professor c: Typically when you you 're ab r starting around forty for most people , it starts to harden and then it 's just harder for the lens to shift things phd d: Oh . professor c: and th the the symptom is typically that you you have to hold stuff   further away to to see it . professor c: In fact ,  m my brother 's a gerontological psychologist and he he  came up with an an  a  body age test which  gets down to sort of only three measurements that are good enough st statistical predictors of all the rest of it . grad a: We 're we 're live by the way , so we 've got a good intro here professor c: Oh .  , she 's probably least involved in the signal - processing stuff so maybe we can just just  , I don't think we should go though an elaborate thing , but   Jose and I were just talking about the   , speech e energy thing , phd e: The @ @ professor c: and I  phd e: Yeah . But I think , you know , the the i if I can if you don't mind my my speaking for you for a bit ,   . Right now , that he 's not really showing any kind of  distinction , but  but we discussed a couple of the possible things that  he can look at . And  one is that  this is all in log energy and log energy is basically compressing the distances  between things . He was he he was taking everything over two hundred milliseconds  , and  he 's going to vary that number and also look at moving windows , as we discussed before .  And  and the other thing is that the yeah doing the subtracting off the mean and the variance in the  and dividing it by the standard deviation in the log domain , may not be the right thing to do . grad a: Could you take that mike there ? phd d: Are these the long term means ? Like , over the whole  , the means of what ? grad a: Thanks . professor c:  B Between between phd d: All the frames in the conversation ? professor c: No . professor c: And so i i his his He 's making the constraint it has to be at least two hundred milliseconds . And then he 's he 's  measuring at the frame level still at the frame level , of what phd d: Right .  and But one thing he was pointing out is when he he looked at a bunch of examples in log domain , it is actually pretty hard to see the change . And you can sort of see that , because of j of just putting it on the board that if you sort of have log - X plus log - X , that 's the log of X plus the log of two phd e: Yep . professor c: and it 's just , you know , it it diminishes the effect of having two of them . phd d: But you could do like a C D F there instead ?  , we don't know that the distribution here is normally . So So what I was suggesting to him is that phd d: So just some kind of a simple professor c: Actually , a PDF . professor c: Yeah , but I think also u I think a good first indicator is when the the the researcher looks at examples of the data and can not see a change in how big the the signal is , when the two speaker phd e: Yeah . professor c: doing casual looking and can get the sense , " Hey , there 's something there . And when he 's looking in straight energy he is , so that 's a good place to start .  , when you did the sampling ?  over the speech segments or s or sampling over the the individual channels in order to do the e  the amplitude equalization , did you do it over just the entire everything in the mike channels ? phd e: How professor c: You didn't try to find speech ? grad a: No , I just took over the entire s  entire channel  sampled ten minutes randomly . professor c: And someone who would who would be So the normalization factor probably is i i i is is grad a: Yeah , this was quite quick and dirty , and it was just for listening . So yeah there there there There 's a good chance then given that different people do talk different amounts that there is there there is still a lot more to be gained from gain norm normalization with some sort phd e: Yeah . But we were agreed that in addition to that  there should be s stuff related to pitch and harmonics and so forth . professor c: So we didn't talk at all about  the other derivatives , but  again just just looking at  , I think  Liz has a very good point , that in fact it would be much more graphic just to show Well , actually , you do have some distributions here ,  for these cases . professor c: You have some histograms ,  and  , they don't look very separate . phd e: This is the the first derivate of log of frame energy  without any kind of normalization . grad a: Except that it 's hard to judge this because the they 're not normalized . phd d: W  , what I meant is , even if you use linear , you know , raw measures , like raw energy or whatever , professor c: " Number " phd d: maybe we shouldn't make any assumptions about the distribution 's shape , and just use you know , use the distribution to model the the mean , or what y you know , rather than the mean take some professor c: Yeah . grad a: Interesting phd e: Here I I professor c: Oh that yeah that 's a good q phd e: in No I I I haven't the result professor c: did did you have this sort of thing , for just the just the