, why don't we s again start off with with , Yeah , I 'll get it . And then , given that , Liz and Andreas are gonna be ten , fifteen minutes late , we can try to figure out what we can do most effectively without them here .  , what else ? grad f:  professor d:  What 's SmartKom ? SmartKom ? grad f: we wanna talk about if w if we wanna add the data to the mar Meeting Recorder corpus . professor d: What what what are we collecting here ? phd e: Data ? grad f: So why don't we have that on the agenda and we 'll we 'll get to it and talk about it ? phd e: The SmartKom data ? professor d: Yeah , right . I think it was Andreas wanted to talk about segmentation and recognition , and update on SRI recognition experiments . professor d:  grad f: And then if ti if there 's time I wanted to talk about digits , but it looked like we were pretty full , so I can wait till next week . I think the a certainly the segmentation and recognition we wanna maybe focus on when An - Andreas is here since that was particularly his thing . phd e: And also the SmartKom thing should b professor d: SmartKom also , Andreas . professor d:  So , I think they 'll be inter I 'll be interested in all this , but but , probably , if we had to pick something that we would talk on for ten minutes or so while they 're coming here . Or I guess it would be , you think , reorganization status , or ? grad f: Yeah . phd b: maybe I said maybe we said this before just that we met and we talked about it and we sort of have a plan for getting things organized and postdoc a: And I and I think a crucial part of that is the idea of of not wanting to do it until right before the next level zero back - up so that there won't be huge number of of added , phd b: Right . Not not much @ @ grad f: Although Dave basically said that if we wanna do it , just tell him and he 'll do a d level zero then . phd b: Oh , so maybe we should just go ahead and get everything ready , and grad f: Yep . So , I think we do need to talk a little bit about Well , we don't need to do it during this meeting . So , naming conventions and things like that , that I 've been trying to keep actually up to date . postdoc a: I 'm sorry , you 've been what ? Showing them ? professor d: OK . Well , maybe  , since that that was a pretty short one , maybe we should talk about the IBM transcription status . So , we ,  we did another version of the beeps , where we separated each beeps with a spoken digit . Chuck came up here and recorded some di himself speaking some digits , and so it just goes " beep one beep " and then the phrase , and then " beep two beep " and then the phrase .  , I think they 'll have a b easier time keeping track of where they are in the file . grad f: And we did it with the automatic segmentation , and I don't think We ne we didn't look at it in detail . phd b: And grad f: I sorta spot - checked here and there and it sounded pretty good . grad f: And , we 'll just hafta see what we get back from them .  phd b: And the main thing will be if we can align what they give us with what we sent them . phd b: And I think we 'll be able to do that at with this new beep format . grad f: so the problem wi last time is that there were errors in the transcripts where they put beeps where there weren't any , or and they put in extraneous beeps . phd b: Yeah , one interesting note is  , or problem I dunno if this was just because of how I play it back , I say , SND - play and then the file , every once in a while , @ @  , like a beep sounds like it 's cut into two beeps . phd b: Yeah , and I I dunno if that 's an , artifact of playback phd e: Yeah . But with this new format , that hopefully they 're not hearing that , and if they are , it shouldn't throw them . grad f: Well , maybe we better listen to it again , make sure , but , certainly the software shouldn't do that , phd b: Yeah . phd b: I it 's probably just , you know , mmm , somehow the audio device gets hung for a second , phd e: Yeah . phd e: Yeah ? postdoc a: As long as they have one number , and they know that there 's only one beep maximum that goes with that number . postdoc a: Well , you know , actually , are we having them phd b: So th grad f: " Seven four eight beep seven beep eight three two " . postdoc a: Yeah , but are we having them do digits ? grad f: Yes . Because , we don't we didn't In order to cut them out we 'd have to listen to it . phd b: We can we can ignore it when we get it back , grad f: Although we could tell them we could tell them , if you hear someone reading a digits string just say " bracket digit bracket " phd b: huh . That 'd be what I 'm having the transcribers here do , cuz it can be extracted later . And then I wanted to talk about but as I said I we may not have time what we should do about digits . professor d: Le - let 's talk about it , because that 's that 's something that I I know Andreas is less interested in than Liz is , grad f: OK . It 's good grad f: Do we have anything else to say about transcription ? About IBM stuff ? phd b: Brian I I sent bresset sent Brian a message about the meeting and I haven't heard back yet .  , how 're we doing on the on the rest of it ? postdoc a: We 're doing well . postdoc a: And , I 've prepared , a set of five which I 'm which I 'm calling set two , which are now being edited by my head transcriber , in terms of spelling errors and all that . She 's also checking through and mar and and monitoring , the transcription of another transcriber . postdoc a: And , I 've moved on now to what I 'm calling set three . I sort of thought if I do it in sets groups of five , then I can have , like , sort of a a parallel processing through through the the current . postdoc a: And and you indicated to me that we have a g a goal now , for the for the , the , DARPA demo , of twenty hours . So , I 'm gonna go up to twenty hours , be sure that everything gets processed , and released , and and that 's that 's what my goal is . Package of twenty hours right now , and then once that 's done , move on to the next . But I guess the other thing is that , that that 's kinda twenty hours ASAP because the longer before the demo we actually have the twenty hours , the more time it 'll be for people to actually do cool things with it . And and I don't think it 's possible , really , to do this full - time , but , that what it shows is motivation to do as many hours as possible . professor d: Yeah , I guess the So the difference if if , if the IBM stuff works out , the difference in the job would be that they p primarily would be checking through things that were already done by someone else ? postdoc a: Again . We 'll we 'll expect that they 'll have to move some time bins and do some corrections . postdoc a: And I you know , I 've also d  , discovered So with the new transcriber I 'm  So  , lemme say that my ,  So ,  At present , the people have been doing these transcriptions a channel at a time . And , that sort of , is useful , and t you know , and then once in a while they 'll have to refer to the other channels to clear something up . Well , I realize that , w i we we 're using the pre - segmented version , and , the pre - segmented version is extremely useful , and wouldn't it be , useful also to have the visual representation of those segments ? And so I 've  , I , I 've trained the new one  , the new the newest one , to , use the visual from the channel that is gonna be transcribed at any given time . Because what happens then , is you scan across the signal and once in a while you 'll find a blip that didn't show up in the pre - segmentation . postdoc a: And that 'll be something like I it 's ver it 's interesting . A backchannel , or postdoc a: Once in a while it 's a backchannel . postdoc a: Sometimes it seems to be , similar to the ones that are being picked up . postdoc a: And they 're rare events , but you can really go through a meeting very quickly . You just you just , you know , yo you s you scroll from screen to screen , looking for blips . And , I think that we 're gonna end up with ,  better coverage of the backchannels , professor d: Yeah . postdoc a: but at the same time we 're benefitting tremendously from the pre - segmentation because there are huge places where there is just absolutely no activity at all . phd b: So they can they can , scroll through that pretty quick ? postdoc a: Yeah . So I think that that 's gonna , also eh , you know , speed the efficiency of this part of the process . grad f: so , we have a whole bunch of digits that we 've read and we have the forms and so on , but only a small number of that ha well , not a small number only a subset of that has been transcribed . And , Liz and Andreas actually they 're not here , but , they did say at one point that they thought they could do a pretty good job of just doing a forced alignment . And , again , I don't think we 'll be able to do with that alone , because , sometimes people correct themselves and things like that . But so , I was just wondering what people thought about how automated can we make the process of finding where the people read the digits , doing a forced alignment , and doing the timing . What about just actually doing recognition ? grad