Meeting transcript:
speaker: E
text: OK , we 're on .
speaker: B
text: OK .
speaker: E
text: So , I mean , everyone who 's on the wireless check that they 're on .
speaker: F
text: C we <disfmarker>
speaker: G
text: Alright .
speaker: C
text: I see .
speaker: F
text: Yeah .
speaker: C
text: Yeah .
speaker: E
text: OK , our agenda was quite short .
speaker: B
text: Oh , could you <pause> close the door , maybe ?
speaker: E
text: Sure .
speaker: B
text: Yeah .
speaker: E
text: Two items , which was , uh , digits and possibly stuff on <disfmarker> on , uh , forced alignment ,
speaker: E
text: which Jane said that Liz and Andreas had in information on ,
speaker: F
text: Mm - hmm .
speaker: E
text: but they didn't ,
speaker: E
text: so .
speaker: B
text: I guess the only other thing , uh , for which I <disfmarker>
speaker: F
text: We should do that second ,
speaker: F
text: because Liz might join us in time for that .
speaker: E
text: OK .
speaker: B
text: Um .
speaker: B
text: OK , so there 's digits , alignments ,
speaker: B
text: and , um ,
speaker: B
text: I guess the other thing , <vocalsound> which I came unprepared for , uh , <vocalsound> is , uh , to dis s s see if there 's anything anybody wants to discuss about the Saturday meeting .
speaker: E
text: Right .
speaker: B
text: So .
speaker: B
text: Any <disfmarker> I mean , maybe not .
speaker: E
text: Digits and alignments .
speaker: E
text: But <disfmarker>
speaker: B
text: Uh .
speaker: F
text: Talk about aligning people 's schedules .
speaker: B
text: Yeah .
speaker: E
text: Yeah .
speaker: C
text: Mm - hmm .
speaker: B
text: Yeah .
speaker: B
text: I mean <disfmarker>
speaker: B
text: Right .
speaker: B
text: Yeah , I mean , it was <disfmarker>
speaker: E
text: Yeah , it 's forced alignment of people 's schedules .
speaker: F
text: Yeah .
speaker: F
text: If we 're very <disfmarker>
speaker: D
text: Forced align .
speaker: B
text: Yeah .
speaker: F
text: Yeah .
speaker: B
text: With <disfmarker> with <disfmarker> whatever it was , a month and a half or something ahead of time , the only time we could find in common <disfmarker> roughly in common , was on a Saturday .
speaker: D
text: Yeah .
speaker: E
text: Yep .
speaker: B
text: Ugh .
speaker: F
text: It 's pretty sad .
speaker: B
text: Yeah .
speaker: F
text: Yeah .
speaker: C
text: Have <disfmarker> Have we thought about having a conference call to include him in more of <disfmarker> <vocalsound> in more of the meeting ?
speaker: C
text: I <disfmarker> I mean , I don't know ,
speaker: C
text: if we had the <disfmarker> if we had the telephone on the table <disfmarker>
speaker: B
text: No .
speaker: B
text: But , h I mean , he probably has to go do something .
speaker: F
text: No , actually I <disfmarker> I have to <disfmarker> I have to shuttle <pause> kids from various places to various other places .
speaker: B
text: Right ?
speaker: C
text: I see . OK .
speaker: F
text: So .
speaker: B
text: Yeah .
speaker: F
text: And I don't have <disfmarker> and I don't , um , have a cell phone
speaker: D
text: A cell phone ?
speaker: F
text: so I can't be having a conference call while driving .
speaker: C
text: No . <comment> It 's not good .
speaker: B
text: R r right .
speaker: C
text: That 's not good .
speaker: B
text: So we have to <disfmarker> we <disfmarker>
speaker: F
text: Plus , it would make for interesting noise <disfmarker> background noise .
speaker: E
text: Yep .
speaker: F
text: Uh <disfmarker>
speaker: B
text: So we have to equip him with a <disfmarker> with a <disfmarker> <vocalsound> with a head - mounted , uh , cell phone
speaker: E
text: Ye - we and we 'd have to force you to read lots and lots of digits ,
speaker: B
text: and <disfmarker>
speaker: F
text: Oh , yeah .
speaker: E
text: so it could get real <disfmarker> <vocalsound> real car noise .
speaker: D
text: Yeah .
speaker: F
text: Oh , yeah .
speaker: G
text: Take advantage .
speaker: D
text: And with the kids in the background .
speaker: F
text: I 'll let <disfmarker> I 'd let <disfmarker>
speaker: D
text: Yeah .
speaker: F
text: I let , uh , my five - year - old have a try at the digits ,
speaker: F
text: eh .
speaker: B
text: Yeah .
speaker: E
text: So , anyway , I can talk about digits .
speaker: E
text: Um , did everyone get the results or shall I go over them again ?
speaker: E
text: I mean that it was basically <disfmarker> the only thing that was even slightly surprising was that the lapel did so well .
speaker: E
text: Um , and in retrospect that 's not as surprising as maybe i
speaker: E
text: it shouldn't have been as surprising as I <disfmarker> as <disfmarker> as I felt it was .
speaker: E
text: The lapel mike is a very high - quality microphone .
speaker: E
text: And as Morgan pointed out , that there are actually some advantages to it in terms of breath noises and clothes rustling <pause> if no one else is talking .
speaker: F
text: Exactly .
speaker: D
text: Yeah .
speaker: G
text: Mm - hmm .
speaker: E
text: Um , so , uh <disfmarker>
speaker: G
text: It 's g it <disfmarker>
speaker: B
text: Well , it 's <disfmarker> Yeah , sort of the bre the breath noises and the mouth clicks and so forth like that , the lapel 's gonna be better on .
speaker: D
text: Or the cross - talk .
speaker: D
text: Yeah .
speaker: B
text: The lapel is typically worse on the <disfmarker> on clothes rustling ,
speaker: B
text: but if no one 's rustling their clothes ,
speaker: E
text: Right . I mean , a lot of people are just sort of leaning over and reading the digits ,
speaker: B
text: it 's <disfmarker> it 's <disfmarker>
speaker: E
text: so it 's <disfmarker> it 's a very different task than sort of the natural .
speaker: D
text: Yeah .
speaker: D
text: You don't move much during reading digits , I think .
speaker: E
text: So .
speaker: B
text: Yeah .
speaker: B
text: Yeah .
speaker: E
text: Right .
speaker: G
text: Probably the fact that it picks up other people 's speakers <disfmarker> other people 's talking is an indication of that it <disfmarker> the fact it is a good microphone .
speaker: D
text: Yeah .
speaker: E
text: Right .
speaker: B
text: Right . So in the digits , in most <disfmarker> most cases , there weren't other people talking .
speaker: G
text: So .
speaker: E
text: Right .
speaker: F
text: D do the lapel mikes have any directionality to them ?
speaker: B
text: So .
speaker: B
text: There typically don't , no .
speaker: F
text: Because I <disfmarker> I suppose you could make some that have sort of <disfmarker> that you have to orient towards your mouth ,
speaker: F
text: and then it would <disfmarker>
speaker: E
text: They have a little bit ,
speaker: E
text: but they 're not noise - cancelling .
speaker: E
text: So , uh <disfmarker>
speaker: B
text: They 're <disfmarker> they 're intended to be omni - directional .
speaker: E
text: Right .
speaker: F
text: Mm - hmm .
speaker: B
text: And th it 's <disfmarker> and because you don't know how people are gonna put them on , you know .
speaker: E
text: Right .
speaker: E
text: So , also , Andreas , on that one the <disfmarker> the back part of it should be right against your head .
speaker: E
text: And that will he keep it from flopping aro up and down as much .
speaker: F
text: It is against my head .
speaker: E
text: OK .
speaker: B
text: Yeah .
speaker: B
text: Um . Yeah , we actually talked about this in the , uh , front - end meeting this morning , too .
speaker: E
text: Uh - huh .
speaker: B
text: Much the same thing ,
speaker: B
text: and <disfmarker> and it was <disfmarker>
speaker: B
text: uh , I mean , there the point of interest to the group was primarily that , um , <vocalsound> the , uh <disfmarker> the system that we had that was based on H T K , that 's used by , you know , <pause> all the participants in Aurora , <vocalsound> was so much worse <vocalsound> than the <disfmarker> than the S R
speaker: E
text: Everybody .
speaker: B
text: And the interesting thing is that even though , <vocalsound> yes , it 's a digits task and that 's a relatively small number of words and there 's a bunch of digits that you train on , <vocalsound> it 's just not as good as having a <disfmarker> a l very large amount of data and training up a <disfmarker> a <disfmarker> a nice good big <vocalsound> HMM .
speaker: B
text: Um , also you had the adaptation in the SRI system , which we didn't have in this .
speaker: B
text: Um . So . Um .
speaker: F
text: And we know <disfmarker>
speaker: F
text: Di - did I send you some results without adaptation ?
speaker: E
text: No .
speaker: E
text: Or if you did , I didn't include them ,
speaker: B
text: I s I think Stephane , uh , had seen them .
speaker: E
text: cuz it was <disfmarker>
speaker: B
text: So <disfmarker>
speaker: F
text: Yeah , I think I did , actually .
speaker: F
text: So there was a significant loss from not doing the adaptation .
speaker: B
text: Yeah .
speaker: F
text: Um .
speaker: F
text: A <disfmarker> a <disfmarker> a couple percent or some
speaker: F
text: I mean <disfmarker>
speaker: F
text: Well , I don't know it <disfmarker> Overall <disfmarker>
speaker: F
text: Uh , I <disfmarker> I don't remember ,
speaker: F
text: but there was <disfmarker> <nonvocalsound> there was a significant , um , loss or win <comment> from adaptation <disfmarker> with <disfmarker> with adaptation .
speaker: F
text: And , um ,
speaker: F
text: that was the phone - loop adaptation .
speaker: F
text: And then there was a very small <disfmarker> like point one percent on the natives <disfmarker> uh , win from doing , um , you know , adaptation to <pause> the recognition hypotheses .
speaker: F
text: And <pause> I tried both means adaptation and means and variances ,
speaker: F
text: and the variances added another <disfmarker> or subtracted another point one percent .
speaker: F
text: So , <vocalsound> it 's , um <disfmarker> that 's the number there .
speaker: F
text: Point six , I believe , is what you get with both , uh , means and variance adaptation .
speaker: E
text: Right .
speaker: B
text: But I think one thing is that , uh , I would presume <disfmarker>
speaker: B
text: Hav - Have you ever t <vocalsound> Have you ever tried this exact same recognizer out on the actual TI - digits test set ?
speaker: F
text: This exact same recognizer ?
speaker: F
text: No .
speaker: B
text: It might be interesting to do that .
speaker: B
text: Cuz my <disfmarker> my <disfmarker> cuz my sense ,
speaker: B
text: um <disfmarker>
speaker: F
text: But <disfmarker> but , I have <disfmarker> I mean , people <disfmarker> people at SRI are actually working on digits .
speaker: E
text: I bet it would do even slightly better .
speaker: F
text: I could <disfmarker> and they are using a system that 's , um <disfmarker> you know , h is actually trained on digits ,
speaker: F
text: um , but h h otherwise uses the same , you know , decoder , the same , uh , training methods , and so forth ,
speaker: B
text: Mm - hmm .
speaker: F
text: and I could ask them what they get <pause> on TI - digits .
speaker: B
text: Yeah , bu although I 'd be <disfmarker> I think it 'd be interesting to just take this exact actual system
speaker: B
text: so that these numbers were comparable
speaker: F
text: Mm - hmm .
speaker: F
text: Well , Adam knows how to run it ,
speaker: B
text: and try it out on TI - digits .
speaker: E
text: Yeah . No problem .
speaker: F
text: so you just make a f
speaker: B
text: Yeah .
speaker: B
text: Yeah .
speaker: B
text: Yeah .
speaker: B
text: Cuz our sense from the other <disfmarker> from the Aurora , uh , task is that <disfmarker>
speaker: E
text: And try it with TI - digits ?
speaker: F
text: Mm - hmm .
speaker: B
text: I mean , cuz we were getting sub one percent <vocalsound> numbers on TI - digits also with the tandem thing .
speaker: F
text: Mm - hmm .
speaker: F
text: Mmm .
speaker: B
text: So , <vocalsound> one <disfmarker> so there were a number of things we noted from this .
speaker: B
text: One is , yeah , the SRI system is a lot better than the HTK <disfmarker>
speaker: F
text: Hmm .
speaker: B
text: this , you know , very limited training HTK system .
speaker: F
text: Mm - hmm .
speaker: B
text: Uh , but the other is that , um , the digits <vocalsound> recorded here in this room with these close mikes , i uh , are actually a lot harder than the <pause> studio - recording TI - digits .
speaker: F
text: Mm - hmm .
speaker: B
text: I think , you know , one reason for that , uh , might be that there 's still <disfmarker> even though it 's close - talking , there still is some noise and some room acoustics .
speaker: F
text: Mm - hmm .
speaker: B
text: And another might be that , uh , I 'd <disfmarker> I would presume that in the studio , uh , uh , situation recording read speech that if somebody
speaker: B
text: did something a little funny or n pronounced something a little funny or made a little <disfmarker> that they didn't include it ,
speaker: E
text: They didn't include it .
speaker: B
text: they made them do it again .
speaker: E
text: Whereas , I took out <pause> the ones that I noticed that were blatant <disfmarker> that were correctable .
speaker: B
text: Mmm .
speaker: B
text: Yeah .
speaker: E
text: So that , if someone just read the wrong digit , I corrected it .
speaker: E
text: And then there was another one where Jose couldn't tell whether <disfmarker> I couldn't tell whether he was saying zero or six .
speaker: B
text: Yeah .
speaker: E
text: And I asked him and he couldn't tell either .
speaker: I
text: Hmm .
speaker: E
text: So I just cut it out .
speaker: E
text: You know , so I just e edited out the first , i uh , word of the utterance .
speaker: B
text: Yeah .
speaker: E
text: Um , so there 's a little bit of correction but it 's definitely not as clean as TI - digits .
speaker: E
text: So my expectations is TI - digits would , especially <disfmarker>
speaker: E
text: I think TI - digits is all <pause> American English .
speaker: E
text: Right ?
speaker: E
text: So it would probably do even a little better still
speaker: B
text: Mm - hmm .
speaker: E
text: on the SRI system ,
speaker: E
text: but we could give it a try .
speaker: F
text: Well .
speaker: F
text: But <pause> remember , we 're using a telephone bandwidth front - end here , uh , on this , uh <disfmarker> on this SRI system ,
speaker: F
text: so , <vocalsound> um , I was <disfmarker> I thought that maybe that 's actually a good thing
speaker: F
text: because it <disfmarker> it gets rid of some of the <disfmarker> uh , the noises ,
speaker: F
text: um , you know , in the <disfmarker> the <disfmarker> below and above the <disfmarker> um , the , you know , speech bandwidth
speaker: B
text: Mm - hmm .
speaker: B
text: Mm - hmm .
speaker: F
text: and , um ,
speaker: F
text: I suspect that to get sort of the last bit out of these higher - quality recordings you would have to in fact , uh , use models that , uh , were trained on wider - band data .
speaker: F
text: And of course we can't do that or <disfmarker>
speaker: E
text: Wha - what 's TI - digits ?
speaker: E
text: I thought t
speaker: B
text: It 's wide - band , yeah .
speaker: B
text: It 's <disfmarker> in <disfmarker> in fact , we looked it up
speaker: E
text: It is wide - band .
speaker: E
text: OK .
speaker: B
text: and it was actually twenty kilohertz sampling .
