Professor F: So , that 's why it was good to have Andreas , say these things but So , we should probably talk about the IBM transcription process stuff that Postdoc C: OK . So , um you know that Adam created um , a b a script to generate the beep file ?
Professor F: Hmm .
Postdoc C: To then create something to send to IBM . And , um , you you should probably talk about that . But but you were gonna to use the originally transcribed file because I tightened the time bins and that 's also the one that they had already in trying to debug the first stage of this . And uh , my understanding was that , um I haven't  I haven't listened to it yet ,
Grad A: Mm - hmm .
Postdoc C: but it sounded very good and and I understand that you guys were going to have a meeting today , before this meeting .
Grad A: It was just to talk about how to generate it . Um , just so that while I 'm gone , you can regenerate it if you decide to do it a different way . So uh , Chuck and Thilo should , now more or less know how to generate the file
Postdoc C: Excellent . OK .
Grad A: and , the other thing Chuck pointed out is that , um , since this one is hand - marked , there are discourse boundaries . Right ? So so when one person is speaking , there 's breaks .
Postdoc C: Mm - hmm .
Grad A: Whereas Thilo 's won't have that . So what what we 're probably gonna do is just write a script , that if two , chunks are very close to each other on the same channel we 'll just merge them .
Postdoc C: Oh ! OK . Ah , interesting . Yeah . Yeah . Oh , sure . Yeah , sure . Makes sense .
Grad A: So , uh , and that will get around the problem of , the , you know " one word beep , one word beep , one word beep , one word beep " .
Postdoc C: Yeah . Ah ! Clever . Yes . Clever . Yeah . Excellent .
PhD D: Yeah , in fact after our meeting uh , this morning Thilo came in and said that um , there could be other differences between the uh already transcribed meeting with the beeps in it and one that has just r been run through his process .
Postdoc C: And that 's the purpose . Yeah .
PhD D: So tomorrow , when we go to make the um uh , chunked file for IBM , we 're going to actually compare the two . So he 's gonna run his process on that same meeting ,
Postdoc C: Great idea !
PhD D: and then we 're gonna do the beep - ify on both , and listen to them and see if we notice any real differences .
PhD G: Beep - ify !
Postdoc C: OK , now one thing that prevented us from apply you you from applying Exactly . The training So that is the training meeting . OK .
PhD D: Yeah , w and we know that . Wel - uh we just wanna if if there 're any major differences between doing it on the hand
Postdoc C: Uh - huh . Oh , interesting . Ah !
Grad A: Hmm .
Postdoc C: OK . Interesting idea . Great .
PhD G: So this training meeting , uh w un is that uh some data where we have uh very um , you know , accurate time marks ? for Postdoc C: I went back and hand - marked the ba the bins , I ment I mentioned that last week .
PhD G: OK , yeah .
PhD D: But the but there 's yeah , but there is this one issue with them in that there 're  there are time boundaries in there that occur in the middle of speech .
PhD G: Because PhD D: So Like when we went t to um When I was listening to the original file that Adam had , it 's like you you hear a word then you hear a beep and then you hear the continuation of what is the same sentence .
Grad A: That 's on the other channel . That 's because of channel overlap .
PhD D: Well , and and so the th
Postdoc C: Hmm .
Grad A: It 's i
PhD D: So there are these chunks that look like uh  that have uh Grad A: I mean that 's not gonna be true of the foreground speaker . That 'll only be if it 's the background speaker .
PhD D: Right . So you 'll you 'll have a chunk of , you know , channel A which starts at zero and ends at ten , and then the same channel starting at eleven , ending at fifteen , and then again , starting at sixteen , ending at twenty . Right , so that 's three chunks where actually we w can just make one chunk out of that which is A , zero , twenty .
PhD G: Mm - hmm .
Postdoc C: Yeah .
Grad A: That 's what I just said ,
Postdoc C: Sure . Sure .
Grad A: yeah .
PhD D: Yeah . So I just wanted to make sure that it was clear .
Postdoc C: Yeah , I thought that was PhD D: So if you were to use these , you have to be careful not to pull out these individual Postdoc C: Yeah .
PhD G: Oh ! I mean it Right , I mean w I mean what I would I was interested in is having  a se having time marks for the beginnings and ends of speech by each speaker .
Grad A: Well , that 's definitely a problem .
PhD G: Uh , because we could use that to fine tune our alignment process
Grad A: Battery .
PhD D: Yeah .
PhD G: to make it more accurate .
PhD B: Battery ?
PhD D: Mm - hmm .
PhD G: So uh , it I don't care that you know , there 's actually abutting segments that we have to join together . That 's fine .
PhD D: OK .
PhD G: But what we do care about is that the beginnings and ends um are actually close to the speech inside of that
PhD D: Yeah , I think Jane tightened these up by hand .
PhD G: uh PhD B: OK .
Postdoc C: Yeah .
PhD G: OK , so what is the sort of how tight are they ?
Professor F: Uh , it looks much better .
