And actually if everyone could cross out the R - nine next to " Session " , and write MR eleven . grad c: And let 's remember also to make sure that one 's gets marked as unread , unused . grad c: There 's lots of clicking I 'm sure as I 'm trying to get this to work correctly . Any agenda items today ? grad c: I wanna talk a little bit about getting how we 're gonna to get people to edit bleeps , parts of the meeting that they don't want to include . What I 've done so far , and I wanna get some opinions on , how to how to finish it up . postdoc f: I wanna ask about  , some aud audio monitoring on some of the  well some of the equipment . postdoc f: Ba - based on some of the tran  i In listening to some of these meetings that have already been recorded there are sometimes big spikes on particular things , and in pact in fact this one I 'm talking on is one of of the ones that showed up in one of the meetings , grad c: Oh really . postdoc f: so I phd b: " Spikes " , you mean like  , instantaneous click type spikes , or ? postdoc f:   grad c: It could be touching and fiddling , and the other thing is that it could the fact that it 's on a wired mike is suspicious . Well maybe Then we don't really have to talk about that as an phd b: You could try an experiment and say " OK , I 'm about to test for spikes " , postdoc f: I I take that off the agenda . phd b: and then wiggle the thing there , and then go and when they go to transcribe it , it could , ask them to come and get you . phd b: " Come get me when you transcribe this and see if there 's spikes . phd b: No I 'm just  professor e: were this a professional audio recording , what we would do what you would do is in testing it is , you would actually do all this wiggling and make sure that that that things are not giving that kind of performance . I guess I would like to have a discussion about you know where we are on  , recording , transcription you know , basically you know where we are on the corpus . professor e: And then  , the other thing which I would like to talk about which is a real meta - quest , I think , deal is , agendas . Andreas brought up the fact that he would kinda like to know , if possible , what we were gonna be talking about because he 's sort of peripherally involved to this point , and if there 's gonna be a topic about discussion about something that he  strongly cares about then he would come and And I think part of part of his motivation with this is that he 's trying to help us out , in the because of  the fact that the meetings are are tending to become reasonably large now on days when everybody shows up and so , he figures he could help that out by not showing grad c: Mmm . by not showing up if it 's a meeting that he 's he 's So ,  in order I 'd I think that this is a wish on his part . It 's actually gonna be hard because it seems like a lot of times  things come up that are unanticipated and and grad c: Right . professor e: But  , we could try anyway , do another try at coming up with the agenda  , at some point before the meeting , say the day before . grad c: Well maybe it would be a good idea for one of us to like on Wednesday , or Tuesday send out a reminder for people to send in agenda items . phd b: That 'll be I think that 'll help grad c: I 'll put that on my spare brain or it will not get done . professor e: Yeah , I have to tell you for the  for the admin meeting that we have , Lila does that  every time before an admin meeting . phd b: I would I would also guess that as we get more into processing the data and things like that there 'll be more things of interest to him . The other topic I was thinking of was the sta status on microphones and channels , and all that . grad c: Yeah , actually I I was going to say we need to talk about that too . First of all , if the other headsets are a lot more comfortable , we should probably just go ahead and get them . So we 'll have to evaluate that when they come in , phd a:  grad c: and get people 's opinions on on what they think of them . professor e: So how many channels do you get to have in a wireless setup ? grad c: well , I 'm pretty sure that you can daisy - chain them together so what we would do is replace the wired mikes with wireless . So we currently have one base station with six wireless mike , possibility of six wireless receivers , and apparently you can chain those together . And so we could replace our wired mikes with wireless if we bought another base station and more wireless mikes . grad c: And So , you know it 's still , it 's fifteen minus six . professor e: So let 's see we grad c: Right ? So we could have up to nine . grad c: And it 's  , about nine hundred dollars for the base station , and then eight hundred per channel . So yeah so the only Beyond the mike the cost of the mikes the only thing is the base station that 's nine hundred dollars . OK , so I 'll look into how you daisy - chain them and and then just go ahead and order them . grad c: No , we 're just replacing the wired the two wired that are still working , phd b: OK . grad c: along with a couple of the wired that aren't working , one of the wired that 's not working , with a wireless . phd b: Three wireds work , professor e: Basically we found phd b: right ? grad c: I I guess three wireds work , yeah . professor e: And so  , we we seem to have  , a reliable way of getting the data in , which is through the ra Sony radio mikes , as long as we 're conscious about the batteries . grad c: Everyone 's battery OK ? phd b: I checked them this morning , they should be . But the quality seems really good and  I heard from UW that they 're they 're  very close to getting their ,  setup purchased . They 're they 're they 're buying something that you can just sort of buy off the shelf . grad c: Well we should talk to them about it because I know that SRI is also in the process of looking at stuff , and so , you know , what we should try to keep everyone on the same page with that . grad c: They got sa apparent Well , Maybe this needs to be bleeped out ? I have no clue . But anyway there 's there 's there 's  ,  other activities that are going on there and and  and NIST and UW . But but yeah I thin I think that at least the message we can tell other people is that our experience is is quite positive with the Sony , grad c: Right . Now the one thing that you have said that actually concerns me a little is you 're talking about changing the headsets meaning changing the connector , which means some hand - soldering or something , right ? grad c: no , we 're having the them do it . professor e: No ? grad c: So it 's so hand - soldering it , but I 'm not doing it . professor e: OK , so that 's being done professionally and grad c: I  professor e: Yeah . professor e: Well , it could if they do a lot of it , it 's grad c:  i it 's just their repair shop . grad c: And ,  we 'll see , tomorrow , you know , what it looks like . So , Dave isn't here but he was going to start working on some things with the digits . I guess Was the decision last time was that the the  transcribers were going to be doing stuff with the digits as well ? Has that started , or is that ? postdoc f:   grad c: Right , so , the decision was that Jane did not want the transcribers to be doing any of the paperwork . And  , then I have a bunch of scripts that we 'll read those and let the  transcribers use different tools . So he has a nice set up that they it w it will be efficient for them to do that . professor e: So anyway grad c: So , you know , just  , a matter of a few days I suspect . professor e: So anyway I think we we have at least one  , user for the digits once they get done , which will be Dave . grad c: So if he wanted to , you know , just have a few to start with , he could . You know , and I also have a bunch of scripts that will , like , generate P - files and run recognition on them also .  , is Dave I don't know if Dave is on the list , if he 's invited to these meetings ,  if he knows . grad c: we don't have a active one but I 'll make sure he 's on the list . Should we call him ?  is he d is he definitely not available today ? professor e: I don't know . phd a: Yeah , he was in s postdoc f: He wasn't there at cof professor e: Yeah , so this might be a conflict for him . grad c: Yeah didn't he say his signal - processing class was like Tuesdays and Thursdays ? phd a: I think he has a class . grad d: Yeah , I think he 's taking two twenty - five A which is now . professor e: And the and the recordings also , postdoc f:  professor e: just where we are . postdoc f: Well , so  , should we we don't wan wanna do the recording status first , or ? grad c: Well , we have about thirty - two hours  as of , I guess a week and a half ago , so we probably now have about thirty - five hours . professor e: And and that 's that 's  How much of that is digits ? It 's  that 's including digits , grad c: That 's including digits . professor e: right ? grad c: I haven't separated it out so I have no clue how much of that is digits . So anyway there 's at least probably thirty hours , or something of There 's got to be more than thirty hour phd a: Mmm . grad c: Of of non - digits ? professor e: i it couldn't of Of non - digits . postdoc f: OK , and the transcribers h I , don't have the exact numbers , but I think it would come to about eleven hours that are finished  , transcribing from them right now . The next step is to that I 'm working on is to insure that the data are clean first , and then channelized . What  by clean is that they 're spell - checked , that the mark - up is consistent all the way throughout , and also that we now incorporate these additional conventions that  , Liz requested in terms of  ,  in terms of having a s a systematic handling of numbers , and acronyms which I hadn't been specific about . And you know , so how you could grad c: Nine two , postdoc f: e Exactly . postdoc f: So if you just say " nine two " , the there are