speaker: E
text: Oh , that 's right .
speaker: E
text: I <disfmarker> I did look that up .
speaker: F
text: Mm - hmm .
speaker: E
text: I couldn't remember whether that was TI - digits or one of the other digit tasks .
speaker: B
text: Yeah .
speaker: F
text: Right .
speaker: F
text: But <disfmarker> but , I would <disfmarker>
speaker: F
text: Yeah .
speaker: F
text: It 's <disfmarker> it 's easy enough to try ,
speaker: F
text: just run it on <disfmarker>
speaker: E
text: Mm - hmm .
speaker: B
text: Yeah .
speaker: E
text: So , Morgan , you 're getting a little breath noise .
speaker: B
text: See w
speaker: F
text: Now , eh , does <disfmarker>
speaker: F
text: one <disfmarker> one issue <disfmarker>
speaker: E
text: You might wanna move the mike down a little bit .
speaker: F
text: one issue with <disfmarker> with that is that <vocalsound> um , the system has this , uh , notion of a speaker to <disfmarker> which is used in adaptation , variance norm uh , you know , both in , uh , mean and variance normalization
speaker: F
text: and also in the VTL <pause> estimation .
speaker: B
text: Mm - hmm .
speaker: F
text: So <disfmarker>
speaker: E
text: Yeah , I noticed the script that extracted it .
speaker: F
text: Do y ?
speaker: F
text: Is <disfmarker> ?
speaker: F
text: So does <disfmarker> so th so does <disfmarker> does , um , <vocalsound> the TI - digits database have speakers that are known ?
speaker: E
text: Yep .
speaker: E
text: Yep .
speaker: F
text: And is there <disfmarker> is there enough data or a comparable <disfmarker> comparable amount of data to <disfmarker> to what we have in our recordings here ?
speaker: E
text: That I don't know .
speaker: E
text: I don't know .
speaker: E
text: I don't know how many speakers there are ,
speaker: E
text: and <disfmarker> and how many speakers per utterance .
speaker: F
text: OK .
speaker: B
text: Yeah .
speaker: B
text: Well , the other thing would be to do it without the adaptation and compare to these numbers without the adaptation .
speaker: B
text: That would <disfmarker>
speaker: F
text: Right . Uh , but I 'm not so much worried about the adaptation , actually , than <disfmarker> than the , um , <vocalsound> um <disfmarker> the , uh , VTL estimation .
speaker: E
text: Right .
speaker: F
text: If you have only one utterance per speaker you might actually screw up on estimating the <disfmarker> the warping , uh , factor .
speaker: F
text: So , um <disfmarker>
speaker: E
text: I strongly suspect that they have more speakers than we do .
speaker: F
text: Right . But it 's not the amount of speakers ,
speaker: E
text: So , uh <disfmarker>
speaker: F
text: it 's the num it 's the amount of data per speaker .
speaker: E
text: Right . So we <disfmarker> we could probably do an extraction that was roughly equivalent .
speaker: F
text: Right .
speaker: F
text: Right .
speaker: E
text: Um .
speaker: F
text: So <disfmarker>
speaker: E
text: So , although I <disfmarker> I sort of know how to run it , there are a little <disfmarker> a f few details here and there that I 'll have to <pause> dig out .
speaker: F
text: OK .
speaker: F
text: The key <disfmarker>
speaker: F
text: So th the system actually extracts the speaker ID from the waveform names .
speaker: E
text: Right . I saw that .
speaker: F
text: And there 's a <disfmarker> there 's a script <disfmarker> and that is actually all in one script .
speaker: F
text: So there 's this one script that parses waveform names
speaker: F
text: and extracts things like the , um , speaker , uh , ID
speaker: F
text: or something that can stand in as a speaker ID .
speaker: F
text: So , we might have to modify that script to recognize the , um , speakers , <vocalsound> um , in the <disfmarker> in the , uh , um , <vocalsound> TI - digits <pause> database .
speaker: E
text: Right .
speaker: E
text: Right .
speaker: E
text: And that , uh <disfmarker>
speaker: F
text: Or you can fake <disfmarker> you can fake <pause> names for these waveforms that resemble the names that we use here for the <disfmarker> for the meetings .
speaker: E
text: Right .
speaker: F
text: That would be the , sort of <disfmarker> probably the safest way to do <disfmarker>
speaker: E
text: I might have to do that anyway to <disfmarker> to do <disfmarker>
speaker: E
text: because we may have to do an extract to get the <pause> amount of data per speaker about right .
speaker: F
text: Uh - huh .
speaker: E
text: The other thing is , isn't TI - digits isolated digits ?
speaker: F
text: Right .
speaker: E
text: Or is that another one ?
speaker: E
text: I 'm <disfmarker> I looked through a bunch of the digits t corp corpora ,
speaker: E
text: and now they 're all blurring .
speaker: B
text: Mm - hmm .
speaker: E
text: Cuz one of them was literally people reading a single digit .
speaker: E
text: And then others were connected digits .
speaker: B
text: Yeah . Most of TI - digits is connected digits , I think .
speaker: E
text: OK .
speaker: B
text: The <disfmarker> I mean , we had a Bellcore corpus that we were using .
speaker: E
text: Maybe it 's the Bell Gram .
speaker: B
text: It was <disfmarker> <vocalsound> that 's <disfmarker> that was isolated digits .
speaker: E
text: Bell Digits .
speaker: E
text: Alright .
speaker: F
text: By the way , I think we can improve these numbers if we care to compr improve them <vocalsound> by , um , <vocalsound> not starting with the Switchboard models but by taking the Switchboard models and doing supervised adaptation on a small amount of digit data collected in this setting .
speaker: B
text: Um .
speaker: E
text: Yep .
speaker: F
text: Because that would adapt your models to the room acoustics
speaker: F
text: and f for the far - field microphones , you know , to the noise .
speaker: F
text: And that should really improve things , um , further .
speaker: F
text: And then you use those adapted models , which are not speaker adapted but sort of acous you know , channel adapted <disfmarker>
speaker: E
text: Channel adapted .
speaker: F
text: use that as the starting models for your speaker adaptation .
speaker: B
text: Yeah . <vocalsound> But the thing is , uh <disfmarker> I mean , w when you <disfmarker> it depends whether you 're ju were just using this as a <disfmarker> <vocalsound> a starter task for <disfmarker> you know , to get things going for conversational or if we 're really interested i in connected digits .
speaker: B
text: And I <disfmarker> I think the answer is both .
speaker: F
text: Well , I don't know .
speaker: B
text: And for <disfmarker> for connected digits over the telephone you don't actually want to put a whole lot of effort into adaptation
speaker: B
text: because <vocalsound> somebody <pause> gets on the phone and says a number
speaker: B
text: and then you just want it .
speaker: B
text: You don't <disfmarker> don't , uh <disfmarker>
speaker: C
text: This is <disfmarker> this <disfmarker> that one 's better .
speaker: F
text: Right .
speaker: C
text: Mm - hmm .
speaker: F
text: Um , but , you know , I <disfmarker> uh , my impression was that you were actually interested in the far - field microphone , uh , problem ,
speaker: F
text: I mean .
speaker: F
text: So ,
speaker: F
text: you want to <disfmarker> you want to <disfmarker> That 's the obvious thing to try .
speaker: C
text: Oh .
speaker: C
text: Oh .
speaker: F
text: Right ?
speaker: F
text: Then , eh <disfmarker> because you <disfmarker> you don't have any <disfmarker>
speaker: B
text: Right .
speaker: C
text: Yeah .
speaker: F
text: That 's where the most m acoustic mismatch is between the currently used models and the <disfmarker> the r the set up here .
speaker: B
text: Right .
speaker: F
text: So .
speaker: B
text: Yeah . So that 'd be anoth another interesting data point .
speaker: F
text: Mm - hmm .
speaker: B
text: I mean , I <disfmarker> I guess I 'm saying I don't know if we 'd want to do that as the <disfmarker> as <disfmarker>
speaker: E
text: Other way .
speaker: D
text: Other way .
speaker: E
text: Liz <disfmarker>
speaker: A
text: Now you 're all watching me .
speaker: E
text: It f it clips over your ears .
speaker: A
text: Alright .
speaker: A
text: This way .
speaker: E
text: There you go .
speaker: C
text: If you have a strong fe if you have a strong preference , you could use this .
speaker: A
text: You 're all watching .
speaker: A
text: This is terrible .
speaker: C
text: It 's just we <disfmarker> we think it has some spikes .
speaker: C
text: So , uh , we <disfmarker> we didn't use that one .
speaker: A
text: I 'll get it .
speaker: C
text: But you could if you want .
speaker: B
text: Yeah . At any rate , I don't know if w
speaker: C
text: I don't know .
speaker: C
text: And Andre - Andreas , your <disfmarker> your microphone 's a little bit low .
speaker: F
text: It is ?
speaker: B
text: Yeah .
speaker: C
text: Yeah .
speaker: B
text: I don't know if we wanna use that as the <disfmarker>
speaker: F
text: Uh .
speaker: E
text: Uh , it pivots .
speaker: C
text: So if you see the picture
speaker: F
text: I I <disfmarker>
speaker: E
text: It <disfmarker> it <disfmarker> like this .
speaker: C
text: and then you have to scr
speaker: F
text: I <disfmarker> I already adjusted this a number of times .
speaker: E
text: Eh .
speaker: F
text: I <disfmarker> I
speaker: E
text: Yeah , I think these mikes are not working as well as I would like .
speaker: F
text: can't quite seem to <disfmarker>
speaker: F
text: Yeah , I think this contraption around your head is not <pause> working so well .
speaker: B
text: Too many adju too many adjustments . Yeah .
speaker: B
text: Anyway , what I was saying is that I <disfmarker> I think I probably wouldn't want to see that as sort of like the norm , that we compared all things to .
speaker: C
text: That looks good .
speaker: C
text: Yeah .
speaker: B
text: To , uh , the <disfmarker> to have <disfmarker> have all this ad all this , uh , adaptation .
speaker: B
text: But I think it 's an important data point , if you 're <disfmarker> if <disfmarker>
speaker: F
text: Right .
speaker: B
text: Yeah .
speaker: B
text: Um .
speaker: B
text: The other thing that <disfmarker> that , uh <disfmarker> of course , what Barry was looking at was <disfmarker> was just that ,
speaker: B
text: the near versus far .
speaker: B
text: And , yeah , the adaptation would get <vocalsound> th some of that .
speaker: F
text: Mm - hmm .
speaker: B
text: But , I think even <disfmarker> even if there was , uh , only a factor of two or something , like I was saying in the email , I think that 's <disfmarker> <vocalsound> that 's a big factor .
speaker: F
text: Mm - hmm .
speaker: B
text: So <disfmarker>
speaker: E
text: Liz , you could also just use the other mike if you 're having problems with that one .
speaker: B
text: N
speaker: C
text: Well .
speaker: A
text: OK .
speaker: C
text: Yeah . This would be OK .
speaker: C
text: We <disfmarker> we <disfmarker> we think that this has spikes on it ,
speaker: A
text: It 's this thing 's <disfmarker> This is too big for my head .
speaker: C
text: so it 's not as good acoustically ,
speaker: F
text: Yeah , basically your ears are too big .
speaker: C
text: but <disfmarker>
speaker: F
text: I mean , mine are too .
speaker: F
text: E th everybody 's ears are too big for these things .
speaker: A
text: No , my <disfmarker> my <disfmarker> But this is too big for my head .
speaker: F
text: Uh <disfmarker>
speaker: A
text: So , I mean , <comment> <comment> it doesn't <disfmarker> you know , it 's sit
speaker: C
text: Well , if you 'd rather have this one then it 's <disfmarker>
speaker: A
text: OK .
speaker: B
text: Yeah .
speaker: E
text: Oh , well .
speaker: B
text: It 's <pause> great .
speaker: E
text: So the <disfmarker> To get that , uh , pivoted this way , it pivots like this .
speaker: A
text: No this way .
speaker: E
text: Yeah .
speaker: A
text: Yeah .
speaker: E
text: There you go .
speaker: C
text: And there 's a screw that you can tighten .
speaker: E
text: And then it <disfmarker>
speaker: E
text: Right .
speaker: A
text: Right .
speaker: A
text: I already <pause> tried to get it close .
speaker: C
text: Good .
speaker: E
text: So if it doesn't bounce around too much , that 's actually good placement .
speaker: C
text: That looks good .
speaker: A
text: OK .
speaker: E
text: But it looks like it 's gonna bounce a lot .
speaker: B
text: So , where were we ?
speaker: B
text: Uh <disfmarker> <vocalsound> Yeah .
speaker: C
text: Yeah .
speaker: E
text: Digits .
speaker: E
text: Adaptation .
speaker: B
text: Uh , adaptation , non - adaptation ,
speaker: B
text: um , factor of two ,
speaker: B
text: um <disfmarker>
speaker: F
text: What k u By the way , wh what factor of two did you <disfmarker> ?
speaker: B
text: Oh , yeah . I know what I was go w
speaker: F
text: I mean <disfmarker>
speaker: B
text: Oh , no , no .
speaker: B
text: It 's tha that <disfmarker> that we were saying , you know , well is <disfmarker> how much worse is far than near , you know .
speaker: F
text: Oh , th OK .
speaker: B
text: And I mean it depends on which one you 're looking at ,
speaker: F
text: That factor of two .
speaker: F
text: Mm - hmm .
speaker: B
text: but for the everybody , it 's <vocalsound> little under a factor or two .
speaker: B
text: Yeah . I <disfmarker> I know what I was thinking was that maybe , uh , i i we could actually t t try at least looking at , uh , some of the <disfmarker> the large vocabulary speech from a far microphone ,
speaker: B
text: at least from the good one .
speaker: F
text: Mm - hmm .
speaker: B
text: I mean , before I thought we 'd get , you know , a hundred and fifty percent error or something ,
speaker: F
text: Mm - hmm .
speaker: B
text: but if <disfmarker> <vocalsound> if , uh <disfmarker> if we 're getting thirty - five , forty percent or something , <vocalsound> u um <disfmarker>
speaker: A
text: Actually if you run , though , on a close - talking mike over the whole meeting , during all those silences , you get , like , four hundred percent word error .
speaker: B
text: Mm - hmm .
speaker: B
text: Right . I understand .
speaker: B
text: But doing the same kind of limited thing <disfmarker>
speaker: A
text: Or <disfmarker> or some high number .
speaker: B
text: Yeah , sure .
speaker: B
text: Get all these insertions .
speaker: B
text: But I 'm saying if you do the same kind of limited thing <vocalsound> as people have done in Switchboard evaluations or as <disfmarker> a
speaker: A
text: Yeah .
speaker: A
text: Where you know who the speaker is and there 's no overlap ?
speaker: B
text: Yeah .
speaker: A
text: And you do just the far - field for those regions ?
speaker: B
text: Yeah . The same sort of numbers that we got those graphs from .
speaker: E
text: Could we do exactly the same thing that we 're doing now , but do it with a far - field mike ?
speaker: B
text: Right ?
speaker: B
text: Yeah , do it with one of <disfmarker> on
speaker: E
text: Cuz we extract the times from the near - field mike ,
speaker: E
text: but you use the acoustics from the far - field mike .
speaker: A
text: Right . I understand that .
speaker: A
text: I just meant that <disfmarker> so you have <pause> three choices .
speaker: A
text: There 's , um <disfmarker> You can use times where that person is talking only from the transcripts but the segmentations were <disfmarker> were synchronized .