PhD B: Yeah . Looks good .
Postdoc C: They were , um , reasonably tight , but not excruciatingly tight .
PhD G: Oh .
Postdoc C: That would 've taken more time . I just wanted to get it so tha So that if you have like " yeah " {comment} in a swimming in a big bin , then it 's PhD G: No , no ! I don
Grad A: Let me make a note on yours .
PhD G: actually I I PhD B: Yeah .
PhD G: I it 's f That 's fine because we don't want to th that 's perfectly fine . In fact it 's good . You always want to have a little bit of pause or nonspeech around the speech , say for recognition purposes . Uh , but just just u w you know get an id I just wanted to have an idea of the  of how much extra you allowed um so that I can interpret the numbers if I compared that with a forced alignment segmentation .
Postdoc C: I can't answer that ,
PhD G: So .
Postdoc C: but but my main goal was um , in these areas where you have a three - way overlap and one of the overlaps involves " yeah " , and it 's swimming in this huge bin , I wanted to get it so that it was clo more closely localized .
PhD G: Mm - hmm . Mm - hmm . Right . But are we talking about , I don't know , a  tenth of a second ? a ? You know ? How how much how much extra would you allow at most Postdoc C: I I wanted to I wanted it to be able to l he be heard normally ,
PhD G: Mm - hmm .
Postdoc C: so that if you if you play back that bin and have it in the mode where it stops at the boundary , it sounds like a normal word .
PhD G: OK .
Postdoc C: It doesn't sound like the person i it sounds normal . It 's as if the person could 've stopped there .
PhD G: Mm - hmm .
Postdoc C: And it wouldn't have been an awkward place to stop .
PhD G: OK .
Postdoc C: Now sometimes you know , it 's these are involved in places where there was no time . And so ,  there wouldn't be a gap afterwards because PhD G: OK .
Postdoc 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 .
PhD G: Mm - hmm .
Postdoc C: But other than that , it 's really pretty continuous and this includes things like going from one sentence into the u one utterance into the next , one sentence into the next , um , w without really stopping . I mean i they , i you know in writing you have this two spaces and a big gap
PhD G: Mm - hmm .
Postdoc C: you know .
PhD G: Right .
Postdoc C: But but uh  i some people are planning and , you know , I mean , a lot we always are planning what we 're going to say next .
PhD G: OK .
Postdoc 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 , but  but it would be a shorter p shorter break than maybe you might like .
PhD G: Mm - hmm .
Postdoc C: But the goal there was to not have the text be so so crudely parsed in a time bin . I mean , because from a discourse m purpose it 's  it 's more  it 's more useful to be able to see 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 , cuz of the memory .
PhD G: Well , yeah . That 's fine .
Postdoc C: So , that means that the amount of time after something is variable depending partly on context , but my general goal when there was sufficient space , room , pause after it to have it be kind of a natural feeling gap .
PhD G: OK .
Postdoc C: Which I c I don't know what it would be quantified as . 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 .
PhD G: Mmm .
Postdoc C: And um , that would be , you know one speaker . The discourse  the people who look at turn taking often do use PhD G: Mm - hmm .
Postdoc C: I was interested that you chose uh , you know um , {comment} the you know that you use cuz I think that 's a unit that would be more consistent with sociolinguistics . Yeah .
PhD G: Well we chose um , you know , half a second 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 ,
Postdoc C: Mm - hmm .
PhD G: because you include more of actual pause time into what you consider overlap speech . Um , so , it 's sort of a compromise ,
PhD B: Yeah . {comment}  Yeah , I also used I think something around zero point five seconds for the speech - nonspeech detector PhD G: and  it 's also based I mean Liz suggested that value based on the distribution of pause times that you see in Switchboard and and other corpora .
Postdoc C: Mm - hmm .
PhD G: Um So PhD B: for the minimum silence length .
PhD G: Mm - hmm . I see .
PhD B: So .
PhD G: Yeah .
Postdoc C: Mm - hmm .
PhD G: OK .
Postdoc C: In any case , this this uh , meeting that I hand I I hand - adjusted two of them I mentioned before ,
PhD G: Mm - hmm .
Postdoc C: and I sent I sent email ,
PhD G: OK ,
Postdoc C: so PhD G: So so at some point we will try to fine - tune our forced alignment
Postdoc C: And I sent the {comment} path .
PhD G: maybe using those as references because you know , what you would do is you would play with different parameters . And to get an object You need an objective measure of how closely you can align the models to the actual speech . And that 's where your your data would be very important to have . So , I will Um PhD B: Yeah and hopefully the new meetings which will start from the channelized version will will have better time boundaries and alignments .
PhD G: Mm - hmm . Right .
Postdoc C: But I like this idea of uh , for our purposes for the for the IBM preparation , uh , n having these joined together ,
PhD B: Yeah . Yeah .
Postdoc C: and uh It makes a lot of sense . And in terms of transcription , it would be easy to do it that way .