f: Well , we we know what they read , because we have the forms . phd b: Right , Morgan ? professor d:  phd b: Is that what you 're ? professor d: Yeah , I 'm I 'm not quite sure what I 'm talking about . And , there 's the issue that that they we know what what was said , but do we ? grad f: so one option i professor d: Because people make mistakes and stuff . I was just asking , just out of curiosity , if if with , the SRI recognizer getting one percent word error , would we would we do better ? So , if you do a forced alignment but the force but the but the transcription you have is wrong because they actually made mistakes , or false starts , it 's it 's much less c it 's much less common than one percent ? grad f: But that 's pretty uncommon . grad f: Well , I guess yeah , I guess if we segmented it , we could get one percent on digits . I 'm not saying it should be one way or the other , but it 's If grad f: But , Well , there there 're a couple different of doing it . You know , they 're doing it anyway , and unless we tell them different , they 're gonna transcribe it . professor d: Well grad f: And my my tendency right now is , well , if IBM comes back with this meeting and the transcript is good , just let them do it . professor d: Yeah , it 's Y you raised a point , kind of , euphemistically but , m maybe it is a serious problem . Ho - what will they do when they go hear " beep seven beep seven three five two "  , you think they 'll we 'll get ? grad f: It 's pretty distinct . postdoc a: Well it it well , it 'd be preceded by " I 'm reading transcript so - and - so " ? phd b: Yeah . postdoc a: So , I think if they 're processing it at grad f: it 'll be it will be in the midst of a digit string . grad f: So  it sure , there there might be a place where it 's " beep seven beep eight beep eight beep " . But , you know , they they 're they 're gonna macros for inserting the beep marks . We 'll have to see , but I don't think it 's gonna be a problem . Well , I I I dunno , I I think that that 's if they are in fact going to transcribe these things , certainly any process that we 'd have to correct them , or whatever is needs to be much less elaborate for digits than for other stuff . grad f: We have so many of them , and it 'd be nice to actually do something with them . Yeah , I phd i: You mean there 're more than ten ? grad f: Anything else ? Your mike is a little low there . So ,  You you have to go a little early , right ? At twenty phd i: Well , I can stay till about , three forty . professor d: So there was some  In in Adam 's agenda list , he had something from you about segmentation this last recognition ? phd i: Well , yeah . phd i: so , we had a discussion Don and Liz and I had discussion last week about how to proceed with , you know , with Don 's work , phd e: Ch phd i: and and and , one of the obvious things that occur to us was that we 're since we now have Thilo 's segmenter and it works , you know , amazingly well , we should actually basically re - evaluate the recognition , results using you know , without cheating on the segmentations . phd e: So phd i: And , that should be fairly phd e: And how do we find the transcripts for those so that ? Yeah . So , there 's actually phd e: It 's not that phd i: Why do you ask ? grad f: I could phd i: No , actually , NIST has ,  m a fairly sophisticated scoring program that you can give a ,  a time , grad f: Hand ones . phd i:  You know , you basically just give two time - marked sequences of words , and it computes the  the ,  you know , the the th phd b: It does all the work for you . phd i: So , it we just and we use that actually in Hub - five to do the scoring . phd e: So , basically you give some time constraints for for the references and for for the hypothesis , phd i: So , we ha Yeah . phd g: Maybe the start of your speech and the end of it , phd i: So do phd e: OK .  , so that was the one thing , and the other was that ,  What was the other problem ? Oh ! That Thilo wanted to use the recognizer alignments to train up his , speech detector . phd i: so that we could use ,  you know there wouldn't be so much hand labelling needed to ,  to generate training data for for the speech detector . phd i: So , you can you can phd b: It 'll give you a lot more data , too . So , it 's basically s I think , eight meetings or something which which I 'm using , and , it 's before it was twenty minutes of one meeting . phd i: That won't be perfect the alignments aren't perfect , phd e: Yeah . But phd i: but , it 's probably still better to have all this extra data , than phd g: Yeah . If you find that you can lower the false alarms that you get where there 's no speech , that would be useful for us to know . So , r right now you get f fal you know , false false , speech regions when it 's just like , breath or something like that , phd e: OK . phd g: and I 'd be interested to know the wha if you retrain  , phd e: Yeah . I 'll can make an can , like , make a c comparison of of the old system to the to the new one , and then phd g: Yeah , just to see if by doing nothing in the modeling of just having that training data wh what happens . professor d:  another one that we had on Adam 's agenda that definitely involved you was s something about SmartKom ? grad f: Right . So , Rob Porzel eh , Porzel ? and the ,  Porzel and the , SmartKom group are collecting some dialogues . grad f: Basically they have one person sitting in here , looking at a picture , and a wizard sitting in another room somewhere . And , it involves starting I believe starting with a It 's it 's always the wizard , but it starts where the wizard is pretending to be a computer and it goes through a , speech generation system . And they wanted to use this equipment , and so the w question came up , is well , here 's some more data . Should this be part of the corpus or not ? And my attitude was yes , because there might be people who are using this corpus for acoustics , as opposed to just for language . So , I just wanted to understand it , cuz I I 'm  , hadn't quite followed this process . So , it 's wizard in the sen usual sense that the person who is asking the questions doesn't know that it 's , a machi not a machine ? phd i: Right . phd i: Actually actually , w w the the We do this I dunno who came up with it , but I think it 's a really clever idea . We simulate a computer breakdown halfway through the session , and so then after that , the person 's told that they 're now talking to a ,  to a human . grad f: But of course they don't know that it 's the same person both times . phd i: So , we we collect we collect both human - computer and human - human data , essentially , in the same session . professor d: You might wanna try collecting it the other way around sometime , saying that th the computer isn't up yet postdoc a:  . professor d: and then so then you can separate it out whether it 's the beginning or end kind of effects . " phd b: It 's a lot more believable , too , grad f: " No ! " phd b: if you tell them that they 're the computer part is running on a Windows machine . grad f: Abort abort , retry , fail ? phd g: So did they actually save the far - field data ? phd e: Yes . phd g: Cuz at first they weren't they weren't sa phd i: Yeah . grad f: and I said , " well that 's silly , if if we 're gonna try to do it for a corpus , there might be people who are interested in acoustics . professor d: S phd e: We wer we just wanted to do phd i: No , the the question is do we save one or two far - field channels or all of them ? phd g: Right . professor d:  grad f: That that if we have someone who is doing acoustic studies , it 's nice to have the same for every recording . phd i: It 's to be traini to b training data and development data for the SmartKom system . phd b: Where does this ? professor d:  phd g: Maybe we can have him vary the microphones , too , professor d: Well , phd e: B phd g: or they 're different s speakers . grad f: Right ? phd e: But but I 'm not sure about the legal aspect of of that . phd e: What they or , is is that our data which we are collecting here , professor d: We 've never signed anything that said that we couldn't use anything that we did . professor d: I L look , it seems to me that if we 're doing it anyway and we 're doing it for these these purposes that we have , and we have these distant mikes , we definitely should re should save it all as long as we 've got disk space , phd i:   professor d: So should we save it ? grad f: And then professor d: Now th Yeah . professor d: anybody who 's training something up could choose to put it eh , to u include this or not . But it 's some other data we have , and if somebody doing experiment wants to train up including that then they can . grad f: So it 's It it I guess it the begs the question of what is the meeting corpus . So if , at UW they start recording two - person hallway conversations is that part of the meeting corpus ? professor d: I think it 's I I think I th think the idea of two or more people conversing with one another is key . phd g: What if we just give it a a name like we give these meetings a name ? professor d: No , it doesn't . phd g: And then later on