speaker: A
text: Or you can do a forced alignment on the close - talking to determine that , the you know , within this segment , these really were the times that this person was talking
speaker: A
text: and elsewhere in the segment other people are overlapping
speaker: A
text: and just front - end those pieces .
speaker: A
text: Or you can run it on the whole data ,
speaker: A
text: which is <disfmarker> which is , you know , a <disfmarker>
speaker: B
text: But <disfmarker> but <disfmarker> but how did we get the <disfmarker> how did we determine the links , uh , that we 're testing on in the stuff we reported ?
speaker: A
text: In the H L T paper we took <pause> segments that are channel <disfmarker> time - aligned ,
speaker: A
text: which is now h being changed in the transcription process ,
speaker: A
text: which is good ,
speaker: A
text: and we took cases where the transcribers said there was only one person talking here ,
speaker: A
text: because no one else had time <disfmarker> any words in that segment
speaker: A
text: and called that " non - overlap " .
speaker: B
text: And tha
speaker: B
text: And that 's what we were getting those numbers from .
speaker: A
text: Yes .
speaker: B
text: Right .
speaker: A
text: Tho - good <disfmarker> the good numbers .
speaker: A
text: The bad numbers were from <pause> the segments where there was overlap .
speaker: B
text: Well , we could start with the good ones .
speaker: B
text: But anyway <disfmarker> so I think that we should try it once with <vocalsound> the same conditions that were used to create those ,
speaker: A
text: Yeah .
speaker: B
text: and in those same segments just use one of the P Z
speaker: A
text: Right . So we <disfmarker> we can do that .
speaker: B
text: And then , you know , I mean , the thing is if we were getting , uh <disfmarker> what , thirty - five , forty percent , something like that on <disfmarker> on that particular set ,
speaker: A
text: Yeah .
speaker: B
text: uh , does it go to seventy or eighty ?
speaker: B
text: Or , does it use up so much memory we can't decode it ?
speaker: A
text: Right .
speaker: A
text: It might also depend on which speaker th it is and how close they are to the PZM ?
speaker: B
text: Uh <disfmarker>
speaker: A
text: I don't know how different they are from each other .
speaker: F
text: You want to probably choose the PZM channel that is closest to the speaker .
speaker: A
text: To be best <disfmarker>
speaker: E
text: For this particular digit ones , I just picked that one .
speaker: D
text: Yeah .
speaker: A
text: f
speaker: B
text: Well <disfmarker>
speaker: A
text: OK .
speaker: F
text: Oh , OK .
speaker: A
text: So we would then use that one , too ,
speaker: E
text: So <disfmarker>
speaker: B
text: This is kind of central .
speaker: A
text: or <disfmarker> ?
speaker: B
text: You know , it 's <disfmarker> so i but I would <disfmarker> I 'd pick that one .
speaker: B
text: It 'll be less good for some people than for other ,
speaker: B
text: but I <disfmarker> I 'd like to see it on the same <disfmarker> exact same data set that <disfmarker> that we did the other thing on .
speaker: E
text: Actually <disfmarker>
speaker: E
text: I sh actually should 've picked a different one ,
speaker: B
text: Right ?
speaker: E
text: because <pause> that could be why the PDA is worse .
speaker: E
text: Because it 's further away from most of the people reading digits .
speaker: D
text: It 's further away . Yeah .
speaker: D
text: Yeah .
speaker: B
text: That 's probably one of the reasons .
speaker: C
text: Hmm .
speaker: C
text: Mm - hmm .
speaker: A
text: Well , yeah . You could look at , I guess , that PZM or something .
speaker: E
text: Yep .
speaker: B
text: But the other is , it 's very , uh <disfmarker> I mean , even though there 's <disfmarker> I 'm sure the f f the <disfmarker> the SRI , uh , front - end has some kind of pre - emphasis , it 's <disfmarker> it 's , uh <disfmarker> <vocalsound> still , th it 's picking up lots of low - frequency energy .
speaker: F
text: Mm - hmm .
speaker: B
text: So , even discriminating against it , I 'm sure some of it 's getting through .
speaker: B
text: Um .
speaker: B
text: But , yeah , you 're right .
speaker: B
text: Prob - a part of it is just the distance .
speaker: A
text: And aren't these pretty bad microphones ?
speaker: E
text: Yep .
speaker: A
text: I mean <disfmarker>
speaker: B
text: Well , they 're bad .
speaker: B
text: But , I mean , if you listen to it , it sounds OK . You know ?
speaker: E
text: Yeah . When you listen to it , uh , the PZM and the PDA <disfmarker> Yeah , th the PDA has higher sound floor
speaker: B
text: u Yeah .
speaker: E
text: but not by a lot .
speaker: E
text: It 's really pretty <disfmarker> uh , pretty much the same .
speaker: A
text: I just remember you saying you got them to be cheap on purpose .
speaker: A
text: Cheap in terms of their quality .
speaker: A
text: So .
speaker: B
text: Well , they 're <pause> twenty - five cents or so .
speaker: E
text: Th - we wanted them to be <disfmarker> to be typical of what would be in a PDA .
speaker: B
text: Yeah .
speaker: E
text: So they are <disfmarker> they 're not the PZM three hundred dollar type .
speaker: A
text: Mm - hmm .
speaker: E
text: They 're the twenty - five cent ,
speaker: B
text: Yeah .
speaker: E
text: buy them in packs of thousand type .
speaker: B
text: But , I mean , the thing is people use those little mikes for everything
speaker: A
text: I see .
speaker: E
text: Everything .
speaker: B
text: because they 're really not bad .
speaker: B
text: I mean , if you 're not <vocalsound> doing something ridiculous like feeding it to a speech recognizer , they <disfmarker> they <disfmarker> <vocalsound> they <disfmarker> you know , you can hear the sou hear the sounds just fine .
speaker: A
text: Mm - hmm .
speaker: A
text: Right .
speaker: B
text: You know , it 's <disfmarker>
speaker: B
text: They <disfmarker> I mean , i it 's more or less the same principles as these other mikes are built under ,
speaker: B
text: it 's just that <pause> there 's less quality control .
speaker: B
text: They just , you know , churn them out and don't check them .
speaker: B
text: Um . So .
speaker: B
text: So that was <disfmarker> Yeah . So that was i interesting result .
speaker: B
text: So like I said , the front - end guys are very much interested in <disfmarker> in this is as <disfmarker> as well
speaker: B
text: and
speaker: F
text: So <disfmarker> so , but where is this now ?
speaker: F
text: I mean , what 's <disfmarker> where do we go from here ?
speaker: F
text: I mean ,
speaker: E
text: Yeah . That was gonna be my question .
speaker: F
text: we <disfmarker> so we have a <disfmarker> we have a <disfmarker> a system that works pretty well
speaker: F
text: but it 's not , you know , the system that people here are used to using <disfmarker> to working with .
speaker: F
text: So what <disfmarker> what do we do now ?
speaker: B
text: Well , I think what we wanna do is we want to <disfmarker> eh ,
speaker: B
text: and we 've talked about this in other <pause> contexts <disfmarker>
speaker: B
text: we want to <vocalsound> have the ability to feed it different features .
speaker: F
text: Mm - hmm .
speaker: B
text: And then , um , <vocalsound> from the point of view of the front - end research , it would be s uh , substituting for HTK .
speaker: F
text: OK .
speaker: F
text: OK .
speaker: B
text: I think that 's the key thing .
speaker: B
text: And then if we can feed it different features , then we can try all the different things that we 're trying there .
speaker: F
text: OK . Alright .
speaker: B
text: And then , um , uh , also Dave is <disfmarker> is thinking about using the data in different ways , uh , to <vocalsound> um , uh , explicitly work on reverberation
speaker: F
text: Mm - hmm .
speaker: B
text: starting with some techniques that some other people have <pause> found somewhat useful , and <disfmarker> Yeah .
speaker: F
text: OK .
speaker: F
text: So <disfmarker> so the key <pause> thing that 's missing here is basically the ability to feed , you know , other features <vocalsound> i into the recognizer
speaker: F
text: and also then to train the system .
speaker: B
text: Right .
speaker: B
text: Right .
speaker: F
text: OK .
speaker: F
text: And , uh , es I don't know when Chuck will be back
speaker: F
text: but that 's exactly what he <disfmarker> he 's gonna <disfmarker>
speaker: B
text: H h
speaker: B
text: He 's <disfmarker> he 's sort of back ,
speaker: B
text: but he drove for fourteen hours an and wasn't gonna make it in today .
speaker: F
text: Oh , OK .
speaker: F
text: So , I think that 's one of the things that he said he would be working on .
speaker: F
text: Um .
speaker: F
text: Just sort of t to make sure that <pause> we can do that
speaker: E
text: Yeah .
speaker: F
text: and <disfmarker> Um .
speaker: B
text: Yeah .
speaker: B
text: Right .
speaker: F
text: It 's <disfmarker> uh , I mean , the <disfmarker> the front - end is f i tha that 's in the SRI recognizer is very nice in that it does a lot of things on the fly
speaker: F
text: but it unfortunately <pause> is not <pause> designed and , um <disfmarker> <vocalsound> like the , uh , ICSI system is , where you can feed it from a pipeline of <disfmarker> of the command .
speaker: F
text: So , the <disfmarker> what that means probably for the foreseeable future is that you have to , uh , dump out , um <disfmarker>
speaker: F
text: you know , if you want to use some new features , you have to dump them into individual files
speaker: F
text: and <pause> give those files to the recognizer .
speaker: E
text: We do <disfmarker> we tend to do that anyway .
speaker: F
text: OK .
speaker: E
text: Oh .
speaker: E
text: So , although you <disfmarker> you can pipe it as well , we tend to do it that way
speaker: E
text: because that way you can concentrate on one block and not keep re - doing it over and over .
speaker: F
text: Oh , OK .
speaker: F
text: Alright .
speaker: B
text: Yeah .
speaker: B
text: Yeah . So I 've <disfmarker> I <disfmarker>
speaker: E
text: So tha that 's exactly what the P - file <pause> is for .
speaker: B
text: Yeah .
speaker: F
text: Yeah , the <disfmarker> the <disfmarker> the cumbersome thing is <disfmarker> is , um <disfmarker> is that you actually have to dump out little <disfmarker> little files .
speaker: A
text: Uh <disfmarker>
speaker: F
text: So for each segment that you want to recognize <vocalsound> you have to <pause> dump out <pause> a separate file .
speaker: E
text: Uh - huh .
speaker: F
text: Just like i th like th as if there were these waveform segments ,
speaker: F
text: but instead you have sort of feature file segments .
speaker: F
text: But , you know <disfmarker>
speaker: F
text: So .
speaker: B
text: Cool .
speaker: B
text: OK . So the s the <disfmarker> the next thing we had on the agenda was something about alignments ?
speaker: A
text: Oh .
speaker: A
text: Yes , we have <disfmarker>
speaker: A
text: I don't know ,
speaker: A
text: did you wanna talk about it ,
speaker: A
text: or <disfmarker> ?
speaker: A
text: I can give a <disfmarker> I was just telling this to Jane
speaker: A
text: and <disfmarker> and <disfmarker> W we <disfmarker> we were able to get some definite improvement on the forced alignments by looking at them first and then realizing the kinds of errors <pause> that were occurring
speaker: A
text: and um ,
speaker: A
text: some of the errors occurring very frequently are just things like the first word being moved to as early as possible in the recognition ,
speaker: A
text: which is a um , I think was both a <disfmarker> a pruning <pause> problem
speaker: A
text: and possibly a problem with needing constraints on word locations .
speaker: A
text: And so we tried both of these st things .
speaker: A
text: We tried saying <disfmarker>
speaker: A
text: I don't know ,
speaker: A
text: I got this <vocalsound> whacky idea that <disfmarker> just from looking at the data , that when people talk <pause> their words are usually chunked together .
speaker: A
text: It 's not that they say one word and then there 's a bunch of words together .
speaker: A
text: They 're <comment> might say one word and then another word far away if they were doing just backchannels ?
speaker: A
text: But in general , if there 's , like , five or six words and one word 's far away from it , that 's probably wrong on average .
speaker: A
text: So , um <disfmarker>
speaker: A
text: And then also , ca the pruning , of course , was too <disfmarker> too severe .
speaker: F
text: So that 's actually interesting .
speaker: F
text: The pruning was the same value that we used for recognition .
speaker: F
text: And we had lowered that <disfmarker> we had used tighter pruning after Liz ran some experiments showing that , you know , it runs slower
speaker: F
text: and there 's no real difference in <disfmarker>
speaker: E
text: No gain .
speaker: A
text: Actually it was better with <disfmarker> slightly better or about th
speaker: F
text: Right .
speaker: A
text: it was the same with tighter pruning .
speaker: F
text: So for free recognition , this <disfmarker> the lower pruning value is better .
speaker: F
text: You <disfmarker>
speaker: A
text: It 's probably cuz the recognition 's just bad en at a point where it 's bad enough that <disfmarker> that you don't lose anything .
speaker: F
text: Correct .
speaker: F
text: Right .
speaker: F
text: Um , but it turned out for <disfmarker> for <disfmarker> to get accurate alignments it was really important to open up the pruning significantly .
speaker: A
text: Right .
speaker: B
text: Hmm .
speaker: F
text: Um <pause> because otherwise it would sort of do greedy alignment , um , in regions where there was no real speech yet from the foreground speaker .
speaker: B
text: Mm - hmm .
speaker: F
text: Um , <vocalsound> so that was one big factor that helped improve things
speaker: F
text: and then the other thing was that ,
speaker: F
text: you know , as Liz said the <disfmarker> we f enforce the fact that , uh , the foreground speech has to be continuous .
speaker: F
text: It cannot be <disfmarker> you cannot have a background speech hypothesis in the middle of the foreground speech .
speaker: F
text: You can only have background speech at the beginning and the end .
speaker: A
text: Yeah . I mean , yeah , it isn't always true ,
speaker: A
text: and I think what we really want is some clever way to do this ,
speaker: A
text: where , um , you know , from the data or from maybe some hand - corrected alignments from transcribers that
speaker: A
text: things like words that do occur just by themselves <pause> a alone , like backchannels or something that we did allow to have background speech around it <disfmarker>
speaker: D
text: Yeah .
speaker: A
text: those would be able to do that ,
speaker: C
text: Sorry .
speaker: A
text: but the rest would be constrained .
speaker: A
text: So , I think we have a version that 's pretty good for the native speakers .
speaker: A
text: I don't know yet about the non - native speakers .
speaker: A
text: And , um ,
speaker: A
text: we basically also made noise models for the different <disfmarker> sort of grouped some of the <pause> mouth noises together .
speaker: A
text: Um , so , and then there 's a background speech model .
speaker: A
text: And we also <disfmarker>
speaker: A
text: There was some neat <disfmarker> or , interesting cases ,
speaker: A
text: like there 's one meeting where , <vocalsound> um , Jose 's giving a presentation
speaker: A
text: and he 's talking about , um , the word " mixed <pause> signal "
speaker: A
text: and someone didn't understand , uh , that you were saying " mixed " <disfmarker>
speaker: A
text: I think , Morgan .
speaker: H
text: Yeah , yeah .
speaker: A
text: And so your speech - ch was s saying something about mixed signal .
speaker: A
text: And the next turn was a lot of people saying " mixed " ,
speaker: A
text: like " he means mixed signal " or " I think it 's mixed " .
speaker: A
text: And the word " mixed " in this segment occurs , like , a bunch of times .