PhD G: Yeah .
Postdoc C: The way that they have with the longer units ,
PhD G: Yeah .
Postdoc C: not having to fuss with adding these units at this time .
PhD B: Yeah . Whi - which could have one drawback . If there is uh a backchannel in between those three things ,
PhD G: Right .
Postdoc C: Mm - hmm .
PhD B: the the n the backchannel will will occur at the end of of those three .
Postdoc C: Yes .
PhD 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 , so .
Postdoc C: I see .
PhD B: That would be more natural
Postdoc C: Yeah . Well ,
PhD B: but Postdoc C: that 's that 's right , but you know , thi this brings me to the other f stage of this which I discussed with you earlier today ,
PhD B: Yeah .
Postdoc C: which is the second stage is um , w what to do in terms of the transcribers adjustment of these data . I discussed this with you too . Um , the tr so the idea initially was , we would get uh , for the new meetings , so the e EDU meetings , that Thilo ha has now presegmented all of them for us , on a channel by channel basis . And um , so , I 've assigned I 've I 've assigned them to our transcribers and um , so far I 've discussed it with one , with uh And I had a about an hour discussion with her about this yesterday , we went through uh EDU - one , at some extent . 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 , we had some discussion over the weekend a about at at this other meeting that we were all a at um , about whether the tran the IBM transcribers should hear a single channel audio , or a mixed channel audio . 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 . And um , it occurred to me in my discussion with her yesterday that um , um , the  the the maximal gain , it 's from the IBM people , may be in long stretches of connected speech . So it 's basically a whole bunch of words which they can really do , because of the continuity within that person 's turn . 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 . 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 . It seems to me that um , you know , the backchannels per - se wouldn't be so hard , but then there 's this question of the time @ @ {comment} uh , marking , and whether the beeps would be uh y y y And I 'm not exactly sure how that how that would work with the with the backchannels . And , so um 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 . 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 , and the idea that these units would be generated for the dominant speakers , and maybe not for the other channels .
Grad A: Yeah the only , um , disadvantage of that is , then it 's hard to use an automatic method to do that . The advantage is that it 's probably faster to do that than it is to use the automated method and correct it . So .
Postdoc C: Well , it Grad A: We 'll just have to see .
Postdoc C: OK . 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 but , you know , that is so time - consuming , and since we have a bottleneck here , we want to get IBM things that are usable s as soon as possible , then this seemed to me it 'd be a way of gett to get them a flood of data , which would be useful when it comes back to us . And um Grad A: Yeah .
Postdoc 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 w uh , so you know , so that that bin would be marked as it as double dots and she 'll just add an S . 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 , 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 . I 'll just , you know , recode them . 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 , so I 'm not stripping out anything , just just you know , being very lenient in what 's considered speech . Yeah ?
PhD D: Jane ? In terms of the this new procedure you 're suggesting , um , u what is the Grad A: It 's not that different .
PhD D: So I 'm a little confused , because how do we know where to put beeps ? Is it i d y is it Postdoc C: Oh , OK .
Grad A: Transcriber will do it .
Postdoc C: So what it what it what it involves is is really a s uh , uh , the original pr procedure , but only applied to uh , a certain strategically chosen s aspect of the data .
Grad A: We pick the easy parts of the data basically ,
Postdoc C: So Grad A: and transcriber marks it by hand .
Postdoc C: You got it .
Grad A: And because PhD D: But after we 've done Thilo 's thing .
Grad A: No .
Postdoc C: Yes !
Grad A: Oh , after . Oh , OK ,
Postdoc C: Yes !
Grad A: I didn't I didn't understand that .
Postdoc C: Oh yeah !
Grad A: OK .
PhD B: So , I 'm @ @ now I 'm confused .
Postdoc C: OK . We start with your presegmented version PhD G: OK , and I 'm leaving .
Grad E: Yeah , I have to go as well .
PhD G: So , um Grad A: OK , leave the mikes on , and just put them on the table .
Grad E: OK . Thanks .
Postdoc C: We start with the presegmented version Grad A: Let me mark you as no digits .
PhD B: You start with the presegmentation , r yeah ?
Postdoc C: Yeah . 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 . OK ? Instead of doing that , which was our original plan , the tra They focus on the dominant speaker PhD D: Mm - hmm . They just do that on the main channels .
Postdoc C: Yeah . So what they do is they identify who 's the di dominant speaker , and when the speaker starts .
PhD D: OK .
PhD B: Yeah ? OK .
Postdoc C: So I mean , you 're still gonna PhD B: And you just Postdoc C: So we 're It 's based on your se presegmentation , that 's the basic thing .
PhD B: and you just use the s the segments of the dominant speaker then ? For for sending to to IBM or ?
Postdoc C: Yeah . Exactly .
PhD 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 ?
Postdoc C: Mm - hmm . Uh No . No , no . Huh - uh . S
PhD D: So how will we know who PhD B: Yeah .