some people will consider it a meeting and some people won't , postdoc a: Well this professor d: Yeah . So so s so part of the reason that I wanted to bring this up is , do we wanna handle it as a special case or do we wanna fold it in , phd g: and Just give it a title . professor d: I think it is a s grad f: we give everyone who 's involved as their own user ID , give it session I Ds , let all the tools that handle Meeting Recorder handle it , or do we wanna special case it ? And if we were gonna special case it , who 's gonna do that ? phd e: So . phd i: Well , it it makes sense to handle it with the same infrastructure , since we don't want to duplicate things unnecessarily . phd e: It it it postdoc a: I think phd i: But as far as distributing it , we shouldn't label it as part of this meeting corpus . phd i: We should let it be its own corp postdoc a: Well it 's it well , because grad f: I don't see why not . professor d: It 's scenario - based , it 's it 's human - computer interface it 's really pretty different . professor d: But I I I have no problem with somebody folding it in for some experiment they 're gonna do , but I don't think i it it doesn't match anything that we 've described about meetings . professor d: Whereas everything that we talked about them doing at at UW and so forth really does . So w so what does that mean for how we are gonna organize things ? postdoc a:  . professor d: You can you can Again , as as I think Andreas was saying , if you wanna use the same tools and the same conventions , there 's no problem with that . It 's just that it 's , you know , different directory , it 's called something different , it 's you know . Right ? grad f: Yeah , but those are folded in , phd i: It might also be potentially confusing . grad f: and just simply in the file you mark somewhere that this is this type of interaction , rather than another type of interaction . phd i: Yeah , I th professor d: Well , I don I wouldn't call reading digits " meetings " . Right ?  , we we we were doing grad f: Well , but but , I put it under the same directory tree . professor d: Well grad f: You know , it 's in " user doctor speech data MR " . phd g: Can we just have a directory called , like , " other stuff " ? grad f: Other . My preference is to have a single procedure so that I don't have to think too much about things . professor d: O - You you can use whatever procedure you want that 's p convenient for you . grad f: If we do it any other way that means that we need a separate procedure , and someone has to do that . professor d: All I 'm saying is that there 's no way that we 're gonna tell people that reading digits is meetings . And similarly we 're not gonna tell them that someone talking to a computer to get travel information is meetings . But if it makes it easier for you to pu fold them in the same procedures and have them under the same directory tree , knock yourself out . phd b: There 's a couple other questions that I have too , professor d: You know ? phd b: and and one of them is , what about , consent issues ? And the other one is , what about transcription ? Are ? phd e: Transcription is done in Munich . phd i: That 's a that 's another argument to keep it separate , because it 's gonna follow the SmartKom transcription conventions and not the ICSI meeting transcription conventions . But I 'm sure no one would have a problem with our folding it in for some acoustic modeling or or some things . Do we h do we have , American - born folk , reading German German , pla  , place names and so forth ? Is that ? phd e: Yeah . professor d: Heidelberg grad f: So phd i: Exactly grad f: Disk might eventually be an issue so we might we we might need to , get some more disk pretty soon . grad f: We 're probably a little more than that because we 're using up some space that we shouldn't be on . So , once everything gets converted over to the disks we 're supposed to be using we 'll be probably , seventy - five percent . phd b: Well , when I was looking for space for Thilo , I found one disk that had , I think it was nine gigs and another one had seventeen .  grad f: Were those backed - up or non - backed - up ? phd b: Those were non - backed - up . The non - backed - up , phd b: I haven't looked to see how much of that we have . So , pretty much anytime we need a disk , we can get it at the rate that we 're phd i: You can I shouldn't be saying this , but , you can just you know , since the back - ups are every night , you can recycle the backed - up diskspace . professor d:  Yeah , I me and there 's been this conversation going on about getting another file server , and and we can do that . professor d: We 'll take the opportunity and get another big raft of of disk , I guess . phd i: Well , I think I think there 's an argument for having you know , you could use our old file server for for disks that have data that is very rarely accessed , and then have a fast new file server for data that is , heavily accessed . It 's the back it 's the back - up capaci grad f: It 's the back - up system . phd b: I think I think the file server could become an issue as we get a whole bunch more new compute machines . phd b: And we 've got , you know , fifty machines trying to access data off of Abbott at once . phd i: I think I think we 've raised this before and someone said this is not a reliable way to do it , but the What about putting the stuff on , like , C - CD - ROM or DVD or something ? grad f: Yeah . The the th phd i: But they wear out just from sitting on the shelf ? grad f: Yep . grad f: But the r the write once , and the read - writes , don't last . postdoc a: Would it be ? professor d: Year or two ? grad f: Yep . phd i: But if that then you would think you 'd hear much more clamoring about data loss phd e: Yeah . phd i: and professor d: yeah , all the L grad f: I I don't know many people who do it on CD .  , they 're the most fo professor d: LDC - all the LDC distributions are on CD - ROM . grad f: They 're on CD , but they 're not tha that 's not the only source . But if you go if you go k phd i: But , you know , we have phd g: But we have like thirty you know , from ten years ago ? professor d: We have all sorts of CD - ROMs from a long time ago . grad f: The the pressed ones last for phd g: usually they 're grad f: well , not forever , they 've been finding even those degrade . grad f: But , the burned ones  , when I say two or three years what I 'm saying is that I have had disks which are gone in a year . phd g: That 's what I grad f: On the average , it 'll probably be three or four years . But ,  I I you don't want to per p have your only copy on a media that fails . phd i: So how about ? So so how about putting them on that plus , like on a on on DAT or some other medium that isn't risky ? grad f: I think th  , we can already put them on tape . Well , if if if you if they last Say , they actually last , like , five years , huh , in in the typical case , and and occasionally you might need to recreate one , and then you get your tape out , but otherwise you don't . Can't you just you just put them on ? grad h: So you just archive it on the tape , and then put it on CD as well ? phd i: Yeah . phd b: What 'd be nice is a system that re - burned the C Ds every year . professor d: Well grad f: Well , the C Ds are are an op phd e: Yeah . professor d: You know I would think grad f: So for archiving , we 'll just use tape . phd i: One one thing I don't understand is , if you have the data if if you if the meeting data is put on disk exactly once , then it 's backed - up once and the back - up system should never have to bother with it , more than once . grad f: Well , regardless Well , first of all there was , a problem with the archive in that I was every once in a while doing a chmod on all the directories an or recursive chmod and chown , because they weren't getting set correctly every once in a while , phd i:   grad f: and I was just , doing a minus R star , not realizing that that caused it to be re - backed - up . phd i: But but this back - up system is smart enough to figure out that something hasn't changed and doesn't need to be backed - up again . professor d: The b I think th the at least the once tha that you put it on , it would it would kill that . grad f: Sure , but we still have enough changed that the nightly back - ups are starting to take too long . So , what if we buy , what what do they call these ,  high density ? grad f: Well , why don't you have this have a this conversation with Dave Johnson tha rather than with me ? phd i: No , no . Because this is maybe something that we can do without involving Dave , and and , putting more burden on him . How about we buy , one of these high density tape drives ? And we put the data actually on non - backed - up disks . And we do our own back - up once and for all all , and then and we don't have to bother this @ @ up ? grad f: Actually , you know , we could do that just with the tape with the current tape . What kind of tape drive is it ? grad f: I dunno but it 's an automatic robot so it 's very convenient . phd i: Is it is ? professor d: Wh The o the one that we have ? grad f: You just run a program to