speaker: H
text: Sh
speaker: A
text: And Chuck 's on the lapel here ,
speaker: A
text: and he also says " mixed "
speaker: A
text: but it 's at the last one ,
speaker: A
text: and of course the aligner th aligns it everywhere else to everybody else 's " mixed " ,
speaker: H
text: Yeah .
speaker: A
text: cuz there 's no adaptation yet .
speaker: A
text: So there 's <disfmarker> <vocalsound> I think there 's some issues about <disfmarker> u
speaker: A
text: We probably want to adapt at least the foreground speaker .
speaker: A
text: But , I guess Andreas tried adapting both the foreground and a background generic speaker ,
speaker: A
text: and that 's actually a little bit of a f funky model .
speaker: A
text: Like , it gives you some weird alignments ,
speaker: A
text: just because often the background speakers match better to the foreground than the foreground speaker .
speaker: F
text: Oh <disfmarker>
speaker: D
text: Yeah .
speaker: H
text: Oh .
speaker: A
text: So there 's some things there ,
speaker: A
text: especially when you get lots of the same words , uh , occurring in the <disfmarker>
speaker: F
text: Well , the <disfmarker>
speaker: F
text: I <disfmarker> I think you can do better by <vocalsound> uh , cloning <disfmarker>
speaker: F
text: so we have a reject phone .
speaker: F
text: And you <disfmarker> and what we wanted to try with <disfmarker> you know , once we have this paper written and have a little more time , <vocalsound> uh , t cloning that reject model
speaker: F
text: and then one copy of it would be adapted to the foreground speaker to capture the rejects in the foreground ,
speaker: F
text: like fragments and stuff ,
speaker: F
text: and the other copy would be adapted to the background speaker .
speaker: A
text: Right . I mean , in general we actually <disfmarker>
speaker: F
text: And <disfmarker>
speaker: A
text: Right now the words like <pause> partial words are <pause> reject models
speaker: F
text: Mm - hmm .
speaker: A
text: and you normally allow those to match to any word .
speaker: A
text: But then the background speech was also a reject model ,
speaker: A
text: and so this constraint of not allowing rejects in between <disfmarker>
speaker: A
text: you know , it needs to differentiate between the two .
speaker: A
text: So just sort of working through a bunch of debugging kinds of issues .
speaker: F
text: Right .
speaker: A
text: And another one is turns , like people starting with <vocalsound> " well I think "
speaker: A
text: and someone else is <pause> " well how about " .
speaker: A
text: So the word " well " is in this <disfmarker> in this <pause> segment multiple times ,
speaker: A
text: and as soon as it occurs usually the aligner will try to align it to the first person who says it .
speaker: A
text: But then that constraint of sort of <disfmarker> uh , proximity constraint will push it over to the person who really said it in general .
speaker: E
text: Is the proximity constraint a hard constraint ,
speaker: E
text: or did you do some sort of probabilistic weighting distance , or <disfmarker> ?
speaker: F
text: We <disfmarker> we didn't <disfmarker>
speaker: F
text: No .
speaker: A
text: Right now it 's a kluge .
speaker: F
text: We <disfmarker> w
speaker: F
text: OK .
speaker: F
text: We <disfmarker> it 's straightforward to actually just have a <disfmarker> a penalty that doesn't completely disallows it but discourages it .
speaker: F
text: But , um , we just didn't have time to play with , you know , tuning yet another <disfmarker> yet another parameter .
speaker: E
text: The ve level .
speaker: E
text: Yeah .
speaker: A
text: Yeah .
speaker: F
text: And really the reason we can't do it is just that we don't have a <disfmarker> we don't have ground truth for these .
speaker: F
text: So , <vocalsound> we would need a hand - marked , um , <vocalsound> word - level alignments
speaker: F
text: or at least sort of the boundaries of the speech betw you know , between the speakers .
speaker: F
text: Um , and then use that as a reference
speaker: F
text: and tune the parameters of the <disfmarker> of the model , uh , to op to get the best <pause> performance .
speaker: A
text: Yeah .
speaker: B
text: G given <disfmarker> I <disfmarker> I mean , I wa I wa I was gonna ask you anyway , uh , how you assessed that things were better .
speaker: F
text: Mm - hmm .
speaker: A
text: I looked at them .
speaker: A
text: I spent two days <disfmarker> um , in Waves <disfmarker>
speaker: B
text: OK .
speaker: A
text: Oh , it was painful
speaker: A
text: because <vocalsound> the thing is , you know the alignments share a lot in common ,
speaker: A
text: so <disfmarker>
speaker: A
text: And you 're <disfmarker> yo you 're looking at these segments where there 's a lot of speech .
speaker: A
text: I mean , a lot of them have a lot of words .
speaker: B
text: Yeah .
speaker: A
text: Not by every speaker
speaker: A
text: but by some speaker there 's a lot of words .
speaker: B
text: Yeah .
speaker: H
text: Ju
speaker: A
text: No , not <disfmarker>
speaker: A
text: I mean that if you look at the individual segments from just one person you don't see a lot of words ,
speaker: B
text: Yeah .
speaker: F
text: Mm - hmm .
speaker: B
text: Yeah .
speaker: A
text: but altogether you 'll see a lot of words up there .
speaker: A
text: And so the reject is also mapping and pauses <disfmarker>
speaker: D
text: Yeah .
speaker: A
text: So I looked at them all in Waves
speaker: A
text: and just lined up all the alignments ,
speaker: A
text: and , at first it sort of looked like a mess
speaker: A
text: and then the more I looked at it , I thought " OK , well it 's moving these words leftward
speaker: A
text: and <disfmarker> " You know , it wasn't that bad .
speaker: A
text: It was just doing certain things wrong .
speaker: A
text: So <disfmarker>
speaker: A
text: But , I don't , you know , have time to l <comment> to look at all of them
speaker: A
text: and it would be really useful to have , like , a <disfmarker> a transcriber who could use Waves ,
speaker: A
text: um , just mark , like , the beginning and end of the foreground speaker 's real words <disfmarker>
speaker: A
text: like , the beginning of the first word , the end of the last word <disfmarker>
speaker: C
text: Yeah .
speaker: A
text: and then we could , you know , do some adjustments .
speaker: C
text: I <disfmarker> OK .
speaker: C
text: I have to ask you something ,
speaker: C
text: is i does it have to be Waves ? Because if we could benefit from what you did , incorporate that into the present transcripts , <comment> that would help .
speaker: F
text: No .
speaker: C
text: And then , um , the other thing is , I believe that I did hand
speaker: C
text: So . One of these transcripts was gone over by a transcriber
speaker: C
text: and then I hand - marked it myself so that we do have , uh , the beginning and ending of individual utterances .
speaker: F
text: Mm - hmm .
speaker: C
text: Um , I didn't do it word level ,
speaker: C
text: but <disfmarker> but in terms <disfmarker>
speaker: C
text: So I <disfmarker> so for <disfmarker> for one of the N S A groups .
speaker: A
text: Mm - hmm .
speaker: C
text: And also I went back to the original one that I first transcribed and <disfmarker> and did it w uh , w uh , utterance by utterance for that particular one .
speaker: C
text: So I think you do have <disfmarker>
speaker: C
text: if that 's a sufficient unit , I think that you do have hand - marking for that .
speaker: C
text: But it 'd be wonderful to be able to <vocalsound> benefit from your Waves stuff .
speaker: A
text: Mm - hmm .
speaker: F
text: We don't care what <disfmarker> what tool you use .
speaker: A
text: Yeah . I mean , if <disfmarker> if you can , um <disfmarker> if you wanna <disfmarker>
speaker: C
text: OK .
speaker: C
text: I used it in Transcriber
speaker: F
text: U uh <disfmarker>
speaker: C
text: and it 's <disfmarker> it 's in the <disfmarker>
speaker: A
text: well , Jane and I were <disfmarker> just in terms of the tool , talking about this .
speaker: A
text: I guess Sue had had some <pause> reactions .
speaker: A
text: You know , interface - wise if you 're looking at speech , you wanna be able to know really where the words are .
speaker: C
text: Yeah , that 's right .
speaker: A
text: And so , <vocalsound> we can give you some examples of sort of what this output looks like ,
speaker: C
text: Middle of the word , or <disfmarker>
speaker: A
text: um , and see if you can in maybe incorporate it into the Transcriber tool some way ,
speaker: A
text: or <disfmarker>
speaker: C
text: Well , I th I 'm thinking just ch e e incorporating it into the representation .
speaker: A
text: Um .
speaker: C
text: I mean , if it 's <disfmarker> if it 's <disfmarker>
speaker: A
text: You mean like <disfmarker> Yeah , word start insights .
speaker: C
text: if you have start points , if you have , like , time tags ,
speaker: A
text: Right .
speaker: C
text: which is what I assume .
speaker: C
text: Isn't that what <disfmarker> what you <disfmarker> ?
speaker: C
text: Well , see , Adam would be <disfmarker>
speaker: F
text: Yeah , whatever you use .
speaker: F
text: I mean , we convert it to this format that the , um , NIST scoring tool unders uh , CTM . Conversation Time - Marked file .
speaker: A
text: Yeah .
speaker: F
text: And <disfmarker> and then that 's the <disfmarker> that 's what the <disfmarker>
speaker: E
text: I think Transcriber , uh , outputs CTM .
speaker: C
text: If it <disfmarker> ?
speaker: C
text: OK .
speaker: E
text: I think so .
speaker: C
text: So you would know this more than I would .
speaker: A
text: Yeah .
speaker: F
text: Right .
speaker: A
text: So , I mean <disfmarker>
speaker: C
text: It seems like she <disfmarker> if she 's g if she 's moving time marks around ,
speaker: C
text: since our representation in Transcriber uses time marks , it seems like there should be some way of <disfmarker> of using that <disfmarker> benefitting from that .
speaker: E
text: Right .
speaker: A
text: Yeah , it wou the advantage would just be that when you brought up a bin you would be able <disfmarker> if you were zoomed in enough in Transcriber to see all the words ,
speaker: B
text: Mm - hmm .
speaker: A
text: you would be able to , like , have the words sort of located in time ,
speaker: A
text: if you wanted to do that .
speaker: B
text: So <disfmarker> so if we e e even just had a <disfmarker> a <disfmarker> It sounds like w we <disfmarker> <vocalsound> we almost do .
speaker: A
text: So .
speaker: B
text: Uh , if we <disfmarker> We have two .
speaker: C
text: We have two .
speaker: B
text: Yeah .
speaker: B
text: Just ha uh , trying out <pause> the alignment <vocalsound> procedure that you have on that
speaker: A
text: Mm - hmm .
speaker: B
text: you could actually get something , um <disfmarker> uh , uh , get an objective measure .
speaker: F
text: Mm - hmm .
speaker: B
text: Uh <disfmarker>
speaker: A
text: You mean on <disfmarker> on the hand - marked , um <disfmarker>
speaker: A
text: So we <disfmarker> we only r hav I only looked at actually alignments from one meeting that we chose ,
speaker: B
text: Yeah .
speaker: A
text: I think MR four ,
speaker: A
text: just randomly , um <disfmarker>
speaker: A
text: And <disfmarker>
speaker: F
text: Actually , not randomly .
speaker: A
text: Not randomly <disfmarker>
speaker: F
text: We knew <disfmarker> we knew that it had these insertion errors from <disfmarker>
speaker: A
text: It had sort of <pause> average recognition performance in a bunch of speakers
speaker: F
text: Yeah .
speaker: F
text: Yeah .
speaker: A
text: and it was a Meeting Recorder meeting .
speaker: A
text: Um .
speaker: A
text: But , yeah , we should try to use what you have .
speaker: A
text: I did re - run recognition on your new version of MR one .
speaker: C
text: Oh , good .
speaker: A
text: I <disfmarker> I mean the <disfmarker> the one with Dan <pause> Ellis in it <vocalsound> and Eric .
speaker: C
text: Good !
speaker: C
text: Uh - huh . Yeah , exactly . Yeah . Yeah .
speaker: G
text: I don't think that was the new version .
speaker: A
text: Um <disfmarker>
speaker: A
text: That <disfmarker>
speaker: A
text: Yeah , actually it wasn't the new new ,
speaker: C
text: OK .
speaker: A
text: it was the medium new .
speaker: A
text: But <disfmarker> but we would <disfmarker> we should do the <disfmarker> the latest version .
speaker: C
text: OK .
speaker: G
text: Yeah .
speaker: G
text: You <disfmarker> did you adjust the <disfmarker> the utterance times , um , for each channel ?
speaker: A
text: It was the one from last week .
speaker: C
text: Yes .
speaker: C
text: Yes , I did .
speaker: C
text: And furthermore , I found that there were a certain number where <disfmarker> <vocalsound> not <disfmarker> not a lot , but several times I actually <vocalsound> moved an utterance from <vocalsound> Adam 's channel to Dan 's or from Dan 's to Adam 's .
speaker: C
text: So there was some speaker identif
speaker: C
text: And the reason was because <vocalsound> I transcribed that at a point before <disfmarker> <vocalsound> uh , before we had the multiple audio available
speaker: C
text: f
speaker: C
text: so I couldn't switch between the audio .
speaker: C
text: I <disfmarker> I transcribed it off of the mixed channel entirely ,
speaker: C
text: which meant in overlaps , I was at a <disfmarker> at a terrific disadvantage .
speaker: A
text: Right .
speaker: A
text: Right .
speaker: C
text: In addition it was before the channelized , uh , possibility was there .
speaker: C
text: And finally I did it using the speakers of my , um <disfmarker> <vocalsound> of <disfmarker> you know , off the CPU on my <disfmarker> on my machine
speaker: C
text: cuz I didn't have a headphone .
speaker: C
text: So it @ @ , like , I mean <disfmarker>
speaker: A
text: Right .
speaker: C
text: Yeah , I <disfmarker> I mean , i in retrospect <vocalsound> it would 've been good to ha <vocalsound> have got I should 've gotten a headphone .
speaker: C
text: But in any case , um , thi this is <disfmarker> this was transcribed in a <disfmarker> in a , <vocalsound> uh , less optimal way than <disfmarker> than the ones that came after it ,
speaker: C
text: and I was able to <disfmarker> you know , an and this meant that there were some speaker identif identifications
speaker: G
text: Well , I know there were some speaker labelling problems , um , after interruptions .
speaker: C
text: which were changes .
speaker: C
text: Yeah .
speaker: C
text: Fixed that .
speaker: G
text: Is that what you 're referring to ?
speaker: G
text: I mean , cuz there 's this one instance when , for example , you 're running down the stairs .
speaker: C
text: Oh , well <disfmarker>
speaker: G
text: I remember this meeting really well .
speaker: D
text: Yeah .
speaker: G
text: Right .
speaker: A
text: Don <disfmarker> Don has had <disfmarker> <vocalsound> He knows <disfmarker> he can just read it like a play .
speaker: G
text: It 's a <disfmarker>
speaker: G
text: Yeah , I 've <disfmarker> I 've <disfmarker> I 'm very well acquainted with this meeting .
speaker: G
text: Yeah , I can s
speaker: D
text: Yeah .
speaker: A
text: " And then she said , and then he said . "
speaker: G
text: Yeah , I know it by heart .
speaker: G
text: So , um , <vocalsound> there 's one point when you 're running down the stairs .
speaker: C
text: Uh - oh .
speaker: G
text: Right ?
speaker: G
text: And , like , there 's an interruption .
speaker: G
text: You interrupt somebody ,
speaker: G
text: but then there 's no line after that .
speaker: G
text: For example , there 's no speaker identification after that line .
speaker: C
text: Uh - huh .
speaker: G
text: Is that what you 're talking about ?