l r  the the unnormalized log energy ? OK . professor c: That 's a phd d: Well it might be just good to know what it looks like . That 's That 's  cuz I 'd mentioned scatter plots before but she 's right , phd d: Cuz phd e: Huh ? professor c: even before you get the scatter plots , just looking at a single feature  , looking at the distribution , is a good thing to do . professor c: Yeah , but but what she 's saying is , which is right , is le phd e: combination of two , of energy and derivate professor c: let 's start with the Before we get complicated , let 's start with the most basic wh thing , which is we 're arguing that if you take energy  if you look at the energy , that , when two people are speaking at the same time , usually there 'll be more energy than when one is right ? phd e: Yeah . professor c: And the first way you 'd look at that ,  s she 's , you know , absolutely right , is that you would just take a look at the distribution of those two things , much as you 've plotted them here , phd e: Yeah . professor c: So ,  with three colors or three shades or whatever , just just look at those distributions . professor c: And then , given that as a base , you can see if that gets improved , you know , or or or worsened by the looking at regular energy , looking at log energy , we were just proposing that maybe it 's you know , it 's harder to see with the log energy ,  and  also these different normalizations , does a particular choice of normalization make it better ? phd e: Yeah . professor c: But I had maybe made it too complicated by suggesting early on , that you look at scatter plots because that 's looking at a distribution in two dimensions . professor c:  And then we w I think we 're agreed that pitch - related things are are are going to be a a really likely candidate to help . professor c:  But since  your intuition from looking at some of the data , is that when you looked at the regular energy , that it did in fact usually go up , when two people were talking , that 's eh you know , you should be able to come up with a measure which will match your intuition . professor c: And she 's right , that a that having a having having this table , with a whole bunch of things , with the standard deviation , the variance and so forth , it 's it 's it 's harder to interpret than just looking at the the same kind of picture you have here . But It it 's curious but  I f I found it in the in the mixed file , in one channel that eh in several oh e eh several times eh you have an speaker talking alone with a high level of energy professor c:   phd e: eh in the middle eh a zone of overlapping with mmm less energy professor c:   So there 'll be some cases for which phd e: Because there reach very many professor c: But , the qu So So they 'll be phd d: Right . professor c: This is I w want to point to visual things , But  they there 'll be time There 'll be overlap between the distributions , but the question is , " If it 's a reasonable feature at all , there 's some separation . grad a: And I was just going to say that that right now we 're just exploring . I grad a: What you would imagine eventually , is that you 'll feed all of these features into some discriminative system . grad a: And so even if if one of the features does a good job at one type of overlap , another feature might do a good job at another type of overlap .  the the reason I had suggested the scatter f p features is I used to do this a lot , when we had thirteen or fifteen or twenty features to look at . phd e: Yeah , this is the professor c:  Because something is a good feature  by itself , you don't really know how it 'll behave in combination and so it 's nice to have as many as many together at the same time as possible in  in some reasonable visual form . There 's cool graphic things people have had sometimes to put together three or four in some funny funny way . But it 's true that you shouldn't do any of that unless you know that the individual ones , at least , have have some  some hope phd e: Yeah . phd d: it 's really important to pick a normalization that matches the distribution for that feature . phd d: And it may not be the same for all the types of overlaps or the windows may not be the same . e Actually , I was wondering , right now you 're taking a all of the speech , from the whole meeting , and you 're trying to find points of overlap , but we don't really know which speaker is overlapping with which speaker , professor c: Right . phd d: right ? So  another way would just be to take the speech from just , say , Morgan , And just Jane and then just their overlaps , phd e: Yeah . phd d: like but by hand , by cheating , and looking at you know , if you can detect something that way , because if we can't do it that way , there 's no good way that we 're going to be able to do it . phd d: That You know , there might be something helpful and cleaner about looking at just individuals and then that combination alone . So if I don't know , if you go through and you find Adam , cuz he has a