B: you can't you can't just look E: Well . are you talking about the fact that the recording software doesn't do time - synchronous ?
E: Is that what you 're referring to ?
E: That seems to me you can do that over the entire file and get a very accurate F: I don't thi I d I don't think that was the issue .
D: I D: yeah , that was sort of a side issue .
F: The issue was that you have to you have have you first have to have a pretty good speech detection on the individual channels .
E: I didn't think so either .
D: And it 's dynamic , so I guess it was more dynamic than some simple models would be able t to D: so so there are some things available ,
D: and I don't know too much about this area
D: where if people aren't moving around much than you could apply them ,
D: and it should work pretty well if you took care of this recording time difference .
E: Right , which should be pretty straight forward .
D: Which a at least is well defined ,
D: and
E: Yeah .
D: um , but then if you add the dynamic aspect of adapting distances , then it wasn't D: I guess it just wasn't something that he could do quickly and not in time for us to be able to do something by two weeks from now ,
D: so .
D: Well less than a week .
D: So um , so I don't know what we can do if anything , that 's sort of worth , you know , a Eurospeech paper at this point .
B: Well , Andreas , how well did it work on the non - lapel stuff ?
E: Yeah . That 's what I was gonna say .
F: I haven't checked those yet .
E: C
F: It 's very tedious to check these .
B: Mmm .
F: Um , we would really need , ideally , a transcriber to time mark the you know , the be at least the beginning and s ends <comment> of contiguous speech .
F: Um ,  and , you know , then with the time marks , you can do an automatic comparison of your of your forced alignments .
B: Because really the the at least in terms of how we were gonna use this in our system was to get an ideal an idea , uh , for each channel about the start and end boundaries .
E: Oh , MNCM .
F: Mm - hmm .
B: We don't really care about like intermediate word boundaries ,
F: No , that 's how I 've been looking at it .
B: so F: I mean , I don't care that the individual words are aligned correctly ,
D: Right .
B: Yeah .
B: Yeah .
F: but you don't wanna , uh , infer from the alignment that someone spoke who didn't .
B: Right , exactly .
F: so , so B: So that 's why I was wondering if it B: I mean , maybe if it doesn't work for lapel stuff , we can just not use that
F: Yeah .
F: I haven't I ha just haven't had the time to , um , do the same procedure on one of the B: and F: so I would need a k I would need a channel that has a speaker whose who has a lot of overlap but s you know , is a non - lapel mike .
F: And , um ,  where preferably , also there 's someone sitting next to them who talks a lot .
E: Hmm !
F: So , I E: So a meeting with me in it .
F: maybe someone can help me find a good candidate and then I would be willing to
B: We c you know what ?
B: Maybe the best way to find that would be to look through these .
F: you know , hand
B: Cuz you can see the seat numbers ,
B: and then you can see what type of mike they were using .
B: And so we just look for , you know , somebody sitting next to Adam at one of the meetings D: Actually y we can tell from the data that we have ,
F: From the insertions , maybe ?
F: fr fr from the D: um , yeah , there 's a way to tell .
D: It might not be a single person who 's always overlapping that person but any number of people ,
F: Right .
D: and , um , if you align the two hypothesis files across the channels , you know , just word alignment , you 'd be able to find that .
D: So so I guess that 's sort of a last D: ther there 're sort of a few things we could do .
D: One is just do like non - lapels if we can get good enough alignments .
D: Another one was to try to get D: somehow align Thilo 's energy segmentations with what we have .
D: But then you have the problem of not knowing where the words are because these meetings were done before that segmentation .
D: But maybe there 's something that could be done .
B: What what is why do you need the , um , the forced alignment for the HLT I mean for the Eurospeech paper ?
D: Well , I guess I I wanted to just do something not on recognition experiments
D: because that 's ju way too early , but to be able to report , you know , actual numbers .
D: Like if we if we had hand - transcribed pe good alignments or hand - checked alignments , then we could do this paper .
D: It 's not that we need it to be automatic .
D: But without knowing where the real words are , in time B: So it was to get it was to get more data and better to to squeeze the boundaries in .
D: To to know what an overlap really if it 's really an overlap , or if it 's just a a a segment correlated with an overlap ,
B: Ah , OK .
B: Yeah .
D: and I guess that 's the difference to me between like a real paper and a sort of , promissory paper .
D: So , um , if we d
D: it might be possible to take Thilo 's output
D: and like if you have , um , like right now these meetings are all ,
E: Ugh !
