E: but but uh , it took you something like twelve hours to mark the forty - five minutes , your
G: Twelve minutes .
D: Twelve minutes .
E: s Twelve minutes !
D: Twelve minutes .
D: Twelve .
E: I thought you did forty - five minutes of D: No , forty - five minutes is the is the session ,
D: all the session .
E: Oh , you haven't done the whole session .
B: Oh .
D: Yeah ,
E: This is just twelve minutes .
D: all is the the session .
E: Oh .
D: Tw - twelve hours of work to  to segment eh and label eh twelve minutes from a session of part of f
E: So <comment> let me back up again .
E: So the when you said there were three hundred speaker overlaps ,
D: Yeah .
E: that 's in twelve minutes ?
D: No no no .
D: I I consider all the all the session because eh I I count the nnn the nnn the overlappings marked by by Jane ,
E: Oh , OK .
E: OK .
B: Oh , I see .
D: in in in in the fin in in the forty - five minutes .
E: So it 's three hundred in forty - five minutes ,
E: but you have you have time uh , uh marked twelve minute the the the um overlaps in twelve minutes of it .
D: Yeah .
E: Got it .
G: Well , not just the overlaps , everything .
F: So , can I ask  can I ask whether you found uh , you know , how accurate uh Jane 's uh uh labels were as far as F: you know , did she miss some overlaps ? or did she n ?
D: But , by by the moment , I I don't compare , my my temporal mark with eh Jane , but eh I I want to do it .
D: Because eh eh i per perhaps I have eh errors in the in the marks ,
D: I and if I I compare with eh Jane , it 's probably I I I can correct and and and to get eh eh a more accurately eh eh transcription in the file .
E: Yeah .
G: Well , also Jane Jane was doing word level .
E: Yeah .
G: So we weren't concerned with <comment> exactly when an overlap started and stopped .
D: Yeah .
F: Right . Right .
F: I 'm expect I 'm not expecting D: Well C: Well , not only a word level , but actually
C: I mean , you didn't need to show the exact point of interruption ,
D: No , it 's C: you just were showing at the level of the phrase or the level of the speech spurt , or G: Right .
E: Mm - hmm .
G: Yep .
D: Yeah .
B: Well D: Yeah .
B: Well , yeah , b yeah , I would say time bin .
B: So my my goal is to get words with reference to a time bin , beginning and end point .
C: Yeah .
D: Yeah .
D: Yeah .
C: Right .
D: Yeah .
B: And and sometimes , you know , it was like you could have an overlap where someone said something in the middle ,
B: but , yeah , w it just wasn't important for our purposes to have it that i disrupt that unit in order to have , you know , a the words in the order in which they were spoken ,
D: Yeah .
B: it would have it would have been hard with the interface that we have .
G: Right .
B: Now , my a Adam 's working on a of course , on a revised overlapping interface ,
D: Uh - huh .
D: I I I think It 's it 's a good eh work ,
B: but D: but eh I think we need eh eh more information .
F: No , of course .
F: I expect you to find more overlaps than than Jane
B: Yeah .
G: Always need more for D: No , no . I I have to go to B: Yeah .
F: because you 're looking at it at a much more detailed level .
D: I want eh I wanted to eh compare the the transcription .
G: But if it takes sixty to one E: I have E: Well , I but I have a suggestion about that .
E: Um , obviously this is very , very time - consuming , and you 're finding lots of things
E: which I 'm sure are gonna be very interesting ,
E: but in the interests of making progress , uh might I s
E: how how would it affect your time if you only marked speaker overlaps ?
D: Only .
E: Yes .
E: Do not mark any other events ,
D: Yeah .
E: but only mark speaker D: Uh - huh .
E: Do you think that would speed it up quite a bit ?
D: OK .
D: OK . I I I I w I I wanted to E: Do y do you think that would speed it up ?
E: Uh , speed up your your your marking ?
D: nnn , I don't understand very .
E: It took you a long time to mark twelve minutes .
D: Yeah .
D: Oh , yeah , yeah .
