H: No , no . We 're talking about close talking , not the not the desktop .
C: Yeah .
D: No , close talk .
B: Are you ?
G: Yes .
H: I sure hope so .
G: Well I th I think so .
H: It 'd be really foolish to do otherwise .
G: Yeah , I I would think that it would be kind of hard to come out with Yeah .
A: I I think it 's sort of hard just playing the you know , just having played the individual files .
A: And I I mean , I know you . I know what your voice sounds like . I 'm sort of familiar with C: Yeah .
A: Uh , it 's pretty hard to follow , especially
H: One side .
G: I agree .
A: there are a lot of words that are so reduced phonetically that make sense when you know what the person was saying before .
E: Yeah ,
E: that 's C: Yeah .
G: And especially since a lot of these A: Uh , it sort of depends where you are in D: Yeah .
H: But I mean we had this we 've had this discussion many times .
H: And the answer is we don't actually know the answer because we haven't tried both ways .
G: Yeah , we have .
G: Well , except I can say that my transcribers use the mixed signal mostly
H: So .
H: Mm - hmm .
A: Mm - hmm .
G: unless there 's a huge disparity in terms of the volume on on the mix .
E: Right .
G: In which case , you know , they they wouldn't be able to catch anything except the prominent <comment> channel ,
H: Right .
G: then they 'll switch between .
H: Well I think that that might change if you wanted really fine time markings .
C: Yeah .
G: But but really G: Well , OK .
H: So .
G: Yeah , well B: But they 're not giving f really fine time markings .
H: Right .
A: Actually , are th so are they giving any time markings ?
A: In other words , if G: Well , I have to ask him .
G: And that 's that 's my email to him . That needs to be forthcoming .
A: Yeah .
A: Cuz A: OK .
G: But but the , uh I did want to say that it 's hard to follow one channel of a conversation even if you know the people ,
G: and if you 're dealing furthermore with highly abstract network concepts you 've never heard of G: So , you know , one of these people was was transcribing the , uh , networks group talk
G: and she said , " I don't really know what a lot of these abbreviations are , "
G: " but I just put them in parentheses cuz that 's the that 's the convention and I just " G: Cuz you know , if you don't know H: Oh , I 'd be curious to to look at that .
E: Just out of curiosity , I mean H: They also all have h heavy accents .
H: The networks group meetings are all C: Yeah .
G: Yeah .
D: Yeah .
E: Given all of the effort that is going on here in transcribing why do we have I B M doing it ?
E: Why not just do it all ourselves ?
B: Um , it 's historical .
B: I mean ,
B: uh , some point ago we thought that uh , it " boy , we 'd really have to ramp up to do that " ,
D: No , just C: Uh - huh .
B: you know , like we just did ,
E: Mm - hmm .
B: and , um , here 's , uh , a a , uh , collaborating institution that 's volunteered to do it .
E: Mm - hmm .
B: So , that was a contribution they could make . Uh in terms of time , money , you know ?
E: Mm - hmm .
B: And it still might be a good thing
E: I 'm just wondering now A: Actu
B: but E: Well , I 'm I 'm wondering now if it 's A: yeah , Mar - Mari asked me the same question as sort of H: Well we can talk about more details later .
A: um , you know ,
A: yeah ,
B: Yeah .
A: whether to B: Yeah .
B: Yeah ,
B: so .
E: Hmm .
B: We 'll see .
B: I mean , I think , th you know , they they they 've proceeded along a bit . Let 's see what comes out of it , and and , uh , you know , have some more discussions with them .
G: Mm - hmm .
G: It 's very a real benefit having Brian involved
G: because of his knowledge of what the how the data need to be used and so what 's useful to have in the format .
H: Yeah .
B: Mm - hmm .
B: Yeah .
H: So , um , Liz , with with the SRI recognizer , <comment> can it make use of some time marks ?
A: OK , so this is a , um ,
H: I I guess I don't know what that means .
A: and actually I should say this is what Don has b uh , he 's already been really helpful in , uh , chopping up these A: So so first of all you A: um , I mean , for the SRI front - end , we really need to chop things up into pieces that are f not too huge .