speaker: G
text: Or were there mislabellings as far as , like , the a Adam was <disfmarker> ?
speaker: C
text: That was fixed , um , before <disfmarker>
speaker: C
text: i i i I think I I think I understood that pretty <disfmarker>
speaker: G
text: Yeah . Cuz I thought I let you know about that .
speaker: C
text: Thank you for mentioning .
speaker: G
text: Yeah .
speaker: C
text: Yeah , no , tha that <disfmarker> That I think went away a couple of versions ago ,
speaker: G
text: OK .
speaker: G
text: But you 're actually saying that certain , uh , speakers were mis mis - identified .
speaker: C
text: but it 's good to know .
speaker: C
text: Yeah . So , with <disfmarker> under <disfmarker> um , uh , listening to the mixed channel , there were times when , as surprising as that is , I got Adam 's voice confused with Dan 's and vice versa <disfmarker>
speaker: G
text: OK .
speaker: C
text: not for long utterances ,
speaker: G
text: OK .
speaker: A
text: Yeah .
speaker: C
text: but jus just a couple of places ,
speaker: B
text: Mm - hmm .
speaker: C
text: and embedde embedded in overlaps .
speaker: C
text: The other thing that was w interesting to me was that I picked up a lot of , um , backchannels which were hidden in the mixed signal ,
speaker: C
text: which , you know , I mean , you c not <disfmarker> not too surprising .
speaker: A
text: Right .
speaker: C
text: But the other thing that <disfmarker>
speaker: C
text: I <disfmarker> I hadn't thought about this ,
speaker: C
text: but I thou I wanted to raise this when you were <disfmarker> uh , with respect to also a strategy which might help with the alignments potentially ,
speaker: C
text: but that 's <disfmarker>
speaker: C
text: When I was looking at these backchannels , they were turning up usually <disfmarker> <vocalsound> very often in <disfmarker> w well , I won't say " usually " <disfmarker> but anyway , very often , I picked them up in a channel <vocalsound> w which was the person who had asked a question .
speaker: C
text: S so , like , someone says " an and have you done the so - and - so ? "
speaker: C
text: And then there would be backchannels ,
speaker: C
text: but it would be the person who asked the question .
speaker: C
text: Other people weren't really doing much backchannelling .
speaker: C
text: And , you know , sometimes you have the <disfmarker> Yeah , uh - huh .
speaker: A
text: Well , that 's interesting .
speaker: C
text: I mean , i it wouldn't be perfect ,
speaker: A
text: Yeah .
speaker: C
text: but <disfmarker> but it does seem more natural to give a backchannel when <disfmarker> when you 're somehow involved in the topic ,
speaker: A
text: No , that 's really interesting .
speaker: C
text: and the most natural way is for you to have initiated the topic by asking a question .
speaker: B
text: Mm - hmm .
speaker: F
text: Well ,
speaker: F
text: I think <disfmarker>
speaker: A
text: That 's interesting .
speaker: F
text: No . I think it 's <disfmarker> actually I think what 's going on is backchannelling is something that happens in two - party conversations .
speaker: C
text: Mm - hmm .
speaker: F
text: And if you ask someone a question , you essentially initiating a little two - party conversation .
speaker: C
text: Yeah .
speaker: A
text: Well , actu Yeah , when we looked at this <disfmarker>
speaker: F
text: So then you 're <disfmarker> so and then you 're expected to backchannel
speaker: C
text: Exactly .
speaker: F
text: because the person is addressing you directly and not everybody .
speaker: C
text: Exactly .
speaker: C
text: Exactly my point .
speaker: F
text: Yeah .
speaker: C
text: An - and so this is the expectation thing that <disfmarker> uh , uh ,
speaker: F
text: Yeah .
speaker: A
text: Mm - hmm .
speaker: F
text: Right .
speaker: F
text: Right .
speaker: C
text: just the dyadic <disfmarker>
speaker: C
text: But in addition , you know , if someone has done this analysis himself and isn't involved in the dyad , but they might also give backchannels to verify what <disfmarker> what the answer is that this <disfmarker> that the <disfmarker> the answerer 's given <disfmarker>
speaker: B
text: H
speaker: B
text: I tell you , I say <disfmarker> I say " uh - huh " a lot ,
speaker: A
text: Right .
speaker: A
text: It 's <disfmarker>
speaker: C
text: There you go .
speaker: A
text: Well , but it 's interesting
speaker: A
text: cuz , uh <disfmarker>
speaker: B
text: while people are talking to each other .
speaker: C
text: There you go .
speaker: A
text: But there are fewer <disfmarker> I think there are fewer " uh - huhs " .
speaker: C
text: Yeah .
speaker: C
text: Yeah .
speaker: A
text: I mean , just from <disfmarker> We were looking at word frequency lists to try to find the cases that we would allow to have the reject words in between in doing the alignment .
speaker: A
text: You know the ones we wouldn't constrain to be next to the other words .
speaker: C
text: Oh , yeah .
speaker: A
text: And " uh - huh " is not as frequent
speaker: A
text: as it sort of would be in Switchboard ,
speaker: A
text: if you looked at just a word frequency list of one - word short utterances .
speaker: A
text: And " yeah " is way up there ,
speaker: A
text: but not " uh - huh " .
speaker: A
text: And so I was thinking
speaker: A
text: thi it 's not like <pause> you 're being encouraged by everybody else to keep <pause> talking in the meeting .
speaker: A
text: And uh , that 's all , I I 'll stop there ,
speaker: A
text: cuz I I think what you say makes a lot of sense .
speaker: C
text: Well , that 's right .
speaker: C
text: And that would <disfmarker>
speaker: C
text: Well , an
speaker: A
text: But it was sort of <disfmarker>
speaker: C
text: And what you say is the <disfmarker> is the re uh , o other side of this ,
speaker: C
text: which is that , you know , so th there are lots of channels where you don't have these backchannels , w when a question has been asked
speaker: C
text: and <disfmarker> and these <disfmarker>
speaker: A
text: Right .
speaker: A
text: There 's just probably less backchannelling in general ,
speaker: C
text: Mm - hmm .
speaker: C
text: So that 's good news , really .
speaker: A
text: even if you consider every other person altogether one person in the meeting ,
speaker: A
text: but we 'll find out anyway .
speaker: A
text: We were <disfmarker> I guess the other thing we 're <disfmarker> we 're <disfmarker> I should say is that we 're gonna , um try <disfmarker> compare this type of overlap analysis to Switchboard ,
speaker: F
text: And
speaker: A
text: where <disfmarker>
speaker: A
text: and CallHome ,
speaker: A
text: where we have both sides , so that we can try to answer this question of , you know , <vocalsound> is there really more overlap in meetings or is it just because we don't have the other channel in Switchboard
speaker: E
text: Mm - hmm .
speaker: B
text: Mm - hmm .
speaker: A
text: and we don't know what people are doing .
speaker: A
text: Try to create a paper out of that .
speaker: B
text: Yeah . I mean , y y you folks have probably <pause> already told me ,
speaker: B
text: but were <disfmarker> were you intending to do a Eurospeech submission ,
speaker: B
text: or <disfmarker> ?
speaker: A
text: Um , you mean the one due tomorrow ?
speaker: B
text: Yeah .
speaker: A
text: Yeah . Well , we 're still , like , writing the scripts for doing the research ,
speaker: A
text: and we will <disfmarker> Yes , we 're gonna try .
speaker: C
text: Mm - hmm .
speaker: A
text: And I was telling Don , do not <pause> take this as an example of how people should work .
speaker: B
text: Do as I say ,
speaker: G
text: That 's r
speaker: A
text: So , <comment> we will try .
speaker: B
text: don't do as I do .
speaker: B
text: Yeah .
speaker: E
text: Well <disfmarker>
speaker: A
text: It 'll probably be a little late ,
speaker: E
text: It is different .
speaker: A
text: but I 'm gonna try it .
speaker: E
text: In previous years , Eurospeech only had the abstract due by now ,
speaker: E
text: not the full paper .
speaker: G
text: Right .
speaker: A
text: Right .
speaker: E
text: And so all our timing was off .
speaker: E
text: I 've given up on trying to do digits .
speaker: E
text: I just don't think that what I have so far makes a Eurospeech paper .
speaker: A
text: Well , I 'm no We may be in the same position ,
speaker: A
text: and I figured <vocalsound> we 'll try ,
speaker: A
text: because that 'll at least get us to the point where we have <disfmarker> We have this really nice database format that Andreas and I were working out that <disfmarker>
speaker: A
text: It <disfmarker> it 's not very fancy .
speaker: A
text: It 's just a ASCII line by line format ,
speaker: A
text: but it does give you information <disfmarker>
speaker: F
text: It 's the <disfmarker> it 's the spurt format .
speaker: A
text: It <disfmarker> Yeah , we 're calling these " spurts " after Chafe .
speaker: A
text: I was trying to find what 's a word for <pause> a continuous region with <pause> pauses around it ?
speaker: C
text: Hmm .
speaker: B
text: Yeah . I know that th the Telecom people use <disfmarker> use " spurt " for that .
speaker: C
text: Good .
speaker: A
text: They do ?
speaker: F
text: Oh .
speaker: B
text: Yes .
speaker: A
text: Oh !
speaker: A
text: Oh .
speaker: B
text: And that 's <disfmarker> I mean , I <disfmarker> I was using that for a while when I was doing the rate of speech stuff ,
speaker: A
text: I would jus
speaker: B
text: because I <disfmarker> because I looked up in some books and I found <disfmarker> OK , I wanna find a spurt <vocalsound> in which <disfmarker>
speaker: A
text: Ah , right !
speaker: A
text: It 's just , like , defined by the acoustics .
speaker: B
text: and <disfmarker> an because <disfmarker> cuz it 's another question about how <pause> many pauses they put in between them .
speaker: E
text: Horrible .
speaker: A
text: Right .
speaker: B
text: But how fast do they do <pause> the words within the spurt ?
speaker: A
text: Right .
speaker: B
text: Yeah .
speaker: G
text: you know " Burst " also ?
speaker: E
text: It 's gonna <disfmarker>
speaker: A
text: Well , that 's what we were calling spurt ,
speaker: E
text: Burst .
speaker: G
text: Isn't " burst " is used also ?
speaker: A
text: so <disfmarker>
speaker: E
text: Spurt has the horrible name overloading with other <disfmarker> with hardware at ICSI .
speaker: B
text: Here .
speaker: B
text: Just very locally , yeah .
speaker: B
text: But <disfmarker> but that just <disfmarker>
speaker: A
text: Well , well , Chafe had this wor I think it was Chafe , or somebody had a <disfmarker> the word " spurt " originally ,
speaker: H
text: Here @ @ <disfmarker>
speaker: A
text: and so I <disfmarker>
speaker: C
text: Actually <disfmarker>
speaker: A
text: But tha that 's good to know .
speaker: A
text: Was thi it 's Chafe ?
speaker: F
text: So maybe we should talk <disfmarker>
speaker: C
text: Well , see , I know S Sue wrote about spurts of development .
speaker: A
text: Maybe it was Sue <disfmarker> ?
speaker: C
text: But , in any case , I think it 's a good term ,
speaker: A
text: Y
speaker: E
text: Hmm !
speaker: C
text: and , uh <disfmarker>
speaker: A
text: So we have spurts and we have spurt - ify dot shell and spurt - ify
speaker: B
text: Yeah .
speaker: C
text: And ma maybe <disfmarker> maybe Chafe did .
speaker: F
text: Uh .
speaker: B
text: Yeah .
speaker: F
text: So s
speaker: C
text: I know <disfmarker> I know Ch - Chafe dealt with <disfmarker>
speaker: A
text: And then it 's got all <disfmarker> it 's a verb now .
speaker: G
text: That 's cool .
speaker: F
text: W uh , w
speaker: C
text: Chafe speaks about intonation units .
speaker: A
text: Yes . Right .
speaker: C
text: But maybe he speaks about spurts as well
speaker: F
text: We
speaker: C
text: and I just don't know .
speaker: C
text: Yeah , go ahead .
speaker: F
text: So what we 're doing <disfmarker>
speaker: E
text: I 've heard " burst " also .
speaker: F
text: uh , this <disfmarker> this is just <disfmarker> maybe someone has s some <disfmarker> some ideas about how to do it better ,
speaker: G
text: Mmm .
speaker: F
text: but we <disfmarker> So we 're taking these , uh , alignments from the individual channels .
speaker: F
text: We 're <disfmarker>
speaker: F
text: from each alignment we 're producing , uh , one of these CTM files ,
speaker: F
text: which essentially has <disfmarker> it 's just a linear sequence of words with the begin times for every word and the duration .
speaker: C
text: Great .
speaker: F
text: And <disfmarker> and <disfmarker> and of course <disfmarker>
speaker: A
text: It looks like a Waves label file almost . Right ?
speaker: F
text: Right . But it has <disfmarker> one <disfmarker> the first column has the meeting name ,
speaker: A
text: It 's just <disfmarker>
speaker: F
text: so it could actually contain several meetings .
speaker: F
text: Um .
speaker: F
text: And the second column is the channel .
speaker: F
text: Third column is the , um , start times of the words and the fourth column is the duration of the words .
speaker: F
text: And then we 're ,
speaker: F
text: um <disfmarker>
speaker: F
text: OK . Then we have a messy alignment process where we actually insert into the sequence of words the , uh , tags
speaker: F
text: for , like , where <disfmarker> where sentence <disfmarker> ends of sentence ,
speaker: F
text: question marks ,
speaker: F
text: um , <vocalsound> various other things .
speaker: A
text: Yeah . These are things that we had Don <disfmarker>
speaker: F
text: Uh .
speaker: A
text: So , Don sort of , um , propagated the punctuation from the original transcriber <disfmarker>
speaker: F
text: Right .
speaker: A
text: so whether it was , like , question mark or period or , <vocalsound> um , you know , comma and things like that ,
speaker: A
text: and we kept the <disfmarker> and disfluency dashes <disfmarker> uh , kept those in because we sort of wanna know where those are relative to the spurt overlaps <disfmarker>
speaker: F
text: Mm - hmm .
speaker: F
text: Right .
speaker: F
text: So <disfmarker> so those are actually sort of retro - fitted into the time alignment .
speaker: A
text: sp overlaps ,
speaker: A
text: or <disfmarker>
speaker: F
text: And then we merge all the alignments from the various channels
speaker: F
text: and we sort them by time .
speaker: F
text: And then there 's a <disfmarker> then there 's a process where you now determine the spurts .
speaker: F
text: That is <disfmarker> Actually , no , you do that before you merge the various channels .
speaker: F
text: So you <disfmarker> you id identify by some criterion ,
speaker: F
text: which is pause length <disfmarker>
speaker: F
text: you identify the beginnings and ends of these spurts ,
speaker: F
text: and you put another set of tags in there to keep those straight .
speaker: B
text: Mm - hmm .
speaker: F
text: And then you merge everything in terms of , you know , linearizing the sequence based on the time marks .
speaker: F
text: And then <vocalsound> you extract the individual channels again ,
speaker: F
text: but this time you know where the other people start and end talking <disfmarker>
speaker: F
text: you know , where their spurts start and end .
speaker: F
text: And so you extract the individual channels , uh , one sp spurt by spurt as it were .
speaker: F
text: Um , and inside the words or between the words you now have begin and end <pause> tags for overlaps .
speaker: F
text: So , you <disfmarker> you basically have everything sort of lined up and in a form where you can look at the individual speakers and how their speech relates to the other speakers ' speech .
speaker: E
text: Right .