restore them . phd i: But it might interfere with their back - up schedule , phd g: But professor d: No , we have s we Don't we have our own ? phd i: eh . professor d: Something wi th that doesn't that isn't used by the back - up gang ? Don't we have something downstairs ? postdoc a: Well they phd b: What kinda tape drive ? professor d: Just in ? Yeah . So your your point is , and I think it 's a good one , that we could just get more disk and put it there . professor d: Yeah , that 's basically what I was gonna say , is that a disk is is so cheap it 's es essentially , you know , close to free . professor d: And we can take care of that by putting it on non - back up drives and just backing it up once onto this tape . phd g: So , who 's gonna do these back - ups ? The people that collect it ? grad f:  Well , I 'll talk to Dave , and and see what th how what the best way of doing that is . phd b: It 's probably gonna n grad f: There 's a little utility that will manually burn a tape for you , and that 's probably the right way to do it . That 's what I 'm wondering , if grad f: Well we 're g we 're gonna automate that . phd g: you don't have to physically put a tape in the drive ? grad f: No . phd i: Yeah , but then you 're effectively using the resources of the back - up system . phd i: Yeah , just give a dedi grad f: It we already have it there and it it 's phd i: Well , I 'm saying is @ @ i if you go to Dave , and and and ask him " can I use your tape robot ? " , he will say , " well that 's gonna screw up our back - up operation . He 'll say " if if that means that it 's not gonna be backed - up standardly , great . phd g: What about if the times overlap with the normal back - up time ? grad f: it 's it 's just it 's just a utility which queues up . grad f: And then you can tell it to then remove it from the disk or you can , you know , do it a a few days later or whatever you wanna do , after you confirm that it 's really backed - up . grad f: NW ? postdoc a: You saying NW archive ? grad f: NW archive . postdoc a: Yep And if you did that during the day it would never make it to the nightly back - ups . phd i: Well , it if he you have to put the data on a on a non - backed - up disk to begin with . postdoc a: Well , but you can have it NW archive to you can have , a non - backed - up disk NW archived , grad f: Right . phd i: So that so that otherwise you don't you postdoc a: and it 'll never show up on the nightly back - ups . grad f: So , that means we 'll probably wanna convert all all those files filesystems to non - backed - up media . professor d: another , thing on the agenda said SRI recognition experiments ? What 's that ? phd i: SRI recognition ? Oh . Chuck , do you have any any updates ? phd b: N I 'm successfully , increasing the error rate . So ,  I 'm just playing with , the number of Gaussians that we use in the the recognizer , and phd i: Well , you have to sa you have to tell people that you 're you 're doing you 're trying the tandem features . It sai because  , the meeting before , you said " OK , we got it down to where they 're they 're within a tenth of a percent " . phd i: So so , when So I I had I ha grad f: That was a quick response . phd i: So , we had reached the point where phd g: I 'm well rehearsed . phd i: we had reached the point where , on the male portion of the development set , the ,  or one of the development sets , I should say the ,  the male error rate with , ICSI PLP features was pretty much identical with , SRI features . phd i: So , phd g: Is there less training data ? phd i:  phd g: we don phd i: No , actually there 's more training data . So ,  so then  Oh , and plus the the vocal tract length normalization didn't actually made things worse . phd i: So So professor d: So but you see , now , between between the males and the females , there 's certainly a much bigger difference in the scaling range , than there is , say , just within the males . And what you were using before was scaling factors that were just from the the m the SRI front - end . professor d: but now you 're looking over a larger range and it may not be so fine . phd i: Well ,  So I just d so the one thing that I then tried was to put in the low - pass filter , which we have in the So , most most Hub - five systems actually band - limit the  , at about , thirty - seven hundred , hertz . So ,  And I 'm now , trying the Oh , and suddenly , also the v the vocal tract length normalization only in the test se on the test data . So , you can do vocal tract length normalization on the test data only or on both the training and the test . phd i: And you expect it to help a little bit if you do it only on the test , and s more if you do it on both training and test . phd i: And so the It now helps , if you do it only on the test , and I 'm currently retraining another set of models where it 's both in the training and the test , and then we 'll we 'll have , hopefully , even better results . So But there 's It looks like there will still be some difference , maybe between one and two percent , for the females . phd i: And it is true that the ,  that the you know , we are using the But it can't be just the VTL , professor d:  - huh . phd i: because if you don't do VTL in both systems , you know , the the females are considerably worse in the with the PLP features . phd g: Well , what 's the standard ? Yeah , so I thought the performance was actually a little better on females than males . phd i: that ye overall , yes , but on this particular development test set , they 're actually a little worse . We 're looking at the discrepancy between the SRI system and the SRI system when trained with ICSI features . I 'm just wondering if that if if you have any indication of your standard features , grad f: What 's Are the freq ? phd g: you know , if that 's also different or in the same direction or not . professor d: You 're This is lemme ask a q more basic que phd g: Cuz professor d: is this , iterative , Baum - Welch training ? phd i:   professor d: Or is it Viterbi training ? Or ? phd i: It 's Baum - Welch training . And how do you determine when to to stop iterating ? phd i:  Well , actually , we we just basically do a s a fixed number of iterations .  , which Eh , we used to do only three , and then we found out we can squeeze And it was basically , we 're s we 're keeping it on the safe side . It might be that one more iteration would would help , but it 's sort of professor d: Or maybe or maybe you 're doing one too many . professor d:  it 's it 's phd i: No , but with Baum - Welch , there shouldn't be an over - fitting issue , really . grad f: Well , you can try each one on a cross - validation set , phd i:  . professor d: It d if you if you remember some years ago Bill Byrne did a thing where he was he was looking at that , grad f: can't you ? professor d: and he showed that you could get it . We can Well , that 's that 's the easy one to check , professor d: Yeah . phd i: because we save all the intermediate models grad f: Do you ? phd i: and we can professor d: And in each case , ho grad f: What ? professor d: I 'm sorry in each case how do you determine , you know , the the usual fudge factors ? The ,  the , language , scaling , acoustic scaling ,  phd i:  I  I 'm actually re - optimizing them . And the pru the question he was asking at one point about pruning ,  Remember that one ? phd i: Pruning ? professor d: Well , he was he 's it looked like the probabil at one point he was looking at the probabilities he was getting out at the likelihoods he was getting out of PLP versus mel cepstrum , and they looked pretty different , phd i: Pruning in the ? phd b: Yeah , the likelihoods were lower for the PLP . professor d: And so , there 's the question phd i: I you mean did you see this in the SRI system ? phd b:   Well , the likelihoods are phd b: and phd i: You can't directly compare them , because , for every set of models you compute a new normalization . professor d: But , still it 's a question phd i: So professor d: if you have some threshold somewhere in terms of beam search or something , phd b: Well , yeah .   phd b: if you have one threshold that works well because the range of your likelihoods is in this area phd i: We prune very conservatively .  , as we saw with the meeting data ,  we could probably tighten the pruning without really So we we basically we have a very open beam . professor d: Right ? Here we 're - we 're saying that we there gee , there 's this b eh , there 's this difference here . Right ? But but but but , let 's suppose just for a second that , we 've sort of taken out a lot of the the major differences , between the two . professor d: we 're already sort of using the mel scale and we 're using the same style filter integration , and and , well , we 're making sure that low and high phd i: Actually , there is the difference in that . grad f: And what 's the top frequency of each ? phd i: Well , now it 's the same . But professor d: Before we i i th with straight PLP , it 's trapezoidal also . phd i: Well But professor d: But then we had a slight difference in the in the scale . phd i: Since currently the Feacalc program doesn't allow me to change the filter shape independently of the scale . phd i: And , I did the experiment on the SRI front - end where I tried the y where the standard used to be to use trapezoidal filters . So , it 's not I don't think the filter shape by itself will make a huge difference . professor d: So , f i We 've always viewed it , anyway , as the major difference between the two , is actually in the smoothing , that the that the , PLP , and and the reason PLP has been advantageous in , slightly noisy situations is because , PLP does the smoothing at the end by an auto - regressive model , phd i:   So one thing I haven't done yet is to actually do all of this with a much larger with our full training set . So right now , we 're using a I don't know , forty ? I i it 's it 's eh it 's a f training set that 's about , you know , by a factor of four smaller than what we use when we train the full system . phd i: And the Baum - Welch should be much less of a factor , if you go full whole hog . phd i: And so , w so , just  so the strategy is to first sort of treat things with fast turn - around on a smaller training set and then , when you 've sort of , narrowed it down , you try it on a larger training set . professor d: Now the other que related question , though , is is , what 's the boot models for these things ? phd i: Th - th the boot models are trained from scratch . So we compute ,  So , we start with a , alil alignment that we computed with the b sort of the best system we have . So we com we do a , you know , w  We collect the  , the observations from those alignments under each of the feature sets that that we train . And then , from there we do ,  There 's a lot of , actually The way it works , you first train a phonetically - tied mixture model . And then from that you you do the you you go to a state - clustered model , professor d: Yeah . This it migh Th - the thought is is is possible another possible partial cause is if the boot models used a comple used a different feature set , that phd i:   phd i: Yeah , but professor d: you know , they they will find boundaries a little differently , though You know , all th all that sort of thing is actually slightly different . I 'd expect it to be a minor effect , phd i: But but but , what I 'm what I 'm saying is professor d: but phd i: So , we e w f w For a long time we had used boot alignments that had been trained with a with the same front - end but with acoustic models that were , like , fifteen percent worse than what we use now . phd i: And with a dict different dictionary with a considerably different dictionary , which was much less detailed and much less well - suited . phd i: And so , then we switched to new boot alignments , which which now had the benefit of all these improvements that we 've made over two years in the system . phd i: So , what I 'm saying is , the exact nature of these boot alignments is probably not a big factor in the quality of the final models . But it it I st still see it as  , there 's there 's a history to this , too , phd i: Yeah . professor d: but but I I I th I think it could be the things that it the data is being viewed in a certain way , that a beginning is here rather than there and so forth , phd i: Yeah . Anyway , I I I should really reserve , any conclusions until we 've done it on the large training set , and until we 've seen the results with the with the VTL in training . At some point you also might wanna take the same thing and try it on , some Broadcast News data or something else that actually has has some noisy noisy components , so we can see if any conclusions we come to holds across different data . grad h:  ! professor d: So , is there something quick about Absinthe that you ? phd i: With this said . Just what we were talking about before , which is that I ported a Blass library to Absinthe , and then got got it working with fast - forward , and got a speedup roughly proportional to the number of processors times the clock cycle . grad f: I 'm in the process of doing it for Quicknet , but there 's something going wrong and it 's about half the speed that I was estimating it should be , and I 'm not sure why . But the what it means is that it 's likely that for net training and forward passes , we 'll Absinthe will be a good machine . phd i: A few more processors ? How many are you shooting for ? grad f: There 're five now . grad f: And it 's also five - fifty megahertz and you can get a gigahertz . phd i: Can you mix t  , processors of different speed ? grad f: I don't think so . grad f: We 'd have to get a almost certainly have to get a , Netfinity server . And , so , these are the demos for the  , July , meeting and ,  DARPA mee grad f: July what ? Early July ? Late July ? professor d: Oh , I think it 's July fifteenth . So , we talked about getting something together for that , but maybe ,  maybe we 'll just put that off for now , given that But I think maybe we should have a a sub - meeting , I think , probably , Adam and and , Chuck and me should talk about should get together and talk about that sometime soon . Gets our grad f: Which is gonna be a little hard for a couple people because we have different digits forms . So , the idea is just to read each line with a short pause between lines , grad c: Alright . grad f: not between And , since we 're in a hurry , we were just gonna read everyone all at once


But  we 're gonna try to make this an abbreviated meeting cuz the the next next occupants were pushing for it , so . Agenda is according to this , is transcription status , DARPA demos XML tools , disks , backups , et cetera and grad h: Does anyone have anything to add to the agenda ? professor b: OK . grad h:  phd d: I g grad h: as a somewhat segue into the next topic ,  could I get a hold of  the data even if it 's not really corrected yet just so I can get the data formats and make sure the information retrieval stuff is working ? postdoc a: Certainly . So I 'll I 'll probably just make some copies of those rather than use the ones that are there . grad h:  and then just we 'll have to remember to delete them once the corrections are made . professor b: OK , wh phd d: I also got anot a short remark to the transcription . I 've  just processed the first five EDU meetings and they are chunked up so they would they probably can be sent to IBM whenever they want them . phd d: but the other ones phd f: That 's the one that we 're waiting to hear from them on . postdoc a: These are separate from the ones that phd f: As soon as postdoc a: these are phd f: They 're the IBM set . And so as soon as we hear from Brian that this one is OK grad h: Is my mike on ? Yeah . phd f: and we get the transcript back and we find out that hopefully there are no problems matching up the transcript with what we gave them , then  we 'll be ready to go and we 'll just send them the next four as a big batch , postdoc a: Excellent . grad h: And so we 're doing those as disjoint from the ones we 're transcribing here ? phd f: Yes , exactly . phd f: We 're sort of doing things in parallel , that way we can get as much done a at once . grad h: Yeah , I think that 's the right way to do it , phd f: Yeah . grad h: Right , which  So I 've been working on using the THISL tools to do information retrieval on meeting data and the THISL tools are there 're two sets , there 's a back - end and a front - end , so the front - end is the user interface and the back - end is the indexing tool and the querying tool . So at least on the one meeting that I had the transcript for  conveniently you can now do information retrieval on it , do type in a a string and get back a list of start - end times for the meeting , phd f: What what kind of  what does that look like ? The string that you type in . phd f: What are you are you are they keywords , or are they ? grad h: Keywords . grad h: Right ? And so and then it munges it to pass it to the THISL IR which uses an SGML - like format for everything . professor b: And then does it play something back or that 's something you 're having to program ? grad h: right now , I have a tool that will do that on a command line using our standard tools , professor b: Yeah . grad h: but my intention is to do a prettier user interface based either So so that 's the other thing I wanted to discuss , is well what should we do for the user interface ? We have two tools that have already been written . grad h:  the other option is Dan did the Tcl - TK THISL GUI front - end for Broadcast News professor b: Yeah . postdoc a: I Can I ask a question ? So  as it stands within the the Channeltrans interface , it 's possible to do a find and a play . So e Are you So you 're adding like  , I don't know ,  are they fuzzy matches or are they  ? grad h: It 's a sort of standard , text - retrieval - based So it 's  term frequency , inverse document frequency scoring . grad h:  and then there are all sorts of metrics for spacing how far apart they have to be and things like that . So it it 's postdoc a: It 's a lot more sophisticated than the  the basically Windows - based grad h: i it 's like doing a Google query or anyth anything else like that . grad h: So i it uses So it pr produces an index ahead of