automated s by B: Oh one thing I guess I didn't get
B: so you know the language model was straight from from bigram from Switchboard
B: the acoustic models were also from Switchboard or or
A: Yeah .
C: Yeah .
G: That 's amazing .
B: So they didn't have anything from this acoustic data in yet ?
E: Yeah , so that 's great .
C: No .
C: And actually we actually um used Switchboard telephone bandwidth models
G: That 's amazing .
B: OK .
B: Yeah .
C: which I guess
D: I was just gonna say ,
A: Well that 's those are the only we ones there are ,
D: yeah .
C: so that 's the on that 's the only acoustic training data that we have a lot of
E: Yeah .
A: I mean
A: Right .
C: and I guess Ramana ,
C: so a guy at SRI said that um there 's not a huge amount of difference going from C: it 's it 's not like we probably lose a huge amount
B: Right .
C: but we won't know
C: because we don't have any full band models for s conversational speech .
D: It 's probably not as bad as going f using full band models on telephone band speech
C: So .
A: Oh yeah .
D: right ?
C: Right .
C: Right , so it 's so
B: Yeah ,
A: Yeah .
B: but for Broadcast News when we we played around between the two there wasn't a huge loss .
E: Right , it was not a big deal .
C: Yeah
C: so I wou
A: I should I should say that the language model is not just Switchboard
C: so that 's good .
E: Although combining em worked well .
A: it 's also A: I mean there 's uh actually more data is from Broadcast News
A: but with a little less weight
C: Yeah .
B: Uh - huh .
C: Like Trent Lott must have been from
A: uh because
C: I guess Switchboard was before
A: mm - hmm ,
A: right .
A: Um By the way just for fun we also ran ,
C: uh .
B: Good point .
A: I mean our complete system starts by doing ge a gender detection
B: Mm - hmm .
A: so just for the heck of it I ran that
E: And it said a hundred percent male ?
A: um and it might be reassuring for everybody to know that it got all the genders right .
C: The j
E: Oh it did ?
A: Yeah so
G: Oh that 's I 'm glad .
E: It got all two genders ?
C: Yeah
C: but you know Jane and Adam have you kn about equal performance
A: Yeah .
A: Yes .
C: and uh and that 's interesting
C: cuz I think the their language models are quite different
C: so
C: and I I 'm pretty sure from listening to Eric that , you know given the words he was saying and given his pronunciation that the reason that he 's so much worse is the lapel .
E: Right .
G: That makes a lot of sense ,
B: Yeah .
C: So it 's nice now if we can just sort of eliminate the lapel one when when we get new microphones
G: yeah .
G: Very possible .
B: Yeah
B: I I I would bet on that too
C: that would be worth it
C: um
B: cuz he certainly in that when as a as a burp user he was he was a pretty uh strong one .