speaker: A
text: Uh , I mean , I think that 's actually really u useful also
speaker: F
text: And <disfmarker>
speaker: A
text: because even if you weren't studying overlaps , if you wanna get a transcription for the far - field mikes , how are you gonna know which words from which speakers occurred at which times relative to each other ?
speaker: A
text: You have to be able to <pause> get a transcript like <disfmarker> like this anyway , just for doing far - field recognition .
speaker: A
text: So ,
speaker: A
text: you know , it 's <disfmarker> it 's sort of <disfmarker>
speaker: F
text: Yeah .
speaker: A
text: I thi it 's just an issue we haven't dealt with before ,
speaker: A
text: how you time - align things that are overlapping anyway .
speaker: F
text: So <disfmarker>
speaker: C
text: That 's wonderful .
speaker: E
text: Well <disfmarker>
speaker: F
text: And <disfmarker> and we <disfmarker>
speaker: A
text: I mean , i I never thought about it before ,
speaker: E
text: Y yes .
speaker: F
text: In <disfmarker>
speaker: A
text: but <disfmarker>
speaker: E
text: I mean , s when I came up with the original data <disfmarker> suggested data format based on the transcription graph , there 's capability of doing that sort of thing in there .
speaker: A
text: Right .
speaker: C
text: Mm - hmm .
speaker: A
text: But you can't get it directly from the transcription .
speaker: F
text: Right .
speaker: C
text: Yeah , that 's right .
speaker: F
text: Well , this is <disfmarker> this is just <disfmarker>
speaker: A
text: Yeah , this is like a poor man 's ver formatting version .
speaker: A
text: But it 's , you know <disfmarker> It 's clean ,
speaker: A
text: it 's just not fancy .
speaker: E
text: Right .
speaker: F
text: Well , there 's lots of little things .
speaker: A
text: Um .
speaker: F
text: It 's like there 're twelve different scripts which you run
speaker: F
text: and then at the end you have what you want .
speaker: F
text: But , um ,
speaker: F
text: at the very last stage we throw away the actual time information .
speaker: F
text: All we care about is whether <disfmarker> that there 's a certain word was overlapped by someone else 's word .
speaker: F
text: So you sort of <disfmarker> at that point , you discretize things into just having overlap or no overlap .
speaker: F
text: Because we figure that 's about the level of analysis that we want to do for this paper .
speaker: E
text: Mm - hmm .
speaker: F
text: But if you wanted to do a more fine - grained analysis and say , you know , how far into the word is the overlap , you could do that .
speaker: F
text: It 's just <disfmarker> it 'll just require more <disfmarker>
speaker: A
text: Yeah .
speaker: A
text: Just <pause> sort of huge .
speaker: F
text: you know , slightly different <disfmarker>
speaker: C
text: What 's interesting is it 's exactly what , um , i in discussing with , um , Sue about this ,
speaker: A
text: Yeah .
speaker: C
text: um , she , um , i i i indicated that that <disfmarker> you know , that 's very important for overlap analysis .
speaker: A
text: Yeah . It 's <disfmarker> it 's nice to know ,
speaker: F
text: Right .
speaker: A
text: and also I think as a human , like , I don't always hear these in the actual order that they occur .
speaker: A
text: So I can have two foreground speakers ,
speaker: A
text: you know , Morgan an and <vocalsound> um , Adam and Jane could all be talking ,
speaker: A
text: and I could align each of them to be starting their utterance at the correct time ,
speaker: A
text: and then look where they are relative to each other ,
speaker: A
text: and that 's not really what I heard .
speaker: C
text: And that 's another thing she said .
speaker: A
text: Cuz it 's just hard to do .
speaker: C
text: This is <disfmarker> This is Bever 's <disfmarker> Bever 's effect ,
speaker: C
text: when <disfmarker> where <disfmarker> In psy ps psycho - linguistics you have these experiments where people have perceptual biases a as to what they hear ,
speaker: A
text: Y Yeah .
speaker: A
text: It 's sort of <disfmarker>
speaker: C
text: that <disfmarker> that <disfmarker> Not the best <disfmarker>
speaker: A
text: Yeah , you sort of move things around until you get to a <pause> low information point
speaker: A
text: and yo then you can bring in the other person .
speaker: A
text: So it 's <vocalsound> actually not even possible , I think , for any person to listen to a mixed signal ,
speaker: A
text: even equalize , and make sure that they have all the words in the right order .
speaker: C
text: Mm - hmm .
speaker: A
text: So , I guess , we 'll try to write this Eurospeech paper .
speaker: C
text: Superb .
speaker: A
text: I mean , we will write it .
speaker: A
text: Whether they accept it <pause> late or not , I don't know .
speaker: A
text: Um , and the good thing is that we have <disfmarker> It 's sort of a beginning of what Don can use to link the prosodic features from each file to each other .
speaker: F
text: Yeah .
speaker: B
text: Yeah . That 's the good thing about these pape
speaker: F
text: Plus , mayb
speaker: A
text: So .
speaker: H
text: Hmm ?
speaker: A
text: i You know , might as well .
speaker: A
text: We - I ju Otherwise we won't get the work done <comment> <vocalsound> on our deadline .
speaker: F
text: I don't know , m
speaker: F
text: I mean , u u Jane likes to look at data .
speaker: B
text: Yeah .
speaker: F
text: Maybe , you know , you could <disfmarker> you could look at this format and see if you find anything interesting .
speaker: F
text: I don't know .
speaker: B
text: Yeah .
speaker: C
text: Well , what I 'm thinking is <disfmarker>
speaker: B
text: No , it 's <disfmarker> that 's the good thing about these pape paper deadlines and , uh , you know , class projects , and <disfmarker> <vocalsound> and things like that ,
speaker: A
text: Yeah .
speaker: F
text: Yeah .
speaker: C
text: Yeah .
speaker: F
text: Mm - hmm .
speaker: A
text: Right .
speaker: C
text: Well , my <disfmarker>
speaker: F
text: Well th th the other thing that <disfmarker> that <disfmarker> that yo that you usually don't tell your graduate students is that these deadlines are actually not that , um , you know , strictly enforced ,
speaker: B
text: because you <disfmarker> you really get g
speaker: C
text: Yeah .
speaker: A
text: Forces you to do the work .
speaker: B
text: Yeah .
speaker: A
text: Exactly .
speaker: E
text: Strict .
speaker: F
text: because <pause> the <disfmarker>
speaker: B
text: Oh , now it 's out in the public ,
speaker: B
text: this <disfmarker> this <disfmarker> this secret information .
speaker: F
text: because <disfmarker>
speaker: C
text: I think we can ha
speaker: B
text: Yeah .
speaker: F
text: bec b <vocalsound> Nah <disfmarker>
speaker: A
text: Right .
speaker: E
text: No .
speaker: A
text: So <disfmarker>
speaker: B
text: No .
speaker: C
text: Nah .
speaker: F
text: i Because these <disfmarker> the conference organizers actually have an interest in getting lots of submissions .
speaker: A
text: Right .
speaker: F
text: I mean , a <disfmarker> a monetary interest .
speaker: E
text: Right .
speaker: B
text: Yeah .
speaker: F
text: So <disfmarker> <vocalsound> Um .
speaker: B
text: Th - that 's <disfmarker> that 's true .
speaker: C
text: And good ones ,
speaker: C
text: good ones ,
speaker: F
text: And good submission
speaker: C
text: which sometimes means <pause> a little extra time .
speaker: B
text: That 's <disfmarker>
speaker: F
text: Right .
speaker: F
text: Well <disfmarker>
speaker: B
text: That 's true .
speaker: F
text: That 's another issue ,
speaker: F
text: but <disfmarker>
speaker: B
text: By th by the way , this is totally unfair , you may <disfmarker> you may feel ,
speaker: B
text: but the <disfmarker> the , uh <disfmarker> the morning meeting folks actually have an <disfmarker> an extra month or so .
speaker: F
text: Mm - hmm .
speaker: D
text: Yep .
speaker: E
text: Yep . The Aurora <disfmarker> there 's a special Aurora <disfmarker>
speaker: F
text: When <disfmarker>
speaker: A
text: Uh <disfmarker>
speaker: B
text: There 's a special Aurora session
speaker: B
text: and the Aurora pe people involved in Aurora have till Ma - uh , early May <pause> or something to turn in their paper .
speaker: A
text: Oh .
speaker: F
text: Mmm .
speaker: A
text: Oh .
speaker: F
text: Mmm .
speaker: F
text: Well , then you can just <disfmarker>
speaker: A
text: Oh , well maybe we 'll submit to s <comment> <vocalsound> Actually <disfmarker>
speaker: F
text: Maybe you can submit the digits paper on e for the Aurora session .
speaker: H
text: Yeah .
speaker: D
text: Yeah .
speaker: A
text: Yeah .
speaker: E
text: Oh , I could !
speaker: B
text: I if it w
speaker: A
text: Yeah .
speaker: E
text: I could submit that to Aurora .
speaker: F
text: Yeah .
speaker: B
text: Well <disfmarker>
speaker: E
text: That would be pretty <disfmarker> pretty <disfmarker>
speaker: B
text: i it has <disfmarker>
speaker: A
text: Yeah .
speaker: E
text: S That wouldn't work .
speaker: B
text: No , it wouldn't work .
speaker: E
text: It 's not Aurora .
speaker: B
text: It 's <disfmarker> it 's not the Aurora <disfmarker>
speaker: B
text: I mean , it <disfmarker> it 's <disfmarker> it 's actually the Aurora task .
speaker: A
text: Maybe they 'll get s
speaker: E
text: Aurora 's very specific .
speaker: A
text: Well , maybe it won't be after this <vocalsound> deadline <pause> extension .
speaker: B
text: It
speaker: F
text: But <disfmarker> but the people <disfmarker> I mean ,
speaker: F
text: a <disfmarker> a paper that is not on Aurora would probably be more interesting at that point
speaker: A
text: Maybe they 'll <disfmarker>
speaker: F
text: because everybody 's so sick and tired of the Aurora task .
speaker: D
text: Yeah .
speaker: E
text: Oh , I thought you meant this was just the digits section .
speaker: E
text: I didn't know you meant it was Aurora digits .
speaker: B
text: Yeah .
speaker: F
text: Well , no . If you <disfmarker> if you have <disfmarker> it 's to <disfmarker> if you discuss some relation to the Aurora task ,
speaker: F
text: like if you use the same <disfmarker>
speaker: B
text: This is not the Aurora task .
speaker: B
text: So they just do a little grep for <disfmarker>
speaker: A
text: Do <disfmarker> uh , d d
speaker: F
text: Um .
speaker: A
text: Do not <disfmarker> do not <disfmarker> we are not setting a good example .
speaker: F
text: Well , a relation other than negation , maybe ,
speaker: A
text: This is not a <disfmarker>
speaker: F
text: um .
speaker: F
text: So .
speaker: F
text: I don't know .
speaker: A
text: Anyway .
speaker: A
text: But the good thing is this does <disfmarker>
speaker: E
text: Well , I I don't know .
speaker: E
text: I mean , you could <disfmarker> you could do a paper on <pause> what 's wrong with the Aurora task by comparing it to <pause> other ways of doing it .
speaker: F
text: How well does an Aurora system do on <disfmarker> on <disfmarker> you know , on digits collected in a <disfmarker> in this environment ?
speaker: E
text: Different way .
speaker: E
text: Yeah .
speaker: F
text: Yeah .
speaker: B
text: Maybe .
speaker: F
text: Maybe .
speaker: E
text: Pretty hokey .
speaker: B
text: I think it 's a littl little far - fetched .
speaker: B
text: Nah , I mean , the thing is Aurora 's pretty closed community .
speaker: E
text: Yep .
speaker: B
text: I mean , you know , the people who were involved in the <disfmarker> <vocalsound> the only people who are allowed to test on that are people who <disfmarker> who made it above a certain threshold in the first round ,
speaker: F
text: Mm - hmm .
speaker: E
text: It 's very specific .
speaker: B
text: uh <vocalsound> w in ninety - nine
speaker: B
text: and it 's <disfmarker> it 's sort of a <disfmarker> it 's <disfmarker>
speaker: F
text: Well , that 's maybe why they don't f know that they have a crummy system .
speaker: B
text: not like a <disfmarker>
speaker: F
text: I mean , a crummy back - end .
speaker: F
text: No , I mean <disfmarker> I mean , seriously ,
speaker: F
text: if you <disfmarker> if you have a very <disfmarker>
speaker: F
text: No , I 'm sorry .
speaker: A
text: Uh , <comment> " beep " <vocalsound> " bee "
speaker: F
text: No . I didn't mean anybody <disfmarker> any particular system .
speaker: E
text: I mean , th
speaker: F
text: I meant this H T K back - end .
speaker: F
text: If they <disfmarker>
speaker: B
text: Oh , you don't like HTK ?
speaker: H
text: Yeah .
speaker: F
text: I don't h I don't have any stock in HTK or Entropic or anything .
speaker: B
text: No . I mean , this <disfmarker> it it 's the HTK <pause> that is trained on a very limited amount of data .
speaker: E
text: It 's d it 's very specific .
speaker: F
text: Right .
speaker: B
text: Yeah .
speaker: F
text: But so , if you <disfmarker> But maybe you should , you know , consider more <disfmarker> using more data ,
speaker: F
text: or <disfmarker> I mean <disfmarker>
speaker: B
text: Oh , yeah . I <disfmarker> I really think that that 's true .
speaker: F
text: If yo if you sort of hermetically stay within one task and don't look left and right , then you 're gonna <disfmarker>
speaker: B
text: And they i i
speaker: E
text: But they <disfmarker> they had <disfmarker>
speaker: B
text: i
speaker: B
text: But <disfmarker>
speaker: E
text: They had something very specific in mind when they designed it . Right ?
speaker: F
text: Right .
speaker: B
text: Well , u i
speaker: E
text: And so <disfmarker> so you can <disfmarker> you can argue about maybe that wasn't the right thing to do ,
speaker: E
text: but , you know , they <disfmarker> they <disfmarker> they had something specific .
speaker: B
text: But , one of the reasons I have Chuck 's messing around with <disfmarker> with the back - end that you 're not supposed to touch <disfmarker>
speaker: F
text: Mm - hmm .
speaker: B
text: I mean , for the evaluations , yes , we 'll run a version that hasn't been touched .
speaker: F
text: Mm - hmm .
speaker: B
text: But , uh , one of the reasons I have him messing around with that , because I think it 's sort of an open question that we don't know the answer to .
speaker: B
text: People always say very glibly <vocalsound> that i if you s show improvement on a bad system , that doesn't mean anything ,
speaker: B
text: cuz it may not be <disfmarker> <vocalsound> show <disfmarker> uh , because , you know , it doesn't tell you anything about the good system .
speaker: F
text: Mm - hmm .
speaker: B
text: And I <disfmarker> I 've always sort of felt that that depends .
speaker: B
text: You know , that if some peopl If you 're actually are getting at something that has some <pause> conceptual substance to it , it will port .
speaker: F
text: Mm - hmm .
speaker: B
text: And in fact , most methods that people now use were originally tried with something that was not their absolute <pause> best system at some level .
speaker: B
text: But of course , sometimes it doesn't , uh , port .
speaker: B
text: So I think that 's <disfmarker> that 's an interesting question .
speaker: B
text: If we 're getting <pause> three percent error on , uh , u uh , English , uh , nati native speakers , <vocalsound> um , using the Aurora system , and we do some improvements and bring it from three to two , <vocalsound> do those same improvements bring , uh , th you know , the SRI system from one point three to <disfmarker> you know , to <vocalsound> point eight ?
