professor g: Alright ! grad a: So , sorry about not professor g: We 're not crashing . postdoc f: I don't know if you 're professor g: Yeah , that 's right . postdoc f: maybe raise the issue of microphone ,  procedures with reference to the cleanliness of the recordings . professor g: OK , transcription , microphone issues postdoc f: And then maybe ask , th  , these guys . The we have great great , p steps forward in terms of the nonspeech - speech pre - segmenting of the signal . phd d: use grad a: but I 'm not sure if that 's of general interest or not . professor g:  phd b: Since ,  since I have to leave as usual at three - thirty , can we do the interesting stuff first ? postdoc f: I beg your pardon ? professor g: Well phd c: Which is ? grad a: What 's the interesting stuff ? postdoc f: I beg your pardon ? phd d: Yeah . professor g: But phd b: Well , I guess the work that 's been done on segmentation would be most phd c: Yeah .  , and , the other thing , which I 'll just say very briefly that maybe relates to that a little bit , which is that , one of the suggestions that came up in a brief meeting I had the other day when I was in Spain with , Manolo Pardo and Javier , Ferreiros , who was here before , was , why not start with what they had before but add in the non - silence boundaries . So , in what Javier did before when they were doing ,  h he was looking for , speaker change points . As a simplification , he originally did this only using silence as , a putative , speaker change point . professor g: And , he did not , say , look at points where you were changing broad sp  , phonetic class , for instance . professor g: And , so one of the things that they were pushing in d in discussing with me is , w why are you spending so much time , on the , feature issue , when perhaps if you sort of deal with what you were using before phd d:  - huh . professor g: and then just broadened it a bit , instead of just ta using silence as putative change point also ? phd d: Nnn , yeah . professor g: So then you 've got you already have the super - structure with Gaussians and H - you know , simple H M Ms and so forth . And you you might So there was a there was a little bit of a a a a difference of opinion because I I thought that it was it 's interesting to look at what features are useful . professor g: But , on the other hand I saw that the they had a good point that , if we had something that worked for many cases before , maybe starting from there a little bit Because ultimately we 're gonna end up with some s su kind of structure like that , phd d: Yeah . professor g: where you have some kind of simple  and you 're testing the hypothesis that , there is a change . Yeah , why don't we do the speech - nonspeech discussion ? postdoc f: Yeah . Do I I hear you you didn't phd c: Speech - nonspeech ? OK . phd c: so , what we basically did so far was using the mixed file to to detect s speech or nonspeech portions in that . phd c: And what I did so far is I just used our old Munich system , which is an  - ba based system with Gaussian mixtures for s speech and nonspeech . And it was a system which used only one Gaussian for silence and one Gaussian for speech . phd c: Adam , Dave , and I , we did , for that dialogue and I trained it on that . They they can use it or ? postdoc f: they they think it 's a terrific improvement . postdoc f: And , y you also did some something in addition which was , for those in which there was , quiet speakers in the mix . phd c: And so I did two mixtures , one for the loud speakers and one for the quiet speakers . grad a: And did you hand - label who was loud and who was quiet , or did you just ? phd c: I did that for for five minutes of one dialogue grad a: Right . phd c: It 's just our our old Munich , loudness - based spectrum on mel scale twenty twenty critical bands and then loudness . phd c: And four additional features , which is energy , loudness , modified loudness , and zero crossing rate . And so I did some some modifications in those parameters , basically changing the minimum minimum length for s for silence to have , er to have ,  yeah to have more or less , silence portions in inserted . grad a: But for overlap I imagine that doesn't work at all , phd c: Yeah . But it it saves so much time the the transcribers professor g:  grad a: Yep . W w we originally we did that professor g: Just phd c: but we saw , when we used it , f for our close - talking microphone , which yeah , for our for our recognizer in Munich we saw that w it 's it 's not it 's not so necessary . professor g: Yeah , I don't think it 's a big deal for this application , phd c: Yeah . But then there 's another thing that also Thilo 's involved with , which is ,  OK , and and also Da - Dave Gelbart .  we ,  regarding the representation of overlaps , because at present , because of the limitations of th the interface we 're using , overlaps are , not being encoded by the transcribers in as complete and , detailed a way as it might be , and as might be desired I think would be desired in the corpus ultimately . postdoc f: So we don't have start and end points at each point where there 's an overlap . So @ @ the limits of the over of of the interface are such that we were at this meeting we were entertaining how we might either expand the the interface or find other tools which already do what would be useful . Because what would ultimately be , ideal in my my view and I think  , I had the sense that it was consensus , is that , a thorough - going musical score notation would be the best way to go . Because you can have multiple channels , there 's a single time - line , it 's very clear , flexible , and all those nice things . So , I spoke I had a meeting with Dave Gelbart on on and he had , excellent ideas on how the interface could be modified to to do this kind of representation . But , he in the meantime you were checking into the existence of already , existing interfaces which might already have these properties .  , I talked with , Munich guys from from Ludwi - Ludwig Maximilians University , who do a lot of transcribing and transliterations . phd c: And they basically said they have they have , a tool they developed themselves and they can't give away , f it 's too error - prone , and had it 's not supported , a a a and professor g: Yeah . phd c: But , Susanne Bur - Burger , who is at se CMU , he wa who was formally at in Munich and w and is now at with CMU , she said she has something which she uses to do eight channels , trans transliterations , eight channels simultaneously , professor g: Excuse me . grad a: Well , maybe we should get it and if it 's good enough we 'll arrange Windows machines to be available . postdoc f: I also wanted to be sure  , I 've I 've seen the this this is called Praat , PRAAT , which I guess means spee speech in Dutch or something . phd c: Yeah , but then I 'm not sure that 's the right thing for us . professor g: The other thing , to keep in mind , we 've been very concerned to get all this rolling so that we would actually have data , postdoc f: Mmm , yeah . professor g: but , I think our outside sponsor is actually gonna kick in postdoc f:   So I don't know if we have a long - term need to do lots and lots of transcribing . I think we had a very quick need to get something out and we 'd like to be able to do some later because just it 's inter it 's interesting . But as far a you know , with with any luck we 'll be able to wind down the larger project . phd b: But you s grad a: What our decision was is that we 'll go ahead with what we have with a not very fine time scale on the overlaps . postdoc f: And and I was just thinking that , if it were possible to bring that in , like , you know , this week , then when they 're encoding the overlaps it would be nice for them to be able to specify when you know , the start points and end points of overlaps . postdoc f: And , so my my goal was w m my charge was to get eleven hours by the end of the month . And it 'll be I 'm I 'm I 'm clear that we 'll be able to do that . postdoc f: I sent it to ,  who did I send that to ? I sent it to a list and I thought I sent it to the e to the local list . postdoc f: You saw that ? So Brian did tell me that in fact what you said , that ,  that our that they are making progress and that he 's going that they 're going he 's gonna check the f the output of the first transcription and and professor g: basically it 's it 's all the difference in the world .  , basically it 's just saying that one of our one of our best people is on it , postdoc f: Yeah . So phd b: But about the need for transcription , postdoc f: Isn't that great ? phd b: don't we didn't we previously decide that the IBM transcripts would have to be checked anyway and possibly augmented ? professor g: So . grad a: Yeah , and Dave Gelbart did volunteer , postdoc f: Good . grad a: and since he 's not here , I 'll repeat it to at least modify Transcriber , which , if we don't have something else that works , I think that 's a pretty good way of going . My approach originally , and I 've already hacked on it a little bit it was too slow because I was trying to display all the waveforms . grad a: That if you just display the mix waveform and then have a user interface for editing the different channels , that 's perfectly sufficient . And and , Dan Ellis 's hack already allows them to be able to display different waveforms to clarify overlaps and things , grad a: No . They can only display one , postdoc f: so that 's already grad a: but they can listen to different ones . postdoc f: Oh , yes , but Well , yes , but what  is that , from the transcriber 's perspective , those two functions are separate . And Dan Ellis 's hack handles the , choice the ability to choose different waveforms from moment to moment . postdoc f:  grad a: The waveform you 're looking at doesn't change . postdoc f: Yeah , but that 's that 's OK , cuz they 're they 're , you know , they 're focused on the ear anyway . postdoc f: the hack to preserve the overlaps better would be one which creates different output files for each channel , grad a: Right . postdoc f: which then would also serve Liz 's request of having , you know , a single channel , separable , cleanly , easily separable , professor g:   Well , holidays may have interrupted things , cuz in in in They seem to want to get absolutely clear on standards for transcription standards and so forth with with us . I just think I told them to contact Jane that , if they had a grad a: Oh , OK . So is it cuz with any luck there 'll actually be a a there 'll be collections at Columbia , collections at at UW  Dan Dan is very interested in doing some other things , grad a: Right . grad a: Well , I think it 's important both for the notation and the machine representation to be the same . postdoc f: N there was also this , email from Dan regarding the speech - non nonspeech segmentation thing . postdoc f: I don't know if , we wanna ,  and Dan Gel - and Dave Gelbart is interested in pursuing the aspect of using amplitude as a a a as a basis for the separation . He was talking he was talking  , we he had postdoc f: Cross professor g: Yeah , cross - correlation . phd c: Cross professor g: I had mentioned this a couple times before , the c the commercial devices that do , voice ,  you know , active miking , postdoc f:  - huh . professor g: So , by doing that , you know , rather than setting any , absolute threshold , you actually can do pretty good , selection of who who 's talking . professor g:  And those those systems work very well , by the way , so people use them in panel discussions and so forth with sound reinforcement differing in in sort of , phd d:  - huh . professor g:  and , those if Boy , the guy I knew who built them , built them like twenty twenty years ago , grad a:  . Cuz there is one thing that we don't have right now and that is the automatic , channel identifier . postdoc f: That that , you know , that would g help in terms of encoding of overlaps . postdoc f: The the transcribers would have less , disentangling to do if that were available . So I think , you know , basically you can look at some p you have to play around a little bit , to figure out what the right statistic is , postdoc f: But . professor g: but you compare each microphone to some statistic based on the on the overall phd c: Yeah . So that , you cou yo grad a: Yeah , although the the using the close - talking I think would be much better . professor g: I just it 'd be If I was actually working on it , I 'd sit there and and play around with it , and and get a feeling for it .  , the the the ,  But , you certainly wanna use the close - talking , as a at least . professor g: I don't know if the other would would add some other helpful dimension or not . What what are the different , classes to to code , the the overlap , you will use ? postdoc f: to code d phd d: What you you postdoc f: so types of overlap ? phd d: Yeah . postdoc f: so at a meeting that wasn't transcribed , we worked up a a typology . postdoc f: And ,  phd d: Look like , you t you explaining in the blackboard ? The ? Yeah ? Yeah . So it i the it 's basically a two - tiered structure where the first one is whether the person who 's interrupted continues or not . And then below that there 're subcategories , that have more to do with , you know , is it , simply backchannel phd d:   postdoc f: or is it , someone completing someone else 's thought , or is it someone in introducing a new thought . And I hope that if we do a forced alignment with the close - talking mike , that will be enough to recover at least some of the time the time information of when the overlap occurred .  , I I I I 've phd b: So who 's gonna do that ? Who 's gonna do forced alignment ? grad a: Well , u  , IBM was going to . grad a: and I imagine they still plan to but but , you know , I haven't spoken with them about that recently . postdoc f: It occurs to me one of my transcribers t told me today that she 'll be finished with one meeting , by professor g:   postdoc f: well , she said tomorrow but then she said you know , but the , you know let 's let 's just , say professor g:   I know these are er , I could send him that if it would be possible , or a good idea or not , to try to do a s forced alignment on what we 're on the way we 're encoding overlaps now . professor g: you know , basically he 's he just studies , he 's a colleague , a friend , and , postdoc f: Yeah ! professor g: they and and , you know , the the organization always did wanna help us . professor g: It was just a question of getting , you know , the right people connected in , who had the time . professor g: So , eh grad a: Is he on the mailing list ? The Meeting Recorder mailing li ? postdoc f: Oh ! grad a: We should add him . phd e: Did something happen , Morgan , that he got put on this , or was he already on it , grad a: Add him . phd e: or ? professor g: No , I , eh , eh , p It it oc I h it 's Yeah , something happened . So , where are we ? Maybe , brief Well , let 's why don't we talk about microphone issues ? postdoc f: Yeah . professor g: That was that was a grad a: so one thing is that I did look on Sony 's for a replacement for the mikes for the head m head - worn ones cuz they 're so uncomfortable . But I think I need someone who knows more about mikes than I do , because I couldn't find a single other model that seemed like it would fit the connector , which seems really unlikely to me . Does anyone , like , know stores or know about mikes who who would know the right questions to ask ? professor g: Oh , I probably would . phd e: You couldn't you couldn't find the right connector to go into these things ? grad a: Yep . When I looked , i they listed one microphone and that 's it phd e: Huh ! grad a: as having that type of connector . Well , let 's look at it together grad a: it seems it seems really unlikely to me that there 's only one . professor g: and postdoc f: And there 's no adaptor for it ? phd c: Yeah . professor g: Who who are we buying these from ? grad a: professor g: That 'd be grad a: I have it downstairs . grad a: And then ,  just in terms of how you wear them  , I had thought about this before .  , when when when you use a product like DragonDictate , they have a very extensive description about how to wear the microphone and so on . grad a: But I felt that in a real situation we were very seldom gonna get people to really do it and maybe it wasn't worth concentrating on . But professor g: Well , I think that that 's that 's a good back - off position . That 's what I was saying earlier , th that , you know , we are gonna get some recordings that are imperfect and , hey , that 's life . But I I think that it it doesn't hurt , the naturalness of the situation to try to have people wear the microphones properly , if possible , grad a:   professor g: because , the natural situation is really what we have with the microphones on the table . professor g: I think , you know , in the target applications that we 're talking about , people aren't gonna be wearing head - mounted mikes anyway . professor g: So this is just for u these head - mounted mikes are just for use with research . professor g: And , it 's gonna make You know , if if An - Andreas plays around with language modeling , he 's not gonna be m wanna be messed up by people breathing into the microphone . professor g: So it 's it 's ,  grad a: Well , I 'll dig through the documentation to DragonDictate and ste s see if they still have the little form . professor g: Right ?  , and any phd b: It 's interesting , I talked to some IBM guys , last January , I think , I was there . phd b: And they said , the breathing is really a a terrible problem for them , to to not recognize breathing as speech . grad a: Well , that 's the It seemed to me when I was using Dragon that it was really microphone placement helped an in ,  an enormous amount . grad a: So you want it enough to the side so that when you exhale through your nose , it doesn't the wind doesn't hit the mike . professor g: I remember when I was when I I I I used , a prominent laboratory 's , speech recognizer about ,  This was , boy , this was a while ago , this was about twelve twelve years ago or something . And , they were they were perturbed with me because I was breathing in instead of breathing out . And they had models for they they had Markov models for br breathing out but they didn't have them for breathing in . Well , what I wondered is whether it 's possible to have to maybe use the display at the beginning grad a: Yeah . postdoc f: to be able to to judge how how correctly  , have someone do some routine whatever , and and then see if when they 're breathing it 's showing . postdoc f: I don't know if the if it 's professor g: I grad a: You can definitely see it . grad a: And so , you know , I 've I 've sat here and watched sometimes the breathing , professor g: I grad a: and the bar going up and down , and I 'm thinking , I could say something , but professor g: I think grad a: I don't want to make people self - conscious . And you can do some , you know , first - order thing about it , which is to have people move it , a away from being just directly in front of the middle phd d: Yeah . postdoc f: Yeah , i professor g: And then , you know , I think there 's not much Because you can't al you know , interfere w you can't fine tune the meeting that much , I think . It just seems like i if something l simple like that can be tweaked and the quality goes , you know , dramatically up , then it might be worth doing . My my feedback from the transcribers is he is always close to crystal clear and and just fan fantastic to phd c: Yeah . postdoc f: I could say something about about the Well , I don't know what you wanna do . professor g: About what ? postdoc f: About the transcribers or anything or ? I don't know . professor g: Well , the other phd b: But , just to to ,  professor g: why don't we do that ? phd b: One more remark , concerning the SRI recognizer . It is useful to transcribe and then ultimately train models for things like breath , and also laughter is very , very frequent and important to to model . phd b: So , grad a: So , phd b: if you can in your transcripts mark grad a: mark them ? phd b: mark very audible breaths and laughter especially , phd c: Mmm . postdoc f: They 're putting Eh , so in curly brackets they put " inhale " or " breath " . Now they 're they 're not being awfully precise , m So they 're two types of laughter that are not being distinguished . postdoc f: One is when sometimes s someone will start laughing when they 're in the middle of a sentence . postdoc f: And and then the other one is when they finish the sentence and then they laugh . So , I I did s I did some double checking to look through  , you 'd need to have extra  e extra complications , like time tags indicating the beginning and ending of of the laughing through the utterance . phd b: It 's not so I don't think it 's ,  postdoc f: And that and what they 're doing is in both cases just saying " curly brackets laughing " a after the unit . phd b: As as long as there is an indication that there was laughter somewhere between two words I think that 's sufficient , phd c: Yeah . phd b: So as long as you can stick a you know , a t a tag in there that that indicates that there was laughter , grad a: Oh , I didn't know that . grad a: That would be a really interesting prosodic feature , postdoc f: Then phd d: Yeah . postdoc f: So , if they laugh between two words , you you 'd get it in between the two words . postdoc f: But if they laugh across three or four words you you get it after those four words . phd b: Well , the thing that you is hard to deal with is whe when they speak while laughing . phd b: But , that 's not as frequent as just laughing between speaking , postdoc f: OK . grad a: So are do you treat breath and laughter as phonetically , or as word models , or what ? phd b: so professor g:  is it ? phd d: Huh . There was a there 's actually a word for  , it 's not just breathing but all kinds of mouth grad a:   grad a: So train a phone in the neural net ? phd b: Same thing ? Yeah . professor g: No grad a: Oh , it does ? phd b: So the so the the mouth noise , word has just a single phone , that is for that . professor g: Right ?  , you could you could say well , let  we now think that laughter should have three sub sub sub - units in the the three states ,  different states . professor g: And then you would have three  , you know , eh , eh , it 's u grad a: Do whatever you want . phd b: And the the pronun the pronunciations the pronunciations are l are somewhat non - standard . phd b: They actually are  , it 's just a single , s  , you know , a single phone in the pronunciation , but it has a self - loop on it , so it can grad a: To go on forever ? phd b: r can go on forever . grad a: And how do you handle it in the language model ? phd b: It 's just a it 's just a word . We also tried , absorbing these  , both laughter and and actually also noise , and ,  phd d: Yeah . We also tried absorbing that into the pause model  , the the the model that that matches the stuff between words . You you did get me to thinking about I I 'm not really sure which is more frequent , whether f f laughing I think it may be an individual thing . grad a: I was noticing that with Dan in the one that we ,  we hand tran hand - segmented , professor g: Yeah . And and one thing that c that we 're not doing , of course , is we 're not claiming to , get be getting a representation of mankind in these recordings . Why don why don't we just since we 're on this vein , why don't we just continue with , what you were gonna say about the transcriptions postdoc f: OK . professor g: and ? postdoc f: the I I 'm really very for I 'm extremely fortunate with the people who , applied and who are transcribing for us . They are ,  really perceptive and very ,  and I 'm not just saying that cuz they might be hearing this . grad a: Cuz they 're gonna be transcribing it in a few days . So I , e you know , I I brought them in and , trained them in pairs because I think people can raise questions grad a: That 's a good idea . postdoc f: you know , i i the they think about different things and they think of different and  , I trained them to , f on about a minute or two of the one that was already transcribed . This also gives me a sense of You know , I can I can use that later , with reference to inter - coder reliability kind of issues . But the main thing was to get them used to the conventions and , you know , the idea of the th th the size of the unit versus how long it takes to play it back so these th sort of calibration issues . And then , I just set them loose and they 're they all have e a already background in using computers . postdoc f: Well , they they 're very perce they 'll So one of them said " well , you know , he really said " n " , not really " and " , phd d: Yeah . postdoc f: so what what should I do with that ? " grad a: Yeah . If it 's an a noncanonical p " That one , I think we you know , with Eric 's work , I sort of figure we we can just treat that as a variant . But I told them if if there 's an obvious speech error , like I said in one thing , professor g: OK . postdoc f: and I gave my my example , like I said , " microfon " in instead of " microphone " . But it but I thought it 's not worth fixing cuz often when you 're speaking everybody knows what what you mean . postdoc 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 . " Then you 'd put a little tick at the beginning of the word , professor g: Yeah . postdoc f: and that just signals that , this is not standard , and then in curly brackets " pron error " . Well Well , you know , it might be something we 'd wanna do with some , s small subset of the whole thing . Where were they when we needed them ? postdoc f: I think professor g: We certainly wouldn't wanna do it with everything .  , if ,  so I I told them that , we don't know if this will continue past the end of the month professor g:  - huh . postdoc f: and I also m I think they know that the data p source is limited and I may not be able to keep them employed till the end of the month even , although I hope to . professor g: The other thing we could do , actually , is , use them for a more detailed analysis of the overlaps . professor g: Right ? grad a: We could get a very detailed overlap if they were willing to transcribe each meeting four or five times . professor g: But I 've been saying the other thing is just go through it for the overlaps . professor g: Right ? postdoc f: And with the right in interface professor g: Given that y and and do so instead of doing phonetic , transcription for the whole thing , phd d: Yeah . professor g: which we know from the Steve 's experience with the Switchboard transcription is , you know , very , very time - consuming . And and you know , it took them I don't know how many months to do to get four hours . But , 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 . professor g: I 'm open to every consideration of what are some other kinds of detailed analysis that would be most useful . professor g: It 's a we have we have due to @ @ variations in funding we have we seem to be doing , very well on m money for this this year , and next year we may have have much less . grad a: Is you mean two thousand one ? professor g: So I don't wanna hire a grad a: Calendar year or ? professor g: calendar year two thousand one . So it 's  , it 's we don't wanna hire a bunch of people , a long - term staff , grad a: Full - time . professor g: because the the funding that we 've gotten is sort of a big chunk for this year . But having temporary people doing some specific thing that we need is actually a perfect match to that kind of , funding . phd e: Are they working full - time now , or ? postdoc f: But Some of them are . But what  is Oh , I shouldn't say it that way because that does sound like forty - hour weeks . I th I I would say they 're probably they don't have o they don't have other things that are taking away their time . professor g: I postdoc f: I I I haven't checked them all , but just spot - checking . grad a: I think it would be professor g: I remember when we were transcribing BeRP , Ron Kay , volunteered to to do some of that . 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 . These people would be great choices for doing coding of that type if we wanted , grad a: We 'd have to mark them . grad a: I think it would also be interesting to have , a couple of the meetings have more than one transcriber do , professor g: Yeah . postdoc f: You know , there 's also , the e In my mind , I think A An - Andreas was leading to this topic , the idea that , we haven't yet seen the the type of transcript that we get from IBM , and it may just be , you know , pristine . But on the other hand , given the lesser interface Cuz this is , you know we 've got a good interface , we 've got great headphones , m  professor g: It could be that they will  theirs will end up being a kind of fir first pass or something . professor g: Maybe an elaborate one , cuz again they probably are gonna do these alignments , which will also clear things up . Al - although you have to s Don't you have to start with a close enough approximation of the of the verbal part to be able to ? professor g: Well , tha that 's that 's debatable . professor g: Right ?  , so the so the argument is that if your statistical system is good it will in fact , clean things up . professor g: And , so in principle you could start up with something that was kind of rough  , to give an example of , something we used to do , at one point , back back when Chuck was here in early times , is we would take , da take a word and , have a canonical pronunciation and , if there was five phones in a word , you 'd break up the word , into five equal - length pieces which is completely gross . professor g: Right ?  , th the timing is off all over the place in just about any word . You start off with that and the statistical system then aligns things , and eventually you get something that doesn't really look too bad . professor g: So so I think using a a good aligner , actually can can help a lot . If you have a good alignment , it helps the , th the human in in taking less time to correct things . I guess there 's another aspect , too , and I don't know  , this this is very possibly a different , topic . So like in a you know , the topics that are covered during a meeting with reference to the other , uses of the data , professor g:   postdoc f: so being able to find where so - and - so talked about such - and - such , then ,  e  , I I I did sort of a a rough pass on encoding , like , episode - like level things on the , transcribed meeting professor g:   postdoc f: where that i if that 's something that we wanna do with each meeting , sort of like a ,  it 's like a manifest , when you get a box full of stuff , or or if that 's ,  professor g:   postdoc f: i I I don't know what  , level of detail would be most useful . 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 . professor g: eh , was p Well , you know , the thing I 'm concerned about is we wanted to do these digits postdoc f: Oh , yeah . But I think , do you , maybe , eh ? Did you prepare some whole thing you wanted us just to see ? phd d: Yeah . professor g: how long a ? phd d: I I think it 's it 's fast , because , I have the results , eh , of the study of different energy without the law length . Eh , eh , in the in the measurement , the average , dividing by the by the , variance . phd d: the other ,  the the last w  , meeting eh , I don't know if you remain we have problem to with the with with the parameter with the representations of parameter , 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 . professor g: No , that there 's no point in going through all of that if that 's the bottom line , really . professor g: So , I I think we have to start  , there there 's two suggestions , really , which is ,  what we said before is that , phd d: Mmm , yeah . professor g: it looks like , at least that you haven't found an obvious way to normalize so that the energy is anything like a reliable , indicator of the overlap . professor g: I I 'm I 'm still a little f think that 's a little funny . professor g: but but you don't want to keep ,  keep knocking at it if it 's if you 're not getting any any result with that . But , the other things that we talked about is , pitch - related things and harmonicity - related things , phd d: Yeah .  But , a completely different tack on it wou is the one that was suggested , by your colleagues in Spain , phd d: Yeah . professor g: That is to say , use , you know , as as you 're doing with the speech , nonspeech , use some very general features . professor g: You know , have a have a couple Markov models and and , 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 . professor g: And let the , statistical system determine what 's the right way to look at the data . professor g: I I , I think it would be interesting to find individual features and put them together . professor g: But given the limitation in time and given the fact that Javier 's system already exists doing this sort of thing , phd d: Yeah . professor g: but , its main limitation is that , again , it 's only looking at silences which would phd d: Yeah . phd d: I I I think that , eh , the possibility , eh , can be that , eh , Thilo , eh , working , eh , with a new class , not only , eh , nonspeech and speech , but , eh , in in in the speech class , professor g:   phd d: dividing , eh , speech , eh , of from a speaker and overlapping , 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 , professor g: Yeah . phd d: And I hope the the next week I will have , eh , some results and we we will show we will see , eh , the the parameter the pitch , eh , tracking in with the program . phd d: And , nnn , nnn professor g: Ha - h have you ever looked at the ,  Javier 's , speech segmenter ? phd c: No . professor g: Cuz again the idea is there the limitation there again was that he was he was only using it to look at silence as a as a as a as a p putative split point between speakers . professor g: But if you included , broadened classes then in principle maybe you can cover the overlap cases . phd c: Yeah , but I 'm not too sure if if we can really represent overlap with with the s detector I I I used up to now , phd d: Mmm , yeah . grad a: I think with phd c: the to speech - nonspeech as grad a: That 's right . But I think Javier 's phd c: it 's only speech or it 's it 's it 's nonspeech . professor g: N n grad a: It doesn't have the same Gaus -  , H M M modeling , phd c: Yeah . grad a: But ,  professor g: Well , it 's sort of has a simple one . grad a: Does it ? professor g: Right ? It 's it 's just it 's just a isn't it just a Gaussian phd d: Yeah . Oh , it doesn't have it doesn't have any temporal ,  ? grad a: Maybe I 'm misremembering , but I did not think it had a Markov professor g: I thought it Yeah . phd d: No , Javier di doesn't worked with , a Markov grad a: Yeah , I didn't think so . So he 's just he just computes a Gaussian over potential grad a: Yep . professor g: And and grad a: It 's just , that i it he has the two - pass issue that What he does is , as a first pass he he p he does , a guess at where the divisions might be and he overestimates . And that 's just a data reduction step , so that you 're not trying at every time interval . grad a: And right now he 's doing that with silence and that doesn't work with the Meeting Recorder . professor g: The other thing one could do is Couldn't  , it 's So you have two categories phd c: Yeah . Couldn't you have a third category ? So you have ,  you have , nonspeech , single - person speech , and multiple - person speech ? postdoc f: He has this on his board actually . Don't you have , like those those several different categories on the board ? professor g: Right ? And then you have a Markov model for each ? phd c:  I 'm not sure . But it 's not too easy , I think , the the transition between the different class , to model them in in the system I have now . professor g: the th the reason why , I was suggesting originally that we look at features is because I thought , well , we 're doing something we haven't done before , phd c: Yeah . professor g: It seems like if two people two or more people talk at once , it should get louder , phd c: Yeah . professor g: and , there should be some discontinuity in pitch contours , phd c: I had the impression . professor g: and , there should overall be a , smaller proportion of the total energy that is explained by any particular harmonic sequence in the spectrum . professor g: So far , Jose has has been By the way , I was told I should be calling you Pepe , but phd d: Yeah . professor g: the has has , been exploring , e largely the energy issue and , as with a lot of things , it is not  , like this , it 's not as simple as it sounds . professor g: And then there 's , you know Is it energy ? Is it log energy ? Is it LPC residual energy ? Is it is it is it , delta of those things ?  , what is it no Obviously , just a simple number absolute number isn't gonna work . So it should be with compared to what ? Should there be a long window for the normalizing factor and a short window for what you 're looking at ? phd c: Yeah . professor g: Or , you know , how b short should they be ? So , phd d:  . professor g: th he 's been playing around with a lot of these different things and and so far at least has not come up with any combination that really gave you an indicator . professor g: So I I still have a hunch that there 's it 's in there some place , but it may be given that you have a limited time here , it it just may not be the best thing to to to focus on for the remaining of it . professor g: So pitch - related and harmonic - related , I 'm I 'm somewhat more hopeful for it . professor g: But it seems like if we just wanna get something to work , phd c: Yeah . professor g: that , their suggestion of of Th - they were suggesting going to Markov models , but in addition there 's an expansion of what Javier did . professor g: even if the features that you give it are maybe not ideal for it , it 's just sort of this general filter bank phd c: Yeah . professor g: or or cepstrum or something ,  Eee it 's in there somewhere probably . phd d: But , eh , what did you think about the possibility of using the Javier software ? Eh , the ,  the ,  the BIC criterion , the the t to train the the Gaussian , eh , using the the mark , eh , by hand , eh , eh , to distinguish be mmm , to train overlapping zone and speech zone .  , eh , I I I think that an interesting , eh , experiment , eh , could be , th eh , to prove that , mmm , if s we suppose that , eh , the the first step  , the the classifier what were the classifier from Javier or classifier from Thilo ? W What happen with the second step ? I  , what what happen with the , eh the , clu the ,  the clu the clustering process ? grad a:   grad a: What do you mean ? phd d: I  , that is is enough is enough , eh , to work well , eh , to , eh , separate or to distinguish , eh , between overlapping zone and , eh , speaker zone ? Because th if if we if we , eh , nnn , develop an classifier and the second step doesn't work well , eh , we have another problem . I had tried doing it by hand at one point with a very short sample , phd d: N grad a: and it worked pretty well , but I haven't worked with it a lot . So what I d I d I took a hand - segmented sample phd d: Nnn , yeah . grad a: and I added ten times the amount of numbers at random , phd d: Yeah . But is is if grad a: But this was just very anecdotal sort of thing . phd d: But it 's possible with my segmentation by hand that we have information about the the overlapping , grad a: Right . So if we if we fed the hand - segmentation to Javier 's and it doesn't work , then we know something 's wrong . phd d: this kind o emph emphasises parameter and Gaussian grad a: Yeah . Y do you know where his software is ? Have you used it at all ? phd d: I yeah have


phd a: Why is it so cold in here ? professor b: so , we haven't sent around the agenda . So , i  , any agenda items anybody has , wants to talk about , what 's going on ? postdoc g: I c I could talk about the meeting .  phd a: Well , I had a just a quick question but I know there was discussion of it at a previous meeting that I missed , but just about the the wish list item of getting good quality close - talking mikes on every speaker . professor b: OK , so let 's let 's So let 's just do agenda building right now . You were gonna starting to say something ? postdoc g: Well , you you , already know about the meeting that 's coming up and I don't know if if this is appropriate for this . phd e: What meeting ? professor b: We can so we can ta so n NIST is NIST folks are coming by next week postdoc g: OK . professor b: I think phd e: Who 's coming ? professor b: John Fiscus postdoc g: An - anything else , strike anybody ? phd a: we started running recognition on one conversation but it 's the r isn't working yet . phd e: Wha phd a: the main thing would be if anyone has , knowledge about ways to , post - process the wave forms that would give us better recognition , that would be helpful to know about . professor b: Yeah , so ,  phd e: What about , is there anything new with the speech , nonspeech stuff ? phd c: Yeah , we 're working more on it but , it 's not finished . postdoc g: I had thought under my topic that I would mention the , four items that I I , put out for being on the agenda f on that meeting , which includes like the pre - segmentation and the and the developments in multitrans . professor b: Alright , why don't we start off with this , u u I guess the order we brought them up seems fine . So the one issue was that the the , lapel mike , isn't as good as you would like . Right ? phd a: Ri -  , professor b: Is that is that basically the point ? phd a: yeah , the And actually in addition to that , that the the close talking mikes are worn in such a way as to best capture the signal . And the reason here is just that for the people doing work not on microphones but on sort of like dialogue and so forth ,  or and even on prosody , which Don is gonna be working on soon , it adds this extra , you know , vari variable for each speaker to to deal with when the microphones aren't similar . phd a: So And I also talked to Mari this morning and she also had a strong preference for doing that . And in fact she said that that 's useful for them to know in starting to collect their data too . Right , so one th grad h: Well , so professor b: well one thing I was gonna say was that , i we could get more , of the head mounted microphones even beyond the number of radio channels we have because I think whether it 's radio or wire is probably second - order . grad h: So it 's towards the corner of your mouth so that breath sounds don't get on it . grad h: And then just sort of about , a thumb or a thumb and a half away from your from your mouth . phd a: But we have more than one type of professor b: How am I d phd a: for instance , you 're phd c: Yeah . phd a: But if we could actually standardize , you know , the the microphones , as much as possible that would be really helpful . professor b: Well ,  it doesn't hurt to have a few extra microphones around , phd d: Yeah . professor b: so why don't we just go out and and get an order of of if this microphone seems OK to people , I 'd just get a half dozen of these things . grad h: Well the onl the only problem with that is right now , some of the Jimlets aren't working . grad h: And so , w  , I 've only been able to find three jacks that are working . phd e: Can we get these , wireless ? grad h: So professor b: No , but my point is phd a: But y we could just record these signals separately and time align them with the start of the meeting . professor b: R r right grad h: I I 'm not sure I 'm follow . Say that again ? professor b: Right now , we 've got , two microphones in the room , that are not quote - unquote standard . professor b: Also what we 've talked before about getting another , radio , grad h: Right . professor b: So ,  so we should go out to our full complement of whatever we can do , but have them all be the same mike . I think the original reason that it was done the other way was because , it w it was sort of an experimental thing and I don't think anybody knew whether people would rather have more variety or or , more uniformity , phd a: Right . phd a: Well , for short term research it 's just there 's just so much effort that would have to be done up front n  , professor b: Yeah . phd e: Is it because You you 're saying the for dialogue purposes , so that means that the transcribers are having trouble with those mikes ? Is that what you mean ? phd a: Well Jane would know more about the transcribers . postdoc g: a couple times , so , yeah , the transcribers notice And in fact there 're some where ,  ugh well ,  there 's it 's the double thing . postdoc g: And he 's always they always they just rave about how wonderful Adam 's Adam 's channel is .  , " Baaah ! " phd a: Even if if you 're talking on someone else 's mike it 's still you w postdoc g: Yeah , but  it 's not just that , it 's also you know you professor b: Yeah . postdoc g: It 's also like n no breathing , no You know , it 's like it 's it 's  , professor b: Yeah . postdoc g: it 's really it makes a big difference from the transcribers ' point of view grad h: Yeah , it 's an advantage when you don't breath . professor b: When we 're doing grad h: Yeah , I think that the point of doing the close talking mike is to get a good quality signal . professor b: Yeah , probably yeah , to the store we talked about and that grad h: Yep . postdoc g: And there was some talk about , maybe the h headphones that are uncomfortable for people , to grad h: Yep . So , as as I said , we 'll do a field trip and see if we can get all of the same mike that 's more comfortable than than these things , which I think are horrible . grad h: And , you know , we 're researchers , so we all have big heads . OK , so , Jonathan Fiscus is coming on the second of February and I 've spoken with , u u a lot of people here , not everyone .  , and , he expressed an interest in seeing the room and in , seeing a demonstration of the modified multitrans , which I 'll mention in a second , and also , he was interested in the pre - segmentation and then he 's also interested in the transcription conventions . postdoc g: And ,  So , it seems to me in terms of like , i i it wou You know , OK . So the room , it 's things like the audio and c and audi audio and acoustic acoustic properties of the room and how it how the recordings are done , and that kind of thing . OK , in terms of the multi - trans , well that that 's being modified by Dave Gelbart to , handle multi - channel recording . grad h: Oh , I should 've I was just thinking I should have invited him to this meeting . I I , @ @ didn't didn't see it , yesterday but I 'm going to see it today . And , that 's that will enable us to do nice  , tight time marking of the beginning and ending of overlapping segments . In terms of , like , pre - segmentation , that that continues to be , a terrific asset to the to the transcribers . What what I 'm doing right now is I 'm trying to include some information about which channel , there 's some speech in . I 'm just trying to do this by comparing energies ,  normalizing energies and comparing energies of the different channels . phd c: And so to to give the transcribers some information in which channel there 's there 's speech in addition to to the thing we we did now which is just , speech - nonspeech detection on the mixed file . So I 'm I 'm relying on on the segmentation of the mixed file postdoc g: This is good . phd c: but I 'm I 'm trying to subdivide the speech portions into different portions if there is some activity in in different channels . postdoc g: Excellent , so this 'd be like w e providing also speaker ID potentially . professor b: something I guess I didn't put in the list but , on that , same day later on in or maybe it 's No , actually it 's this week , Dave Gelbart and I will be , visiting with John Canny who i you know , is a CS professor , postdoc g: Oh . You know , maybe they 'd wanna stick an array mike here when we 're doing things phd e: That would be cool . professor b: or or maybe it 's it 's not a specific array microphone they want phd d: Yeah . professor b: but they might wanna just , you know , you could imagine them taking the four signals from these these table mikes and trying to do something with them  , I also had a discussion So , w  , we 'll be over over there talking with him , after class on Friday . I had a , discussion today with , Birger Kollmeier who 's a , a German , scientist who 's got a fair sized group doing a range of things . But but , he does stuff with auditory models and he 's very interested in directionality , and location , and and , head models and microphone things . And so , he 's he and possibly a student , there w there 's , a student of his who gave a talk here last year , may come here , in the fall for , sort of a five month , sabbatical . phd e: That that reminds me , I had a a thought of an interesting project that somebody could try to do with the data from here , either using , you know , the the mikes on the table or using signal energies from the head worn mikes , phd d:   phd e: and that is to try to construct a map of where people were sitting , professor b: Right . phd e: And so you could plot out who was sitting next to who professor b: A little bit , phd e: and professor b: he didn't do a very extreme thing but just it was just sort of phd d: Yeah , yeah . professor b: e e given that , the the the block of wood with the the the two mikes on either side , grad h:   professor b: if I 'm speaking , or if you 're speaking , or someone over there is speaking , it if you look at cross - correlation functions , you end up with a phd d: Yeah . professor b: if if someone who was on the axis between the two is talking , then you you get a big peak there . And if if someone 's talking on on on , one side or the other , it goes the other way . professor b: And then , it it it even looks different if th t if the two two people on either side are talking than if one in the middle . Well I was just thinking , you know , as I was sitting here next to Thilo that  , when he 's talking , my mike probably picks it up better than your guys 's mikes . phd e: So if you just looked at grad h: Oh , that 's another cl cue , phd d: Yeah . phd e: yeah , looked at the energy on my mike and you could get an idea about who 's closest to who . professor b: Yeah , well you have to the appropriate normalizations are tricky , and and and are probably the key . phd a: You just search for Adam 's voice on each individual microphone , you pretty much know where everybody 's sitting . postdoc g: Can I ask one thing ?  , so , Jonathan Fiscus expressed an interest in , microphone arrays . postdoc g: is there  b And I also want to say , his he can't stay all day . He needs to  , leave for  , from here to make a two forty - five flight grad h: Oh , so just morning . postdoc g: So it makes the scheduling a little bit tight but do you think that ,  that , i John Canny should be involved in this somehow or not . professor b: Probably not but I I 'll I 'll I 'll know better after I see him this Friday what what kind of level he wants to get involved . professor b: he might be excited to and it might be very appropriate for him to , or he might have no interest whatsoever . grad h: Is he involved in Ach ! I 'm blanking on the name of the project . NIST has has done a big meeting room instrumented meeting room with video and microphone arrays , and very elaborate software . Is is he the one working on that ? professor b: Well that 's what they 're starting up . professor b: well I think they 've instrumented a room but I don't think they they haven't started recordings yet . They don't have the phd e: Are they going to do video as well ? grad h:  . grad h: Oh , cuz what what I had read was , they had a  very large amount of software infrastructure for coordinating all this , both in terms of recording and also live room where you 're interacting the participants are interacting with the computer , and with the video , and lots of other stuff . professor b: All all I know is that they 've been talking to me about a project that they 're going to start up recording people meet in meetings . professor b: And one one notable difference u u actually I can't remember whether they were going to routinely collect video or not , but one one , difference from the audio side was that they are interested in using array mikes . The reason I didn't go for that here was because , the focus , both of my interest and of Adam 's interest was  , in impromptu situations . And we 're not recording a bunch of impromptu situations but that 's because it 's different to get data for research than to actually apply it . professor b: And so , for scientific reasons we thought it was good to instrument this room as we wanted it . But the thing we ultimately wanted to aim at was a situation where you were talking with , one or more other people i  , in in an p impromptu way , where you didn't didn't actually know what the situation was going to be . And therefore it would not it 'd be highly unlikely that room would be outfitted with with some very carefully designed array of microphones . It was just , you know , yet another piece of research and it seemed like we had enough troubles just phd e: So there 's no like portable array of mikes ? professor b: No . So there 's there 's  , there 's a whole range of things there 's a whole array of things , that people do on this . professor b: So , the ,  the big arrays , places , like  , Rutgers , and Brown , and other other places , they have , big arrays with , I don't know , a hundred hundred mikes or something . professor b: And it 's and , in fact at one point we had a a proposal in with Rutgers where we were gonna do some of the sort of per channel signal - processing and they were gonna do the multi - channel stuff , but it d it d we ended up not doing it . grad h: And then they have little ones too professor b: And then they had the little ones , yeah . grad h: but  but they don't have our block of wood , right ? professor b: Yeah , our block of wood is unique . professor b: But the But the No , there are these commercial things now you can buy that have four mikes or something phd a:   professor b: and and ,  So , yeah , there 's there 's there 's a range of things that people do . professor b: so if we connected up with somebody who was interested in doing that sort of thing that 's that 's a good thing to do .  , whenever I 've described this to other people who are interested on the with the acoustic side that 's invariably the question they ask . Just like someone who is interested in the general dialogue thing will always ask "  , are you recording video ? " phd a: Right , professor b: right ? phd a: right . professor b: And and the acoustic people will always say , " well are you doing , array microphones ? " So it 's it 's a good thing to do , but it doesn't solve the problem of how do you solve things when there 's one mike or at best two mikes in in this imagined PDA that we have .  , I know that having an array of  , I would imagine it would be more expensive to have a an array of microphones . But couldn't you kind of approximate the natural sis situation by just shutting off  , channels when you 're later on ?  , it seems like if the microphones don't effect each other then couldn't you just , you know , record them with an array and then just not use all the data ? grad h: It 's it 's just a lot of infrastructure that for our particular purpose we felt we didn't need to set up . professor b: Yeah , if ninety - nine percent of what you 're doing is c is shutting off most of the mikes , then going through the postdoc g: OK . professor b: But if you get somebody who 's who who has that as a primary interest then that put then that drives it in that direction . grad h: That 's right ,  if someone if someone came in and said we really want to do it , phd a: Right . That would be fine , phd e: So to save that data you You have to have one channel recording per mike in the array ? grad h: Buy more disk space . professor b: But then , you know , there 's it there 's phd e: What you save , if you 're going to do research with it . yeah professor b: There 's I I don't know what they 're going to do and I don't know how big their array is . Obviously if you were gonna save all of those channels for later research you 'd use up a lot of space . grad h: Well their software infrastructure had a very elaborate design for plugging in filters , and mixers , and all sorts of processing . But I think in practical situations you would have some engine of some sort doing some processing to reduce this to some to the equivalent of a single microphone that was very directional . professor b: Right ? phd a: it seems professor b: So phd e: Sort of saving the result of the beam - forming . phd a: it seems to me that there 's you know , there are good political reasons for for doing this , just getting the data , because there 's a number of sites like right now SRI is probably gonna invest a lot of internal funding into recording meetings also , which is good , but they 'll be recording with video and they 'll be You know , it 'd be nice if we can have at least , make use of the data that we 're recording as we go since it 's sort of this is the first site that has really collected these really impromptu meetings , and just have this other information available . So , if we can get the investment in just for the infra infrastructure and then , I don't know , save it out or have whoever 's interested save that data out , transfer it there , it 'd be g it 'd be good to have have the recording . grad h: You mean to to actually get a microphone array and do that ? phd a: Well , if Even if we 're not grad h: And video and phd a: I 'm not sure about video . That 's sort of an video has a little different nature since right n right now we 're all being recorded but we 're not being taped .  , but it definitely in the case of microphone arrays , since if there was a community interested in this , then grad h: Well , but I think we need a researcher here who 's interested in it . professor b: See the problem is it it took , it took at least six months for Dan to get together the hardware and the software , and debug stuff in in the microphones , and in the boxes . And so I think we could get a microphone array in here pretty easily and , have it mixed to to one channel of some sort . professor b: But , e I think for  , how we 're gonna decide For for maximum flexibility later you really don't want to end up with just one channel that 's pointed in the direction of the the the p the person with the maximum energy or something like that .  , you you want actually to you want actually to have multiple channels being recorded so that you can And to do that , it we 're going to end up greatly increasing the disk space that we use up , we also only have boards that will take up to sixteen channels and in this meeting , we 've got eight people and and six mikes . phd a: Well if there 's a way to say time to sort of solve each of these f those professor b: Yeah . phd a: So suppose you can get an array in because there 's some person at Berkeley who 's interested and has some equipment , and suppose we can as we save it we can , you know , transfer it off to some other place that that holds this this data , who 's interested , and even if ICSI it itself isn't .  , and it it seems like as long as we can time align the beginning , do we need to mix it with the rest ? I don't know . phd a:  it 's just it 's worth considering as sort of grad h: And y it 'd certainly gets skew . phd a: once you make the up front investment and can sort of save it out each time , and and not have to worry about the disk space factor , then it mi it might be worth having the data . I mentioned that , b as a practical matter , grad h: Just professor b: but the real issue is that , there is no way to do a recording extended to what we have now with low skew . professor b: which would mean that the sampling times and so forth would be all over the place compared to this . So it would depend on the level of pr processing you were doing later , but if you 're d i the kind of person who 's doing array processing you actually care about funny little times . And and so you actually wou would want to have a completely different set up than we have , phd a: I see . But what we could do is if there was someone else who 's interested they could have a separate set up which they wouldn't be trying to synch with ours which might be useful for for them . phd a: Right ,  at least they 'd have the data and the transcripts , professor b: And then we can offer up the room , phd a: and Right . professor b: Yeah , we can o offer the meetings , and the physical space , and and yeah , the transcripts , and so on . phd a: But it 's if it 's impossible or if it 's a lot of effort then you have to just balance the two , professor b: Well I thi phd a: so professor b: yeah , the thing will be , u u in in again , in talking to these other people to see what you know , what what we can do . phd e: Is there an interest in getting video recordings for these meetings ?  professor b: Right , so we have we phd e:  grad h: Yes , absolutely . But it 's exactly the same problem , that you have an infrastructure problem , you have a problem with people not wanting to be video taped , and you have the problem that no one who 's currently involved in the project is really hot to do it . Internally , but I know there is interest from other places that are interested in looking at meeting data and having the video . So it 's just postdoc g: Yeah , w although I m I I have to u u mention the human subjects problems , that i increase with video . There 's the fact that then  , if i I I 've heard comments about this before , " why don't you just put on a video camera ? " But you know , it 's sort of like saying , "  , well we 're primarily interested in in some dialogue things , but , why don't we just throw a microphone out there . "  , the thing is , once you actually have serious interest in any of these things then you actually have to put a lot of effort in . professor b: So I think NIST or LDC , or somebody like that I think is much better shape to do all that . postdoc g: I it it occurred to me , has Don signed a human subject 's form ? grad h: Oh ! Probably not . postdoc g: A permission form ? grad h: Has Don have you s did you si I thought you did actually . grad h: Didn't you read a digit string ? phd e: You were here at a meeting before . postdoc g: Did you sign a form ? grad f: Did I ? I don't know . professor b: Yeah , we we postdoc g: But I just grad f: Can I verbally consent ? postdoc g: you know . You 're on recor you 're being recorded postdoc g: o grad f: Yeah . phd a: and professor b: we don't we don't perform electro - shock during these meetings , grad f: I don't care . phd e: How big is the data set ? postdoc g: Oh , it 's what  is one meeting . I didn't want to have any conflicts of , you know , of of when to stop transcribing this one or So I wanted to keep it clear whose data were whose , and and and so phd e:  - huh . postdoc g: And , meetings , you know , I think that they 're they go as long as a almost two hours in some in some cases . So , you know , that means you know , if we 've got two already finished and they 're working on  , right now all eight of them have differe  , additional data sets . postdoc g: And , also Dan Ellis 's innovation of the ,  the multi - channel to here really helped a r a lot in terms of clearing clearing up h hearings that involve overlaps . But , just out of curiosity I asked one of them how long it was taking her , one of these two who has already finished her data set .  , these still , when they 're finished , that means that they 're finished with their pass through . They still need to be edited and all but But it 's word level , speaker change , the things that were mentioned . OK , now I wanted to mention the , teleconference I had with , Jonathan Fiscus . postdoc g: He , he in indicated to me that they 've that he 's been , looking , spending a lot of time with I 'm not quite sure the connection , but spending a lot of time with the ATLAS system . But it looks to me like that 's the name that has developed for the system that Bird and Liberman developed for the annotated graphs approach . postdoc g: So what he wants me to do and what we what we will do and  , is to provide them with the u already transcribed meeting for him to be able to experiment with in this ATLAS System . And they do have some sort of software , at least that 's my impression , related to ATLAS and that he wants to experiment with taking our data and putting them in that format , and see how that works out . I I I explained to him in in detail the , conventions that we 're using here in this in this word level transcript . And , you know , I I explained , you know , the reasons that that we were not coding more elaborately and and the focus on reliability . He 's he 's very  , independently he asked , " well what about reliability ? " So , he 's interested in the consistency of the encoding and that sort of thing . OK ,  phd a: Sorry , can you explain what the ATLAS I 'm not familiar with this ATLAS system . postdoc g: Well , you know , at this point I think  , well Adam 's read more in more detail than I have on this . But , there there is a way of viewing  , whenever you have coding categories , and you 're dealing with  , a taxonomy , then you can have branches that that have alternative , choices that you could use for each each of them . grad h: Is is Is ATLAS the his annotated transcription graph stuff ? I don't remember the acronym . The the one the what I think you 're referring to , they they have this concept of an an annotated transcription graph representation . grad h: And that 's basically what I based the format that I did I based it on their work almost directly , in combination with the TEI stuff . And so it 's it 's a data representation and a set of tools for manipulating transcription graphs of various types . phd e: Is this the project that 's sort of , between , NIST and and , a couple of other places ? postdoc g:   And I looked through them and they mainly had to do with this , this , tree structure , annotated tree diagram thing . postdoc g: So ,  and , you know , in terms of like the conventions that I 'm a that I 've adopted , it there there 's no conflict at all . And , " oh , and how 'd you handle this ? " And I said , " well , you know , this way " and And and we had a really nice conversation .  , OK , now I also wanted to say in a different a different direction is , Brian Kingsbury . I told him he could SSH on and use multi - trans , and have a look at the already done , transcription . And what he said was that , what they 'll be providing is will not be as fine grained in terms of the time information . And , that 's ,  You know , I need to get back to him and and , you know , explore that a little bit more and see what they 'll be giving us in specific , phd a:  . phd e: The p the people postdoc g: but I just haven't had time yet . phd e: The the folks that they 're , subcontracting out the transcription to , are they like court reporters postdoc g: Sorry , what ? Yes . phd e: or postdoc g: Apparently Well , I get the sense they 're kind of like that . Like it 's like a pool of of somewhat  , secretarial I don't think that they 're court reporters . Like medical transcriptionist type people grad h: Nu - it 's mostly it 's for their speech recognition products , phd e: But aren't they 're postdoc g: Yep . grad h: Well they they do send it out but my understanding is that that 's all this company does is transcriptions for IBM for their speech product . grad h: So most of it 's ViaVoice , people reading their training material for that . postdoc g: Up to now it 's been monologues , as far my understood . postdoc g: Brian himself downloaded So So , Adam sent them a CD and Brian himself downloaded  , cuz , you know , we wanted to have it so that they were in familiar f terms with what they wanted to do . postdoc g: And then what he 's going to do is check it , a before they go be beyond the first one . professor b: So if they hear something off in the distance they don't they just go phd e: OK . grad h: Well , but that 's OK , because , you know , you 'll do all them and then combine them . phd e: Well if you 're tran if you got that channel right there postdoc g: d  , in my case phd c: Yeah . postdoc g: Yeah , I I would think that it would be kind of hard to come out with Yeah . phd a: I I think it 's sort of hard just playing the you know , just having played the individual files . phd a: there are a lot of words that are so reduced phonetically that make sense when you know what the person was saying before . phd e: Yeah , that 's phd a: it sort of depends where you are in postdoc g: And especially since a lot of these phd d: Yeah . grad h: And the answer is we don't actually know the answer because we haven't tried both ways . postdoc g: Well , except I can say that my transcribers use the mixed signal mostly grad h: So . postdoc g: unless there 's a huge disparity in terms of the volume on on the mix . In which case , you know , they they wouldn't be able to catch anything except the prominent channel , grad h: Right . postdoc g: Yeah , well phd a: Actually , are th so are they giving any time markings ? grad h: Right . phd a: In other words , if postdoc g: Well , I have to ask him . postdoc g: But but the ,  I did want to say that it 's hard to follow one channel of a conversation even if you know the people , and if you 're dealing furthermore with highly abstract network concepts you 've never heard of So , you know , one of these people was was transcribing the , networks group talk and she said , " I don't really know what a lot of these abbreviations are , " " but I just put them in parentheses cuz that 's the that 's the convention and I just " Cuz you know , if you don't know grad h: Oh , I 'd be curious to to look at that . grad h: The networks group meetings are all phd e: Given all of the effort that is going on here in transcribing why do we have I B M doing it ? Why not just do it all ourselves ? professor b: it 's historical .  , some point ago we thought that  , it " boy , we 'd really have to ramp up to do that " , phd c:  - huh . phd d: No , just professor b: you know , like we just did , and , here 's , a a , collaborating institution that 's volunteered to do it . professor b: And it still might be a good thing phd e: I 'm just wondering now phd a: Actu yeah , Mar - Mari asked me the same question as sort of professor b: but phd e: Well , I 'm I 'm wondering now if it 's grad h: Well we can talk about more details later . Let 's see what comes out of it , and and , you know , have some more discussions with them . It 's very a real benefit having Brian involved because of his knowledge of what the how the data need to be used and so what 's useful to have in the format . grad h: So , Liz , with with the SRI recognizer , can it make use of some time marks ? phd a: OK , so this is a , grad h: I I guess I don't know what that means . phd a: and actually I should say this is what Don has b  , he 's already been really helpful in , chopping up these So so first of all you  , for the SRI front - end , we really need to chop things up into pieces that are f not too huge .  , but second of all ,  in general because some of these channels , I 'd say , like , I don't know , at least half of them probably on average are g are ha are have a lot of cross - ta sorry , some of the segments have a lot of cross - talk .  , it 's good to get sort of short segments if you 're gonna do recognition , especially forced alignment . So , Don has been taking a first stab actually using Jane 's first the fir the meeting that Jane transcribed which we did have some problems with , and Thilo , I think told me why this was , but that people were switching microphones around in the very beginning , so the SRI re phd c: No , th Yeah . They they were not switching them but what they were they were adjusting them , phd a: and they They were not phd c: so . phd a: So we have to sort of normalize the front - end and so forth , and have these small segments . phd a: So we 've taken that and chopped it into pieces based always on your your , cuts that you made on the mixed signal . Right ? phd a: the problem is if we have no time marks , then for forced alignment we actually don't know where you know , in the signal the transcriber heard that word . And so grad h: Oh , I see , phd a: if if it 's a whole conversation and we get a long , you know , par paragraph of of talk , grad h: it 's for the length . phd a: And , I think with phd e: Well you would need to like a forced alignment before you did the chopping , right ? phd a: No , we used the fact that So when Jane transcribes them the way she has transcribers doing this , whether it 's with the pre - segmentation or not , grad h: It 's already chunked . And maybe they choose the chunk or now they use a pre - segmentation and then correct it if necessary . That 's great , cuz the recognizer can grad h: it 's all pretty good sized for the recognizer also . phd a: Right , and it it helps that it 's made based on sort of heuristics and human ear I think . phd a: Th - but there 's going to be a real problem , even if we chop up based on speech silence these , the transcripts from I B M , we don't actually know where the words were , which segment they belonged to . phd e: Why not do a a a forced alignment ? grad h: That 's what she 's saying , is that you can't . phd a: If you do a forced alignment on something really grad h: Got  six sixty minutes of phd a: well even if you do it on something really long you need to know you can always chop it up but you need to have a reference of which words went with which , chop . postdoc g: Now wasn't I thought that one of the proposals was that IBM was going to do an initial forced alignment , phd a: So postdoc g: after they grad h: Yeah , but professor b: I I think that they are , grad h: We 'll have to talk to Brian . professor b: yeah , I 'm sure they will and so we we have to have a dialogue with them about it . professor b: it sounds like Liz has some concerns phd a: Maybe they have some you know , maybe actually there is some , even if they 're not fine grained , maybe the transcribers professor b: and phd a: I don't know , maybe it 's saved out in pieces or or something . postdoc g: I just you know , it 's like I got over - taxed with the timing . But the it is true that the segments I haven't tried the segments that Thilo gave you but the segments that in your first meeting are great . phd a: Right , cuz postdoc g: Well , I I was thinking it would be fun to to  , if if you wouldn't mind , to give us a pre - segmentation . postdoc g: maybe you have one already of that first m of the meeting that  , the first transcribed meeting , the one that I transcribed . phd c: I 'm sure I have some postdoc g: Do you have a could you generate a pre - segmentation ? grad h: February sixteenth I think . phd c: but but that 's the one where we 're , trai training on , so that 's a little bit grad h: Oh . phd c: It 's a little bit at odd to postdoc g: Oh , darn . phd a: And actually as you get transcripts just , for new meetings , we can try postdoc g:  - huh . So it 'd be good for just to know as transcriptions are coming through the pipeline from the transcribers , just to sort of we 're playing around with sort of  , parameters f on the recognizer , postdoc g:   phd a: The first meeting had I think just four people , phd c: Four speakers , yeah . postdoc g: Yeah , Liz and I spoke d w at some length on Tuesday 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 . I guess the other thing , I I can't remember if we discussed this in the meeting but , I know you and I talked about this a little bit , there was an issue of , suppose we get in the , I guess it 's enviable position although maybe it 's just saying where the weak link is in the chain , where we we , we have all the data transcribed and we have these transcribers and we were we 're the we 're still a bit slow on feeding at that point we 've caught up and the the the , the weak link is is recording meetings . OK , two questions come , is you know what how how do we  , it 's not really a problem at the moment cuz we haven't reached that point but how do we step out the recorded meetings ? And the other one is , is there some good use that we can make of the transcribers to do other things ? So , I I can't remember how much we talked about this in this meeting but there was grad h: We had spoken with them about it . postdoc g: And there is one use that that also we discussed which was when , Dave finishes the and maybe it 's already finished the the modification to multi - trans which will allow fine grained encoding of overlaps .  , then it would be very these people would be very good to shift over to finer grain encoding of overlaps . It 's just a matter of , you know , providing So if right now you have two overlapping segments in the same time bin , well with with the improvement in the database in in the , sorry , in the interface , it 'd be possible to , you know , just do a click and drag thing , and get the  , the specific place of each of those , the time tag associated with the beginning and end of of each segment . professor b: One one was  , we had s had some discussion in the past about some very high level labelings , postdoc g: Yeah . The types of overlaps professor b: types of overlaps , and so forth that that someone could do . And the third one is is , just a completely wild hair brained idea that I have which is that , if ,  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 . For instance , marking in some overlapping potentially overlapping fashion , the value of , ar articulatory features . professor b: You know , just sort of say , OK , it 's voiced from here to here , there 's it 's nasal from here to here , and so forth .  , as opposed to doing phonetic  , you know , phonemic and the phonetic analysis , grad h:  professor b: and , assuming , articulatory feature values for those those things . postdoc g: Also if you 're dealing with consonants that would be easier than vowels , wouldn't it ?  , I would think that that , 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 . professor 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 postdoc g:   grad h: Yeah , but but just saying what the professor b: because it 's you know , there 's this movement from here to here postdoc g: Yeah , I 'm sure . professor b: and and and it 's so I phd e: You 're saying r sort of remove the high level constraints and go bottom - up . Maybe there 's there 's even a better way to do it but it but but that 's , you know , sort of a traditional way of describing these things , phd e:   professor b: and  , actually this might be a g neat thing to talk to postdoc g: That 's nice . professor b: some sort of categories but but something that allows for overlapping change of these things 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 , you 're now in this state , which corresponds to this speech sound " and so on . phd a: So this is like gestural  , these g professor b: Yeah , something like that . professor b: actually if we get into that it might be good to , haul John Ohala into this phd a: Right . phd a: But is is the goal there to have this on meeting data , postdoc g: Excellent . phd a: like so that you can do far field studies of those gestures or  , or is it because you think there 's a different kind of actual production in meetings that people use ? Or ? professor 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 . And then you have i and then and then it 's natural in all senses , phd e: Just a source of data ? phd a: I see . professor b: in the sense that you have microphones that are at a distance that you know , one might have , and you have the close mikes , and you have people talking naturally . And the overlap is just indicative of the fact that people are talking naturally , phd a:  - huh . professor b: right ? So so I think that given that it 's that kind of corpus , phd d: Yeah . professor b: if it 's gonna be a very useful corpus  , if you say w OK , we 've limited the use by some of our , censored choices , we don't have the video , we don't and so forth , but there 's a lot of use that we could make of it by expanding the annotation choices . professor b: And , most of the things we 've talked about have been fairly high level , and being kind of a bottom - up person I thought maybe we 'd , do some of the others . professor b: people have made a lot of use of of TIMIT and ,  w due to its markings , and then the Switchboard transcription thing , well I think has been very useful for a lot of people . professor b: So phd a: I guess I wanted to , sort of make a pitch for trying to collect more meetings . phd a: I actually I talked to Chuck Fillmore and I think they 've what , vehemently said no before but this time he wasn't vehement and he said you know , " well , Liz , come to the meeting tomorrow professor b: Yeah . Go to their meeting tomorrow and see if we can try , to convince them postdoc g:   professor b: Cuz they have something like three or four different meetings , phd a: because they have And they have very interesting meetings from the point of view of a very different type of of talk than we have here professor b: right ? postdoc g:    phd e: You mean in terms of the topic topics ? phd a: Well , yes and in terms of the the fact that they 're describing abstract things and , just dialogue - wise , professor b:   And then the other thing is , I don't know if this is at all useful , but I asked Lila if I can maybe go around and talk to the different departments in this building to see if there 's any groups that , for a free lunch , professor b: Yes . grad h: You mean non - ICSI ? phd a: non - ICSI , non - academic , grad h: Yeah , I guess you you can try phd a: you know , like government people , grad h: but phd a: I don't know .  , it seems like we we had this idea before of having like linguistics students brought down for free lunches grad h: Well , tha I think that 's her point . phd a: Right , and then we could also we might try advertising again because I think it 'd be good if if we can get a few different sort of non - internal types of meetings postdoc g: Yeah . phd e: Does does John Ohala have weekly phonetics lab meetings ? postdoc g:   grad h: And I think , if we could get phd a: So I actually wrote to him and he answered , " great , that sounds really interesting " . grad h: But , it would be nice if we got someone other than me who knew how to set it up and could do the recording phd a: So grad h: so u I didn't have to do it each time . phd a: and I was thinking professor b: He - he 's supposed he 's supposed to be trained to do it .  , the other thing is that there was a number of things at the transcription side that , transcribers can do , like dialogue act tagging , grad h: It 's not that hard . phd a: disfluency tagging , things that are in the speech that are actually something we 're y working on for language modeling . So if you wanna process a utterance and the first thing they say is , " well " , and that " well " is coded as some kind of interrupt u tag .  , and things like that , th postdoc g: Of course some of that can be li done lexically . phd a: A lot of it can be done postdoc g: And I also they are doing disfluency tagging to some degree already . phd a: I think there 's a second pass and I don't really know what would exist in it . But there 's definitely a second pass worth doing to maybe encode some kinds of , you know , is it a question or not , postdoc g:   postdoc g: I wanted to whi while we 're  , so , to return just briefly to this question of more meeting data ,  I have two questions . One of them is , Jerry Feldman 's group , they they , are they I know that they recorded one meeting . professor b: I think there 's we should go beyond , ICSI but , there 's a lot of stuff happening at ICSI that we 're not getting now that we could . So th there was the thing in Fillmore 's group but even there he hadn't What he 'd said " no " to was for the main meeting . phd e: Well , and and the other thing too is when they originally said " no " they didn't know about this post - editing capability thing . professor b: there 's there 's , the networks group , I don't Do they still meeting regularly or ? grad h: Well , I don't know if they meet regularly or not but they are no longer recording . professor b: But  , ha ha have they said they don't want to anymore or ? grad h: ugh , what was his name ? professor b: i i postdoc g: Joe Sokol ? grad h: Yeah . professor b: OK , so they 're down to three or four people grad h: They and they stopped Yeah . postdoc g: We might be able to get the administration grad h: Well he was sort of my contact , so I just need to find out who 's running it now . phd a: Yeah , it One thing that would be nice postdoc g: I don't know phd a: and this it sounds bizarre but , I 'd really like to look at to get some meetings where there 's a little bit of heated discussion , like ar arguments and or emotion , and things like that . Some group , " yes , we must " grad h: Who 's willing to get recorded and distributed ? phd a: Well , you know , something phd c: Yeah . grad f: Yeah , I don't think the more political argumentative ones would be willing to phd a:  professor b: Yeah , with with with potential use from the defense department . phd a: No , but maybe stu student , groups or , film - makers , or som Something a little bit colorful . Yeah , th there 's a problem there in terms of , the  commercial value of of st  , postdoc g: Yeah , of course there is this problem though , that if we give them the chance to excise later we e might end up with like five minutes out of a f of m one hour phd d: Film - maker . phd a: And I don't mean that they 're angry phd d: Is postdoc g: of Yes . phd a: but just something with some more variation in prosodic contours and so forth would be neat . So if anyone has ideas , I 'm willing to do the leg work to go try to talk to people but I don't really know which groups are worth pursuing . postdoc g: Well there was this K P F A grad h: No that 's postdoc g: but OK . phd a: Or postdoc g: And I had one other one other aspect of this which is , Jonathan Fiscus expressed primar  y a major interest in having meetings which were all English speakers . phd e: Did he mean ,  did he mean and non - British ? grad h: Well phd c: The all native . phd e: He said British was OK ? postdoc g: But but Sure , sure , sure . professor b: Why ? grad h: British is English ? phd c:  postdoc g: Yeah . professor b: Well , I don't I don't I don't think if he didn't say that postdoc g: Native speaking . grad h: So , why would he care ? phd e: Knowing the application phd a: That 's professor b: I remember wh I I remember a study phd a: I was thinking , knowing the , n National Institute of Standards , it is all professor b: I remember a study that BBN did where they trained on this was in Wall Street Journal days or something , they trained on American English and then they tested on , different native speakers from different areas . professor b: it was Swiss w Yeah , so it 's so I think , you know , if he 's if he 's thinking in terms of recognition kind of technology I I I think he would probably want ,  American English , postdoc g: All America , OK . It it yeah , unless we 're gonna train with a whole bunch of postdoc g: I think that the Feldman 's meetings tend to be more that way , aren't they ?  , I sort of feel like they have professor b: I think so , grad h: Maybe . grad h: And maybe there are a few of with us where it was professor b: Yeah . grad h: you know , Dan wasn't there and before Jose started coming , professor b: Yeah . professor b: So , what about what about people who involved in some artistic endeavor ? phd d: Yeah . phd a: Exactly , that 's what I was professor b: You 'd think like they would be phd d: A film - maker . phd a: something where there there is actually discussion where there 's no right or wrong answer but but it 's a matter of opinion kind of thing . phd a: Yeah , we could phd e: A any department that calls itself science phd d: Department . phd d: Computer sci grad h: That postdoc g: We could get Julia Child . phd a: I 'm I 'm actually serious grad h: That 's phd a: because , you know , we have the set up here grad h: Got a ticket . grad f: I know grad h: I could phd a: Not not professor b: Put a little ad up saying , " come here and argue " . grad h: and they they they expressed willingness back when they thought they would be doing more stuff with speech . grad h: But when they lost interest in speech they also stopped answering my email about other stuff , so . phd a: Or people who are really h professor b: They could have a discussion about te grad f: I grad h: We should probably bleep that out . grad f: I heard that at Cal Tech they have a special room someone said that they had a special room to get all your frustrations out that you can go to and like throw things and break things . professor b: Yeah , now that is not actually what we grad f: So we can like post a grad h: Th - that 's not what we want . grad f: No , not to that extent phd a: Well , far field mikes can pick up where they threw stuff on the wall . professor b: Yeah , but we don't want them to throw the far field mikes is the thing . postdoc g: It 'd be fun to get like a a p visit from the grad h: There was a dorm room at Tech that , someone had coated the walls and the ceiling , and , the floor with mattresses . professor b: What did we mean by that ? Remember @ @ ? grad h: Liz wanted to talk about methods of improving accuracy by doing pre - processing . phd a: Well I think that that was just sort of I I already asked Thilo professor b: Oh , you already did that . phd a: but that , it would be helpful if I can stay in the loop somehow with , people who are doing any kind of post - processing , whether it 's to separate speakers or to improve the signal - to - noise ratio , or both , that we can sort of try out as we 're running recognition .  , so , i is that Who else is work I guess Dan Ellis and you phd c: Dan , yeah . professor b: he 's he 's interested in in fact we 're look starting to look at some echo cancellation kind of things . professor b: Which  grad h: I am not sure how much that 's an issue with the close talking mikes , professor b:  ? grad h: but who knows ? professor b: Well , let 's w i isn't that what what you want phd a: I don't know . I 'm bad professor b: t No , so No , i w wha what you what you want when you 're saying improving the wave form you want the close talking microphone to be better . professor b: And the question is to w to what extent is it getting hurt by ,  by any room acoustics or is it just  , given that it 's close it 's not a problem ? phd a: It doesn't seem like big room acoustics problems to my ear professor b:  phd a: but I 'm not an expert . grad h: e I bet with the lapel mike there 's plenty , room acoustic phd a: That that may be true . phd a: But I don't know how good it can get either by those the those methods grad h: Yeah . grad h: So I I think it 's just , phd a: Oh , I don't know . phd a: All I meant is just that as sort of as this pipeline of research is going on we 're also experimenting with different ASR , techniques . phd e: So the problem is like , on the microphone of somebody who 's not talking they 're picking up signals from other people and that 's causing problems ? phd a: R right , although if they 're not talking , using the the inhouse transcriptions , were sort of O K because the t no one transcribed any words there and we throw it out . phd a: But if they 're talking at all and they 're not talking the whole time , so you get some speech and then a "  -  " , and some more speech , so that whole thing is one chunk . And the person in the middle who said only a little bit is picking up the speech around it , that 's where it 's a big problem . postdoc g: You know , this does like seem like it would relate to some of what Jose 's been working on as well , the encoding of the phd d: Yeah . postdoc g: And and he also , he was phd a: The energy , phd d: Yeah , phd a: right . postdoc g: I was t I was trying to remember , you have this interface where you i you ha you showed us one time on your laptop that you you had different visual displays as speech and nonspeech events . Because , eh , it 's possible , eh , eh , in a simp sample view , to , nnn , to compare with c with the segment , the the kind of assessment what happened with the the different parameters . And only with a different bands of color for the , few situation , eh , I consider for acoustic event is enough to @ @ . phd d: I I I see that , eh , you are considering now , eh , a very sophisticated , eh , ehm , eh , @ @ set of , eh , graphic s eh , eh , ehm , si symbols to to transcribe . No ? Because , before , you you are talking about the the possibility to include in the Transcriber program eh , a set of symbols , of graphic symbol to t to mark the different situations during the transcription postdoc g: Oh , I w  - huh . No ? postdoc g: Well , you 're saying So , symbols for differences between laugh , and sigh , and and and slam the door and stuff ? phd d: Yeah . postdoc g: Or some other kind of thing ? phd d: No ? To to mark postdoc g: Well , I wouldn't say symbols so much . The the main change that I that I see in the interface is is just that we 'll be able to more finely c  , time things . postdoc g: But I I also st there was another aspect of your work that I was thinking about when I was talking to you phd a:  . postdoc g: which is that it sounded to me , Liz , as though you and , maybe I didn't q understand this , but it sounded to me as though part of the analysis that you 're doing involves taking segments which are of a particular type and putting them together . postdoc g: And th so if you have like a p a s you know , speech from one speaker , then you cut out the part that 's not that speaker , phd a:   postdoc g: and you combine segments from that same speaker to and run them through the recognizer . Is that right ? phd a: Well we try to find as close of start and end time of as we can to the speech from an individual speaker , postdoc g:   phd a: because then we we 're more guaranteed that the recognizer will for the forced alignment which is just to give us the time boundaries , because from those time boundaries then the plan is to compute prosodic features . phd a: And the sort of more space you have that isn't the thing you 're trying to align the more errors we have .  , so , you know , that that it would help to have either pre - processing of a signal that creates very good signal - to - noise ratio , postdoc g:   phd a: which I don't know how possible this is for the lapel , or to have very to have closer , time you know , synch times , basically , around the speech that gets transcribed in it , or both . So I just wanted to see , you know , on the transcribing end from here things look good . And then the issue of like global processing of some signal and then , you know , before we chop it up is is yet another way we can improve things in that . You can ,   The problem is just that the acoustic when the signal - to - noise ratio is too low , you you 'll get , a  an alignment with the wrong duration pattern or it phd e: Oh , so that 's the problem , is the the signal - to - noise ratio . It 's not the fact that you have like  , what he did is allow you to have , words that were in another segment move over to the at the edges of of segmentations . phd a: Right , things things near the boundaries where if you got your alignment wrong phd e:   It 's that there are problems even in inside the alignments , because of the fact that there 's enough acoustic signal there t for the recognizer to to eat , as part of a word . So , yeah , bottom bottom line is just I wanted to make sure I can be aware of whoever 's working on these signal - processing techniques for , detecting energies , phd d: Yeah . professor b: O K ,  tea has started out there I suggest we c run through our digits and , postdoc g: OK