E: I forgot the digital camera again .
D: um ,
E: Every meeting !
D: you know , they 're time - aligned ,
D: so if these are two different channels and somebody 's talking here and somebody else is talking here , just that word ,
E: Mm - hmm .
D: if Thilo can tell us that there 're boundaries here , we should be able to figure that out
D: because the only thing transcribed in this channel is this word .
D: But , um , you know , if there are things E: Two words .
D: Yeah , if you have two and they 're at the edges , it 's like here and here ,
D: and there 's speech here , then it doesn't really help you ,
D: so , um B: Thilo 's won't put down two separate marks in that case D: Well it w it would , but , um , we don't know exactly where the words are because the transcriber gave us two words in this time bin
E: Thilo 's will . But .
D: and we don't really know ,
A: Well it 's a merging problem .
D: I mean ,
D: yeah it 's A: If you had a if you had a s if you had a script which would A: I 've thought about this ,
D: I mean , if you have any ideas .
A: um , and I 've discussed I 've discussed it with Thilo ,
D: I would A: um , the , I mean , I I in principle I could imagine writing a script which would approximate it to some degree ,
A: but there is this problem of slippage ,
E: Well maybe Maybe that will get enough of the cases to be useful .
A: yeah .
D: Right .
D: I mean , that that would be really helpful .
D: That was sort of another possibility .
E: You know s cuz it seemed like most of the cases are in fact the single word sorts ,
E: or at least a single phrase
F: Mmm .
A: Well they they can be stretched .
E: in most of the bins .
A: I wouldn't make that generalization
D: Yeah .
A: cuz sometimes people will say , " And then I " and there 's a long pause
A: and finish the sentence
A: and and sometimes it looks coherent and and the A: I mean it 's it 's not a simple problem .
A: But it 's really A: And then it 's coupled with the problem that sometimes , you know , with with a fricative you might get the beginning of the word cut off
A: and so it 's coupled with the problem that Thilo 's isn't perfect either .
A: I mean , we 've i th it 's like you have a merging problem plus so merging plus this problem of , uh , not E: Right .
E: Hmm !
A: y i i if the speech - nonspeech were perfect to begin with , the detector , that would already be an improvement ,
A: but that 's impossible , you know , i that 's too much to ask .
D: Right .
E: Yes .
A: And so i and may you know , I mean , it 's A: I think that there always th there would have to be some hand - tweaking ,
A: but it 's possible that a script could be written to merge those two types of things .
A: I 've I 've discussed it with Thilo and I mean A: in terms of not him doing it ,
A: but we we discussed some of the parameters of that
A: and how hard it would be to in principle to write something that would do that .
D: I mean , I guess in the future it won't be as much as an issue if transcribers are using the tightened boundaries to start with ,
D: then we have a good idea of where the forced alignment is constrained to .
A: Well , it 's just , you know , a matter of we had the revolution we had the revolution of improved , uh , interface , um , one month too late ,
E: Oh .
D: So I 'm no I don't know if this
E: Tools .
A: but it 's like , you know , it 's wonderful to have the revolution ,
D: Oh it 's it 's a A: so it 's just a matter of of , you know , from now on we 'll be able to have things channelized to begin with .
D: yeah .
E: Right .
E: And we 'll just have to see how hard that is .
A: Yeah ,
A: that 's right .
E: So so whether the corrections take too much time .
A: That 's right .
E: I was just thinking about the fact that if Thilo 's missed these short segments , that might be quite time - consuming for them to insert them .
D: Yeah .
A: Good point .
D: But he he also can adjust this minimum time duration constraint and then what you get is noises mostly ,
A: Yeah .
E: Spurious .
D: but that might be OK ,
E: It might be easier to delete something that 's wrong than to insert something that 's missing .
D: an
D: Right .
D: And you can also see in the waveform E: What do you think , Jane ?
D: exac
D: yeah .
C: If you can feel confident that what the yeah , that there 's actually something D: Yeah .
E: Yeah .
E: Cuz then then you just delete it , and you don't have to pick a time .
C: that you 're not gonna miss something ,
C: yeah .
D: I think it 's A: Well the problem is I you know I I it 's a it 's a really good question ,
A: and I really find it a pain in the neck to delete things
A: because you have to get the mouse up there on the t on the text line
A: and i and otherwise you just use an arrow to get down A: I mean , i it depends on how lar
A: th there 's so many extra things that would make it one of them harder than the other , or or vice versa .