E: Now , my suggestion was for the other thirty - three D: On - only to mark only to mark overlapping zone , but E: Yeah , and my question is , if you did that , if you followed my suggestion , would it take much less time ?
D: Oh ,
D: yeah .
E: Yeah OK .
D: Sure .
D: Yeah sure .
E: Then I think it 's a good idea .
E: Then I think it 's a good idea , because it
D: Sure sure .
D: Sure ,
D: because I I need a lot of time to to put the label or to do that .
D: Yeah .
E: Yeah , I mean , we we know that there 's noise .
G: And
D: Uh - huh .
E: There 's there 's uh continual noise uh from fans and so forth ,
E: and there is uh more impulsive noise from uh taps and so forth
D: Yeah .
E: and and something in between with paper rustling .
E: We know that all that 's there
E: and it 's a g worthwhile thing to study ,
E: but obviously it takes a lot of time to mark all of these things .
D: Yeah .
E: Whereas th i I would think that uh you we can study more or less as a distinct phenomenon the overlapping of people talking .
D: Uh - huh .
D: OK .
E: So . Then you can get the Cuz you need D: OK .
E: If it 's three hundred uh i i it sounds like you probably only have fifty or sixty or seventy events right now that are really D: Yeah .
E: And and you need to have a lot more than that to have any kind of uh even visual sense of of what 's going on , much less any kind of reasonable statistics .
G: Right .
C: Now , why do you need to mark speaker overlap by hand if you can infer it from the relative energy in the G: Well , that 's G: That 's what I was gonna bring up .
C: I mean , you shouldn't need to do this p completely by hand ,
E: Um , OK , yeah . So let 's back up because you weren't here for an earlier conversation .
C: right ?
C: I 'm sorry .
E: So the idea was that what he was going to be doing was experimenting with different measures
E: such as the increase in energy , such as the energy in the LPC residuals , such as E: I mean there 's a bunch of things I mean , increased energy is - is sort of an obvious one .
C: Mm - hmm .
C: In the far - field mike .
E: Yeah .
C: Oh , OK .
E: Um , and uh , it 's not obvious ,
E: I mean , you could you could do the dumbest thing and get get it ninety percent of the time .
E: But when you start going past that and trying to do better , it 's not obvious what combination of features is gonna give you the you know , the right detector .
E: So the idea is to have some ground truth first .
E: And so the i the idea of the manual marking was to say " OK this , i you know , it 's it 's really here " .
A: But I think Liz is saying why not get it out of the transcripts ?
C: What I mean is get it from the close - talking mikes .
E: Uh , yeah .
C: A or ge get a first pass from those ,
E: We t we t w we t we talked about that .
C: and then go through sort of C: It 'd be a lot faster probably to F: And you can G: Yeah , that 's his , uh E: We we we talked about that .
E: s But so it 's a bootstrapping thing and the thing is ,
C: Yeah , I just E: the idea was , i we i i we thought it would be useful for him to look at the data anyway ,
E: and and then whatever he could mark would be helpful ,
C: Right .
E: and we could Uh
E: it 's a question of what you bootstrap from .
E: You know , do you bootstrap from a simple measurement which is right most of the time and then you g do better ,
E: or do you bootstrap from some human being looking at it and then then do your simple measurements , uh from the close - talking mike .
E: I mean , even with the close - talking mike you 're not gonna get it right all the time .
C: Well , that 's what I wonder , because um C: or how bad it is ,
E: Well
G: I 'm working on a program to do that , and C: be um , because that would be interesting
C: especially because the bottleneck is the transcription .
C: Right ?
C: I mean , we 've got a lot more data than we have transcriptions for .
C: We have the audio data ,
E: Yeah .
C: we have the close - talking mike ,
C: so I mean it seems like one kind of project
C: that 's not perfect , but C: um , that you can get the training data for pretty quickly is , you know ,
C: if you infer form the close - talking mikes where the on - off points are of speech ,
E: Right , we discussed that .
C: you know , how can we detect that from a far - field ?