Postdoc C: That 's that 's why she 's notating the start and end points of the dominant speakers . 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 . So Jerry starts at minute so - and - so , and goes until minute so - and - so . And then Mark Paskin comes in . And he starts at minute such - and - such , and goes on till minute so - and - so . OK . And then meanwhile , she 's listening to  both of these guys ' channels , determining if there 're any cases of misclassification of speech as nothing , and nothing as speech ,
PhD D: Mm - hmm . OK .
Postdoc C: and a and adding a tag if that happens .
PhD D: So she does the adjustments on those guys ?
Postdoc 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 .
PhD B: On that meeting .
PhD D: Mm - hmm .
Postdoc C: So far we haven't . So this is not gonna be a major part of the process , at least least not in not on ones that that really PhD D: So if you don't have to adjust the bins , why not just do what it for all the channels ?
Postdoc C: Mm - hmm ?
PhD D: Why not just throw all the channels to IBM ?
Postdoc C: Well there 's the question o of whether Well , OK . 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 .
PhD D: Mm - hmm .
Postdoc 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 .
PhD D: Mm - hmm . Right .
PhD B: Yeah . But But then we could just use the the output of the detector , and do the beeping on it , and send it to I B
PhD D: Without having her check anything .
PhD B: Yeah .
Professor F: Right .
Postdoc C: Well , I guess Grad A: I think we just we just have to listen to it and see how good they are .
PhD B: For some meetings , I 'm I 'm sure it i n
Postdoc C: I 'm I 'm open to that , it was Professor F: Yeah , if it 's working well ,
PhD B: That 's And some on some meetings it 's good .
Professor F: that sounds like a good idea since as you say you have to do stuff with the other end anyway .
PhD B: Yeah .
Postdoc C: Well yea OK , good . I mean the detector , this PhD D: Yeah , I mean we have to fix it when it comes back anyhow .
PhD B: Yeah .
Postdoc C: Now , you were saying that they they differ in how well they work depending on channel s sys systems and stuff .
PhD B: Yeah . So we should perhaps just select meetings on which the speech - nonspeech detection works well ,
Postdoc C: But EDU is great .
PhD B: and just use , those meetings to to to send to IBM and , do the other ones .
Grad A: Release to begin with .
Postdoc C: How interesting . You know Professor F: What 's the problem the l I forget . Is the problem the lapel , or or PhD B: Uh , it really depends . Um , my my my impression is that it 's better for meetings with fewer speakers , and it 's better for  for meetings where nobody is breathing .
Professor F: Oh ,
PhD B: Yeah ,
Professor F: the dead meetings .
PhD B: get That 's it .
PhD D: So in fact this might suggest an alternative sort of a a c a hybrid between these two things .
Grad A: No , the undead meeting , yeah .
Postdoc C: Yeah . Yeah ?
PhD D: So the the one suggestion is you know we  we run Thilo 's thing and then we have somebody go and adjust all the time boundaries
PhD B: Yeah .
Postdoc C: Yeah ?
PhD D: and we send it to IBM . The other one is we just run his thing and send it to IBM .
PhD B: Yeah .
PhD D: There 's a a another possibility if we find that there are some problems ,
PhD B: Yeah . Yeah .
PhD 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 .
PhD B: Yeah . And erase PhD D: And they listen to each section and say " yes , no " whether that section is
PhD B: Yeah .
Postdoc C: Is intelligible .
PhD D: i i intelligible or not . 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 .
PhD B: Yeah .
Grad A: Blech .
Postdoc C: That 's interesting ! Cuz that 's that 's directly related to the e end task .
Grad A: Stress test .
PhD D: Mm - hmm .
Postdoc C: How interesting !
PhD D: Yeah . I mean it wouldn't be that much fun for a transcriber to sit there , hear it , beep , yes or no .
PhD B: Nope .
Professor F: I I I don't know .
PhD D: But it would be quick .
Professor F: It would be kind of quick but they 're still listening to everything .
PhD D: But there 's no adjusting . And that 's what 's slow . There 's no adjusting of time boundaries .
Postdoc C: Well , eh , listening does take time too .
PhD D: Yeah .
Professor F: Yeah . I don't know , I I think I 'm I 'm really tending towards Grad A: One and a half times real time .
Professor F: I mean , what 's the worst that happens ? Do the transcribers I mean as long as th on the other end they can say there 's there 's something conventions so that they say " huh ? "
PhD D: Yeah . Right . They they Professor F: and then we can flag those later .
PhD D: Yeah . That 's true .
Professor F: i i It i
PhD D: We can just catch it at the catch everything at this side .
Professor F: Yeah .
PhD D: Well maybe that 's the best way to go ,
Postdoc C: How interesting !
PhD D: just Grad A: I mean it just depends on how Postdoc C: Well EDU PhD B: Yeah ,
Grad A: Sorry , go ahead .
PhD B: u u u
Postdoc C: So I was gonna say , EDU - one is good enough ,
PhD B: Yeah .