A: Um , but second of all , uh in general because some of these channels ,
A: I 'd say , like , I don't know , at least half of them probably <comment> on average are g are ha are A: have a lot of cross - ta
A: sorry , some of the segments have a lot of cross - talk .
A: Um , it 's good to get sort of short segments if you 're gonna do recognition ,
A: especially forced alignment .
A: So ,
A: uh , Don has been taking a first stab actually using Jane 's first the fir the meeting that Jane transcribed
A: which we did have some problems with ,
A: and Thilo , uh , I think told me why this was ,
A: but that people were switching microphones around <comment> in the very beginning ,
A: so A: the SRI re
C: No , th Yeah . No . They they were not switching them but what they were they were adjusting them ,
A: and they A: They were not F: Mmm .
H: Adjusting . Oh .
C: so .
A: Yeah .
C: And aft after a minute or so it 's it 's way better .
C: So A: So we have to sort of normalize <comment> the front - end and so forth , and have these small segments .
C: Yep .
A: So we 've taken that and chopped it into pieces based always on your your , um , cuts that you made on the mixed signal .
A: And so that every every speaker has the same cuts .
A: And if they have speech in it we run it through .
A: And if they don't have speech in it we don't run it through .
A: And we base that knowledge on the transcription .
H: On Just on the marks .
H: Right ?
A: Um , the problem is if we have no time marks ,
A: then for forced alignment we actually don't know where you know , in the signal the transcriber heard that word .
A: And so H: Oh , I see ,
H: it 's for the length .
A: I mean , if if it 's a whole conversation and we get a long , uh , you know , par paragraph of of talk ,
H: I see .
A: uh , I don't know how they do this .
A: Um , we actually don't know which piece goes where .
H: I understand .
A: And , um , I think with E: Well you would need to like a forced alignment before you did the chopping ,
E: right ?
A: No , we used the fact that A: So when Jane transcribes them the way she has transcribers doing this ,
H: It 's already chunked .
A: whether it 's with the pre - segmentation or not ,
A: they have a chunk and then they transcribes <comment> the words in the chunk .
A: And maybe they choose the chunk or now they use a pre - segmentation and then correct it if necessary .
G: Mm - hmm .
A: But there 's first a chunk and then a transcription .
A: Then a chunk , then a transcription .
A: That 's great ,
A: cuz the recognizer can H: Uh , it 's all pretty good sized for the recognizer also .
A: Right , and it it helps that it 's made based on sort of heuristics and human ear I think .
G: Good .
G: Oh good .
A: Th - but there 's going to be a real problem ,
A: uh , even if we chop up based on speech silence these , uh , the transcripts from I B M , we don't actually know where the words were ,
H: Right .
A: which segment they belonged to .
A: So that 's sort of what I 'm worried about right now .
E: Why not do a a a forced alignment ?
H: That 's what she 's saying , is that you can't .
A: If you do a forced alignment on something really H: Got uh six sixty minutes of A: well even if you do it on something really long you need to know A: you can always chop it up
A: but you need to have a reference of which words went with which , uh , chop .
G: Now wasn't I thought that one of the proposals was that IBM was going to do an initial forced alignment ,
A: So G: after they H: Yeah , but B: I I think that they are ,
H: We 'll have to talk to Brian .
B: um ,
B: yeah , I 'm sure they will
B: and so we we have to have a dialogue with them about it .
A: Yeah .
B: I mean , it sounds like Liz has some concerns
A: Maybe they have some you know , maybe actually there is some , even if they 're not fine grained , maybe the transcribers B: and A: uh , I don't know , maybe it 's saved out in pieces or or something . That would help .
G: Yeah .
A: But ,
A: uh , it 's just an unknown right now .
G: Yeah . I I need to to write to him .
A: So .
G: I just you know , it 's like I got over - taxed with the timing .
A: Right . But the it is true that the segments I haven't tried the segments that Thilo gave you
A: but the segments that in your first meeting are great .
G: Mm - hmm .
A: I mean , that 's that 's a good length .