lot of overlaps and some other speaker who also has e enough speech phd e: Yeah . phd d: and just sort of look at those three cases of Adam and the other person and the overlaps , phd e: Yeah . phd d: maybe and just look at the distributions , maybe there is a clear pattern phd e: Yeah . phd d: but we just can't see it because there 's too many combinations of of people that can overlap . postdoc b: I think it 's to start with it 's s your your idea of simplifying , starting with something that you can see eh you know without the extra layers of phd d: Right . Cuz if energy doesn't matter there , like I don't think this is true , but what if phd e: To study individual ? postdoc b: Sorry , what ? phd d:  ? phd e: To study individual ? postdoc b: Well , you you you don't have to study everybody individually phd d: Well , to study the simplest case to get rid of extra phd e: The the the But Consider postdoc b: but just simple case and the one that has the lot of data associated with it . Cuz what if it 's the case and I don't think this is true grad a: That was a great overlap by the way . phd d: What if it 's the case that when two people overlap they equate their you know , there 's a conservation of energy and everybody both people talk more softly ? I don't think this happens at all . postdoc b: Or or what if what if the equipment what if the equipment adjusts somehow , phd d: Or they get louder . postdoc b: there 's some equalizing in there ? phd d: Yeah or professor c: no we don't have that . grad a: Well , but But I think that 's what I was saying about different types of overlap . phd d: There are there are different types , and within those types , like as Jose was saying , that sounded like a backchannel overlap , meaning the kind that 's a friendly encouragement , like "    , but , some of those , as you showed , I think can be discriminated by the duration of the overlap . It Actually the s new student , Don , who  Adam has met , and he was at one of our meetings He 's getting his feet wet and then he 'll be starting again in mid - January . phd d: and So maybe phd e: This is a s a general studio of the overlapping we 're studying the i professor c: Yeah . Well I I I I would s actually still recommend that he do the overall thing phd d: So it might be something that we can help by categorizing some of them and then , you know , look at that . professor c: he has the histogram mechanism , he has the stuff that subtracts out and all he has to do is change it   from from log to plain energy and plot the histogram and look at it . And then he should go on and do the other stuff bec but But this will phd d: Yeah . I didn't mean that that for you to do that , but I was thinking if if Don and I are trying to get categories professor c:   phd d: and we label some data for you , and we say this is what we think is going So you don't have to worry about it . phd e: Consider different class of overlap ? phd d: Yeah , that we would be working on anyway . phd d: Then maybe you can try some different things for those three cases , and see if that helps , or phd e: Yeah . This is the thing I I comment with you before , that  we have a great variation of th situation of overlapping . phd e: And the behavior for energy is ,  log energy , is not  the same all the time . phd e: And professor c: But I guess I was just saying that that right now  from the means that you gave , I don't have any sense of whether even , you know , there are any significant number of cases for which there is distinct and I would imagine there should be some you know , there should be The distributions should be somewhat separated . professor c:  and I I would still guess that if they are not separated at all , that there 's some there 's there 's most likely something wrong in the way that we 're measuring it . professor c: but  For instance ,  I wouldn't expect that it was very common overall , that when two people were talking at the same time , that it would that it really was lower , phd e: Yeah . phd d: or a sort of , a case where where you would never know that unless you actually go and look at two individuals . phd d: It might the case , though , that the significant energy , just as Jose was saying , comes in the non - backchannel cases . Because in back Most people when they 're talking don't change their own energy when they get a backchannel , cuz they 're not really predicting the backchannel . professor c: e e and and again what they what difference there was would kind of be lost in taking the log , phd d: and the backchannels are sort of easy to spot s in terms of their words or  , just listen to it . phd d: It just professor c: Mmm , no , if it 's if i if it 's grad a: Tone professor c: Well , it won't be as big . phd d: even if you take the log , you can your model just has a more sensitive measures . grad a: You could imagine doing specialized ones for different types of backchannels , if you could if you had a good model for it . professor c: If if you 're a I guess my point is , if you 're