Postdoc C: maybe we could include it in this in this set of uh , this stuff we send .
PhD B: Yeah there 's I I think there are some meetings where it would would It 's possible like this .
Grad 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 .
PhD B: Yeah . Yeah .
PhD D: Yeah .
Postdoc C: Mm - hmm .
PhD D: We won't be able to s include it with this first thing ,
Grad A: If Postdoc C: Hmm . Oh , OK .
PhD D: because there 's a part of the process of the beep file which requires knowing the normalization coefficients .
Postdoc C: Oh , I see .
PhD D: And  So a
Grad A: That 's not hard to do . Just it takes you know , it just takes five minutes rather than , taking a second .
PhD D: OK
PhD B: Yeah .
Grad A: So . I just hand hard - coded it .
PhD D: Right , except I don't think that the c the instructions for doing that was in that directory , right ? I I didn't see where you had gener
Grad A: No , but it 's easy enough to do .
PhD B: What Professor F: But I but I have a PhD B: Doing the gain ? It 's no problem . Adjusting the gain ?
PhD D: n Doing th No , getting the coefficients , for each channel .
PhD B: Yeah , that 's no problem .
Postdoc C: Know what numbers .
PhD D: OK . So we just run that one Grad A: There are lots of ways to do it .
PhD B: We can do that .
Grad A: I have one program that 'll do it . You can find other programs .
PhD B: Yeah . I I used it , so .
PhD D: We just run that
Grad A: Yep .
PhD B: Yeah .
PhD D: J - sound - stat ? OK .
Professor F: Yeah .
Grad A: Minus D , capital D .
PhD B: Yeah .
Professor F: But but but I I I have another suggestion on that , which is , since , really what this is , is is is trying to in the large , send the right thing to them and there is gonna be this this post - processing step , um , why don't we check through a bunch of things by sampling it ?
PhD D: Mm - hmm .
Professor F: Right ? In other words , rather than , um , uh , saying we 're gonna listen to everything Grad A: I didn't mean listen to everything , I meant , just see if they 're any good .
Professor F: Yeah . So y you do a bunch of meetings , you listen to to a little bit here and there ,
PhD D: Yeah .
Professor F: if it sounds like it 's almost always right and there 's not any big problem you send it to them .
PhD D: Send it to them .
PhD B: Yeah .
PhD D: OK .
Professor F: And , you know , then they 'll send us back what we w what what they send back to us ,
Postdoc C: Oh , that 'd be great .
Professor F: and we 'll we 'll fix things up and some meetings will cost more time to fix up than others .
Grad A: We should Yeah .
PhD B: Yeah .
Grad A: And we should just double - check with Brian on a few simple conventions on how they should mark things .
PhD B: Sure .
PhD D: OK . When they when there 's either no speech in there ,
PhD B: Yeah . Yeah .
PhD D: or something they don't understand ,
Postdoc C: Yeah . Mm - hmm .
PhD D: things like that .
Grad A: Yeah , cuz @ @ uh what I had originally said to Brian was well they 'll have to mark , when they can't distinguish between the foreground and background ,
Professor F: Yeah .
Grad A: because I thought that was gonna be the most prevalent . But if we send them without editing , then we 're also gonna hafta have m uh , notations for words that are cut off ,
PhD D: Mm - hmm .
PhD B: Yeah .
PhD D: Mm - hmm .
Grad A: and other sorts of , uh , acoustic problems .
PhD B: Yeah .
Postdoc C: They do already .
PhD D: And they may just guess at what those cut - off words are ,
Postdoc C: Yeah .
PhD D: but w I mean we 're gonna adjust everything when we come back Grad A: But what what we would like them to do is be conservative so that they should only write down the transcript if they 're sure .
PhD B: Yeah .
Grad A: And otherwise they should mark it so that we can check .
PhD B: Mark it . Sure . Yeah . Yeah .
PhD D: Mm - hmm .
Postdoc C: Well , we have the unintelligibility convention .
Grad A: Mm - hmm .
Postdoc C: And actually they have one also ,
Grad A: Right .
Postdoc C: which Professor F: i Can I maybe have have an order of it 's probably in your paper that I haven't looked at lately , but Postdoc C: Certainty .
Professor F: Uh , an order of magnitude notion of of how on a good meeting , how often uh , do you get segments that come in the middle of words and so forth , and uh in a bad meeting how often ?
PhD B: Uh .
Postdoc C: Was is it in a in a what what is the t
Professor F: Well he 's saying , you know , that the the EDU meeting was a good good meeting ,
Postdoc C: In a good meeting , what ?
PhD B: Yeah .
Postdoc C: Yeah .
Professor F: right ?
Postdoc C: Oh I see ,
Professor F: Uh , and so so so it was almost it was almost always doing the right thing .
Postdoc C: the characteristics .
Professor F: So I wanted to get some sense of what what almost always meant . And then , uh in a bad meeting , or p some meetings where he said oh he 's had some problems , what does that mean ?