speaker: F
text: Hmm .
speaker: F
text: Mm - hmm .
speaker: E
text: Zero .
speaker: B
text: Well .
speaker: F
text: Mmm .
speaker: B
text: You know , so that 's <disfmarker> that 's something we can test .
speaker: F
text: Right .
speaker: B
text: So .
speaker: B
text: Anyway .
speaker: F
text: OK .
speaker: B
text: I think we 've <disfmarker> <vocalsound> we 've covered that one up extremely well .
speaker: C
text: Mm - hmm .
speaker: F
text: Whew !
speaker: B
text: OK .
speaker: B
text: So , um <disfmarker>
speaker: B
text: Yeah .
speaker: B
text: So tha so we 'll <disfmarker> you know , maybe you guys 'll have <disfmarker> have one .
speaker: B
text: Uh , you <disfmarker> you and , uh <disfmarker> and Dan have <disfmarker> have a paper that <disfmarker> that 's going in .
speaker: D
text: Yeah .
speaker: D
text: Yeah .
speaker: B
text: You know , that 's <disfmarker> that 's pretty solid , on the segmentation <pause> stuff .
speaker: D
text: Yeah .
speaker: D
text: I will send you the <disfmarker> the final version ,
speaker: B
text: Yeah .
speaker: B
text: And the Aurora folks here will <disfmarker> will definitely get something in on Aurora ,
speaker: D
text: which is not <disfmarker>
speaker: F
text: Actually this <disfmarker> this , um <disfmarker> So , there 's another paper .
speaker: B
text: so .
speaker: F
text: It 's a Eurospeech paper but not related to meetings .
speaker: F
text: But it 's on digits .
speaker: F
text: So , um ,
speaker: F
text: uh , a colleague at SRI developed a improved version of MMIE training .
speaker: B
text: Uh - huh .
speaker: F
text: And he tested it mostly on digits
speaker: F
text: because it 's sort of a <disfmarker> you know , it doesn't take weeks to train it .
speaker: B
text: Right .
speaker: F
text: Um .
speaker: F
text: And got some very impressive results , um , with , you know , discriminative , uh , Gaussian training . Um , you know , like , um , error rates <pause> go from <disfmarker> I don't know , in very noisy environment , like from ,
speaker: F
text: uh , uh <disfmarker>
speaker: F
text: I for now I <disfmarker> OK , now I have the order of magnit
speaker: F
text: I 'm not sure about the order of magnitude .
speaker: F
text: Was it like from ten percent to <vocalsound> eight percent or from e e you know , point <disfmarker> you know , from one percent to point eight percent ?
speaker: B
text: H i it got <disfmarker> it got better .
speaker: F
text: I mean , it 's a <disfmarker>
speaker: F
text: It got better .
speaker: D
text: Yeah .
speaker: F
text: That 's the important thing .
speaker: B
text: Yeah , yeah .
speaker: F
text: Yeah .
speaker: E
text: Hey , that 's the same percent relative ,
speaker: F
text: But it 's <disfmarker>
speaker: E
text: so <disfmarker>
speaker: F
text: Yeah . Right .
speaker: B
text: Yeah .
speaker: F
text: It 's , uh , something in <disfmarker>
speaker: B
text: Yeah .
speaker: F
text: Right .
speaker: E
text: Twenty percent relative gain .
speaker: F
text: Yeah .
speaker: B
text: Yeah .
speaker: B
text: Yeah .
speaker: B
text: Um , <vocalsound> let 's see .
speaker: B
text: I think the only thing we had left was <disfmarker> unless somebody else <disfmarker>
speaker: B
text: Well , there 's a couple things .
speaker: B
text: Uh , one is <pause> anything that , um , <vocalsound> anybody has to say about Saturday ?
speaker: B
text: Anything we should do in prep for Saturday ?
speaker: B
text: Um <disfmarker>
speaker: B
text: I guess everybody knows about <disfmarker>
speaker: B
text: I mean , u um , Mari was asking <disfmarker> was trying to come up with something like an agenda
speaker: B
text: and we 're sort of fitting around people 's times a bit .
speaker: B
text: But , um , <vocalsound> clearly when we actually get here we 'll <pause> move things around this , as we need to ,
speaker: B
text: but <disfmarker>
speaker: D
text: OK .
speaker: B
text: so you can't absolutely count on it .
speaker: D
text: Yeah .
speaker: B
text: But <disfmarker> but , uh <disfmarker>
speaker: A
text: Are we meeting in here probably
speaker: A
text: or <disfmarker> ?
speaker: B
text: Yeah .
speaker: A
text: OK .
speaker: B
text: That was my thought .
speaker: B
text: I think this is <disfmarker>
speaker: F
text: Are we recording it ?
speaker: A
text: Yeah .
speaker: A
text: We won't have enough microphones ,
speaker: B
text: u
speaker: B
text: No . I <disfmarker> I hadn't in intended to .
speaker: A
text: but <disfmarker>
speaker: A
text: There 's no way .
speaker: F
text: OK .
speaker: B
text: We won we wanna <disfmarker> I mean , they 're <disfmarker> there 's gonna be , uh , Jeff , Katrin , Mari and two students .
speaker: B
text: So there 's five <pause> from there .
speaker: E
text: And Brian .
speaker: F
text: But you know th
speaker: B
text: And Brian 's coming ,
speaker: B
text: so that 's six .
speaker: F
text: Mm - hmm .
speaker: E
text: And plus all of us .
speaker: F
text: Can use the Oprah mike .
speaker: B
text: Uh <disfmarker>
speaker: A
text: Depends how fast you can <pause> throw it .
speaker: E
text: It seems like too many <disfmarker> too much coming and going .
speaker: A
text: It 's just <disfmarker>
speaker: F
text: Mm - hmm .
speaker: A
text: Yeah .
speaker: B
text: Well <disfmarker>
speaker: A
text: We don't even have enough channel <disfmarker>
speaker: F
text: Because it would be a different kind of meeting ,
speaker: D
text: Yeah .
speaker: F
text: that 's what I 'm <disfmarker>
speaker: H
text: Yeah .
speaker: B
text: Well <disfmarker>
speaker: F
text: But <disfmarker>
speaker: B
text: I hadn't <pause> really thought of it ,
speaker: F
text: Maybe just <disfmarker> maybe not the whole day
speaker: B
text: but <disfmarker>
speaker: F
text: but just , you know , maybe some <disfmarker> I mean ,
speaker: B
text: Maybe part of it .
speaker: F
text: part of it ?
speaker: B
text: Maybe part of it .
speaker: E
text: Make everyone read digits .
speaker: B
text: At the same time .
speaker: E
text: At the same time .
speaker: F
text: Please .
speaker: A
text: At the same time .
speaker: B
text: Yeah .
speaker: A
text: We c
speaker: B
text: I don't know .
speaker: B
text: Any
speaker: A
text: That 's their initiation into our
speaker: E
text: Into our <disfmarker> our <disfmarker> our cult .
speaker: A
text: w
speaker: A
text: Yeah , our <disfmarker> Yeah , our <disfmarker>
speaker: F
text: Maybe the sections that are not right afte you know , after lunch when everybody 's still munching
speaker: F
text: and <disfmarker>
speaker: B
text: OK .
speaker: A
text: So can you send out a schedule once you know it , jus ?
speaker: B
text: Well <disfmarker>
speaker: B
text: OK . Yeah . I guess I sent it around a little bit .
speaker: A
text: Is <disfmarker> is there a r ?
speaker: A
text: There 's a res
speaker: B
text: But <disfmarker>
speaker: A
text: Is it changed now , or <disfmarker> ?
speaker: B
text: I hadn't heard back from Mari after I <disfmarker> I u u uh , brought up the point abou about Andreas 's schedule .
speaker: B
text: So , <vocalsound> um , maybe when I get back there 'll be <pause> some <disfmarker> some mail from her .
speaker: A
text: OK .
speaker: B
text: So , I 'll make a <disfmarker>
speaker: C
text: I 'm looking forward to seeing your representation .
speaker: C
text: That 'd be , uh <disfmarker>
speaker: A
text: And w we should get <pause> the two meetings from y
speaker: C
text: I 'd like to see that .
speaker: C
text: Yeah .
speaker: A
text: I mean , I know about the first meeting ,
speaker: A
text: um ,
speaker: A
text: but the other one that you did ,
speaker: A
text: the NSA one ,
speaker: A
text: which we <pause> hadn't done cuz we weren't running recognition on it ,
speaker: C
text: Mm - hmm .
speaker: A
text: because the non - native speaker <disfmarker>
speaker: A
text: there were five non - native speakers .
speaker: C
text: Mm - hmm .
speaker: C
text: I see .
speaker: C
text: Mm - hmm .
speaker: A
text: But , it would be useful for the <disfmarker> to see what we get <pause> with that one .
speaker: C
text: Great .
speaker: A
text: So .
speaker: C
text: OK .
speaker: C
text: It 's , uh , two thousand eleven twenty - one one thousand .
speaker: A
text: Yeah , three .
speaker: A
text: Right .
speaker: A
text: So <disfmarker>
speaker: C
text: Great .
speaker: C
text: I sent email when I finished the <disfmarker> that one .
speaker: A
text: N S A three , I think .
speaker: C
text: That was sort of son
speaker: C
text: Yeah , that 's right . That 's right .
speaker: C
text: That 's much simpler .
speaker: A
text: I don't know what they said
speaker: A
text: but I know the number .
speaker: B
text: Th - that part 's definitely gonna confuse somebody who looks at these later .
speaker: F
text: Right .
speaker: F
text: Um .
speaker: B
text: I mean , this is <disfmarker> we we 're recording secret NSA meetings ?
speaker: F
text: Not the <disfmarker>
speaker: B
text: I mean , it 's <disfmarker>
speaker: F
text: Yeah .
speaker: F
text: Uh .
speaker: C
text: Yeah . Not that NSA .
speaker: F
text: The <disfmarker> th the <disfmarker>
speaker: B
text: It 's network services and applications .
speaker: A
text: They are hard to understand .
speaker: F
text: Wait .
speaker: A
text: They 're very , uh , out there .
speaker: F
text: The <disfmarker>
speaker: A
text: I have no idea what they 're talking about .
speaker: F
text: The , um <disfmarker>
speaker: B
text: Yeah .
speaker: F
text: th the other good thing about the alignments is that , um , it 's not always the machine 's fault if it doesn't work .
speaker: F
text: So , you can actually find , um ,
speaker: A
text: It 's the person 's fault .
speaker: F
text: problem <disfmarker> uh , proble
speaker: A
text: It 's Morgan 's fault .
speaker: F
text: You can find <disfmarker>
speaker: F
text: You can find , uh , problems with <disfmarker> with the transcripts ,
speaker: B
text: It 's always Morgan 's fault .
speaker: F
text: um , you know ,
speaker: E
text: Oh .
speaker: F
text: and go back and fix them .
speaker: A
text: Yeah .
speaker: F
text: But <disfmarker>
speaker: A
text: Tha - There are some cases like where the <disfmarker> the wrong speaker <disfmarker> uh , these ca Not a lot , but where the <disfmarker> the wrong person <disfmarker> the <disfmarker> the speech is addre attached to the wrong speaker
speaker: A
text: and you can tell that when you run it .
speaker: A
text: Or at least you can get <pause> clues to it .
speaker: C
text: Interesting .
speaker: C
text: I guess it does w
speaker: A
text: So these are from the early transcriptions that people did on the mixed signals , like what you have .
speaker: C
text: Mm - hmm .
speaker: C
text: It also raises the possibility of , um , using that kind of representation <disfmarker> I mean , I don't know , this 'd be something we 'd wanna check , <comment> but maybe using that representation for data entry
speaker: C
text: and then displaying it on the channelized , uh , representation ,
speaker: C
text: cuz it <disfmarker> I think that the <disfmarker> I mean , my <disfmarker> my preference in terms of , like , looking at the data is to see it <pause> in this kind of musical score format .
speaker: A
text: Mm - hmm .
speaker: C
text: And also , s you know , Sue 's preference as well .
speaker: A
text: Yeah , if you can get it to <disfmarker>
speaker: C
text: And <disfmarker> and <disfmarker>
speaker: C
text: but , I mean , this <disfmarker> if this is a better interface for making these kinds of , uh , you know , lo clos local changes , then that 'd be fine , too .
speaker: C
text: I don't <disfmarker> I have no idea .
speaker: C
text: I think this is something that would need to be checked .
speaker: C
text: Yeah .
speaker: B
text: OK .
speaker: B
text: Th - the other thing I had actually was ,
speaker: B
text: I <disfmarker> I didn't realize this till today ,
speaker: B
text: but , uh , this is , uh , Jose 's last day .
speaker: H
text: Is my last <disfmarker> my last day .
speaker: E
text: Yeah .
speaker: A
text: Oh !
speaker: F
text: Oh !
speaker: C
text: Oh .
speaker: H
text: My <disfmarker> <vocalsound> my last meeting <pause> about meetings .
speaker: E
text: You 're not gonna be here tomorrow ?
speaker: E
text: Oh , that 's right .
speaker: H
text: Yeah .
speaker: E
text: Tomorrow <disfmarker>
speaker: H
text: Because , eh , I leave , eh , the next Sunday .
speaker: D
text: The last meeting meeting ?
speaker: E
text: It 's off .
speaker: H
text: I will come back to home <disfmarker> to Spain .
speaker: F
text: Mm - hmm .
speaker: A
text: Oh .
speaker: B
text: Yeah .
speaker: B
text: I d so I <disfmarker> I jus
speaker: F
text: Mm - hmm .
speaker: H
text: And I <disfmarker> I would like to <disfmarker> to <disfmarker> to say thank you very much , eh , to all people <pause> in the group and at ICSI ,
speaker: A
text: Oh .
speaker: F
text: Mm - hmm .
speaker: E
text: Yeah .
speaker: E
text: It was good having you .
speaker: F
text: Mmm .
speaker: A
text: Yeah .
speaker: H
text: because I <disfmarker> I enjoyed @ @ very much ,
speaker: F
text: Mmm .
speaker: H
text: uh .
speaker: H
text: And I 'm sorry by the result of overlapping ,
speaker: H
text: because , eh , <vocalsound> I haven't good results , eh , yet
speaker: H
text: but , eh , <vocalsound> I <disfmarker> <vocalsound> I pretend <comment> to <disfmarker> to continuing out to Spain , eh , during the <disfmarker> the following months ,
speaker: H
text: eh , because I have , eh , another ideas
speaker: B
text: Uh - huh .
speaker: H
text: but , eh , I haven't enough time to <disfmarker> to <disfmarker> <vocalsound> with six months it 's not enough to <disfmarker> <vocalsound> to <disfmarker> to research ,
speaker: E
text: Yep .
speaker: B
text: Yeah .
speaker: H
text: eh , and e i I mean , if , eh , the topic is , eh , so difficult ,
speaker: H
text: uh , in my opinion , there isn't <disfmarker>
speaker: B
text: Yeah . Maybe somebody else will come along and will be , uh , interested in working on it
speaker: B
text: and could start off from where you are also , you know .
speaker: B
text: They 'd make use of <disfmarker> of what you 've done .
speaker: H
text: Yeah .
speaker: H
text: Yeah .
speaker: B
text: Yeah .
