C: And so ,  there wouldn't be a gap afterwards because G: OK .
C: I mean some cases , there 're some people um , who who have very long segments of discourse where , you know , they 'll they 'll breath and then I put a break .
G: Mm - hmm .
C: But other than that , it 's really pretty continuous
C: and this includes things like going from one sentence into the u one utterance into the next , one sentence into the next ,
C: um ,
C: w without really stopping .
C: I mean i they , i
C: you know in writing you have this two spaces and a big gap
G: Mm - hmm .
C: you know .
G: Right .
C: But but uh  i some people are planning
C: and , you know , I mean , a lot we always are planning what we 're going to say next .
G: OK .
C: But uh , in which case , the gap between these two complete syntactic units , um , which of course n spoken things are not always complete syntactically ,
C: but  but it would be a shorter p shorter break than maybe you might like .
G: Mm - hmm .
C: But the goal there was to not have the text be so so crudely parsed in a time bin .
C: I mean , because from a discourse m purpose it 's  it 's more  it 's more useful to be able to see C: and also you know , from a speech recognition purpose my impression is that if you have too long a unit , it 's it doesn't help you very much either ,
C: cuz of the memory .
G: Well , yeah .
G: That 's fine .
C: So , that means that the amount of time after something is variable depending partly on context ,
C: but my general goal when there was sufficient space , room , pause after it to have it be kind of a natural feeling gap .
G: OK .
C: Which I c I don't know what it would be quantified as .
C: You know , Wally Chafe says that um , in producing narratives , the spurts that people use tend to be , uh , that the the what would be a pause might be something like two two seconds .
G: Mmm .
C: And um , that would be , you know one speaker .
C: The discourse  the people who look at turn taking often do use G: Mm - hmm .
C: I was interested that you chose uh , you know um , <comment> the you know that you use
C: cuz I think that 's a unit that would be more consistent with sociolinguistics .
G: Well we chose um , you know , half a second
C: Yeah .
G: because if if you go much larger , you have a y you know , your your statement about how much overlap there is becomes less , um , precise ,
G: because you include more of actual pause time into what you consider overlap speech .
C: Mm - hmm .
G: Um ,
G: so ,
G: it 's sort of a compromise ,
G: and  it 's also based B: Yeah . <comment>  Yeah , I also used I think something around zero point five seconds for the speech - nonspeech detector G: I mean Liz suggested that value based on the distribution of pause times that you see in Switchboard and and other corpora .
C: Mm - hmm .
G: Um G: So B: for the minimum silence length .
G: Mm - hmm .
G: I see .
B: So .
G: Yeah .
C: Mm - hmm .
G: OK .
C: In any case , this this uh , meeting that I hand C: I I hand - adjusted two of them
C: I mentioned before ,
G: Mm - hmm .
G: OK ,
C: and I sent I sent email ,
G: So so at some point we will try to fine - tune our forced alignment
C: so C: And I sent the <comment> path .
G: maybe using those as references
G: because you know , what you would do is you would play with different parameters .
G: And to get an object You need an objective measure of how closely you can align the models to the actual speech .
G: And that 's where your your data would be very important to have .
G: So , I will G: Um B: Yeah and hopefully the new meetings which will start from the channelized version will will have better time boundaries and alignments .
G: Mm - hmm .
G: Right .
C: But I like this idea of uh , for our purposes for the for the IBM preparation , uh , n having these joined together ,
B: Yeah .
C: and uh B: Yeah .
C: It makes a lot of sense .
C: And in terms of transcription , it would be easy to do it that way .
G: Yeah .
C: The way that they have with the longer units ,
G: Yeah .
C: not having to fuss with adding these units at this time .
B: Yeah .
G: Right .
B: Whi - which could have one drawback . If there is uh a backchannel in between those three things ,
C: Mm - hmm .
B: the the n the backchannel will will occur at the end of of those three .
C: Yes .
B: And and in in the in the previous version where in the n which is used now , there , the backchannel would would be in - between there somewhere ,
C: I see .
B: so .
C: Yeah .