many s ways that could have been expressed . An - and I just had them I  , a certain number of them did put the words down , but now we have a convention which also involves having it followed by , a gloss th and things . phd b: one suggestion and you may already be doing this , but I 've noticed in the past that when I 've gone through transcriptions and you know in in order to build lexicons and things , if you  , just take all the transcriptions and separate them into words and then alphabetize them , a lot of times just scanning down that list you 'll find a lot of inconsistencies and mis grad c: Misspelled . postdoc f: You 're talking about the type token frequency listings , and I use those too . Y you mean just  on each on each line there 's a one word right ? It 's one token from the from the corpus . postdoc f: Yeah , those are e extremely efficient and I and I I agree that 's a very good use of it . postdoc f: Well that 's that 's a way that 's You know , the spell - check basically does that but but in addition yes , that 's that 's exactly the strategy I wanna do in terms of locating these things which are you know colloquial spoken forms which aren't in the lexicon . Cuz a lot of times they 'll appear next to each other , and  , postdoc f: Exactly . phd b: i in alphabetized lists , they 'll appear next to each other and and so it makes it easier . And that was that 's my strategy for handling a lot of these things , in terms of things that need to be glossed . I didn't get to that point but So there are numbers , then there are acronyms , and then  , there 's a he she wants the  , actually a an explicit marker of what type of comment this is , so i curly b inside the curly brackets I 'm gonna put either " VOC " for vocalized , like cough or like laugh or whatever , " NONVOC " for door - slam , and " GLOSS " for things that have to do with if they said a s a spoken form with this m this pronunciation error . postdoc f: but I I haven't been asking these people to do it systematically cuz I think it most ha most efficiently handled by  by a a filter . So that , you know you get a whole long list exactly what you 're saying , you get a whole list of things that say " curly bracket laugh curly bracket " , phd b:   postdoc f: then y you know it 's it 's You you risk less error if you handle it by a filter , than if you have this transcriber ch laboriously typing in sort of a VOC space , phd b: Yeah . postdoc f: So ,  I 'm I 'm going to convert that via a filter , into these tagged  , subcategorized comments , and same thing with you know , we see you get a subset when you do what you 're saying , phd b:   postdoc f: you end up with a s with  , you 're collapsing across a frequency you just have the tokens phd b:   But the numbers and acronyms have to be handled by hand , because , you know  , jus grad c: You don't know what they could be . postdoc f: Yeah now TIMIT 's clear  and PLP is clear but  there are things that are not so well known , in or or have variant u u uses like the numbers you can say " nine two " or you can say " ninety - two " , grad c: So how are you doing the postdoc f: and  I 'd handle the numbers individually . grad c: How are you doing the  , acronyms so if I say PZM what would it appear on the transcript ? postdoc f: It would be separate The letters would be separated in space grad c: OK . postdoc f: and potentially they 'll have a curly bracket thing afterwards e but I 'm not sure if that 's necessary , clarifying what it is , grad c:   Maybe it 's a nice thing to do because of it then indicating this is  , a step away from i indicating that it really is intentional that those spaces are there , and indicating why they 're there to indicate that it 's  the you know ,  enumerated , or i grad c:   postdoc f: it 's not a good way of saying but it 's it 's the specific  way of stating these these letters . postdoc f: And so anyway , the clean those are those things and then channelized is to then  , get it into this multichannel format . But that 's been my top priority beyond getting it tanel channelized , the next step is to work on tightening up the boundaries of the time bins . postdoc f: And  , Thilo had a e e a breakthrough with this this last week in terms of getting the channel - based   s s speech - nonspeech segmentation  , up and running and I haven't I haven't been able to use that yet cuz I 'm working s re this is my top priority get the data clean , and channelized . phd a: I actually gave grad c: Have you also been doing spot checks , Jane ? postdoc f: Oh yes . I spent  actually  I have a segment of ten minutes that was transcribed by two of our transcribers , grad c: Oh good . postdoc f: and I went through it last night , it 's it 's almost spooky how similar these are , word for word . And there are some differences in commas cuz commas I I left them discretion at commas . postdoc f:  and so because it 's not part of our st of our ne needed conventions . postdoc f: And  , and so they 'll be a difference in commas , but it 's word - by - word the same , in in huge patches of the data . And and sometimes it turns out that one of these transcribers has a better ear for technical jargon , and the other one has a better ear for colloquial speech . So  , the one i i the colloquial speech person picked up " gobbledy - gook " . And on this side , this one 's picking up things like " neural nets " and the one that 's good on the sp o on th the vocabulary on the  colloquial didn't . phd b: When for the person who missed " gobbledy - gook " what did they put ? postdoc f: It was an interesting approximation , put in parentheses , cuz I have this convention that , i if they 're not sure what it was , they put it in parentheses . postdoc f: So they tried to approximate it , but it was phd b: Oh good . More of an attempt to  apparently it was very clear to her that these the a this this was a sound these are the sounds , grad c: It was a technical term that she didn't recognize , phd b: Yeah . But she even though her technical perception is just really  you know I 've I 'm tempted to ask her if she 's taken any courses in this area or if she 's taken cognitive science courses grad c: Right . postdoc f: then cuz " neural nets " and oh she has some things that are oh " downsampled " , she got that right . postdoc f: But ch ten solid  m ch s chunk of ten solid minutes where they both coded the same data . professor e: And and again the main track that you 're working with is elev eleven hours ? postdoc f: And  professor e: Is that right ? postdoc f: Yes exactly . professor e: So let 's say roughly ten hours or so of postdoc f:   postdoc f: It 'd be more than that because I my recollection is the minutes that da digits don't take more than half a minute . postdoc f: But  the the total set that I gave them is twelve hours of tape , professor e: Oh , I see . postdoc f: So they 're still working some of them are Two of them are still working on completing that . professor e: So what what what 's the deal with with your phd a: The channel u thing ? professor e: Yeah . phd a: Oh , it 's just  , I ran the recognizer  , the speech - nonspeech detector on different channels and , it 's just in  in this new multi - channel format and output , and I just gave one one meeting to to Liz who wanted to to try it for for the recognizer professor e: Oh , I see . phd a: as  , apparently the recognizer had problems with those long chunks of speech , which took too much memory or whatever , professor e: Right . So , I hope grad c: Is this anything different than the  system you were using before ? professor e: Yeah . phd a: There is some ,  as the energy is normalized across channels grad c: You know what  ? Across all of them . What are some of the other features ? Besides the energy ? You said you 're trying some different features , or something . phd a: Oh I just  Mmm , I just use  our loudness - based things now as they before there were they were some in in the log domain and I I changed this to the to the professor e: Cu - Cube root ? phd a: Yeah . To No , I changed this to the to the to the loudness thingy with the with the grad c:  . Yeah , and I and I tried t to normalize   the features , there 's loudness and modified loudness , within one channel , professor e: OK . phd a: because they 're , yeah to to be able to distinguish between foreground and background speech . I think the  Were were you basically done with the transcription part ? So I guess the next thing is this  bleep editing . So the The idea is that we need to have We need to provide the transcripts to every participant of every meeting to give them an opportunity to bleep out sections they don't want . So I 've written a bunch of tools that will generate web pages ,  with the transcription in it so that they can click on them and piece pieces and they can scroll through and read them , and then they can check on each one if they want it excluded . And then , it 's a form , HTML form , so they can submit it and it will end up sending me email with the times that they want excluded . And so I thought about this a little bit and I think the best way to do it is every participant will have a password , professor e: Yeah . And then each meeting , we 'll only allow the participants who were at that meeting to look at it . professor e: I I can't help but wonder if this is maybe a little more elaborate than is needed .  