F: Um , um , the I I 'm really very for I 'm extremely fortunate with the people who , uh , applied and who are transcribing for us .
F: They are , um , um , uh really perceptive and very , um F: and I 'm not just saying that cuz they might be hearing this .
A: Cuz they 're gonna be transcribing it in a few days .
F: No , they 're super . They 're the they very quick .
E: OK . Turn the mikes off and let 's talk .
F: Yeah , I know . I am I 'm serious .
F: They 're just super .
F: So I , um , e you know , I I brought them in and , um , trained them in pairs
F: because I think people can raise questions F: you know , i i the they think about different things
A: That 's a good idea .
F: and they think of different F: and um ,
F: I trained them to , uh , f on about a minute or two of the one that was already transcribed .
F: This also gives me a sense of F: You know , I can I can use that later , with reference to inter - coder reliability kind of issues .
F: But the main thing was to get them used to the conventions
F: and , you know , the idea of the th th the size of the unit versus how long it takes to play it back
F: so these th sort of calibration issues .
F: And then , um , I just set them loose
F: and they 're F: they all have e a already background in using computers .
F: They 're , um they 're trained in linguistics .
A: Good .
F: They got G: Uh - huh .
A: Oh , no .
A: Is that good or bad ?
F: Well , they they 're very perce
F: they 'll So one of them said " well , you know , he really said " n " ,
F: not really " and " ,
D: Yeah .
F: so what  what should I do with that ? "
D: Yeah .
F: And I said , " well for our purposes ,
A: Yeah .
G: Yeah .
F: I do have a convention . If it 's an a noncanonical p "
F: That one , I think we you know , with Eric 's work , I sort of figure we we can just treat that as a variant .
G: OK .
F: But I told them if if there 's an obvious speech error , uh , like I said in one thing ,
G: Yes .
F: and I gave my my example , like I said , " microfon " in instead of " microphone " .
F: Didn't bother F: I knew it when I said it .
F: I remember s thinking " oh , that 's not correctly pronounced " .
F: But it but I thought it 's not worth fixing
F: cuz often when you 're speaking everybody knows what what you mean .
A: You 'll self - repair .
A: Yeah .
C: Yeah .
F: But I have a convention that if it 's obviously a noncanonical pronunciation a speech error with you know , wi within the realm of resolution that you can tell in this native English American English speaker , you know that I didn't mean to say " microfon . "
F: Then you 'd put a little tick at the beginning of the word ,
G: Yeah .
F: and that just signals that , um , this is not standard ,
F: and then in curly brackets " pron <nonvocalsound> error " .
F: And , um , and other than that , it 's w word level .
F: But , you know , the fact that they noticed , you know , the " nnn " . " He said " nnn " , not " and " .
F: What shall I do with that ? "
F: I mean , they 're very perceptive .
F: And and s several of them are trained in IPA .
F: C they really could do phonetic transcription if if we wanted them to .
G: Mm - hmm .
G: Right . Well  Well , you know , it might be something we 'd wanna do with some , uh , s small subset of the whole thing .
A: Hmm .
A: Where were they when we needed them ?
F: I think G: We certainly wouldn't wanna do it with everything .
F: And I 'm also thinking these people are a terrific pool .
F: I mean , if , uh so I I told them that , um , we don't know if this will continue past the end of the month
G: Uh - huh .
F: and I also F: m I
F: think they know that the data p source is limited
F: and I may not be able to keep them employed till the end of the month
F: even , although I hope to .
G: The other thing we could do , actually , uh , is , uh , use them for a more detailed analysis of the overlaps .
F: And F: Oh , that 'd be so super .
F: They would be so s so terrific .
G: Right ?
A: I mean , this was something that we were talking about .
A: We could get a very detailed overlap if they were willing to transcribe each meeting four or five times .
A: Right ?
A: One for each participant .
A: So they could by hand G: Well , that 's one way to do it .
A: Yeah .