A: It 's not a simple question .
A: But , you know , I mean , in principle , like , you know , if one of them is easier then to bias it towards whichever one 's easier .
E: Yeah , I guess the semantics aren't clear when you delete a segment ,
E: right ?
E: Because you would say You would have to determine what the surroundings were .
D: You could just say it 's a noise , though , and write , you know , a post - processor will just D: all you have to do is just E: If it 's really a noise .
D: or just say it 's just put " X , " you know , like " not speech " or something ,
D: and then you can get A: I think it 's easier to add than delete , frankly ,
D: Yeah , or
A: because you have to , uh , maneuver around on the on both windows then .
E: To add or to delete ?
A: To delete .
E: OK .
D: Anyways , so I I guess E: That Maybe that 's an interface issue that might be addressable .
E: But I think it 's the semantics that are that are questionable to me ,
A: It 's possible .
E: that you delete something E: So let 's say someone is talking to here , and then you have a little segment here .
E: Well , is that part of the speech ?
E: Is it part of the nonspeech ?
E: I mean , w what do you embed it in ?
D: There 's something nice , though , about keeping , and this is probably another discussion , keeping the stuff that Thilo 's detector detected as possible speech and just marking it as not speech than deleting it .
D: Because then when you align it , then the alignment can you can put a reject model or whatever ,
E: Oh , I see .
E: So then they could just like put E: Oh that 's what you meant by just put an " X " there .
D: and you 're consistent with th the automatic system ,
E: Uh , that 's an interesting idea .
D: whereas if you delete it E: So so all they So that all they would have to do is put like an " X " there .
D: Yeah , or some , you know , dummy reject mod
E: So blank for blank for silence , " S "
E: " S " for speech , " X "
E: " X " for something else .
D: whatever ,
D: yeah .
D: That 's actually a better way to do it
D: cuz the a the forced alignment will probably be more consistent than A: Well , like , I think there 's a complication which is that that you can have speech and noise in s
D: I mean if it 's just as easy ,
D: but A: uh , you know , on the same channel , the same speaker ,
A: so now sometimes you get a ni microphone pop
A: and , uh , I mean , there 're these fuzzy hybrid cases ,
A: and then the problem with the boundaries that have to be shifted around .
A: It 's not a simple not a simple problem .
D: Anyway , quick question , though , at a high level do people think ,
D: let 's just say that we 're moving to this new era of like using the , um , pre - segmented t you know , non - synchronous conversations ,
D: does it make sense to try to take what we have now , which are the ones that , you know , we have recognition on which are synchronous and not time - tightened , and try to get something out of those for sort of purposes of illustrating the structure and the nature of the meetings , or is it better to just , you know , forget that and tr
E: Well , I think we 'll have to , eventually .
D: I mean , it 's E: And my hope was that we would be able to use the forced alignment to get it .
D: Right .
E: But if we can't D: That was everybody 's hope .
E: But if we can't , then maybe we just have to D: And maybe we can for the non - lapel , but
D: is it worth D: if we can't then we can fake it even if we 're we report , you know , we 're wrong twenty percent of the time or ten percent of the time .
E: Well , I 'm thinking E: are you talking about for a paper , or are talking about for the corpus .
D: Uh uh , that 's a good question actually .
E: I mean cuz for the corpus it would be nice if everything were D: Actually that 's a good question
D: because we 'd have to completely redo those meetings , and we have like ten of them now .
E: We wouldn't have to re - do them ,
E: we would just have to edit them .
A: Well , and also , I mean , I still haven't I still haven't given up on forced alignment .
D: No , you 're right ,
D: actually A: I think that when Brian comes , this 'll be uh an interesting aspect to ask him as well b
E: When A: when Brian Kingsbury comes .
E: Oh , Brian .
E: You s I thought you said Ryan .
E: And it 's like , " Who 's Ryan ? "
E: OK .
A: Yeah , good question .
A: Well , Ryan could come .
D: Uh , no , that 's a good point , though ,
D: because for feature extraction like for prosody or something , I mean , the meetings we have now ,
D: it 's a good chunk of data E: Yep .
D: we need to get a decent f
D: OK .
A: That 's what my hope has been ,
D: So we should at least try it even if we can't ,
A: and that 's what that 's what you know , ever since the the February meeting that I transcribed from last year , forced alignment has been on the on the table as a way of cleaning them up later .
D: right ?
E: On the table ,
E: right ?