if people have  , for me I would actually want to have some pieces of paper that had the transcription and I would sort of flip through it . professor e: And , I   it depends how this really ends up working out , but I guess my thought was that the occasion of somebody wondering whether something was OK or not and needing to listen to it was gonna be extremely rare . grad c: Right ,  so th th th the fact that you could listen to it over the web is a minor thing that I had already done for other reasons . grad c: And so that that 's a minor part of it , I just wanted some web interface so that people you didn't actually have to send everyone the text . So m what my intention to do is that as the transcripts become ready ,  I would take them , and generate the web pages and send email to every participant or contact them using the contact method they wanted , and just  , tell them , " here 's the web page " , " you need a password " . So th th question number one is how do we distribute the passwords , and question number two is how else do we wanna provide this information if they want it . professor e: That 's I think what I was sort of saying is that if you just say " here is a here is "  this maybe it sounds paleolithic but but I just thought if you handed them some sheets of paper , that said , " here 's what was said in this transcription is it OK with you ? and if it is , here 's this other sheet of paper that you sign that says that it 's OK " . grad c: I think that  there are a subset of people who will want printouts that we can certainly provide . These are big , and I would much rather be ha be able to just sit and leaf through it . professor e: You find it easier to go through a large  how do you read books ? grad c: Well I certainly read books by hand . professor e: Really ?  , it grad c: Cuz you 're gonna get , you know , if I I 'm I 'm in a bunch of meetings and I don't wanna get a stack of these . professor e: Going to a web site is easy , but flipping through a hundred pounds a hundred pages of stuff is not easy on the web . grad c: Well , I don't think it 's that much harder than , paper . So are you thinking that  the person would have a transcript and go strictly from the transcript ? Because I I do think that there 's a benefit to being able to hear the tone of voice and the professor e: So here 's the way I was imagining it , and maybe I 'm wrong , postdoc f: Yeah . professor e: but the way I imagined it was that  , the largest set of people is gonna go " oh yeah , I didn't say anything funny in that meeting just go ahead , where 's the where 's the release ? " And then there 'll be a subset of people , right ? OK there 's  think of who it is we 've been recording mostly . professor e: OK there 'll be a subset of people , who  , will say  " well , yeah , I really would like to see that . " And for them , the easiest way to flip through , if it 's a really large document ,  unless you 're searching . Searching , of course , should be electronic , but if you 're not so if you provide some search mechanism you go to every place they said something or something like that , phd a: Yeah .  if if  you don't have search mechanisms you just sort of have this really , really long document ,  whenever I 've had a really , really long document that it was sitting on the web , I 've always ended up printing it out .  , so it 's it 's  , you you 're you 're not necessarily gonna be sitting at the desk all the time , you wanna figure you have a train ride , and there 's all these situations where where I  , this is how I was imagining it , anyway . And then I figured , that out of that group , there would be a subset who would go "  you know I 'm really not sure about this section here , " and then that group would need it S It seems like i if I 'm right in that , it seems like you 're setting it up for the most infrequent case , rather than for the most frequent case . So that  , now we have to worry about privacy , grad c: Well , no fre for the most professor e: we have to worry about all these passwords , for different people grad c: For the most frequent case they just say " it 's OK " and then they 're done . postdoc f: The other thing too is it seems like professor e: yeah , that 's true . grad c: cuz you don't have to visit the web page if you don't want to . grad c: Oh that was another thing I I had assumed that we didn't need their signature , that it that an email approval was sufficient . phd b: Are are people going to be allowed to bleep out sections of a meeting where they weren't speaking ? grad c: Yes . If someone feels strongly enough about it , then I I I think they should be allowed to do that . phd b: So that means other people are editing what you say ? professor e:  I don't know about that . grad c: Well , the only other choice is that the person would say " no , don't distribute this meeting at all " , and I would rather they were able to edit out other people then just say " don't distribute it at all " . professor e: But th what they signed in the consent form , was something that said you can use my voice . grad c: Well , but if if someone is having a conversation , and you only bleep out one side of it , that 's not sufficient . grad c: If I say " we were having a conversation , and I consider that conversation private , " and I consider that your side of it is enough for other people to infer , I wanna be able to bleep out your side . postdoc f: The I agree that the consent forms were  , I cons agree with what Adam 's saying , that  , the consent form did leave open this possibility that they could edit things which they found offensive whe whether they said them or didn't say them . postdoc f: And the other thing is from the standpoint of the l of the l I 'm not a law lawyer , but it strikes me that  , we wouldn't want someone to say " oh yes , I was a little concerned about it but it was too hard to access " . Now in terms of like editing it by hand ,  I think it 's i some people would find that easier to specify the bleep part by having a document they edited . But but it seems to me that sometimes  , you know i if a person had a bad day , and they had a tone in their voice that they didn't really like , you know it 's nice it 's nice to be able to listen to it and be sure that that was OK . professor e:   it 's also a mixture of people ,  some people are r do their work primarily by sitting at the computer , flipping around the web , and others do not . You know ? grad c: Well I think most of the people in the meetings are the former . grad c: And that Well , but if they want to print it out that 's alright . I I think grad c: OK , so does that mean that I can't use email ? Or what ? postdoc f: Cuz you could send it through email you 're thinking . professor e: I I th grad c: Well , I don't think I professor e: well we there was this grad c: well I don't think we can send the text through email because of the privacy issues . So giving them , you think a web site to say , " if you wanna print it out here it is " , is not sufficient ? postdoc f: Good point . I professor e: Certainly for everybody who 's been in the meetings so far it would be sufficient . grad c: Yeah , I 'm just thinking for people that that 's not sufficient for , what the only sufficient thing would be for me to walk up to them and hand it to them . professor e: I 'm just wondering about postdoc f: You could mail it to them . phd a: But postdoc f: But I think it 's easier to drop in the box . phd a: Just put the button on on the web page which say " please send me the the scripts " . phd b: What  When you display it on the web page , what are what are you showing them ? Utterances , or ? grad c:   phd b: And so can they bleep within an utterance ? grad c: No . grad c: And that was just convenience for my sake , that it 's  ,  it would end up being fairly difficult to edit the transcripts if we would do it at the sub - utterance level . Because this way I can just delete an entire line out of a transcript file rather than have to do it by hand . professor e: There 's another aspect to this which maybe is part of why this is bothering me .  , I think you 're really trying very hard to make this as convenient as possible for people to do this . grad c:  that 's why I did the web form , because for me that would be my most convenient . You 're gonna end up with all these little patchy things , whereas really what we want to do is have the the the bias towards letting it go . Because nob you know it There was a one or twi once or twice , in the re in the meetings we 've heard , where somebody said something that they might be embarrassed by , but overall people are talking about technical topics . You know , this is this we 're we 're covering We 're playing the lawyer 's game , and we 're playing we 're we 're we 're looking for the extreme case . If we really orient it towards that extreme case , make it really easy , we 're gonna end up encouraging a headache . That I think that 's I 'm sort of psyching myself out here , I I 'm trying to  grad c: I guess I don't see having a few phrases here and there in a meeting being that mu much of a headache , bleeped out . professor e: but I I think that 's Well , it 's grad c: So . phd b: I think what Morgan 's saying is the easier it is , the more is gonna be bleeped . I think some researchers who are gonna be working with this corpus years from now are really gonna be cursing the fact that there 's a bunch of stuff in there that 's missing from the dialogue . professor e: You know , it depends on the kind of research they 're doing , phd a: Yeah . And , you know where it 's really gonna hurt somebody , in some way the one who said it or someone who is being spoken about , we definitely want to allow the option of it being bleeped out . And and  , I am just a little worried about making it so easy for people to do , and so much fun ! that they 're gonna go through and bleep out stuff . professor e: and they can bleep out stuff they don't like too , right from somebody else , as you say , you know , so " well I didn't like what he said .  , we have to provi we have promised that we would provide them the transcript and that they can remove parts that they don't like . No , no , I I I don't grad c: The only question is professor e: You - you 've talked me into that , but I I just think that we should make it harder to do . grad c: The problem is if it 's harder for them it 's also harder for me . Whereas this web interface , I just get email , it 's all formatted , it 's all ready to go and I can just insert it . professor e: So maybe you don't give them access to the web interface unless they really need it . professor e: I 'm sorry so so So maybe this is a s a way out of it . professor e: You 've provided something that 's useful for you to do handle , and useful for someone else if they need it . But I think the issue of privacy and ease and so forth should be that  , they get access to this if they really need it . grad c: Well phd b: So you 're saying the the sequence would be more like first Adam goes to the contact lists , contacts them via whatever their preferred method is , to see if they want to review the meeting . grad c: Well , to some extent I have to do that anyway because as I said we have to distribute passwords . professor e: There 's there grad c: So , professor e: y but you don't necessarily have to distribute passwords is what I 'm saying . grad c: what I 'm saying is that I can't just email them the password because that 's not secure . professor e: We 're We 're trying i We 're trying to make it less of an obvious just l l l l  fall off a log , to do this . professor e: Right ? So th so what I would see , is that first you contact them and ask them if they would like to review it for to check for the postdoc f: Yeah . professor e: not just for fun , OK ? but to to check this for  things that they 're worried about having said or if they 're willing to just send an approval of it , at from their memory .  and , and we should think carefully actually we should review go through how that 's worded , OK ? Then , if someone  wants to review it , and I know you don't like this , but I 'm offering this as a suggestion , is that is that we then give them a print out . And then if they say that " I have a potential problem with these things , " then , you you say " OK well you might wanna hear this in context to s think if you need that , " you issue them a password , i in the grad c: But the the problem with what you 're suggesting is it 's not just inconvenient for them , it 's inconvenient for me . professor e: I know you 'd prefer it , but the proble grad c: Yeah . professor e: we have grad c: So I think you 're thinking people are going to arbitrarily start bleeping and I just don't think that 's gonna happen . postdoc f: I 'm also concerned about the spirit of the of the informed consent thing . Cuz I think if they feel that  , it 's I th I th You know , if it turns out that something gets published in this corpus that someone really should have eliminated and didn't detect , then it could have been because of their own negligence that they didn't pursue that next level and get the password and do that , but but they might be able to argue " oh well it was cumbersome , and I was busy and it was gonna take me too much time to trace it down " . So I 'm a little bit worried about  , making it harder for them , from the legal standpoint . professor e: Well you can go too far in that direction , and you need to find somewhere between I think , postdoc f: Yeah . grad c: It seems to me that sending them email , saying " if you have an O - OK reply to this email and say OK , professor e: because  - huh . grad c: If you have a problem with it contact me and I 'll give you a password " , seems like is a perfectly , reasonable compromise . postdoc f:  we could offer that but but there 's  , another aspect to that and that is that in the informed consent form , my impression is that they that we offered them at the very least that they definitely would have access to the transcript . postdoc f: I don't know that there 's a chance of really skipping that stage .  I I thought that you were Maybe I misinterpreted what you said but it 's professor e: Having access to it doesn't necessarily mean , that having it grad c: Having it . grad c: Well the in professor e: right ? It just means they have the right to have it . grad c: the consent form is right in there if anyone wants to look at it , postdoc f: Alright . grad c: D you want me to grab one ? postdoc f: Sh - sh well I could I 'm closer . grad c: Yeah , but you 're wired postdoc f: I could grad c: aren't you ? postdoc f: Yeah . Yeah ,  I don't wanna fool them , postdoc f: I don't know professor e: I just meant that e every ev any time you say anything to anyone there is in fact a a bias that is presented , postdoc f: Oh yeah yeah oh I know . professor e: right ? grad c: " If you agree to participate you 'll have the opportunity to have anything ex anything excised , which you would prefer not to have included in the data set . grad c: " Once a transcript is available we will ask your permission to include the data in the corpus for the r larger research community . grad c: There again you will be allowed to indicate any sections that you 'd prefer to have excised from the database , and they will m be removed both from the transcript and the recording . grad c: Well ,  it The one question is definitely clear with anything as opposed to just what you said . professor e: Yeah ,  no that it tha postdoc f: Tha - that 's true . postdoc f: And it doesn't really say we 'll send it to you , or wi it 'll be available for you on the web , or anything .  like like Morgan was saying they they grad c: They just have to make sure that it is available to them . wh  I think I have an idea that may be sat may satisfy both you and me in this which is , it 's a it we just go over carefully how these notes to people are worded . So I I just want it to be worded in such a way where it gives the strong impre it gives very ,  nothing hidden , v very strongly the bias that we would really like to use all of these data . professor e: That that we really would rather it wasn't a patchwork of things tossed out , postdoc f: Good . But if you really think something is gonna And I don't think there 's anything in the legal aspects that that is hurt by our expressing that bias . professor e: you know you might be right , it may be it was just paranoia on my part ,  but people just See I 'm @ @ worried about this interface so much fun that people start bleeping stuff out just as just because they can . grad c: It 's just a check box next to the text , it 's not any fun at all . professor e: I grad c: All no because it doesn't automatically bleep it at the time . professor e: Oh they won't ? grad c: It just sends me professor e: Oh good . professor e: OK , grad c: And then at some point I 'll incorporate them all and put bleeps .  I don't wanna have t ha do that yet until we actually release the data professor e: Yeah . grad c: because  , then we have to have two copies of every meeting and we 're already short on disk space . grad c: So I I wanna I just keep the times until we actually wanna release the data and then we bleep it . Alright , so I think Yeah so if we have if i Again let 's you know , sort of circulate the the wording on each of these things and get it right , grad c: Well since you seem to feel heart  , strongest about it , would you like to do the first pass ? professor e: but but OK . Turn about is fair play , postdoc f: Al - Also it ther there is this other question , the legal question that that Adam 's raised ,  about whether we need a concrete signature , or email c i suffices or whatever professor e: Sorry . i There 's something down there about " if you agree to " professor e: I 'm I 'm I 'm I thought I I thought about it with one of my background processes grad c: I don't think so . professor e: and I  it 's  it 's  , it 's fine to do the email . grad c: Yeah because thi th they 're signing here that they 're agreeing to the paragraph which says " you 'll be given an opportunity . professor e: And Well and furthermore I it 's now fairly routine in a lot of arrangements that I do with people on contracts and so forth that that  if it 's if it 's that sort of thing where you 're you 're saying  " OK I agree , we want eighty hours of this person at such - and - such amount , and I agree that 's OK , "  if it 's a follow up to some other agreement where there was a signature it 's often done in email now grad c: Right . grad c: So I guess I probably should at the minimum , think about how to present it in a printed form . The problem is a lot of them are really short , postdoc f: Well grad c: and so I don't necessarily wanna do one per line . postdoc f: Well I s I also have this I I think it 's nice you have it  , viewab her hearable on the on the web for those who might wonder about  , the non nonverbal side ,  I I agree that our bias should be as as expressed here , and but I I think it 's nice that a person could check . Cuz sometimes you know you the words on a on the page , come out soun sounding different in terms of the social dynamics if they hear it . postdoc f: And I realize we shouldn't emphasize that people you know , shouldn't borrow trouble . What it comes down to but grad c: Yeah I think actually my opinion probably is that the only time someone will need to listen to it is if the transcript is  not good . postdoc f: Oh , you know , or what if there was an error in the transcript that didn't get detected and there was a whole  i segment a against some personal i th grad c: Right . grad c: I think Microsoft is postdoc f: Yeah exactly phd a: Oh , grad c: Sorry transcribers . postdoc f: Or or even or even there was a a line you know about how "  - mmm - mmm Bill Gates duh - duh - duh - duh . postdoc f: but but it was all the words were all visible , but they didn't end up i some there was a slip in the transcript .  , I I guess we 're assuming that the transcript is a close enough approximation and that that my double checking will be so close to absolutely perfect that it that nothing will slip by . professor e: But it the some something might sometime , and they  if if it 's something that they said , they might i i  , you might be very accurate in putting down what they actually said , postdoc f:   professor e: but , when they hear it , themselves , they may hear something different because they know what they meant . phd b: how do you how do you indicate sarcasm ? postdoc f: Yeah that 's right . So the so i the so we might we might get some feedback from people that such - and - such was , you know , not not really what I said . grad c: So  , in terms of password distribution , I think phone is really the only way to do it , phone and in person . postdoc f: You know I just realized something , which is of e th this question about the  the possible mismatch of  i well , and actually also the lawyer saying that  , we shouldn't really have them have the people believing that they will be cleared by our checks . So it 's like i in a way it 's it 's nice to have the responsibility still on them to listen to the tape and and hear the transcript , to have that be the professor e: Well yeah , but you can't dep  , most people will not wanna take the time to do that , though . professor e: And they they have to postdoc f: So it 's not it 's not  Yeah , good . professor e: But  if you were at a meeting , and and you you don't think , at least , that you said anything funny and the meeting was about , you know , some some funny thing about semantics or something , or  grad c: You probably won't listen to it . postdoc f: It is true that tec that the content is technical , I and so i and we 're not having these discussions which professor e: Yeah . postdoc f: I  , when I listen to these things , I don't find things that are questionable , in other people 's speech or in my own . professor e:  we 're not talking about the energy crisis or something , people have postdoc f: Yeah . Actually , I was gonna Di - Did you have anything n that 's going on , or grad d: Not really .  , my project is going along but  , I 'm really just here to  fill the project  the overall progress . grad c:   professor e: Transcribers , he was rattling the b marbles in his brain back and forth just then this this grad c: Shall we do digits ? professor e: Oh yeah . grad c: oh by the way I did find a bunch grad d: It  grad c: we should count out how many more digits to forms do we have back there ? phd b: There were quite a few . I f I was going through them all and I found actually a lot filed in with them , that were blanks , that no one had actually read . postdoc f: Oh , did you do that ? phd a: Burger King grad c: I 'd like a burger with that , phd b: No I never did


grad b: We didn't crash we 're not crashing anymore phd c: One , two , three , four , f grad b: and it really bothers me . phd c: Yeah ? professor a: Oh ! Well maybe it 's just , you know , how many t u u u u how many times you crash in a day . phd g: Or maybe it 's once you 've done enough meetings it won't crash on you anymore . professor a: Do we have an agenda ? Liz Liz and Andreas can't sh can't  , can't come . phd g: Did they send , the messages to you about the meeting today ? grad b: I have no idea but I just got it a few minutes ago . grad b: So , does anyone have any a agenda items other than me ? I actually have one more also which is to talk about the digits . professor a: right , so so I I was just gonna talk briefly about the NSF ITR . professor a: and then , you have postdoc f: Can w professor a: I won't say much , but  , but then , you said wanna talk about digits ? grad b: I have a short thing about digits and then  I wanna talk a little bit about naming conventions , although it 's unclear whether this is the right place to talk about it . So maybe just talk about it very briefly and take the details to the people who for whom it 's relevant . I 've been but but  , well professor a: Well if we Yeah , we shouldn't add things in just to add things in . grad b: So the only thing I wanna say about digits is , we are pretty much done with the first test set . There are probably forms here and there that are marked as having been read that weren't really read . So I won't really know until I go through all the transcriber forms and extract out pieces that are in error . The first is what should we do about digits that were misread ? My opinion is , we should just throw them out completely , and have them read again by someone else . grad b: so it it 's perfectly fine to put a a group together again of errors and have them re - read , just to finish out the test set . postdoc f: Oh ! By throw them out completely ? grad b: the other thing you could do is change the transcript to match what they really said . I know I 've done it , where I say say a grad b: What the transcribers did with that is if they did a correction , and they eventually did read the right string , you extract the right string . phd g: Oh , you 're talking about where they completely read the wrong string and didn't correct it ? phd e: Yeah . grad b: So so postdoc f: Well , and s and you 're talking string - wise , you 're not talking about the entire page ? grad b: Correct . grad b: And so the the two options are change the transcript to match what they really said , but then but then the transcript isn't the Aurora test set anymore . phd g: Well how many are how how often does that happen ? grad b: Mmm , five or six times . professor a: Yeah , it 's five or six times out of thousands ? phd c: Yeah . phd g: Yeah , it 's professor a: Yeah , I would , tak do the easy way , phd g: Yeah . professor a: It it 's kinda nice  , wh who knows what studies people will be doing on on speaker - dependent things phd c: Mmm . phd g: So you  , how many digits have been transcribed now ? grad b: Four thousand lines . phd g: Four thousand lines ? grad b: I didn't I didn't compute the average . grad b: And , Jane , I do have a set of forms which I think you have copies of somewhere . grad b: Yeah , I was just wond I thought I had had all of them back from you . And then the other thing is that , the forms in front of us here that we 're gonna read later , were suggested by Liz postdoc f: No , not yet . And so , I just wanted people to , take a quick look at the instructions phd c:   grad b: and the way it wa worked and see if it makes sense and if anyone has any comments on it . Although we could switch it back and tell them always to say " zero " or always to say " O " . professor a: that 's the only thought I have because if you t start talking about these , you know u tr She 's trying to get at natural groupings , but it there 's there 's nothing natural about reading numbers this way . grad b: But , the other problem we were thinking about is if you just put the numerals , they might say forty - three instead of four three .  , you can With when you space them out they don't look like , forty - three anymore . grad b: and she felt that it 's very , very natural to do that sort of chunking .  it 's a it 's a it 's an interesting problem  , we 've done stuff with numbers before , and yeah sometimes people If you say s " three nine eight one " sometimes people will say " thirty - nine eighty - one " or " three hundred three hundred eighty - nine one " , or I don't think they 'd say that , phd c: Yeah . professor a: but but th grad b: Not very frequently professor a: no grad b: but , they certainly could . grad b: and , since this was something that Liz asked for specifically , I think we need to defer to her . Well , we 're probably gonna be collecting meetings for a while and if we decide we still wanna do some digits later we might be able to do some different ver different versions , grad b: Do something different , professor a: but this is the next suggestion , grad b: yeah . OK , so  e l I guess , let me , get my my short thing out about the NSF .  , I I sent to what I thought we had , in some previous mail , as the right joint thing to send to , which was " M MTG RCDR hyphen joint " . professor a: But then I got some sort of funny mail saying that the moderator was going to grad b: It 's That 's because they set the one up at UW postdoc f:  grad b: that 's not on our side , that 's on the U - dub side . grad b: And , I have no idea whether it actually ever goes to anyone so you might just wanna mail to Mari professor a: No no , th I got I got , little excited notes from Mari and Jeff and so on , grad b: and professor a: so it 's grad b: OK , good . grad b: Cuz I had sent one earlier Actually the same thing happened to me I had sent one earlier . The message says , " You 'll be informed " and then I was never informed but I got replies from people indicating that they had gotten it , so . Well , anyway , I guess everybody here Are y are you are on that list , right ? So you got the note ? phd g:   professor a: so this was , a , proposal that we put in before on on more more higher level , issues in meetings , from I guess higher level from my point of view .  , and , meeting mappings , and ,  so is i for it was a proposal for the ITR program , Information Technology Research program 's part of National Science Foundation . They 're they 're a lot of them are some of them anyway , are larger larger grants than the usual , small NSF grants , and . So , they 're very competitive , and they have a first phase where you put in pre - proposals , and we we , got through that . grad b: When 's when 's the full proposal due ? professor a: I think April ninth , or something . And they said end of business day you could check on the reviewer forms , phd g: u grad b: is that phd g: Tomorrow . grad b: I guess that 's a good thing cuz that way I got my papers done early . phd g: It would be interesting professor a: So that 's amazing you showed up at this meeting ! grad b: It is . My favorite is was when when when one reviewer says , " you know , this should be far more detailed " , and the nex the next reviewer says , " you know , there 's way too much detail " . Or " this is way too general " , and the other reviewer says , " this is way too specific " . Is that right ? That they didn't reject a lot of the pre - proposals ? professor a: Do you know anything about the numbers ? grad b: No . phd g: Gary Strong 's professor a: I phd g: there was a sentence at the end of one of his paragraphs phd e: Yeah . He said the next phase 'll be very , competitive phd e: Very very , phd g: because we didn't want to weed out much in the first phase . professor a: So , you know , maybe they didn't r weed out as much as usual , but it 's it 's usually a pretty But it Yeah . It 's it 's certainly not I 'm sure that it 's not down to one in two or something of what 's left . professor a: I 'm sure it 's , you know grad b: How how many awards are there , do you know ? professor a: Well there 's different numbers of w awards for different size They have three size grants . This one there 's ,  See the small ones are less than five hundred thousand total over three years and that they have a fair number of them .  , and the large ones are , boy , I forget , I think , more than , more than a million and a half , more than two million or something like that . But , I don't remember , but it 's pr probably along the li I I could be wrong on this yeah , but probably along the lines of fifteen or that they 'll fund , or twenty .  when they Do you do you know how many they funded when they f in in Chuck 's , that he got last year ? phd g: I don't I don't know . grad b: I thought it was smaller , that it was like four or five , wasn't it ? professor a: Well they fund phd g: I I 'm professor a: they phd g: I don't remember . professor a: and this time they came up with a middle one , so it 'll there 'll be more of them that they fund than of the big . phd g: If we end up getting this , what will it mean to ICSI in terms of , w wh where will the money go to , what would we be doing with it ? professor a:  . professor a: You know , it i None of it will go for those yachts that we 've talking about . phd g:  Dang ! professor a: well , no ,  it 's u It phd g: It 's just for the research to continue the research on the Meeting Recorder stuff ? professor a: It 's extending the research , right ? Because the other phd g: Yeah . grad b: Yeah it 's go higher level stuff than we 've been talking about for Meeting Recorder . Yeah the other things that we have , been working on with , the c with Communicator  , especially with the newer things with the more acoustically - oriented things are are are are lower level . And , this is dealing with , mapping on the level of of , the conversation of mapping the conversations phd g:   So it 's all it 's all stuff that none none of us are doing right now , or none of us are funded for , so it 's so it 's it would be new . phd g: So assuming everybody 's completely busy now , it means we 're gonna hafta , hire more students , or , something ? professor a: Well there 's evenings , and there 's weekends , and  . Yeah , there there would be there would be new hires , and and there there would be expansion , but , also , there 's always for everybody there 's there 's always things that are dropping off , grants that are ending , or other things that are ending , so , phd g: Right . professor a: But but there definitely would be new new new , students , phd g: I see . grad b: Are there any students in your class who are expressing interest ? professor a: not clear yet . professor a:  we got we have yeah , two of them are two in the c There 're two in the class already here , and then and and , then there 's a third who 's doing a project here , who ,  But he he he won't be in the country that long , grad b:   professor a: Actually there is one other guy who 's looking that that 's that guy , Jeremy ? I think .  professor a: Anyway , yeah that 's that 's all I was gonna say is that that that 's you know , that 's nice and we 're sorta preceding to the next step , and , it 'll mean some more work , you know , in in March in getting the proposal out , and then , it 's , you know We 'll see what happens . It just ,  we 've been cutting up sound files , in for ba both digits and for , doing recognition . And Liz had some suggestions on naming and it just brought up the whole issue that hasn't really been resolved about naming . So , one thing she would like to have is for all the names to be the same length so that sorting is easier . grad b: same number of characters so that when you 're sorting filenames you can easily extract out bits and pieces that you want . And I don't think we have so many meetings that that 's a big deal just to change the names . So that means , instead of calling it " MR one " , " MR two " , you 'd call it " MRM zero zero one " , " MRM zero zero two " , things like that . postdoc f: But , you know , when you , do things like that you can always as long as you have  , you can always search from the beginning or the end of the string . postdoc f: You know , so " zero zero two " grad b: Alright , postdoc f: Yeah . grad b: so we we have th we 're gonna have the speaker ID , the session , information on the microphones , postdoc f: Yeah , well , your example was really grad b: information on the speak on the channels and all that . postdoc f: i grad b: And so if each one of those is a fixed length , the sorting becomes a lot easier . So like , the NSA meeting lengths , all filenames are gonna be the same length as the Meeting Recorder meeting names ? grad b: Yep . And as I said , the it 's we just don't have that many that that 's a big deal . grad b: And so , at some point we have to sort of take a few days off , let the transcribers have a few days off , make sure no one 's touching the data and reorganize the file structures . postdoc f: I I would think though that the transcribe the transcripts themselves wouldn't need to have such lengthy names . postdoc f: So , you 're dealing with a different domain there , and with start and end times and all that , and channels and stuff , grad b: Right . So the only thing that would change with that is just the directory names , postdoc f: so , it 's a different set . grad b: So for for m the meetings we were thinking about three letters and three numbers for meeting I Ds .  , for speakers , M or F and then three numbers , For ,  and , that also brings up the point that we have to start assembling a speaker database so that we get those links back and forth and keep it consistent . We want some way of specifying , more than looking in the " key " file , what channel and what mike . grad b: that 's gonna become especially important once we start changing the microphone set - up . We have some new microphones that I 'd like to start trying out , once I test them . professor a: since we have such a short agenda list I guess I wi I will ask how how are the transcriptions going ? Yeah . postdoc f: The the news is that I 've I  s So in s  So I 've switched to Start my new sentence . I I switched to doing the channel - by - channel transcriptions to provide , the  , tighter time bins for partly for use in Thilo 's work and also it 's of relevance to other people in the project . And , I discovered in the process a couple of of interesting things , which , one of them is that , it seems that there are time lags involved in doing this , using an interface that has so much more complexity to it . And I and I wanted to maybe ask , Chuck to help me with some of the questions of efficiency . Maybe I was thinking maybe the best way to do this in the long run may be to give them single channel parts and then piece them together later .  , so it 's like , I I know that I can take them apart and put them together and I 'll end up with the representation which is where the real power of that interface is . postdoc f: And it may be that it 's faster to transcribe a channel at a time with only one , sound file and one , set of of , utterances to check through . I thought that that one of the reason we thought we were so much faster than than , the the other transcription , thing was that that we were using the mixed file . But , with the mixed , when you have an overlap , you only have a a choice of one start and end time for that entire overlap , which means that you 're not tightly , tuning the individual parts th of that overlap by different speakers . postdoc f: So someone may have only said two words in that entire big chunk of overlap . postdoc f: And for purposes of of , things like well , so things like training the speech - nonspeech segmentation thing . postdoc f: And w and w and , you know , is a It would be wonderful if , it 's possible then to use that algorithm to more tightly tie in all the channels after that but , you know , I 've th the So , I I don't know exactly where that 's going at this point . But m I was experimenting with doing this by hand and I really do think that it 's wise that we 've had them start the way we have with , m y working off the mixed signal , having the interface that doesn't require them to do the ti  , the time bins for every single channel at a t  , through the entire interaction . postdoc f: I did discover a couple other things by doing this though , and one of them is that , once in a while a backchannel will be overlooked by the transcriber . postdoc f: because when it 's a b backchannel could well happen in a very densely populated overlap . And if we 're gonna study types of overlaps , which is what I wanna do , an analysis of that , then that really does require listening to every single channel all the way through the entire length for all the different speakers . Now , for only four speakers , that 's not gonna be too much time , but if it 's nine speakers , then that i that is more time . So it 's li you know , kind of wondering And I think again it 's like this it 's really valuable that Thilo 's working on the speech - nonspeech segmentation because maybe , we can close in on that wi without having to actually go to the time that it would take to listen to every single channel from start to finish through every single meeting .  