G: And B: Oh .
G: I 've I 've written a program to do that ,
C: OK ,
G: and it , uh C: I 'm sorry I missed the E: It 's OK .
G: and so but it 's it 's doing something very , very simple .
G: It just takes a threshold , based on on the volume ,
C: Uh - huh .
F: Or you can set the threshold low and then weed out the false alarms by hand .
C: Right ,
C: by hand . Yeah .
F: Yeah .
G: um , and then it does a median filter , and then it looks for runs .
G: And , it seems to work ,
G: I 've I 'm sort of fiddling with the parameters , to get it to actually generate something ,
G: and I haven't G: I don't what I 'm working on was working on was getting it to a form where we can import it into the user interface that we have , into Transcriber .
G: And so I told I said it would take about a day .
G: I 've worked on it for about half a day ,
H: I have to go .
G: so give me another half day and I we 'll have something we can play with .
C: OK .
E: See , this is where we really need the Meeting Recorder query stuff to be working ,
E: because we 've had these meetings and we 've had this discussion about this , and I 'm sort of remembering a little bit about what we decided ,
C: Right .
C: I 'm sorry .
C: I just E: but I couldn't remember all of it .
C: It
E: So , I think it was partly that , you know , give somebody a chance to actually look at the data and see what these are like , partly that we have e some ground truth to compare against , you know , when when he he gets his thing going ,
G: But E: uh , and C: Well , it 's definitely good to have somebody look at it .
C: I was just thinking as a way to speed up you know , the amount of E: That was that was exactly the notion that that that we discussed .
B: Mm - hmm .
C: OK .
G: Thanks .
B: Another thing we discussed was um that E: So .
C: It looks good .
C: I 'll be in touch .
C: Thanks .
E: S See ya .
E: Yeah .
B: Was that um there m there was this already a script I believe uh that Dan had written , <comment> that uh handle bleedthrough ,
B: I mean cuz you have this this close you have contamination from other people who speak loudly .
G: Yeah ,
G: and I haven't tried using that .
G: It would probably help the program that I 'm doing to first feed it through that .
G: It 's a cross - correlation filter .
G: So I I haven't tried that , but that If It it might be something it might be a good way of cleaning it up a little .
B: So , some thought of maybe having B: Yeah , having that be a preprocessor and then run it through yours .
G: Exactly . Yep .
E: But but that 's a refinement
B: That 's what we were discussing .
E: and I think we wanna see try the simple thing first ,
E: cuz you add this complex thing up uh afterwards that does something good y y yo you sort of wanna see what the simple thing does first .
G: Yep .
E: But uh , having having somebody have some experience , again , with with uh with marking it from a human standpoint ,
E: we 're I mean , I don't expect Jose to to do it for uh f fifty hours of <comment> of speech ,
E: but I mean we <comment> if uh if he could speed up what he was doing by just getting the speaker overlaps so that we had it , say , for forty - five minutes , then at least we 'd have three hundred examples of it .
D: Yeah . Sure .
D: Sure .
E: And when when uh Adam was doing his automatic thing he could then compare to that and see what it was different .
C: Oh yeah , definitely .
A: You know , I did I did uh something almost identical to this at one of my previous jobs , and it works pretty well .
A: I mean , i almost exactly what you described , an energy detector with a median filter , you look for runs .
A: And uh ,
A: you know , you can G: It seemed like the right thing to do .
A: Yeah . I mean , you you can get y I mean , you get them pretty close .
G: That was with zero literature search .
A: And so I think doing that to generate these possibilities and then going through and saying yes or no on them would be a quick way to to do it .
G: That 's good validation .
A: Yeah .
B: Is this proprietary ?
G: Yeah , do you have a patent on it ?
A: Uh . <comment> No . No .
A: It was when I was working for the government .
E: Oh , then everybody owns it .
E: It 's the people .
B: Well , I mean , is this something that we could just co - opt ,
B: or is it ?
B: No .
A: Nah .
B: OK .