Postdoc C: Uh - huh . OK .
Professor F: So I mean does one of the does it mean one percent and ten percent ? Or does it mean five percent and fifty percent ?
Postdoc C: OK .
Professor F: Uh PhD B: So Professor F: Or Maybe percentage isn't the right word ,
Postdoc C: Just
PhD B: Yeah th
Professor F: but you know how many how many per minute , or You know .
PhD B: Yeah , the the problem is that , nnn , the numbers Ian gave in the paper is just uh , some frame error rate . So that 's that 's not really  What will be effective for for the transcribers , is They have to yeah , in in they have to insure that that 's a real s spurt or something . And but , the numbers Oops . Um Postdoc C: Hmm !
PhD B: Let me think . So the speech the amount of speech that is missed by the detector , for a good meeting , I th is around or under one percent , I would say . But there can be Yeah . For yeah , but there can be more There 's There 's more amount speech uh , more amount of Yeah well , the detector says there is speech , but there is none . So that that can be a lot when when it 's really a breathy channel .
Professor F: But I think that 's less of a problem .
PhD B: Yeah .
Professor F: They 'll just listen . It 's just wasted time .
PhD B: Yeah .
Professor F: And th and that 's for a good meeting . Now what about in a meeting that you said we 've you 've had some more trouble with ?
PhD B: I can't {comment} really hhh , {comment} Tsk . {comment} I don't have really representative numbers , I think . That 's really I I did this on on four meetings and only five minutes of of every meet of of these meetings so , it 's not not that representative , but , it 's perhaps , Fff . Um Yeah , it 's perhaps then it 's perhaps five percent of something , which s uh the the frames speech frames which are which are missed , but um , I can't can't really tell .
Professor F: Right . So I  So i Sometime , we might wanna go back and look at it more in terms of how many times is there a spurt that 's that 's uh , interrupted ?
PhD B: Yeah . Yeah . Yeah .
Professor F: Something like that ?
Postdoc C: The other problem is , that when it when it uh d i on the breathy ones , where you get  breathing , uh , inti indicated as speech .
Professor F: And PhD B: So Postdoc C: And I guess we could just indicate to the transcribers not to encode that if they We could still do the beep file .
Professor F: Yeah again I I think that that is probably less of a problem because if you 're if there 's  If if a if a word is is split , then they might have to listen to it a few times to really understand that they can't quite get it .
Postdoc C: OK . OK .
PhD B: But Postdoc C: OK .
Professor F: Whereas if they listen {nonvocalsound} to it and there 's don't hear any speech I think they 'd probably just listen to it once .
PhD B: Yeah .
Professor F: So there 'd you 'd think there 'd be a a factor of three or four in in , uh , cost function ,
Postdoc C: OK .
Professor F: you know , between them or something .
PhD B: Yeah , so but I think that 's n that really doesn't happen very often that that that a word is cut in the middle or something . That 's that 's really not not normal .
Professor F: So so what you 're saying is that nearly always what happens when there 's a problem is that is that uh , there 's some uh , uh nonspeech that uh that is b interpreted as speech .
PhD B: That is marked as speech . Yeah . Yeah .
Professor F: Well then , we really should just send the stuff .
Postdoc C: That would be great .
Professor F: Right ? Because that doesn't do any harm .
PhD B: Yeah , it 's Professor F: You know , if they they hear you know , a dog bark and they say what was the word , they {comment} you know , they PhD B: Yeah , I als I Professor F: Ruff ruff !
PhD B: Yeah I also thought of there there are really some channels where it is almost {comment} um , only bre breathing in it . And to to re - run 's
Professor F: Yeah ?
PhD B: Eh , um . Yeah . I 've got a a P - a method with loops into the cross - correlation with the PZM mike , and then to reject everything which which seems to be breath .
Professor F: Uh - huh .
PhD B: So , I could run this on those breathy channels , and perhaps throw out Grad A: That 's a good idea .
Postdoc C: Wow , that 's a great idea .
Professor F: Yeah . But I think I th Again , I think that sort of that that would be good ,
PhD B: Yeah .
Professor F: and what that 'll do is just cut the time a little further .
PhD B: Yeah .
PhD D: Mm - hmm .
Professor F: But I think none of this is stuff that really needs somebody doing these these uh , uh , explicit markings .
PhD D: Yeah .
Postdoc C: Excellent . Oh , I 'd be delighted with that , I I was very impressed with the with the result . Yeah .
Professor F: Yeah , cuz the other thing that was concerning me about it was that it seemed kind of specialized to the EDU meeting , and and that then when you get a meeting like this or something ,
PhD B: Yeah .
Professor F: and  and you have a b a bunch of different dominant speakers
Postdoc C: Oh yeah , interesting .
Professor F: you know , how are you gonna handle it .
Postdoc C: Oh yeah .
Professor F: Whereas this sounds like a more general solution
Postdoc C: Oh yeah , I pr I much prefer this ,
Professor F: is Postdoc C: I was just trying to find a way Cuz I I don't think the staggered mixed channel is awfully good as a way of handling overlaps .