especially if they 're really short and they 're not very loud and so it it can it it will always happen that also the automatic s detection system will miss some of them , so . Well so then then , maybe the answer is to , listen especially densely in places of overlap , phd e: Yeah . postdoc f: just so that they 're they 're not being overlooked because of that , and count on accuracy during the sparser phases . postdoc f: Cuz there are large s spaces of the That 's a good point . I I think it 's really interesting data to work with , I have to say , it 's very enjoyable .  , you 're you 're you 're still in the midst of what you 're doing from what you described last time , I assume , phd c: Is true . postdoc f:  professor a: and phd c: I haven't results , eh , yet professor a: Yeah . phd c: but , eh , I I 'm continue working with the mixed signal now , after the the last experience . phd c: And and I 'm tried to to , adjust the to to improve , eh , an harmonicity , eh , detector that , eh , I I implement . phd c: But I have problem because , eh , I get , eh , eh , very much harmonics now . phd c: harmonic possi possible harmonics , eh , and now I 'm I 'm I 'm trying to to find , eh , some kind of a ,  of h of help , eh , using the energy to to distinguish between possible harmonics , and and other fre frequency peaks , that , eh , corres not harmonics . And , eh , I have to to talk with y with you , with the group , eh , about the instantaneous frequency , because I have , eh , an algorithm , and , I get , mmm , eh , t t results similar results , like , eh , the paper , eh , that I I am following . But , eh , the the rules , eh , that , eh , people used in the paper to to distinguish the harmonics , is doesn't work well . phd c: And I I I I not sure that i eh , the the way o to ob the way to obtain the the instantaneous frequency is right , or it 's it 's not right . If if if ,  If I don't have enough time and y you wanna discuss with someone else some someone else besides us that you might want to talk to , might be Stephane . phd c: and , professor a: Yeah , but phd c: they nnn they they they didn't phd e: I 'm not too experienced with harmonics professor a: I see . phd c: they think that the experience is not enough to phd e: and phd g: Is is this the algorithm where you hypothesize a fundamental , and then get the energy for all the harmonics of that fundamental ? phd c: No , no it 's No No . phd g: And then hypothesize a new fundamental and get the energy professor a: Yeah , that 's wh phd c: No . phd c: And The algorithm said that , eh , if you if you change the the the , eh , nnn the X - the frequency " X " , eh , using the in the instantaneous frequency , you can find , eh , how , eh , in several frequencies that proba probably the the harmonics , eh , professor a:  - huh . phd c: the errors of peaks the frequency peaks , eh , eh , move around these , eh eh frequency harmonic the frequency of the harmonic . And , eh , if you if you compare the the instantaneous frequency , eh , of the of the , eh , continuous , eh , eh , filters , that , eh that , eh , they used eh , to to to get , eh , the the instantaneous frequency , professor a:   phd c: it probably too , you can find , eh , that the instantaneous frequency for the continuous , eh , eh the output of the continuous filters are very near . phd c: And professor a: It 's it 's it 's I haven't worked with that either so I 'm not sure The way the simple - minded way I suggested was what Chuck was just saying , is that you could make a a sieve . professor a: Let 's let 's hypothesize that it 's this frequency or that frequency , and and , maybe you maybe you could use some other cute methods to , short cut it by by  , making some guesses , phd c: Yeah . professor a: but but    , I would ,   you could make some guesses from ,  from the auto - correlation or something but but then , given those guesses , try , only looking at the energy at multiples of the of that frequency , and and see how much of the take the one that 's maximum . phd g: Do you hafta do some kind of , low - pass filter before you do that ? phd c: I don't use . phd g: Or phd c: But , I I know many people use , eh , low - pass filter to to to get , eh , the pitch . phd g: But i But the harmonics are gonna be , I don't know what the right word is .  , they 're gonna be dampened by the  , vocal tract , right ? The response of the vocal tract . professor a: Yeah ? phd c: Yeah ? phd g: And so just looking at the energy on those at the harmonics , is that gonna ? professor a: Well so the thing is that the This is for , a ,  phd g: I m what you 'd like to do is get rid of the effect of the vocal tract . professor a: But ,  but I but but I don't know that you need to grad b: Open wide ! professor a: but I don't need you know if you need to get rid of it .  that 'd that 'd be nice but I don't know if it 's ess if it 's essential .  ,  cuz I think the main thing is that , you 're trying phd g:  - huh . professor a: wha what are you doing this for ? You 're trying distinguish between the case where there is ,  where where there are more than  , where there 's more than one speaker and the case where there 's only one speaker . professor a: So if there 's more than one speaker ,  yeah I guess you could I guess yeah you 're so you 're not distinguished between voiced and unvoiced , so so , i if you don't if you don't care about that phd c: Yeah . professor a: See , if you also wanna just determine if you also wanna determine whether it 's unvoiced , then I think you want to look look at high frequencies also , because the f the fact that there 's more energy in the high frequencies is gonna be an ob sort of obvious cue that it 's unvoiced . professor a: But , i i   i i but , other than that I guess as far as the one person versus two persons , it would be primarily a low frequency phenomenon . And if you looked at the low frequencies , yes the higher frequencies are gonna there 's gonna be a spectral slope .  that 's that 's w phd c: I will prepare for the next week eh , all my results about the harmonicity and will will try to come in and to discuss here , because , eh , I haven't enough feeling to to u many time to to understand what happened with the with , eh , so many peaks , eh , eh , and I I see the harmonics there many time but , eh , there are a lot of peaks , eh , that , eh , they are not harmonics . phd c: I have to discover what what is the the w the best way to to to c to use them professor a: Well , but yeah I don't think you can  you 're not gonna be able to look at every frame , so  I  I I really I I really thought that the best way to do it , and I 'm speaking with no experience on this particular point , but , my impression was that the best way to do it was however you You 've used instantaneous frequency , whatever . However you 've come up you with your candidates , you wanna see how much of the energy is in that phd c: Yeah . And , if it 's voiced , I guess so so y I think maybe you do need a voiced - unvoiced determination too . professor a: and the ,  e the fraction of the energy that 's in the harmonic sequence that you 're looking at is relatively low , then it should be then it 's more likely to be an overlap . This this is the idea the idea I I I had to to compare the the ratio of the the energy of the harmonics with the eh , with the , eh , total energy in the spectrum and try to get a ratio to to distinguish between overlapping and speech . professor a: But you 're looking a y you 're looking at Let 's take a second with this .  , you 're looking at f at the phase derivative , in in , what domain ?  this is this is in in in in bands ? Or or phd c: No , no , no . professor a: Just just overall phd c: It 's a it 's a o i w the band the band is , eh , from zero to to four kilohertz . And I I ot I professor a: And you just take the instantaneous frequency ? phd c: Yeah . to FFT to to obtain the or to study the harmonics from from the spectrum directly , professor a: Yeah . And another another algorithm I have is the in the instantaneous frequency , based on on on the FFT to to to calculate the the phase derivate in the time . phd c: But , eh , in m i in my opinion the the the instantaneous frequency , the the the behavior , eh , was th it was very interesting . Because I I saw eh , how the spectrum concentrate , eh , professor a: Oh ! phd c: around the the harmonic . But then when I apply the the rule , eh , of the in the the instantaneous frequency of the ne of the continuous filter in the the near filter , the the rule that , eh , people propose in the paper doesn't work . professor a: But the instantaneous frequency , wouldn't that give you something more like the central frequency of the you know , of the where most of the energy is ?  , I think if you Does i does it Why would it correspond to pitch ? phd c: Yeah . phd c: When first I I calculate , eh , using the FFT , postdoc f: Di - digital camera . professor a: Oh , so you scale you s you do a a scaling along that axis according to instantaneous phd c: I use Yeah . phd c: eh , when i I I use these these frequency , eh , the range is different , and the resolution is different . phd c: But , eh , they used , eh , a rule , eh , based in the in the because to to calculate the instantaneous frequency , they use a Hanning window . phd c: And , they said that , eh , if these peak are , eh , harmonics , the f instantaneous frequency , of the contiguous , eh w eh eh , filters are very near , or have to be very near . But , eh , phh ! I don't I I I I don I I and I don't know what is the what is the distance . And I tried to to put different distance , eh , to put difference , eh eh , length of the window , eh , different front sieve , Pfff ! and I I not sure what happened . I 'll probably gonna hafta look at the paper , but which I 'm not gonna have time to do in the next few days , but but I 'm I 'm curious about it . postdoc f: I I did i it did occur to me that this is  , the return to the transcription , that there 's one third thing I wanted to to ex raise as a to as an issue which is , how to handle breaths . So , I wanted to raise the question of whether people in speech recognition want to know where the breaths are . And the reason I ask the question is , aside from the fact that they 're obviously very time - consuming to encode , the fact that there was some I had the indication from Dan Ellis in the email that I sent to you , phd e: Yeah . postdoc f: and you know about , that in principle we might be able to , handle breaths by accessi by using cross - talk from the other things , be able that in principle , maybe we could get rid of them , so maybe And I was I I don't know ,  we had this an and I didn't couldn't get back to you , phd e: Yeah . postdoc f: but the question of whether it 'd be possible to eliminate them from the audio signal , which would be the ideal situation , professor a: I don't know think it 'd be ideal . professor a: We - See , we 're we 're dealing with real speech and we 're trying to have it be as real as possible phd e: Yeah . postdoc f: Well , except that these are really truly  , ther there 's a segment in o the one I did n the first one that I did for i for this , phd e: Yeah . postdoc f: where truly w we 're hearing you breathing like as if we 're you 're in our ear , you know , and it 's like it 's like professor a: Yeah . postdoc f: I y i  , breath is natural , but not professor a: It is but it is if you record it . postdoc f: Except that we 're we 're trying to mimic Oh , I see what you 're saying . grad b: The P D A might not have to , phd e: No i grad b: but more people than just PDA users are interested in this corpus . grad b: So so mean you 're right postdoc f: OK , then the then I have two questions . grad b: we could remove it , postdoc f: Yeah ? grad b: but I I think we don't wanna w remove it from the corpus , in terms of delivering it because the people will want it in there . If if it gets in the way of what somebody is doing with it then you might wanna have some method which will allow you to block it , but you it 's real data . You don't wanna b but you don't postdoc f: OK , well professor a: If s you know , if there 's a little bit of noise out there , and somebody is is talking about something they 're doing , that 's part of what we accept as part of a real meeting , even And we have the f  the  the the fan and the in the projector up there , and , this is it 's this is actual stuff that we we wanna work with . postdoc f: because i it basically has a i it shows very clearly the contrast between , speech recognition research and discourse research because in in discourse and linguistic research , what counts is what 's communit communicative . postdoc f: And breath , you know , everyone breathes , they breathe all the time . postdoc f: and the idea is that the transcripts will that get stored as a master there 'll be a master transcript which has in it everything that 's needed for both of these uses . postdoc f: And the one that 's used for speech recognition will be processed via scripts . Discourse side will have this this side over he the we we 'll have a s ch Sorry , not being very fluent here . But , this the discourse side will have a script which will stri strip away the things which are non - communicative . So then the then let 's let 's think about the practicalities of how we get to that master copy with reference to breaths . So what I would r r what I would wonder is would it be possible to encode those automatically ? Could we get a breath detector ? grad b: Oh , just to save the transcribers time . postdoc f: and just simply the keystrokes it takes to negotiate , to put the boundaries in , to to type it in , i it 's just a huge amount of time . postdoc f: And you wanna be sure it 's used , and you wanna be sure it 's done as efficiently as possible , and if it can be done automatically , that would be ideal . professor a: what if you put it in but didn't put the boundaries ? postdoc f: Well , but professor a: So you just know it 's between these other things , postdoc f: Well , OK . So now there 's there 's another another possibility professor a: right ? postdoc f: which is , the time boundaries could mark off words from nonwords . professor a: Yeah  I 'm think if it 's too if it 's too hard for us to annotate the breaths per se , we are gonna be building up models for these things and these things are somewhat self - aligning , so if so , we i i if we say there is some kind of a thing which we call a " breath " or a " breath - in " or " breath - out " , the models will learn that sort of thing .  , so but you but you do want them to point them at some region where where the breaths really are . But that would maybe include a pause as well , phd g: Well , there 's a there 's postdoc f: and that wouldn't be a problem to have it , pause plus breath plus laugh plus sneeze ? professor a: Yeah , i You know there is there 's this dynamic tension between between marking absolutely everything , as you know , and and and marking just a little bit and counting on the statistical methods . But if there seems to be a lot of effort for a small amount of reward in some area , and this might be one like this Although I I I 'd be interested to h get get input from Liz and Andreas on this to see if they Cuz they 've - they 've got lots of experience with the breaths in in , their transcripts . grad b: They have lots of experience with breathing ? phd g: I professor a: Actually Well , yes they do , but we we can handle that without them here . But but but , you were gonna say something about phd g: Yeah , I I think , one possible way that we could handle it is that , you know , as the transcribers are going through , and if they get a hunk of speech that they 're gonna transcribe , u th they 're gonna transcribe it because there 's words in there or whatnot . But if there 's a big hunk of speech , let 's say on Morgan 's mike where he 's not talking at all , don't don't worry about that . phd g: So what we 're saying is , there 's no guarantee that ,  So for the chunks that are transcribed , everything 's transcribed . So you just somebody can't rely on that data and say " that 's perfectly clean data " .  do you see what I 'm saying ? postdoc f: Yeah , you 're saying it 's uncharted territory . phd g: So I would say don't tell them to transcribe anything that 's outside of a grouping of words . phd e: Yeah , and that 's that that quite co corresponds to the way I I try to train the speech - nonspeech detector , as I really try to not to detect those breaths which are not within a speech chunk but with which are just in in a silence region . phd e: And they so they hopefully won't be marked in in those channel - specific files . professor a: u I I wanted to comment a little more just for clarification about this business about the different purposes . professor a: See , in a in a way this is a really key point , that for speech recognition , research , e a it 's not just a minor part . In fact , the I think I would say the core thing that we 're trying to do is to recognize the actual , meaningful components in the midst of other things that are not meaningful . So it 's critical it 's not just incidental it 's critical for us to get these other components that are not meaningful . professor a: if we had only linguistically - relevant things if if we only had changes in the spectrum that were associated with words , with different spectral components , and , we we didn't have noise , we didn't have convolutional errors , we didn't have extraneous , behaviors , and so forth , and moving your head and all these sorts of things , then , actually speech recognition i i isn't that bad right now . professor a: The the the reason we still complain about it is because is when when you have more realistic conditions then then things fall apart . I guess , I  , what I was wondering is what what at what level does the breathing aspect enter into the problem ? Because if it were likely that a PDA would be able to be built which would get rid of the breathing , so it wouldn't even have to be processed at thi at this computational le well , let me see , it 'd have to be computationally processed to get rid of it , but if there were , like likely on the frontier , a good breath extractor then , and then you 'd have to professor a: But that 's a research question , you know ? And so postdoc f: Yeah , well , see and that 's what I wouldn't know .  so so the thing is it 's it right now it 's just raw d it 's just data that we 're collecting , and so we don't wanna presuppose that people will be able to get rid of particular degradations because that 's actually the research that we 're trying to feed . So , you know , an and maybe maybe in five years it 'll work really well , postdoc f: OK . professor a: and and it 'll only mess - up ten percent of the time , but then we would still want to account for that ten percent , so . postdoc f: I guess there 's another aspect which is that as we 've improved our microphone technique , we have a lot less breath in the in the more recent , recordings , so it 's in a way it 's an artifact that there 's so much on the on the earlier ones . phd g: One of the  , just to add to this one of the ways that we will be able to get rid of breath is by having models for them . phd g: And so in order to build the model you need to have some amount of it marked , so that you know where the boundaries are . phd g: So  , I don't think we need to worry a lot about breaths that are happening outside of a , you know , conversation . We don't have to go and search for them to to mark them at all , but , if they 're there while they 're transcribing some hunk of words , I 'd say put them in if possible . postdoc f: OK , and it 's also the fact that they differ a lot from one channel to the other because of the way the microphone 's adjusted