E: Well , i i i he 's pretty close , anyway . I think I think it 's A: Yeah , he 's it it doesn't take a long time .
B: Right .
B: I just thought if it was tried and true , then <comment> and he 's gone through additional levels of of development .
G: Just output .
G: Although if you if you have some parameters like what 's a good window size for the median filter A: Oh ! <comment> I have to remember .
A: I 'll think about it ,
A: and try to remember .
F: And it might be different for government people .
G: That 's alright .
E: Yeah , good enough for government work , as they say .
C: They they A: Di - dif different different bandwidth .
F: They
G: I was doing pretty short , you know , tenth of a second , <comment> sorts of numbers .
F: OK .
E: Uh , I don't know , it if if we want to uh E: So , uh , maybe we should move on to other other things in limited time .
B: Can I ask one question about his statistics ?
B: So so in the tw twelve minutes , um , if we took three hundred and divided it by four , which is about the length of twelve minutes , i Um , I 'd expect like there should be seventy - five overlaps .
E: Yeah .
B: Did you find uh more than seventy - five overlaps in that period , or ?
D: More than ?
B: More than B: How many overlaps in your twelve minutes ?
D: How many ?
D: Eh , not @ @ I
D: Onl - only I I transcribe eh only twelve minutes from the
E: Yeah .
D: but eh I I don't co eh I don't count eh the the overlap .
B: The overlaps .
B: OK .
D: I consider I I The the nnn The the three hundred is eh considered only you your transcription .
D: I have to  to finish transcribing .
D: So .
G: I b I bet they 're more , because the beginning of the meeting had a lot more overlaps than than sort of the middle .
D: Yeah .
G: Middle or end .
D: Yeah .
G: Because i we 're we 're dealing with the Uh , in the early meetings ,
B: I 'm not sure .
G: we 're recording while we 're saying who 's talking on what microphone , <comment> and things like that ,
D: Yeah .
G: and that seems to be a lot of overlap .
D: Yeah .
B: I think it 's an empirical question .
B: I think we could find that out .
D: Yeah .
G: Yep .
B: I 'm I 'm not sure that the beginning had more .
E: So so I was gonna ask , I guess about any any other things that that that either of you wanted to talk about ,
E: especially since Andreas is leaving in five minutes ,
E: that that you wanna go with .
C: Can I just ask about the data ,
C: like very straightforward question is where we are on the amount of data and the amount of transcribed data ,
C: just cuz I 'm C: I wanted to get a feel for that
C: to sort of be able to know what what can be done first
C: and like how many meetings are we recording
E: Right so there 's this this There 's this forty - five minute piece that Jane transcribed .
C: and E: That piece was then uh sent to IBM so they could transcribe so we have some comparison point .
E: Then there 's s a larger piece that 's been recorded and uh put on CD - ROM and sent uh to IBM .
E: Right ?
E: And then we don't know .
C: How many meetings is that ?
G: What 's that ?
C: Like how many E: That was about ten hours , and there was about C: t ten It 's like ten meetings or something ?
G: Yeah , something like that .
C: Uh - huh .
G: And then then we
A: Ten meetings that have been sent to IBM ?
C: And G: Well , I haven't sent them yet because I was having this problem with the missing files .
E: Yeah .
E: Oh .
E: Oh , that 's right , that had those have not been sent .
A: H how many total have we recorded now , altogether ?
E: We 're saying about twelve hours .
G: About twelve by now . Twelve or thirteen .
C: Uh - huh . And we 're recording only this meeting , like continuously
C: we 're only recording this one now ? or ?
E: No .
G: Nope .
E: No , so the the that 's the that 's the biggest one uh , chunk so far ,
C: OK .
A: It was the morning one .
E: but there 's at least one meeting recorded of uh the uh uh natural language guys .
G: Jerry .
C: Do they meet every week ,
E: And then there E: Uh , they do .
C: or every E: w w And we talked to them about recording some more
E: and we 're going to ,
E: uh , we 've started having a morning meeting , today uh i starting a w a week or two ago , on the uh front - end issues ,