speaker: H
text: But , eh , I <disfmarker> I will try to recommend , eh , at , eh , <vocalsound> the Spanish government
speaker: H
text: but , eh , the following @ @ scholarship , eh , eh , <vocalsound> eh , will be here <pause> more time ,
speaker: H
text: because eh , i in my opinion is <disfmarker> is better , <vocalsound> eh , for us <pause> to <disfmarker> to spend more time here
speaker: H
text: and to work more time i i in a topic .
speaker: H
text: No ?
speaker: B
text: Yeah , it 's a very short time .
speaker: H
text: But , uh <disfmarker>
speaker: B
text: Yeah .
speaker: E
text: Yeah , six months is hard .
speaker: B
text: Yeah .
speaker: H
text: Yeah . It is .
speaker: E
text: I think a year is a lot better .
speaker: H
text: Yeah .
speaker: B
text: Yeah .
speaker: H
text: It 's difficult .
speaker: H
text: You <disfmarker> e you have , eh <disfmarker> you are lucky ,
speaker: H
text: and you <disfmarker> you find a solution <comment> in <disfmarker> in <disfmarker> in some few tim uh , months , eh ?
speaker: H
text: OK .
speaker: H
text: But , eh , I think it 's not , eh , common .
speaker: H
text: But , eh , anyway , thank you .
speaker: H
text: Thank you very much .
speaker: H
text: Eh , I <disfmarker> I bring the chocolate , eh , to <disfmarker> <vocalsound> <vocalsound> to tear , uh , with <disfmarker> with you ,
speaker: F
text: Mmm .
speaker: C
text: Ah .
speaker: A
text: Oh .
speaker: C
text: Nice .
speaker: H
text: uh .
speaker: H
text: I <disfmarker> I hope if you need , eh , something , eh , from us in the future , I <disfmarker> I will be at Spain , <vocalsound> to you help ,
speaker: H
text: uh .
speaker: E
text: Great .
speaker: B
text: Well .
speaker: C
text: Great .
speaker: B
text: Thank you , Jose .
speaker: C
text: Thank you .
speaker: A
text: Right .
speaker: H
text: And , thank you very much .
speaker: F
text: Have a good trip .
speaker: B
text: Yeah .
speaker: H
text: Thank you .
speaker: C
text: Yeah .
speaker: F
text: Keep in touch .
speaker: B
text: Yeah .
speaker: B
text: OK .
speaker: B
text: I guess , uh , unless somebody has something else , we 'll read <disfmarker> read our digits
speaker: E
text: Digits ?
speaker: B
text: and we 'll get our <disfmarker>
speaker: D
text: Uh .
speaker: E
text: Are we gonna do them simultaneously
speaker: D
text: Oops .
speaker: B
text: get our last bit of , uh , Jose 's <disfmarker> Jose <disfmarker> Jose 's digit <disfmarker>
speaker: E
text: or <disfmarker> ?
speaker: H
text: You <disfmarker> eh <disfmarker>
speaker: B
text: Uh , I 'm sorry ?
speaker: H
text: Ye - ye you prefer , eh , to eat , eh , chocolate , eh , at the coffee break , eh , at the <disfmarker> ? <vocalsound> Or you prefer now , before after <disfmarker> ?
speaker: C
text: Well , we have a time <disfmarker>
speaker: F
text: No , we prefer to keep it for ourselves .
speaker: D
text: During <disfmarker>
speaker: F
text: Yeah , yeah .
speaker: C
text: Well , we have a s a time <disfmarker> time constraint .
speaker: D
text: during digits .
speaker: B
text: So keep it away from that end of the table .
speaker: C
text: Yeah .
speaker: F
text: Yeah .
speaker: H
text: Yeah .
speaker: C
text: Yeah .
speaker: A
text: Why is it that I can read your mind ?
speaker: E
text: Well , we 've gotta wait until after di after we take the mikes off .
speaker: D
text: No , no .
speaker: E
text: So are we gonna do digits simultaneously
speaker: B
text: Well ?
speaker: A
text: You <disfmarker> This is our reward if we <pause> do our digi
speaker: D
text: Yeah .
speaker: E
text: or what ?
speaker: B
text: Yeah .
speaker: C
text: OK .
speaker: D
text: Simultaneous digit chocolate task .
speaker: H
text: I <disfmarker> I think , eh , it 's enough , eh , for more peopl for more people <pause> after .
speaker: B
text: We 're gonna <disfmarker> we 're gonna do digits at the same <disfmarker>
speaker: A
text: Oh .
speaker: F
text: Mmm !
speaker: H
text: But , eh <disfmarker>
speaker: C
text: That 's nice .
speaker: F
text: Mm - hmm .
speaker: B
text: Um .
speaker: A
text: Oh , thanks , Jose .
speaker: C
text: Wow .
speaker: H
text: To Andreas , the idea is <disfmarker> is good . <vocalsound> s To eat here .
speaker: B
text: Well <disfmarker>
speaker: F
text: Mmm .
speaker: C
text: Wow .
speaker: F
text: Oh .
speaker: C
text: Very nice .
speaker: B
text: Tha - that 's <disfmarker> that looks great .
speaker: A
text: Oh , wow .
speaker: F
text: Oh , yeah .
speaker: F
text: Th - it doesn't <disfmarker> it won't leave this room .
speaker: B
text: Alright , so in the interest of getting to the <disfmarker>
speaker: A
text: We could do digits while other people eat .
speaker: D
text: Yeah .
speaker: D
text: Yeah .
speaker: A
text: So it 's background crunching .
speaker: H
text: Yeah .
speaker: F
text: Mmm .
speaker: H
text: Is , eh , a <disfmarker> another acoustic event .
speaker: C
text: Nice .
speaker: A
text: We don't have background chewing .
speaker: D
text: Background crunch . Yeah .
speaker: A
text: No , we don't have any data with background eating .
speaker: F
text: Mmm .
speaker: D
text: Yeah .
speaker: A
text: I 'm serious .
speaker: A
text: You
speaker: B
text: She 's <disfmarker> she 's serious .
speaker: E
text: It 's just the rest of the digits <disfmarker> the rest of the digits are very clean ,
speaker: A
text: I am serious .
speaker: B
text: She is serious .
speaker: F
text: Mmm .
speaker: H
text: Are you <disfmarker> ?
speaker: H
text: Oh , they 're clean .
speaker: A
text: Well <disfmarker> ?
speaker: E
text: um , without a lot of background noise ,
speaker: D
text: Yeah !
speaker: A
text: And it <disfmarker>
speaker: E
text: so I 'm just not sure <disfmarker>
speaker: A
text: You have to write down , like , while y what you 're <disfmarker> what ch chocolate you 're eating
speaker: A
text: cuz they might make different sounds ,
speaker: A
text: like n nuts <disfmarker> chocolate with nuts , chocolate without nuts .
speaker: C
text: Oh .
speaker: D
text: Crunchy frogs .
speaker: B
text: Um <disfmarker>
speaker: F
text: Chocolate adaptation .
speaker: B
text: Actually <disfmarker> <vocalsound> actually kind of careful
speaker: B
text: cuz I have a strong allergy to nuts ,
speaker: B
text: so I have to sort of figure out one without th
speaker: A
text: That w Oh , yeah , they <disfmarker> they might .
speaker: B
text: It 's hard to <disfmarker> hard to say .
speaker: A
text: Maybe those ?
speaker: A
text: They 're so <disfmarker>
speaker: B
text: I don't know .
speaker: A
text: I don't know .
speaker: B
text: Um <disfmarker>
speaker: A
text: This is <disfmarker> You know , this is a different kind of speech ,
speaker: B
text: Well <disfmarker>
speaker: H
text: Take <disfmarker> take several .
speaker: A
text: looking at chocolates , deciding <disfmarker>
speaker: F
text: Mmm .
speaker: A
text: you know , it 's another style .
speaker: F
text: Mmm .
speaker: B
text: Yeah . I may <disfmarker> I may hold off .
speaker: B
text: But if I was <disfmarker> eh , but maybe I 'll get some later .
speaker: F
text: Mmm .
speaker: B
text: Thanks .
speaker: B
text: Well <disfmarker> well , why don't we <disfmarker> ?
speaker: B
text: He <disfmarker> he 's worried about a ticket .
speaker: B
text: Why don't we do a simultaneous one ?
speaker: A
text: OK .
speaker: E
text: OK .
speaker: C
text: OK .
speaker: F
text: Mmm .
speaker: B
text: Simultaneous one ?
speaker: B
text: OK .
speaker: E
text: Remember to read the transcript number , please .
speaker: A
text: And you laughed at me , too , f the first time I said that .
speaker: F
text: Right .
speaker: H
text: OK .
speaker: D
text: Oops .
speaker: B
text: I have to what ?
speaker: H
text: Yeah .
speaker: A
text: You laughed at me , too , the first time I sa said <disfmarker>
speaker: B
text: I did ,
speaker: B
text: and now I love it so much .
speaker: A
text: You really shouldn't , uh , te
speaker: E
text: OK , everyone ready ?
speaker: A
text: You have to sort of , um <disfmarker> Jose , if you haven't done this , you have to plug your ears while you 're t talking
speaker: B
text: W wait <disfmarker> wait a minute <disfmarker> wait a minute .
speaker: B
text: W we want <disfmarker> we want <disfmarker>
speaker: A
text: so that you don't get confused , I guess .
speaker: B
text: we want it synchronized .
speaker: H
text: Yeah .
speaker: C
text: Hey , you 've done this before . Haven't you ?
speaker: A
text: Yeah .
speaker: A
text: Oh , you 've done this one before ?
speaker: D
text: That 's <disfmarker>
speaker: C
text: You 've read <pause> digits together with us , haven't you <disfmarker>
speaker: A
text: Together ?
speaker: C
text: I mean , at the same time ?
speaker: H
text: No .
speaker: C
text: Oh , you haven't !
speaker: A
text: I 'm not <disfmarker> we <disfmarker> we <disfmarker> Oh , and you haven't done this either .
speaker: B
text: OK .
speaker: C
text: Oh , OK .
speaker: D
text: Oh , yeah .
speaker: A
text: I the first time is <pause> traumatic ,
speaker: B
text: We
speaker: B
text: Y <vocalsound> Yeah ,
speaker: A
text: but <disfmarker>
speaker: C
text: Oh , and the groupings are important ,
speaker: B
text: bu
speaker: H
text: Mmm .
speaker: C
text: so yo you 're supposed to pause between the groupings .
speaker: H
text: The grouping .
speaker: B
text: Yeah .
speaker: H
text: Yeah .
speaker: B
text: OK .
speaker: B
text: So , uh <disfmarker>
speaker: F
text: You mean that the <disfmarker> the grouping is supposed to be synchronized ?
speaker: E
text: Yeah , sure .
speaker: C
text: No .
speaker: B
text: No , no .
speaker: F
text: No ?
speaker: F
text: No ?
speaker: B
text: Synchronized digits .
speaker: C
text: No .
speaker: A
text: That 'd be good .
speaker: A
text: We - we 'll give everybody the same sheet
speaker: F
text: It 's like a <disfmarker> like a Greek <disfmarker> like a Greek choir ?
speaker: A
text: but they say different <disfmarker>
speaker: F
text: You know ?
speaker: F
text: Like <disfmarker>
speaker: B
text: Yes .
speaker: E
text: Hey , what a good idea .
speaker: F
text: Yeah .
speaker: E
text: We could do the same sheet for everyone .
speaker: E
text: Have them all read them at once .
speaker: A
text: Well , different digits
speaker: D
text: Eh <disfmarker>
speaker: A
text: but same groupings .
speaker: E
text: Or <disfmarker> or just same digits .
speaker: A
text: So they would all be <disfmarker>
speaker: E
text: See if anyone notices .
speaker: A
text: Yeah .
speaker: C
text: Yeah . That 'd be good .
speaker: B
text: There 's so many possibilities .
speaker: C
text: And then <disfmarker> then we can sing them next time .
speaker: B
text: Uh . OK , why don't we go ?
speaker: B
text: Uh , one two three <disfmarker> Go !
speaker: C
text: OK .
speaker: C
text: Mmm !
speaker: B
text: And Andreas has the last word .
speaker: E
text: Did you read it twice or what ?
speaker: A
text: He 's try No , he 's trying to get good recognition performance .
speaker: C
text: He had the h
speaker: H
text: Yeah .
speaker: H
text: Yeah .
speaker: C
text: He had the <disfmarker> the long form .
speaker: F
text: No .
speaker: E
text: And we 're off .

Meeting summary:
text: The Berkeley Meeting Recorder group discussed efforts to train and test the Aurora group's HTK-based recognition system on ICSI's digits corpus.
text: Members also discussed efforts to produce forced alignments from a selection of Meeting Recorder data.
text: Performance in both tasks was adversely affected by the manner of recording conditions implemented and difficulties attributing utterances to the appropriate speakers.
text: While debugging efforts resulted in improved forced alignments, dealing with mixed channel speech and speaker overlap remains a key objective for future work.
text: The group is additionally focused on a continued ability to feed different features into the recognizer and then train the system accordingly.
text: For comparing Meeting Recorder digits results, it was decided that the Aurora HTK-based system should be tested on data from the TI digits corpus.
text: The script for extracting speaker ID information will require modifications to obtain a more accurate estimation of the amount of data recorded per speaker.
text: Subsequent recognition experiments will look at large vocabulary speech from a far-field microphone (as performed in Switchboard evaluations).
text: Hand-marked, word-level alignments are needed to reveal speaker boundaries and tune the parameters of the model.
text: Modifications to the Transcriber tool are required for allowing transcribers to simultaneously view the signal in XWaves and see where words are located in time.
text: Digits training needs to be performed on a larger data set.
text: A significant loss in recognition resulted from not having included the type of phone-loop adaptation found in the SRI system.
text: Recognition performance was worse for digits recorded in closed microphone conditions versus those recorded in a studio (e.g. TI-digits).
text: A mismatch between the manner in which data were collected and the models used for doing recognition---e.g. bandwidth parameterization and the use of near- versus far-field microphones---was identified.
text: Too little data per speaker can have a negative effect on VTL estimation.
text: The PZM channel selected for obtaining digits data was too far away from most of the speakers.
text: Current speech alignment techniques assume that foreground speech must be continuous and, barring some isolated words and backchannels, can not cope with overlapping background speech.
text: Performing adaptations on both the foreground and background speaker produced a new variety of misalignments, a problem resulting, in part, from the fact that background speakers often match better to foreground conditionss.
text: Transcribers occasionally misidentified speakers and omitted backchannels that were more hidden in the mixed signal.
text: Good recognition performance was achieved with the lapel microphones.
text: The recognizer performed well on time-aligned segments labelled as 'non-overlap' (i.e. one person talking), while segments labelled as 'overlap' (i.e. multiple speakers talking at the same time) yielded poor results.
text: Future recognition efforts will include looking at reverberation.
text: Forced alignment improvements were gained by examining the types of errors generated and making the necessary adjustments.
text: More accurate alignments were achieved by significantly increasing the pruning value.
text: Future alignment efforts will include cloning the reject model, and adapting it to both the foreground and background speaker.
text: Members of the group will also compare Meeting Recorder data with other corpora (e.g. Switchboard) to determine whether speaker overlap is a feature that is more specific to meetings versus other modes of spoken interaction.
text: A cursory analysis of background speech revealed that backchannels frequently occurred after a question was asked.
text: Backchannels also featured a high proportion of 'yeahs' and a substantially fewer 'uh-huhs'.
text: Several group members are preparing Eurospeech submissions.
text: Speakers fe016 and mn017 are preparing a paper about the 'spurt' format, wherein spurts from individual channels---i.e. continuous speech regions delineated by pauses---will be extracted, merged with alignments from different channels, and time-aligned.