Professor F: Yeah . Uh - huh .
Postdoc C: But but uh PhD D: Well good . That that really simplifies thing then .
Postdoc C: Yeah .
PhD D: And we can just , you know , get the meeting , process it , put the beeps file , send it off to IBM .
Postdoc C: Mm - hmm .
PhD D: You know ?
PhD B: Yeah .
PhD D: With very little work on our side .
PhD B: Process it , hear into it . I would PhD D: Do what ?
PhD B: Um , listen to it , and then Grad A: Or at least sample it .
PhD B: Yeah .
PhD D: Well , sample it .
PhD B: Yeah .
PhD D: Sample it .
Professor F: I I would just use some samples ,
PhD B: Yeah . Yeah .
Professor F: make sure you don't send them three hours of " bzzz " {comment} or something .
PhD D: Yeah .
PhD B: No .
PhD D: Yeah . Right .
PhD B: That won't be good .
Postdoc C: Yeah .
PhD D: Yeah . Yeah that would be very good .
PhD B: Yeah .
PhD D: And then we can you know Professor F: Yeah .
PhD D: That 'll oughta be a good way to get the pipeline going .
Postdoc C: Oh , I 'd be delighted . Yeah .
PhD B: And there 's there 's one point which I {comment} uh  yeah , which which I r we covered when I when I r listened to one of the EDU meetings ,
Professor F: Great .
PhD B: and that 's that somebody is playing sound from his laptop .
Grad A: Uh - huh
PhD B: And i the speech - nonspeech detector just assigns randomly the speech to to one of the channels , so . Uh - I haven't - I didn't think of of s of this before ,
Grad A: What can you do ?
PhD B: but what what shall we do about s things like this ?
Postdoc C: Well you were suggesting You suggested maybe just not sending that part of the meeting .
Grad A: Yep . Mmm .
Postdoc C: But PhD B: But , sometimes the  the the laptop is in the background and some somebody is is talking , and , that 's really a little bit confusing , but Grad A: It 's a little bit confusing .
Professor F: That 's life .
PhD B: Yeah .
Grad A: I mean , {comment} what 're we gonna do ?
PhD B: Yeah .
Grad A: Even a hand - transcription would PhD B: OK .
Postdoc C: Do you Professor F: Yeah .
Grad A: a hand - transcriber would have trouble with that .
PhD B: Yeah ,
Grad A: So .
PhD B: that 's that 's a second question , " what what will different transcribers do with with the laptop sound ? "
Postdoc C: Would you would Professor F: What was the l what was the laptop sound ?
Postdoc C: Yeah , go ahead .
Professor F: I mean was it speech ,
PhD B: Yeah .
Professor F: or was it PhD B: It 's speech .
Professor F: Great .
Postdoc C: Well , so I mean So my standard approach has been if it 's not someone close - miked , then , they don't end up on one of the close - miked channels . They end up on a different channel . And we have any number of channels available ,
Professor F: Uh - huh .
PhD B: Yeah .
Postdoc C: I mean it 's an infinite number of channels .
PhD B: But ,
Postdoc C: So just put them on some other channel .
PhD B: when thi when this is sent to to the I M - eh , I B M transcribers , I don't know if if they can tell that 's really Postdoc C: Yeah , that 's right .
Grad A: Yeah cuz there will be no channel on which it is foreground .
PhD B: Yeah . Yeah .
Grad A: Uh Postdoc C: Well , they have a convention , in their own procedures , which is for a background sound .
Grad A: Right , but , uh , in general I don't think we want them transcribing the background , cuz that would be too much work .
PhD B: Yeah .
Grad A: Right ? For it because in the overlap sections , then they 'll
PhD D: Well I don't think Jane 's saying they 're gonna transcribe it , but they 'll just mark it as being there 's some background stuff there ,
Grad A: But that 's gonna be all over the place .
Postdoc C: Yeah .
PhD D: right ?
Grad A: How w how will they tell the difference between that sort of background and the dormal normal background of two people talking at once ?
PhD B: Yeah .
Postdoc C: Oh , I think I think it 'd be easy to to say " background laptop " .
Grad A: How would they know that ?
PhD D: But wait a minute , why would they treat them differently ?
PhD B: Yeah .
Postdoc C: Well because one of them Grad A: Because otherwise it 's gonna be too much work for them to mark it . They 'll be marking it all over the place .
PhD B: Yeah .
Postdoc C: Oh , I s background laptop or , background LT  wouldn't take any time .
Grad A: Sure , but how are they gonna tell bet the difference between that and two people just talking at the same time ?
Postdoc C: And PhD B: Yeah .
Postdoc C: Oh , you can tell . Acoustically , can't you tell ?
PhD B: It 's really good sound , so Postdoc C: Oh is it ? Oh !
Professor F: Well , I mean , isn't there a category something like uh , " sounds for someone for whom there is no i close mike " ?