B: That would be more natural
C: Well ,
B: but C: that 's that 's right ,
C: but you know , thi this brings me to the other f stage of this which I discussed with you earlier today ,
B: Yeah .
C: which is the second stage is um , w what to do in terms of the transcribers adjustment of these data .
C: I discussed this with you too .
C: Um , the tr
C: so the idea initially was , we would get uh , for the new meetings ,
C: so the e EDU meetings , that Thilo ha has now presegmented all of them for us , on a channel by channel basis .
C: And um ,
C: so , I 've assigned I 've I 've assigned them to our transcribers
C: and um ,
C: so far I 've discussed it with one ,
C: with uh C: And I had a about an hour discussion with her about this yesterday ,
C: we went through uh EDU - one , at some extent .
C: And it occurred to me that um that basically what we have in this kind of a format is you could consider it as a staggered mixed file ,
C: we had some discussion over the weekend a about at at this other meeting that we were all a at C: um , about whether the tran the IBM transcribers should hear a single channel audio , or a mixed channel audio .
C: And um , in in a way , by by having this this chunk and then the backchannel after it , it 's like a stagal staggered mixed channel .
C: And um , it occurred to me in my discussion with her yesterday that um ,
C: um ,
C: the  the the maximal gain , it 's from the IBM people , may be in long stretches of connected speech .
C: So it 's basically a whole bunch of words which they can really do , because of the continuity within that person 's turn .
C: So , what I 'm thinking , and it may be that not all meetings will be good for this , <comment> but but what I 'm thinking is that in the EDU meetings , they tend to be driven by a couple of dominant speakers .
C: And , if the chunked files focused on the dominant speakers , then , when when it got s patched together when it comes back from IBM , we can add the backchannels .
C: It seems to me that um , you know , the backchannels per - se wouldn't be so hard ,
C: but then there 's this question of the time @ @ <comment> uh , marking , and whether the beeps would be uh y y y
C: And I 'm not exactly sure how that how that would work with the with the backchannels .
C: And ,
C: so um C: And certainly things that are intrusions of multiple words , taken out of context and displaced in time from where they occurred , that would be hard .
C: So , m my thought is i I 'm having this transcriber go through the EDU - one meeting , and indicate a start time <nonvocalsound> f for each dominant speaker , endpoi end time for each dominant speaker ,
C: and the idea that these units would be generated for the dominant speakers , and maybe not for the other channels .
A: Yeah the only , um , disadvantage of that is , then it 's hard to use an automatic method to do that .
A: The advantage is that it 's probably faster to do that than it is to use the automated method and correct it .
A: So .
C: Well , it C: OK .
A: We 'll just have to see .
C: I think  I I think um , you know , the original plan was that the transcriber would adjust the t the boundaries , and all that for all the channels
C: but , you know , that is so time - consuming ,
C: and since we have a bottleneck here , we want to get IBM things that are usable s as soon as possible ,
C: then this seemed to me it 'd be a way of gett to get them a flood of data ,
C: which would be useful when it comes back to us .
C: And um C: Oh also , at the same time she when she goes through this , she 'll be uh If there 's anything that was encoded as a pause , but really has something transcribable in it , then she 's going to uh , make a mark A: Yeah .
C: w uh , so you know , so that that bin would be marked as it as double dots
C: and she 'll just add an S .
C: And in the other in the other case , if it 's marked as speech , and really there 's nothing transcribable in it , then she 's going to put a s dash ,
C: and I 'll go through and it and um , you know , with a   with a substitution command , get it so that it 's clear that those are the other category .
C: I 'll just , you know , recode them .
C: But um , um , the transcribable events that um , I 'm considering in this , uh , continue to be laugh , as well as speech , and cough and things like that ,
C: so I 'm not stripping out anything ,
C: just just you know , being very lenient in what 's considered speech .
D: Jane ?
C: Yeah ?
D: In terms of the this new procedure you 're suggesting , um , u what is the A: It 's not that different .
D: So I 'm a little confused ,
D: because how do we know where to put beeps ?
D: Is it i d y is it C: Oh , OK .