G: But I 've been saying the other thing is just go through it for the overlaps .
A: Yeah .
F: Mm - hmm , that 's right .
G: Right ?
F: And with the right in interface G: Given that y and and do so instead of doing phonetic , uh , uh , transcription for the whole thing ,
G: which we know from the Steve 's experience with the Switchboard transcription is , you know , very , very time - consuming .
D: Yeah .
G: And  and you know , it took them I don't know how many months to do to get four hours .
G: And so that hasn't been really our focus .
G: Uh , we can consider it .
G: But , I mean , the other thing is since we 've been spending so much time thinking about overlaps is is maybe get a much more detailed analysis of the overlaps .
D: Yeah .
F: Mm - hmm .
G: But anyway , I 'm I 'm open to c our consideration .
F: That 'd be great .
G: I I don't wanna say that by fiat .
D: Hmm .
G: I 'm open to every consideration of what are some other kinds of detailed analysis that would be most useful .
F: Yeah .
G: And , uh , uh ,
F: Mm - hmm .
D: Hmm .
G: I I I think this year we we actually , uh , can do it .
F: Oh , wonderful .
G: It 's a we have we have due to @ @ <comment> variations in funding we have we seem to be doing , uh , very well on m money for this this year ,
G: and next year we may have have much less .
G: So I don't wanna hire a A: Is you mean two thousand one ?
A: Calendar year
A: or ?
G: Uh , I mean , calendar year two thousand one .
A: OK .
G: Yeah . So it 's uh , it 's we don't wanna hire a bunch of people , a long - term staff ,
A: Full - time .
F: Mm - hmm . Yeah .
A: Yeah .
G: because the the funding that we 've gotten is sort of a big chunk for this year .
G: But having temporary people doing some specific thing that we need is actually a perfect match to that kind of , uh , funding .
F: Wonderful .
F: And then school will start in in the sixt on the sixteenth .
D: Yeah .
G: So .
F: Some of them will have to cut back their hours at that point .
G: Yeah .
E: Are they working full - time now ,
E: or ?
F: But <nonvocalsound> Some of them are .
F: Yeah .
A: Wow .
F: Well , why do I wouldn't say forty - hour weeks .
F: No .
F: But what I mean is F: Oh , I shouldn't say it that way
F: because <nonvocalsound> that does sound like forty - hour weeks .
F: No .
F: I th I I would say they 're probably <nonvocalsound> they don't have o they don't have other things that are taking away their time .
A: I don't see how someone could do forty hours a week on transcription .
E: Hmm .
F: But <nonvocalsound> it 's F: you can't .
G: Yeah . Yeah .
F: No . You 're right .
F: It 's i it would be too taxing .
F: But , um , they 're putting <nonvocalsound> in a lot of G: Yeah .
F: And and I checked them over .
G: I F: I I I haven't checked them all ,
F: but just spot - checking .
F: They 're fantastic .
G: I remember when we were transcribing BeRP , uh , uh , uh , Ron Kay , uh , volunteered to to do some of that .
A: I think it would be G: And , he was the first first stuff he did was transcribing Chuck .
G: And he 's saying " You you know , I always thought Chuck spoke really well . "
F: Yeah . Yeah .
F: Well , you know , and I also thought , y Liz has this , eh , you know , and I do also , this this interest in the types of overlaps that are involved .
F: These people would be <nonvocalsound> great choices for doing coding of that type if we wanted ,
A: We 'd have to mark them .
F: or
G: Mm - hmm .
F: whatever . So , um .
D: Mm - hmm .
G: Yeah .
A: I think it would also be interesting to have , uh , a couple of the meetings have more than one transcriber do ,
F: Mm - hmm .
A: cuz I 'm curious about inter - annotator agreement .
D: Yeah .
F: OK .
F: Yeah .
F: Th - that 'd be I think that 's a a good idea .
G: Yeah .