PhD B: Yeah that would be very important ,
Grad A: But how do we d how do we do that for the I B M folks ?
Postdoc C: Yeah .
PhD B: yeah .
Grad A: How can they tell that ?
PhD D: Well we may just have to do it when it gets back here .
Grad A: Yes , that 's my opinion as well .
PhD B: Yeah .
Grad A: So we don't do anything for it with it .
Postdoc C: OK .
PhD D: Yeah .
Postdoc C: That sounds good .
Grad A: And they 'll just mark it however they mark it ,
Postdoc C: That sounds good .
PhD D: Yeah .
Grad A: and we 'll correct it when it comes back .
PhD B: So th
Professor F: Yeah .
PhD B: there was a category for @ @ {comment} speech .
Postdoc C: OK .
Grad A: Yeah , the default .
Postdoc C: Yeah , s a
Grad A: No , not default .
PhD B: OK .
Postdoc C: Well , as it comes back , we have a uh when we can use the channelized interface for encoding it , then it 'll be easy for us to handle .
PhD B: Yeah .
Postdoc C: But  but if if out of context , they can't tell if it 's a channeled speak uh , you know , a close - miked speaker or not , then that would be confusing to them .
PhD B: OK .
Grad A: Right .
PhD B: OK .
Postdoc C: I don't know , I it doesn't I don't Either way would be fine with me , I don't really care .
Professor F: Yeah . So . Shall we uh , do digits and get out of here ?
Grad A: Yep .
Postdoc C: I have o I have one question . Do you think we should send the um that whole meeting to them and not worry about pre - processing it ?
Professor F: Yes ma '
Postdoc C: Or Uh , what I mean is we we should leave the part with the audio in the uh , beep file that we send to IBM for that one , or should we start after the that part of the meeting is over in what we send .
Professor F: Which part ?
PhD B: With Postdoc C: So , the part where they 're using sounds from their from their laptops .
PhD B: with the laptop sound , or ? just Postdoc C: w If we have speech from the laptop should we just uh , excise that from what we send to IBM , or should we i give it to them and let them do with it what they can ?
PhD D: I think we should just it it 's gonna be too much work if we hafta worry about that I think .
Postdoc C: OK , that 'd be nice to have a a uniform procedure .
PhD D: Yeah , I think if we just m send it all to them . you know .
Grad A: Worry about it when we get back .
Postdoc C: Good . And see how well they do .
PhD D: Let Yeah , worry about it when we get back in .
Postdoc C: And give them freedom to  to indicate if it 's just not workable .
Professor F: Yeah .
Postdoc C: Yeah ,
PhD D: Yeah .
Postdoc C: OK ,
Professor F: Yeah .
Postdoc C: excellent .
Professor F: Cuz , I wouldn't don't think we would mind having that transcribed , if they did it .
Grad A: I think PhD D: Yeah , e
Grad A: As I say , we 'll just have to listen to it and see how horrible it is .
Postdoc C: Yeah , yeah .
PhD B: Yeah .
Grad A: Sample it , rather .
Postdoc C: OK . Alright .
PhD B: I think that that will be a little bit of a problem
PhD D: Yeah .
Postdoc C: That 's great .
PhD B: as it really switches around between two different channels , I think .
Grad A: Mm - hmm , and and they 're very it 's very audible ? on the close - talking channels ?
PhD B: What what I would Yeah .
Grad A: Oh well . I mean , it 's the same problem as the lapel mike .
Professor F: Yeah .
PhD B: Yeah .
Grad A: But Postdoc C: Oh , interesting .
PhD B: Comparable , yeah .
Professor F: Yeah .
PhD B: OK .
Postdoc C: OK , alright . Digits .
Professor F: Let 's do digits .
Postdoc C: OK , so we read the transcript number first , right ?
Grad A: Are we gonna do it altogether or separately ?
PhD B: So What time is it ?
Professor F: Uh , why don't we do it together ,
Postdoc C: Uh , quarter to four .
PhD B: Oh , OK .
Professor F: that 's that 's a nice fast way to do it .
Postdoc C: Mm - hmm .
Professor F: One , two , three , go !
Postdoc C: It 's kind of interesting if there 're any more errors in these , than we had the first set .
Grad A: Nnn , yeah , I think there probably will be .
PhD B: Yeah .
PhD D: Do you guys plug your ears when you do it ?
Grad A: I do .
PhD B: No .
Postdoc C: I usually do .
PhD D: I do .
PhD B: I don't .
Postdoc C: I didn't this time .
PhD D: You don't ?
PhD B: No .
Professor F: I haven't been ,
PhD D: How can you do that ?
Professor F: no .
PhD D: I I Professor F: Uh , concentration .
PhD B: Perhaps there are lots of errors in it
PhD D: Gah !
Grad A: Total concentration . Are you guys ready ?
PhD D: You hate to have your ears plugged ?
Professor F: Yeah .
PhD D: Really ?