C: So what it what it what it involves is is really a s uh , uh , the original pr procedure ,
A: Transcriber will do it .
C: but only applied to uh , a certain strategically chosen s aspect of the data .
A: We pick the easy parts of the data basically ,
C: So A: and transcriber marks it by hand .
C: You got it .
A: And because D: But after we 've done Thilo 's thing .
A: No .
C: Yes !
A: Oh , after .
C: Yes !
A: Oh , OK ,
C: Oh yeah !
A: I didn't I didn't understand that .
A: OK .
B: So ,
B: I 'm @ @ now I 'm confused .
C: OK .
C: We start with your presegmented version G: OK , and I 'm leaving .
E: Yeah , I have to go as well .
G: So , um A: OK , leave the mikes on ,
A: and just put them on the table .
E: OK .
E: Thanks .
C: We start with the presegmented version A: Let me mark you as no digits .
B: You start with the presegmentation ,
B: r yeah ?
C: Yeah .
C: And then um , the transcriber , instead of going painstakingly through all the channels and moving the boundaries around , and deciding if it 's speech or not , but not transcribing anything .
C: OK ?
C: Instead of doing that , which was our original plan , the tra They focus on the dominant speaker D: Mm - hmm .
D: They just do that on the main channels .
C: Yeah .
C: So what they do is they identify who 's the di dominant speaker , and when the speaker starts .
D: OK .
B: Yeah ?
B: OK .
C: So I mean , you 're still gonna C: So we 're B: And you just C: It 's based on your se presegmentation ,
C: that 's the basic thing .
B: and you just use the s the segments of the dominant speaker then ? For for sending to to IBM
B: or ?
C: Yeah .
C: Exactly .
D: So , now Jane , my question is when they 're all done adjusting the w time boundaries for the dominant speaker , <comment> have they then also erased the time boundaries for the other ones ?
C: Mm - hmm .
C: Uh No . No , no .
D: So how will we know who C: Huh - uh .
C: S
B: Yeah .
C: That 's that 's why she 's notating the start and end points of the dominant speakers .
C: So , on a you know , so i in EDU - one , i as far as I listened to it , you start off with a a s section by Jerry .
C: So Jerry starts at minute so - and - so ,
C: and goes until minute so - and - so .
C: And then Mark Paskin comes in .
C: And he starts at minute such - and - such ,
C: and goes on till minute so - and - so .
C: OK .
C: And then meanwhile , she 's listening to  both of these guys ' channels ,
C: determining if there 're any cases of misclassification of speech as nothing , and nothing as speech ,
D: Mm - hmm .
D: OK .
C: and a and adding a tag if that happens .
D: So she does the adjustments on those guys ?
C: But you know , I wanted to say , his segmentation is so good , that um , the part that I listened to with her yesterday didn't need any adjustments of the bins .
B: On that meeting .
D: Mm - hmm .
C: So far we haven't .
C: So this is not gonna be a major part of the process ,
C: at least least not in not on ones that that really D: So if you don't have to adjust the bins , why not just do what it for all the channels ?
C: Mm - hmm ?
D: Why not just throw all the channels to IBM ?
C: Well there 's the question o of whether C: Well , OK .
C: She i It 's a question of how much time we want our transcriber to invest here when she 's gonna have to invest that when it comes back from IBM anyway .
D: Mm - hmm .
C: So if it 's only inserting " mm - hmm "s here and there , then , wouldn't that be something that would be just as efficient to do at this end , instead of having it go through I B M , then be patched together , then be double checked here .
D: Mm - hmm .
D: Right .
B: Yeah .
B: But B: But then we could just use the the output of the detector , and do the beeping on it , and send it to I B
D: Without having her check anything .
F: Right .
B: Yeah .
C: Well , I guess B: For some meetings , I 'm I 'm sure it i
A: I think we just we just have to listen to it and see how good they are .
B: n
C: I 'm I 'm open to that ,
C: it was F: Yeah , if it 's working well ,
F: that sounds like a good idea
B: That 's And some on some meetings it 's good .