F: You know , there 's also , the e In my mind ,
F: I think A An - Andreas was leading to this topic ,
F: the idea that , um , we haven't yet seen the the type of transcript that we get from IBM ,
F: and it may just be , you know , pristine .
F: But on the other hand , given the lesser interface F: Cuz this is , you know we 've got a good interface ,
F: we 've got great headphones , m
F: um G: It could be that they will uh theirs will end up being a kind of fir first pass or something .
F: Something like that .
G: Maybe an elaborate one ,
G: cuz again they probably are gonna do these alignments ,
G: which will also clear things up .
F: That 's that 's true .
F: Al - although you have to s Don't you have to start with a close enough approximation <nonvocalsound> of the of the verbal part <nonvocalsound> to be able to ?
G: Well , tha that 's that 's debatable .
G: Right ?
G: I mean , so the so the argument is that if your statistical system is good it will in fact , uh , clean things up .
F: OK .
G: Right ?
F: OK .
G: So it it 's got its own objective criterion .
D: Yeah .
G: And , uh , so in principle you could start up with something that was kind of rough G: I mean , to give an example of , um , something we used to do , uh , at one point , uh , back back when Chuck was here
G: in early times ,
G: is we would take ,
G: um , da take a word and , uh , have a canonical pronunciation
G: and , uh , if there was five phones in a word , you 'd break up the word , uh , into five equal - length pieces
G: which is completely gross .
A: Wrong .
G: Right ?
D: Yeah .
G: I mean , th the timing is off all over the place in just about any word .
F: Mm - hmm .
F: OK .
G: But it 's O K .
G: You start off with that and the statistical system
G: then aligns things ,
G: and eventually you get something that doesn't really look too bad .
F: Oh , excellent .
F: OK .
G: So so I think using a a good aligner , um , actually can can help a lot .
G: Um . But , uh ,
G: you know , they both help each other .
G: If you have a if you have a better starting point , then it helps the aligner .
G: If you have a good alignment , it helps the , uh , th the human in in taking less time to correct things .
G: So so F: OK .
F: Excellent .
F: I guess there 's another aspect , too ,
F: and I don't know F: uh , this this is very possibly a different , uh , topic .
F: But , <nonvocalsound> uh , just let me say with reference to this idea of , um , higher - order organization within meetings .
F: So like in a F: you know , the topics that are covered during a meeting with reference to the other , uh , uses of the data ,
G: Mm - hmm .
F: so being able to find where so - and - so talked about such - and - such ,
F: then , um , um F: e I mean , I I I did sort of a  a rough pass <nonvocalsound> on encoding , like , episode - like level things on the , uh , transcribed meeting G: Mm - hmm .
F: already transcribed meeting .
G: Mm - hmm .
F: And I don't know if , um F: where <nonvocalsound> that i if that 's something that we wanna do with each meeting ,
F: sort of like a , um F: it 's like a manifest , when you get a box full of stuff ,
G: Mm - hmm .
F: or or if that 's , um F: I mean , i I I don't know what uh , level of detail would be most useful .
F: I don't know i if that 's something that I should do when I look over it , or if we want someone else to do , or whatever .
G: Mm - hmm .
F: But this issue of the contents of the meeting
F: in an outline form .
F: OK .
G: Yeah .
G: Meaning really isn't my thing .
G: Um A: I think it just whoever is interested can do that .
A: I mean , so if someone wants to use that data F: OK .
G: We 're running a little short here .
G: We , uh , uh , cou trying to F: That 's fine .
F: I 'm finished .
G: eh , was p Well , you know , the thing I 'm concerned about is we wanted to do these digits
G: and and I haven't heard , uh , from Jose yet .
F: Oh , yeah .
F: Oh , yes .
G: So F: Mm - hmm .
D: OK . What do you want ?
G: Uh A: We could skip the digits .
A: We don't have to read digits each time .
G: Uh G: I I I think it you know , another another bunch of digits .
G: More data is good .
A: OK .
G: So so I 'd like to do that .
D: Yeah . Sure .