time so you don't you 're not doing a linear search through all the documents . Cuz you can imagine if with if we have the sixty hours ' worth you do wouldn't wanna do a search . grad h:  you have to do preindexing and so that these tools do all that . And so the work to get the front - end to work would be porting it well  to get it to work on the UNIX systems , our side is just rewriting them and modifying them to work for meetings . grad h: So that it understands that they 're different speakers and that it 's one big audio file instead of a bunch of little ones and just sorta things like that . phd f: So what does the user see as the result of the query ? grad h: On which tool ? phd f: THISL . grad h: The THISL GUI tool which is the one that Dan wrote , Tcl - TK phd f: Yeah . grad h:  you type in a query and then you get back a list of hits and you can type on them and listen to them . professor b: Mmm phd f: So if you typed in " small heads " or something you could grad h: Right , you 'd get phd f: get back a   something that would let you click and listen to some audio where that phrase had occurred grad h: something You you 'd get to listen to " beep " . It 's too bad that that couldn't come into the grad h: You couldn't get a video . phd g: Guess who I practice on ? postdoc a: At some point we 're gonna have to say what that private joke is , that keeps coming up . Yeah , it loo it my my recollection of it is it 's it 's a pretty reasonable  demo sort of format . grad h: And so I think there 'd be minimal effort to get it to work , minimally phd f: That sounds really neat . grad h: and then we 'd wanna add things like query by speaker and by meeting and all that sort of stuff .  Dave Gelbart expressed some interest in working on that so I 'll work with him on it . And it it 's looking pretty good , you know , the fact that I got the query system working . grad h: If we wanna get it to Windows it 's gonna be a little more work because the THISL IR , the information retrieval tool 's  , I had difficulty just compiling them on Solaris . phd f: But you were saying that that the  that there 's that set of tools , Cygnus tools , that grad h: So . grad h: But what those they what those do is provide sort of a BSD compatibility layer , professor b:   phd f: And you have to have all the o grad h: But the problem is that that the THISL tools didn't use anything like Autoconf and so you have the normal porting problems of different header files and th some things are defined and some things aren't and  different compiler work - arounds and so on . So the fact that  it took me a day to get it c to compile under Solaris means it 's probably gonna take me s significantly more than that to get it to compile under Windows . professor b: How about having it run under free BSD ? phd e: Well what you need grad h: Free BSD would probably be easier . phd e: All you need to do is say to Dan " gee it would be nice if this worked under Autoconf " and it 'll be done in a day . phd d:  phd e: Right ? grad h: Actually you know I should check because he did port it to SPRACHcore phd e: Right . professor b: So grad h: I 'll check at that professor b: But it would what would serve would serve both purposes , is if you contact him and ask him if he 's already done it . phd e: What I phd f: How does it play ? grad h: Yeah , right . professor b: If he has then you learn , if he hasn't then he 'll do it . So , and I 've been corresponding with Dan and also with   , SoftSound guy ,  postdoc a: It 's amazing . professor b: Tony Robinson ? phd f: Tony Robinson ? grad h: Do  Tony ? I guess I do . grad h: Which one do  ? phd e: Steve Renals is not SoftSound , is he ? professor b: No . grad h: so that 's all going pretty well , professor b: Assuming we 're phd e: Right . phd f: What about issues of playing sound files @ @ between the two platforms ? grad h: I think we 'll be OK with that . phd e: Why don't you try and merge Transcriber and THISL IR ? They 're both Tcl interfaces . grad h: Well this is one of the reasons This is the one of the reasons that I 'm gonna have  Dave Gelbart Gelbart Having him volunteer to work on it is a really good thing because he 's worked on the Transcriber stuff phd e: Right . But the point is that the Transcriber uses Snack and then you can but you can use a a lot of the same functionality and it 's grad h: Yeah , yeah , I I think THISL THISL GUI probably uses Snack . Well my thought was is that it would be nice it would be nice to have the running transcripts  eh you know , from speaker to speaker . grad h: And if it doesn't phd e: Right ? Do you have you have , you know , a speaker mark here and a speaker mark here ? grad h: Right , we 'll have to figure out a user interface for that , so . It might be fairly difficult to get that to work in the little short segments we 'd be talking about and having the search tools and so on . grad h: but professor b: The thing I was asking about with , free BSD is that it might be easier to get PowerPoint shows running in free BSD than to get this other package running in grad h: Yeah ,  we have to I have to sit down and try it before I make too many judgments , professor b: Yeah . grad h: so   My experience with the Gnu compatibility library is really it 's just as hard and just as easy to port to any system . grad h: It 's just , you know , just like all of them , the " include " files are a little different and the function calls are a little different . grad h: So I it might be a little easier but it 's not gonna be a lot easier . So there was that demo , which was one of the main ones , then we talked about  some other stuff which would basically be  showing off the the Transcriber interface itself and as you say , maybe we could even merge those in some sense , but but  ,  and part of that was showing off what the speech - non  nonspeech stuff that Thilo has done s looks like . postdoc a: Can I ask one more thing about THISL ? So with the IR stuff then you end up with a somewhat prioritized  ? grad h:   phd g: So another idea I w t had just now actually for the demo was whether it might be of interest to sh to show some of the prosody  work that Don 's been doing . phd g:  actually show some of the features and then show for instance a task like finding sentence boundaries or finding turn boundaries . professor b: Well I think at at the very least we 're gonna want something illustrative with that phd g: I don't know if that would be of interest or not . professor b: cuz I 'm gonna want to talk about it and so i if there 's something that shows it graphically it 's much better than me just having a bullet point phd g: Yeah . professor b: pointing at something I don't know much about , phd g: you 're looking at this now professor b: so . phd g: Are you looking at Waves or Matlab ? grad c:  yeah I 'm starting to and  Yeah we can probably find some examples of different type of prosodic events going on . phd g: Yeah def professor b: S so when we here were having this demo meeting , what we 're sort of coming up with is that we wanna have all these pieces together , to first order , by the end of the month phd g: I professor b: and then that 'll give us a week or so . The end of phd g: Oh , the end of this month or next month ? Oh , you mean like today ? grad h: This month . professor b:  that 'll that 'll give us that 'll give us a week or so to  to port things over to my laptop and make sure that works , phd e: Exactly . phd g: Yeah if d if Don can sort of talk to whoever 's professor b: Yeah . phd g: cuz we 're doing this anyway as part of our you know , the research , visualizing what these features are doing professor b: Yeah . professor b: so  , you know , to let s the goal is to let them know what it is we 're doing . professor b: So that 's phd g: I don't think anyone has done this on meeting data so it might be neat , you know . So I 've been doing a bunch of XML tools where you we 're sort of moving to XML as the general format for everything and I think that 's definitely the right way to go because there are a lot of tools that let you do extraction and reformatting of XML tools . So yet again we should probably meet to talk about transcription formats in XML because I 'm not particularly happy with what we have now .  it works with Transcriber but it it 's a pain to use it in other tools  because it doesn't mark start and end .  , but I 've installed XML tools of various sorts in various languages and so if people are interested in doing extracting any information from any of these files , either  information on users because the user database is that way I 'm converting the Key files to XML so that you can extract m  various inf  sorted information on individual meetings grad c: Cool . And so l just let me know there it 's mostly Java and Perl but we can get other languages too if if that 's desirable . Is do we have the the seat information ? In in the Key files now ? postdoc a:   grad h: The seat information is on the Key files for the ones which postdoc a: Ah . phd g: Oh in For the new one grad h: it 's been recorded , phd g: OK . phd g: I 'm just trying to figure out , you know , when Morgan 's voice appears on someone 's microphone are they next to him or are they across from him ? professor b: Yeah . phd f: how how w eh where is it in the Key file ? grad h: Right . phd g: Cuz  I haven't been putting it in and in by grad h: You haven't been putting it in . postdoc a: Isn't it always on the digits ? professor b: Some of these are missing . phd g: And professor b: Aren't they ? postdoc a: Isn't it always on the digits forms ? professor b: Some fall out of phd g: Well it grad h: Yeah so we can go back and fill them in for the ones we have . phd g:  they 're on th right , these , but I just hadn't ever been putting it in the Key files . phd f: Yeah I I never phd g: And I don't think Chuck was either phd f: I never knew we were supposed to put it in the Key file . phd g: cuz grad h: I had told you guys about it phd f: Oh really ? phd g: Oh , so we 're both sorry . grad h: but phd g: So grad h:  this is why I wanna use a g a tool to do it rather than the plain text phd g: OK . grad h: I think it 's Edit - key , command Did I show you guys that ? phd d: Yep . phd f: You mentioned it , grad h: I did show it to you , phd f: yeah . grad h: but I think you both said " no , you 'll just use text file " . grad h: Yeah , and so if you don't fill it in , you 're not gonna get it in the meetings . grad c: u grad h: Yeah and then the other thing also that Thilo noticed is , on the microphone , on channel zero it says hand - held mike or Crown mike , phd g: Yeah . phd g: maybe I forgot to d phd f: Takes me no time at all to edit these . grad h: Yeah that 's cuz you kn phd f: I 'm not doing anything . phd g: And I was I was looking at Chuck 's , like , " oh what did Chuck do , OK I 'll do that " . grad h: And then  also in a couple of places instead of filling the participants under " participants " they were filled in under " description " . Oh  also I 'm working on another version of this tool , the the one that shows up here , that will flash yellow if the mike isn't connected . And it 's not quite ready to go yet because  it 's hard to tell whether the mike 's connected or not because the best quality ones , the Crown ones , are about the same level if they 're off and no one 's o off or if they 're on and no one 's talking . So I 'm working on that and it it sorta works and so eventually we will change to that and then you 'll be able to see graphically if your mike is dropping in or out . grad c: Will that also include like batteries dying ? Just a any time the mike 's putting out zeros basically . phd f: But with the screensaver kicking in , it phd d: But grad h: Now phd d: y yeah . grad h:  the other thing is as I 've said before , it is actually on the thing . postdoc a: It would be nice if if these had little light indicators , little L E Ds for grad h:  buzzer . grad h: " Bamp , bamp ! " professor b: Small shocks postdoc a: Yeah . Oh grad h: OK , disk backup , et cetera ?  I spoke with Dave Johnson about putting all the Meeting Recorder stuff on non - backed - up disk to save the overhead of backup and he pretty much said " yeah , you could do that if you want " but he thought it was a bad idea . In fact what he said is doing the manual one , doing  NW archive to copy it is a good idea and we should do that and have it backed up . grad h: And so if a mistake is made and we lose the backup we should have the archive and if then a mistake is made and we lose the archive we should have the backup . professor b: Well I guess it is true that even with something that 's backed up it 's not gonna if it 's stationary it 's not going to go through the increment it 's not gonna burden things in the incremental backups . But he said that that we sh shouldn't worry too much about that , that we 're getting a new backup system and we 're far enough away from saturation on full backups that it 's w probably OK . professor b: Really ? grad h: And  , so the only issue here is the timing between getting more disks and  recording meetings . professor b: So I guess the idea is that we would be reserving the non - backed - up space for things that took less than twenty - four hours to recreate or something like that , right ? grad h: Things that are recreatable easily and also Yeah , basically things that are recreatable . professor b: Well I was allowing someone else to come up with something related that they had  phd e: I thought you guys were gonna burn C Ds ? grad h:  unfortunately we could burn C Ds but first of all it 's a pain . grad h: Because you have to copy it down to the PC and then burn it and that 's a multi - step procedure . And second of all the the write - once burners as opposed to a professional press don't last . grad h: So I think burning them for distribution is fine but burning them for backup is not a good idea . Can I add one top topic ? We have time ? I wanted to ask , I know that  that Thilo you were , bringing the Channeltrans interface onto the Windows machine ? And I wanted to know is th phd d: Yeah it 's it Basically it 's done , postdoc a: It 's all done ? That 's g wonderful . grad h: Yes , since Tcl - TK runs on it , basically things 'll just work . phd d: Yeah it Yeah , it was just a problem with the Snack version and the Transcriber version but it 's solved . Does this mean that the that this could be por  ported to a Think - Pad note or some other type of  phd d: Yeah , basically  I did install it on my laptop and yeah postdoc a: Wonderful . CrossPads ? CrossPads ? grad h:  got an email from  James Landay who basically said " if you 're not using them , could you return them ? " So he said he doesn't need them , he just periodically w at the end of each term sends out email to everyone who was recorded as having them and asks them if they 're still using them . professor b: Once ? grad h: We we used them a couple times , postdoc a:   phd f: Them ? There 's more than one ? grad h: but postdoc a: Yeah . professor b: But grad h: My opinion on it is , first , I never take notes anyway so I 'm not gonna use it ,  and second , it 's another level of infrastructure that we have to deal with . postdoc a: And I have  so my my feeling on it is that I think in principle it 's a really nice idea , and you have the time tags which makes it better tha than just taking ra raw notes . On the other hand , I the down side for me was that I think the pen is really noisy . And I and I don't know if it 's audible on the but I I sort of thought that was a disadvantage . I do take notes , I could be taking notes on these things and I guess the plus with the CrossPads would be the time markings but I don't know . phd d: what is a CrossPad ? professor b: So it 's it 's  it 's a regular pad , just a regular pad of paper but there 's this pen which indicates position . grad h: And then you can download it and they have OCR and searching and all sorts of things . grad h: But I don't take notes , professor b: And one of the reasons that it was brought up originally was because  we were interested in in higher - level things , grad h: so . professor b: not just the , you know , microphone stuff but also summarization and so forth and the question is if you were going to go to some gold standard of what wa what was it that happened in the meeting you know , where would it come from ? And  I think that was one of the things , phd d: Yeah . We 'll have a you know , have a scribe , have somebody  take good notes and then that 's part of the record of the meeting . And then we did it once or twice and we sort of grad h: Yep , and then just sort of died out . professor b: probably chose the wrong scribe but it was It 's  phd g:  grad h: Yeah that 's right . postdoc a: u but I guess the the other thing I 'm thinking is if we wanted that kind of thing I wonder if we 'd lose that much by having someone be a scribe by listening to the tape , to the recording afterwards and taking notes in some other interface . phd f:  we 're transcribing it anyways , why do we need notes ? postdoc a: Oh it 's la it 's useful , grad h: Because that 's summary . phd g: I think there 's also there 's this use that phd f: Summarize it from the transcription . phd g: the Well , what if you 're sitting there and you just wanna make an X and you don't wanna take notes and you 're you just wanna phd f: Doodle . phd g: get the summary of the transcript from this time location like you know , and and then while you 're bored you don't do anything and once in a while , maybe there 's a joke and you put a X and But in in other words you can use that just to highlight times in a very simple way . Also with I was thinking and I know Morgan disagrees with me on this but suppose you have a group in here and you wanna let them note whenever they think there might be something later that they might not wanna distribute in terms of content , they could just sort of make an X near that point or a question mark that sort of alerts them that when they get the transcript back they c could get some red flags in that transcript region and they can then look at it . I know we haven't been using it but I w I can imagine it being useful just for sort of marking time periods grad h: Right . professor b: I guess so , you know , what what makes one think i is maybe we