doing essentially a linear separation , taking the log first does in fact make it harder to separate . professor c: So it 's So ,  if you i i So i if there if there close to things it does phd e: Yeah . And right now we 're essentially doing this linear thing by looking across here and and saying we 're going to cut it here . But anyway , yeah , we 're not disagreeing on any of this , we should look at it more  more finely , but   I think that This often happens , you do fairly complicated things , and then you stand back from them and you realize that you haven't done something simple . So  , if you generated something like that just for the energy and see , and then , a a a as as Liz says , when they g have   smaller  , more coherent groups to look at , that would be another interesting thing later . professor c: And then that should give us some indication between those , should give us some indication of whether there 's anything to be achieved f from energy at all . But then the Have you started looking at the pitch related stuff at all , or ? Pitch related ? phd e: The ? professor c: Harmonicity and so on ? phd e: I I 'm preparing the the program but I don't I don't begin because eh I saw your email professor c: Preparing to Yeah . phd e: and I agree with you it 's better to I suppose it 's better to to consider the the energy this kind of parameter bef professor c: Yeah . I I I I Well , we certainly should see this but I I I I think that the harm I certainly wasn't saying this was better than the harmonicity and pitch related things I was just saying phd e: I I go on with the with the pitch , professor c: Yeah . professor c: Yeah , I was just saying phd e: I I I I understood  that eh I I had to finish by the moment with the and and concentrate my my energy in that problem . But I think , like , all these derivatives and second derivatives and all these other very fancy things , I think I would just sort of look at the energy and then get into the harmonicity as as a suggestion . So maybe  since w we 're trying to  compress the meeting , I know Adam had some form stuff he wanted to talk about and did you have some ? postdoc b: I wanted to ask just s something on the end of this top topic . So , when I presented my results about the  distribution of overlaps and the speakers and the profiles of the speakers , at the bottom of that I did have a proposal , phd e:  - huh . postdoc b: and I had plan to go through with it , of of co coding the types of overlaps that people were involved in s just with reference to speaker style so , you know , with reference phd d: Oh . postdoc b: and you know I said that on my in my summary , phd d: That 'd be great . postdoc b: that you know so it 's like people may have different amounts of being overlapped with or overlapping phd d: Yeah , I remem Right . postdoc b: but that in itself is not informative without knowing what types of overlaps they 're involved in so I was planning to do a taxonomy of types overlaps with reference to that . postdoc b: So , but it you know it 's like it sounds like you also have  something in that direction . postdoc b: Is is it phd d: We have nothing You know , basically , we got his environment set up . It 's mostly that , if we had to label it ourselves , we we would or we 'd have to , to get started , but if It it would be much better if you can do it . You 'd be much better at doing it also because you know , I I 'm not I don't have a good feel for how they should be sorted out , postdoc b: Interesting . phd d: and I really didn't wanna go into that if I didn't have to . So if If you 're w willing to do that or or grad a: It would be interesting , though , to talk , maybe not at the meeting , but at some other time about what are the classes . phd d: I think that 's a research effort in and of itself , phd e: Yeah . phd d: because you can read the literature , but I don't know how it 'll turn out phd e: Yeah . postdoc b: It seems like we also s with reference to a purpose , too , that we we 'd want to have them coded . phd d: And we 'd still have some funding for this project , phd e:   phd d: like probably , if we had to hire some like an undergrad , because  Don is being covered half time on something else postdoc b:   phd d: he we 're not paying him the full RA - ship for all the time .  