G: But I think , do you , maybe ,
G: eh ?
G: Did you prepare some whole thing you wanted us just to see ?
G: Or what was that ?
D: Yeah . It 's it 's prepared .
G: Yeah .
G: Uh , how long a ?
F: Oh , k Sorry .
D: I I think it 's it 's fast ,
D: because , uh , I have the results , eh , of the study of different energy without the law length .
D: Eh , um , eh ,
D: in the in the measurement , uh , the average , uh , dividing by the by the , um , variance .
G: Yeah .
D: Um , I th i
D: the other , uh the the last w uh , meeting D: eh , I don't know if you remain
D: we have problem to with the  with with the parameter D: with the representations of parameter ,
G: Yes .
D: because the the valleys and the peaks in the signal , eh , look like , eh , it doesn't follow to the to the energy in the signal .
G: Right .
D: And it was a problem , uh , with the scale .
D: Eh , the scale .
A: With what ?
F: Scale .
A: Scale .
D: Eh , and I I change the scale and we can see the the variance .
G: OK .
G: But the bottom line is it 's still not , uh , separating out very well .
D: Yeah .
G: Right ?
D: Yeah .
G: OK .
D: The distribution the distribution is is similar .
G: So that 's G: that 's that 's enough then .
G: OK .
D: Yeah .
G: No , I mean , that there 's no point in going through all of that if that 's the bottom line , really .
D: Yeah .
F: Mm - hmm .
G: So , I I think we have to start D: Yeah .
G: Uh , I mean , there there 's two suggestions , really ,
G: which is , uh what we said before is that ,
D: Mmm ,
D: yeah .
G: um ,
G: it looks like ,
G: at least that you haven't found an obvious way to normalize
G: so that the energy is anything like a reliable , uh , indicator of the overlap .
D: Yeah .
G: Um , I I 'm I 'm still a little f think that 's a little funny . These things l @ @ seems like there should be ,
D: Yeah .
D: Yeah .
G: but  but you don't want to keep , uh keep knocking at it if it 's if you 're not getting any any result with that .
G: But , I mean , the other things that we talked about is , uh , pitch - related things and harmonicity - related things ,
D: Yeah .
G: so which we thought also should be some kind of a reasonable indicator .
G: Um G: But , uh ,
G: a completely different tack on it wou is the one that was suggested , uh , by your colleagues in Spain ,
D: Yeah .
G: which is to say , don't worry so much about the , uh , features .
D: Yeah .
G: That is to say , use , you know , as as you 're doing with the speech , uh , nonspeech , use some very general features .
C: Yeah .
G: And , uh , then , uh , look at it more from the aspect of modeling .
D: Yeah .
G: You know , have a have a couple Markov models
D: Yeah .
G: and G: and , uh , try to indi try to determine , you know , w when is th when are you in an overlap , when are you not in an overlap .
D: Hmm .
G: And let the , uh , uh , statistical system determine what 's the right way to look at the data .
G: I I , um ,
D: Yeah .
G: I think it would be interesting to find individual features and put them together .
G: I think that you 'd end up with a better system overall .
G: But given the limitation in time and given the fact that Javier 's system already exists doing this sort of thing ,
D: Yeah .
D: Yeah .
G: uh , but , uh ,
G: its main limitation is that , again , it 's only looking at silences which would D: Yeah .
G: maybe that 's a better place to go .
D: Yeah .
D: Yeah .
G: So .
F: Mm - hmm .
D: I I I think that , eh , the possibility , eh , can be that , eh ,
D: Thilo , eh , working , eh , with a new class ,
G: Mm - hmm .
D: not only , eh , nonspeech and speech , but , eh , in in in the speech class ,
G: Mm - hmm .
D: dividing , eh , speech , eh , of from a speaker and overlapping ,
D: to try to to do , eh , eh , a fast a fast , eh , experiment to to prove that , nnn , this fea eh , general feature , eh , can solve the the the problem ,