A: And and so I 'm hopeful that that 's possible .
A: I know that there 's complication in the overlap sections and with the lapel mikes ,
F: There 's F: Yeah .
A: but D: I mean , we might be able , at the very worst , we can get transcribers to correct the cases where D: I mean , you sort of have a good estimate where these places are because the recognition 's so poor .
D: Right ?
D: And so you 're B: Yeah , we were never just gonna go with these as the final alignments .
A: I agree .
D: Yeah .
A: I agree .
B: We were always gonna run them past somebody .
D: So we need some way to push these first chunk of meetings into a state where we get good alignments .
A: Absolutely .
F: I 'm probably going to spend another day or so trying to improve things by , um ,  by using , um , acoustic adaptation .
F: Um , the  Right now I 'm using the unadapted models for the forced alignments ,
F: and it 's possible that you get considerably better results if you , uh , manage to adapt the , uh , phone models to the speaker and the reject model to the to to all the other speech .
F: Um , so
B: Could you could you at the same time adapt the reject model to the speech from all the other channels ?
C: That 's what he just said .
E: That 's what he was saying .
F: That 's what I just said .
D: Yeah .
B: Oh , not just the speech from that of the other people from that channel ,
F: Right .
D: Right .
B: but the speech from the a actual other channels .
F: Oh , oh , I see .
F: Um ,
E: I don't think so .
C: Oh .
E: I don't think that would work ,
F: No , it E: right ?
E: Because you 'd E: A lot of it 's dominated by channel properties .
F: th
F: Exactly .
D: But what you do wanna do is take the , even if it 's klugey , take the segments the synchronous segments , the ones from the HLT paper , where only that speaker was talking .
F: So you want to u
D: Use those for adaptation ,
D: cuz if you if you use everything , then you get all the cross - talk in the adaptation , and it 's just sort of blurred .
F: That 's a good point .
F: Yep .
B: If you D: And that we know , I mean , we have that .
D: And it 's about roughly two - thirds , I mean , very roughly averaged .
F: Yeah .
D: That 's not completely negligible .
F: Mm - hmm .
D: Like a third of it is bad for adaptation or so .
E: Cool .
E: I thought it was higher than that , that 's pr
D: It really it depends a lot .
D: This is just sort of an overall F: So .
C: Well I know what we 're not turning in to Eurospeech ,
C: a redo of the HLT paper .
E: Right .
C: That I don't wanna do that ,
E: Yeah , I 'm doing that for AVIOS .
C: but .
D: Yeah .
D: But I think we 're oh , Morgan 's talk went very well , I think .
C: Bleep .
E: Uh , " bleep " .
E: Yeah , really .
D: I think Morgan 's talk went very well it woke A: Excellent .
D: you know , it was really a well presented and got people laughing F: Some good jokes in it ?
A: Yeah .
E: Especially the batteried meter popping up ,
E: that was hilarious .
D: Yeah .
E: Right when you were talking about that .
C: You know , that wa that was the battery meter saying that it was fully charged ,
E: It 's full .
E: Yeah .
C: yeah .
A: You said , " Speaking about energy " , or something .
E: But that was funny .
C: Yeah .
E: He he he was onto the bullet points about talking about the you know the little hand - held , and trying to get lower power and so on ,
A: That was very nice .
F: Po - low power
E: and Microsoft pops up a little window saying " Your batteries are now fully charged . "
A: That 's great .
C: Yeah , yeah , yeah .
E: I 'm thinking about scripting that for my talk , you know , put put a little script in there to say " Your batteries are low " right when I 'm saying that .
C: Yeah .
C: Yeah .
C: No I mean , i in in your case , I mean , you were joking about it , but , I mean , your case the fact that your talking about similar things at a couple of conferences , it 's not C: these are conferences that have d really different emphases .
C: Whereas HLT and and Eurospeech , pretty pretty pretty similar , so I I I can't see really just putting in the same thing ,
E: Are too close ,
E: yeah .
D: No , I d I don't think that paper is really C: but D: the HLT paper is really more of a introduction - to - the - project paper , and , um C: Yeah .
E: Yeah , for Eurospeech we want some results
E: if we can get them .
D: Well , yeah , it it 's probably wouldn't make sense ,
C: Or some or some D: but C: I mean , I would see Eurospeech if we have some Eurospeech papers , these will be paper p p uh , submissions .
C: These will be things that are particular things ,
C: aspects of it that we 're looking at , rather than , you know , attempt at a global paper about it .