F: since as you say you have to do stuff with the other end anyway .
B: Yeah .
C: Well yea
C: OK , good .
D: Yeah , I mean we have to fix it when it comes back anyhow .
C: I mean the detector , this B: Yeah .
C: Now , you were saying that they they differ in how well they work depending on channel s sys systems and stuff .
B: Yeah .
B: So we should perhaps just select meetings on which the speech - nonspeech detection works well ,
C: But EDU is great .
B: and just use , those meetings to to to send to IBM and , do the other ones .
A: Release to begin with .
C: How interesting .
F: What 's the problem the l I forget .
C: You know F: Is the problem the lapel ,
F: or or B: Uh , it really depends .
B: Um , my my my impression is that it 's better for meetings with fewer speakers ,
B: and it 's better for  for meetings where nobody is breathing .
F: Oh ,
F: the dead meetings .
B: Yeah ,
B: get B: That 's it .
D: So in fact this might suggest an alternative sort of a a c a hybrid between these two things .
A: No , the undead meeting ,
A: yeah .
C: Yeah .
C: Yeah ?
D: So the the one suggestion is you know we  we run Thilo 's thing
D: and then we have somebody go and adjust all the time boundaries
C: Yeah ?
D: and we send it to IBM .
B: Yeah .
D: The other one is we just run his thing and send it to IBM .
D: There 's a a another possibility if we find that there are some problems ,
B: Yeah .
B: Yeah .
D: and that is if we go ahead and we just run his , and we generate the beeps file , then we have somebody listen beeps file .
B: Yeah .
B: Yeah .
D: And they listen to each section and say " yes , no " whether that section is
B: And erase B: Yeah .
C: Is intelligible .
D: i i intelligible or not .
D: And it just You know , there 's a little interface which will for all the " yes " - es it then that will be the final beep file .
B: Yeah .
A: Blech .
C: That 's interesting !
C: Cuz that 's that 's directly related to the e end task .
A: Stress test .
D: Mm - hmm .
C: How interesting !
D: Yeah .
D: I mean it wouldn't be that much fun for a transcriber to sit there , hear it , beep , yes or no .
B: Nope .
F: I I I don't know .
D: But it would be quick .
F: It would be kind of quick
F: but they 're still listening to everything .
D: But there 's no adjusting .
D: And that 's what 's slow .
D: There 's no adjusting of time boundaries .
C: Well , eh , listening does take time too .
F: Yeah .
D: Yeah .
F: I don't know ,
F: I I think I 'm I 'm really tending towards A: One and a half times real time .
F: I mean , what 's the worst that happens ?
F: Do the transcribers F: I mean as long as th on the other end they can say there 's there 's something conventions so that they say " huh ? "
D: Yeah .
D: Right .
F: and then we can flag those later .
D: They they D: Yeah .
F: i i It i
D: That 's true .
D: We can just catch it at the catch everything at this side .
F: Yeah .
D: Well maybe that 's the best way to go ,
D: just C: How interesting !
A: I mean it just depends on how C: Well EDU B: Yeah ,
B: u u u
A: Sorry , go ahead .
C: So I was gonna say , EDU - one is good enough ,
B: Yeah .
C: maybe we could include it in this in this set of uh , this stuff we send .
B: Yeah there 's I I think there are some meetings where it would would It 's possible like this .
A: Yeah I I think , we won't know until we generate a bunch of beep files automatically , listen to them and see how bad they are .
B: Yeah .
B: Yeah .
D: Yeah .
D: We won't be able to s include it with this first thing ,
C: Mm - hmm .
C: Hmm .
A: If C: Oh , OK .
D: because there 's a part of the process of the beep file which requires knowing the normalization coefficients .
C: Oh , I see .
D: And  So a
A: That 's not hard to do .
A: Just it takes you know , it just takes five minutes rather than , taking a second .
D: OK
B: Yeah .
D: Right ,
D: except I don't think that the c the instructions for doing that was in that directory ,
A: So . I just hand hard - coded it .
D: right ?
D: I I didn't see where you had gener