G: A good size .
G: Good .
A: Right , cuz G: Well , I I was thinking it would be fun to to uh , uh , if if you wouldn't mind , <comment> to give us a pre - segmentation .
A: y yeah .
C: Yeah .
G: Uh , maybe you have one already of that first m of the meeting that uh , the first transcribed meeting ,
G: the one that I transcribed .
G: Do you have a could you generate a pre - segmentation ?
C: Um , I 'm sure I have some
H: February sixteenth I think .
C: but but that 's the one where we 're , um , trai training on ,
C: so that 's a little bit H: Oh .
G: Oh , I see .
G: Oh , darn .
C: It 's a little bit at odd to G: Of course , of course , of course .
G: Yeah , OK .
C: Yeah .
A: And actually as you get transcripts just , um , for new meetings , <comment> um , we can try G: Uh - huh .
A: I mean , the the more data we have to try the the alignments on , um , the better .
A: So it 'd be good for just to know as transcriptions are coming through the pipeline from the transcribers ,
A: just to sort of we 're playing around with sort of uh , parameters f on the recognizer ,
G: Mm - hmm .
A: cuz that would be helpful .
G: Excellent , good .
A: Especially as you get , en more voices .
A: The first meeting had I think just four people ,
C: Four speakers ,
G: Mm - hmm .
C: yeah .
G: Yeah , Liz and I spoke d w at some length on Tuesday
A: yeah .
G: and and I and I was planning to do just a a preliminary look over of the two that are finished and then give them to you .
A: Oh , great ,
A: great .
G: Yeah .
A: So .
B: That 's great .
B: I guess the other thing ,
B: I I can't remember if we discussed this in the meeting but , uh , I know you and I talked about this a little bit ,
B: there was an issue of , uh ,
B: suppose we get in the , uh ,
B: I guess it 's enviable position although maybe it 's just saying where the weak link is in the chain ,
B: uh , where we we ,
B: uh uh ,
B: we have all the data transcribed
B: and we have these transcribers
B: and we were we 're the B: we 're still a bit slow on feeding B: at that point we 've caught up
B: and the the the , uh , the weak link is is recording meetings .
B: OK ,
B: um ,
B: two questions come , is you know what how how do we B: uh , it 's not really a problem at the moment cuz we haven't reached that point
B: but how do we step out the recorded meetings ?
B: And the other one is , um , uh , is there some good use that we can make of the transcribers to do other things ?
B: So , um , I I can't remember how much we talked about this in this meeting
H: We had spoken with them about it .
B: but there was G: And there is one use that that also we discussed which was when , uh , Dave finishes the G: and maybe it 's already finished G: the the modification to multi - trans which will allow fine grained encoding of overlaps .
G: Uh , then it would be very these people would be very good to shift over to finer grain encoding of overlaps .
G: It 's just a matter of , you know , providing G: So if right now you have two overlapping segments in the same time
G: bin , well with with the improvement in the database in in the , uh , sorry , in the interface , it 'd be possible to , um , you know , just do a click and drag thing , and get the uh , the specific place of each of those , the time tag associated with the beginning and end of of each segment .
B: Right , so I think we talking about three level three things .
A: Mm - hmm .
G: Yeah .
B: One one was uh , we had s had some discussion in the past about some very high level labelings ,
G: The types of overlaps B: types of overlaps , and so forth that that someone could do .
G: Mm - hmm .
B: Second was , uh , somewhat lower level
B: just doing these more precise timings .
B: And the third one is is , uh , just a completely wild hair brained idea that I have
B: which is that , um , if , uh if we have time and people are able to do it , to take some subset of the data and do some very fine grained analysis of the speech .
B: For instance , uh , marking in some overlapping B: potentially overlapping fashion , uh , the value of , uh , ar articulatory features .
G: Yeah .
B: You know , just sort of say , OK , it 's voiced from here to here ,
B: there 's it 's nasal from here to here , and so forth .
B: Um , as opposed to doing phonetic uh , you know , phonemic and the phonetic analysis ,
B: and , uh , assuming , uh , articulatory feature values for those those things .