should actually schedule some periods where people go over something later phd g: so . professor b: and and and put some kind of summary or something  you know , some there 'd be some scribe who would actually listen , w who 'd agreed to actually listen to the whole thing , not transcribe it , but just sort of write down things that struck them as important . But then you don't you don't have the time reference  that you 'd have if you had it live . And you don't have a lot of other cues that might be useful , professor b: Yeah . phd f: How do you synchronize the time in the CrossPad and the time of the recording ? phd g: so . grad h:  that was one of the issues we talked about originally and that that 's w part of the difficulty is that we need an infrastructure for using the time the CrossPads and so that means synchronizing the time phd g:  postdoc a:   grad h: You know you want it pretty close and there 's a fair amount of skew because it 's a hand - held unit with a battery postdoc a: Well when when I d grad h: and so you postdoc a: OK . grad h: so you have to synchronize at the beginning of each meeting all the pads that are being used , so that it 's synchronized with the time on that and then you have to download to an application , and then you have to figure out what the data formats are and convert it over if you wanna do anything with this information . phd e: Why grad h: And so there 's a lot of infrastructure which postdoc a: There is an alternative . grad h: unless someone postdoc a: There is an alternative , it 's still , there 's  you know , your point stands about there be needing to be an infrastructure , but it doesn't have to be synchronized with the little clock 's timer on it . You c  , I when I when I did it I synchronized it by voice , by whispering " one , two , three , four " onto the microphone grad h:  . grad h: Well , but then there 's the infrastructure at the other end phd e: Right . grad h: which someone has to listen to that and find that point , postdoc a: Yeah , it 's transcribed . phd g: Well , could we keep one of these things for another year ? Would h  is there a big cau grad h: We can keep all both of them for the whole whole year . phd g: just just in case we grad h: it 's just phd g: even maybe some of the transcribers who might be wanting to annotate  f just there 's a bunch of things that might be neat to do but I it might not be the case that we can actually synchronize them and then do all the infrastructure but we could at least try it out . professor b: Well one thing that we might try  is on some set of meetings , some collection of meetings , maybe EDU is the right one or maybe something else , we we get somebody to buy into the idea of doing this as part of the task . professor b:  part of the reason I think part of the reason that Adam was so interested in  the SpeechCorder sort of f idea from the beginning is he said from the beginning he hated taking notes and grad h: Yep . professor b: and so forth so and and Jane is more into it but eh  you know I don't know if you wanna really do do this all the time so I think the thing is to to get someone to actually buy into it and have at least some series of meetings where we do it . The p the the problem with the the more extended view , all these other you know with  quibbling about particular applications of it is that it looks like it 's hard to get people to   routinely use it ,  it just hasn't happened anyway . But maybe if we can get a person to phd g: Yeah I don't think it has to be part of a what everybody does in a meeting but it might be a useful , neat part of the project that we can , you know , show off as a mechanism for synchronizing events in time that happen that you just wanna make a note of , like what Jane was talking about with some later browsing , just just as a convenience , even if it 's not a full - blown note taking substitute . phd e: Well if you wanted to do that maybe the right architecture for it is to get a PDA with a wireless card . And and that way you can synchronize very easily with the the the meeting because you 'll be synchroni you can synchronize with the the Linux server and  phd g: So what kind of input would you be ? phd e: so so , if you 're not worried about grad h: Buttons . phd g: You 'd just be pressing like a a phd e: Well well you have a PDA and may and you could have the same sort of X interface or whatever , you 'd have to do a little eh a little bit of coding to do it . phd e: if if all you really wanted was you didn't want this secondary note - taking channel but just sort of being able to use m markers of some sort , a PDA with a l a wireless card would be the probably the right way to go . grad h:  for what what you 've been describing buttons would be even more convenient than anything else , phd g: M right . grad h: right ? You have the phd g: I don't have , you know , grandiose ideas in mind but I 'm just sort of thinking well we 've we 're getting into the next year now and we have a lot of these things worked out at in terms of the speech maybe somebody will be interested in this and postdoc a: I like this PDA idea . professor b: where like one one button was "  - oh " and then another button was " that 's great " and another button " that 's f " phd g: Or like this is my " I 'm supposed to do this " kind of button , postdoc a: Yeah . phd g: Yeah something like that or postdoc a: And then grad h:  I think the CrossPad idea is a good one . grad h: It 's just a question of getting people to use it and getting the infrastructure set up in such a way that it 's not a lot of extra work .  that 's part of the reason why it hasn't happened is that it 's been a lot of extra work for me phd g: Yeah . grad h: and postdoc a: But it 's also , it has this problem of having to go from an analog to a d a digital record too , phd g: W postdoc a: doesn't it ?  grad h: Well it 's digital but it 's in a format that is not particularly standard . postdoc a: But  , say , if i if if you 're writing if you 're writing notes in it does it it can't do handwriting recognition , right ? professor b: No , no , but it 's just it 's just storing the pixel informa position information , postdoc a: OK . postdoc a: I I guess what I 'm thinking is that the PDA solution you h you have it already without needing to go from the pixelization to a to a  professor b: Right . You don't have to phd e: The transfer function is less errorful , postdoc a: Oh , nicely put . phd g: Well it also it 's maybe realistic cuz people are supposed to be bringing their P D As to the meeting eventually , right ? That 's why we have this little I don't know what I don't wanna cause more work for anyone but I can imagine some interesting things that you could do with it and so if we don't have to return it and we can keep it for a year I don't know . grad h: Well w we don't we certainly don't have to return it , as I said . All all he said is that if you 're not using it could you return it , if you are using it feel free to keep it . The point is that we haven't used it at all and are we going to ? professor b: So we have no but  by I I would suggest you return one . phd g: We c professor b: We have some aspirations of using them phd g: One would probably be fine . professor b: and phd g: Maybe we could do like a student project , you know , maybe someone who wants to do this as their main like s project for something would be cool .  if we had them out and sitting on the table people might use them a little more professor b: Maybe Jeremy could sit in some meetings and press a button when there when when somebody laughed . grad h: although there is a little phd g: Well , I 'm yeah , that 's not a bad professor b: Yeah , yeah . phd g: Jeremy 's gonna be an he 's a new student starting on modeling brea breath and laughter , actually , which sounds funny but I think it should be cool , professor b: Yeah . phd g: You 're you 're gonna tease me ? grad h: Oh , equipment . grad h: And then at the same time I 'll probably rewire the room as per Jane 's suggestion so that  the first N channels are wireless , eh are the m the close - talking and the next N are far - field . professor b: You know what he means but isn't that funny sounding ? " We ordered more wireless . " It 's like wires are the things so you 're wiring you 're you 're you we 're we ordered more absence of the thing . phd g: I just it 's sort of a anachronism ,  it 's like It 's great . professor b:  there 's there 's all this stuff going on  between  Andreas and and and Dave and Chuck and others with various kinds of runs   recognition runs , trying to figure things out about the features but it 's it 's all sort of in process , so there 's not much to say right now . grad h: So just the transcript number and then the then the phd e: This is Yes , this is number two for me today . professor b: See all you have to do is go away to move way up in the phd e: Oh . grad h: Should we do simultaneous ? phd g: Well , I 'm just thinking , are you gonna try to save the data before this next group comes in ? professor b: Yeah . phd g: You have to plug your ears , by the way  Eric , grad h: Well I have to , phd d: You don't have to