B: Um , obviously that 's extremely time - consuming .
B: Uh E: That would be really valuable I think .
B: but , uh ,
B: we could do it on some small subset .
G: Also if you 're dealing with consonants that would be easier than vowels ,
G: wouldn't it ?
G: I mean , I would think that that , uh , being able to code that there 's a a fricative extending from here to here would be a lot easier than classifying precisely which vowel that was .
H: Which one .
A: Mmm .
G: I think vowels vowels are I think harder .
B: Mm - hmm .
C: Yeah .
B: Well , yeah ,
B: but I think also it 's just the issue that that when you look at the u w u u when you look at Switchboard for instance very close up there are places where whether it 's a consonant or a vowel you still have trouble calling it a particular phone
G: Mm - hmm .
G: Mm - hmm , OK .
H: Yeah , but but just saying what the B: at that point
B: because it 's you know , there 's this movement from here to here
G: Yeah , I 'm sure .
G: Uh , yeah , I I know .
A: Right .
B: and and and it 's E: You 're saying r sort of remove the high level constraints
B: so I
E: and go bottom - up .
H: Yep , just features .
E: Then just say B: Yeah , describe describe it .
A: Mmm .
B: Now I 'm suggesting articulatory features .
B: Maybe there 's there 's even a better way to do it
B: but it but but that 's , you know , sort of a traditional way of describing these things ,
E: Mm - hmm .
B: um , and uh ,
G: That 's nice .
B: I mean , actually this might be a g neat thing to talk to E: Acoustic features versus psychological categories .
B: Sort of .
G: Yeah .
B: I mean , it 's still E: Yeah .
B: some sort of categories
B: but but something that allows for overlapping change of these things
B: and then this would give some more ground work for people who were building statistical models that allowed for overlapping changes , different timing changes as opposed to just " click ,
B: you 're now in this state , which corresponds to this speech sound " and so on .
E: Mm - hmm . Mm - hmm .
A: So this is like gestural uh , these g
B: Yeah , something like that .
A: Right .
B: I mean , actually if we get into that it might be good to , uh , uh , haul John Ohala into this
A: OK .
B: and ask his his views on it I think .
H: Yeah .
A: Right .
A: But is is the goal there to have this on meeting data ,
G: Excellent .
A: like
A: so that you can do far field studies <comment> of those gestures
A: or um ,
A: or is it because you think there 's a different kind of actual production in meetings <comment> that people use ?
B: No , I think I think it 's for for for that purpose I 'm just viewing meetings as being a a neat way to get people talking naturally .
A: Or ?
B: And then you have i and then and then it 's natural in all senses ,
E: Just a source of data ?
A: I see .
B: in the sense that you have microphones that are at a distance that you know , one might have ,
B: and you have the close mikes ,
B: and you have people talking naturally .
B: And the overlap is just indicative of the fact that people are talking naturally ,
A: Uh - huh .
D: Yeah .
B: right ?
B: So so I think that given that it 's that kind of corpus ,
A: Right .
D: Yeah .
B: if it 's gonna be a very useful corpus
B: um , if you say w OK , we 've limited the use by some of our , uh , uh , censored choices ,
B: we don't have the video , we don't and so forth ,
B: but there 's a lot of use that we could make of it by expanding the annotation choices .
A: Mm - hmm .
B: And , uh , most of the things we 've talked about have been fairly high level ,
B: and being kind of a bottom - up person I thought maybe we 'd , do some of the others .
H: Hmm .
G: It 's a nice balance .
A: Right . Yeah , that would be good .
G: That would be really nice to offer those things with that wide range .
B: Yeah .
A: Right .
B: Yeah
B: and hopefully someone would make use of it .
G: Really nice .
B: I mean , people didn't G: Yeah .
B: uh , I mean , people have made a lot of use of of TIMIT
B: and , uh w due to its markings ,
B: and then the Switchboard transcription thing ,
B: well I think has been very useful for a lot of people .
H: Right .
A: That 's true .
B: So A: I guess I wanted to , um , sort of make a pitch for trying to collect more meetings .