If we got it to where we wanted we needed someone to do that I don't think there 's really enough data where where postdoc b:   Yeah , I see this as a prototype , to use the only the the already transcribed meeting as just a prototype . phd e: I I think a a another parameter we c we we can consider is eh the duration . Because is possible eh some s s  eh some classes eh has eh a type of a duration , eh , a duration very short  when we have we have overlapping with speech . And it 's interesting , I think , to consider the the window of normalization , normalization window . Eh because eh if we have a type of , a kind of eh overlap , eh backchannel overlap , with a short duration , is possible eh to normali i i that if we normalize eh with eh eh consider only the the eh window eh by the left eh ri eh side on the right side overlapping with a a very eh oh a small window eh the if the fit of normalization is eh mmm bigger eh in that overlapping zone eh very short postdoc b:    that you have eh you have a backchannel , eh , eh you have a overlapping zone very short phd d: Yeah . phd e: and you consider eh n eh all the channel to normalize this very short eh professor c:   phd e: for example " mmm  -   " eh And the energy is not eh height eh I think if you consider all the channel to normalize and the channel is mmm bigger eh eh eh compared with the with the overlapping eh duration , professor c:   phd e: eh the effect is mmm stronger eh that I  the the e effect of the normalization eh with the mean and the and the variance eh is different that if you consider only a window compared eh with the n the duration of overlapping . phd e: Is s If phd d: Well it 's a sliding window , right ? So if you take the the measure in the center of the overlapped piece , you know , there 'd better be some something . phd d: But if your window is really huge then yeah you 're right you won't even phd e: Yeah , This is the This is the the idea , to consider only the the small window near near near the the overlapping zone . You know , you shouldn't be more than like You should definitely not be three times as big as your as your backchannel . And hopefully it 's more like on the order of professor c: I 'm not sure that 's necessarily true . professor c: Because because it because  again if you 're just compensating for the gain , phd d: Yea phd e: Yeah . professor c: you know , the fact that this this gain thing was crude , and the gain wh if someone is speaking relatively at consistent level , just to to give a an extreme example , all you 're doing is compensating for that . And then you still s And then if you look at the frame with respect to that , it still should should  change phd d: Yeah , it depends how different your normalization is , as you slide your window across . postdoc b: It 's possible to try it both ways , grad a: Well ,  we 're also talking about a couple of different things . postdoc b: isn't it ? in this small grad a: one is your analysis window and then the other is any sort of normalization that you 're doing . phd d: But it is definitely true that we need to have the time marks , phd e: Yeah . phd d: and I was assuming that will be inherited because , if you have the words and they 're roughly aligned in time via forced alignment or whatever we end up using , then you know , this student and I would be looking at the time marks postdoc b: Yep , I agree . Coming off of the other phd d: and classifying all the frames inside those as whatever labels Jane gave phd e: Yeah . phd d:  phd e: I can give you my transcription file , postdoc b: I was thinking that that would come from the engineering side , phd d: I don't think you need to . That should be linked to the words which are linked to time somehow , postdoc b: There you go . grad a:  If it 's not hand - marked then we 're not going to get the times . phd d: Well , it 's something that w Well , we we wouldn't be able to do any work without a forced alignment anyway , phd e: Yes phd d: so somehow if once he gets going we 're gonna hafta come up with one professor c: Yes . professor c: Well again for the close mike stuff , we could come up take a s take the Switchboard system or something , grad a: That might be good enough . professor c: Just , you know , low - pass filter the speech and phd d: Cuz there 's there 's a lot of work you can't do without that , how how would you professor c: Yeah . phd d: You 'd have to go in and measure every start and stop point next to a word grad a: Yep . But , should talk about our options as far as the   transcription grad a: Yep , if IBM doesn't professor c: But . postdoc b: How So it 's two pages per person ? grad a: Nope . postdoc b: Oh ! grad a: So one is a one time only speaker form and the other is the digits .  why did you switch the order of the Date and Time fields ? This is rather a low - level , but grad a: On which one ? postdoc b: On on the new one , Time comes first and then Date , but I thought grad a: Oh you mean on the digit form ? postdoc b: This is this is rather a low level question , but but it used used to be Date came first . postdoc b: Well , how would the How would the user know the time if they didn't know the date ? grad a: It 's an interesting observation , but it was intentional . Because the date is when you actually read the digits and the time and , excuse me , the time is when you actually read the digits , but I 'm filling out the date beforehand . If you look at the form in front of you ? that you 're going to fill out when you read the digits ? you 'll see I 've already filled in the date but not the time . I always assumed So the time is supposed to be pretty exact , because I 've just been taking beginning time time of the meeting . grad a: The the reason I put the time in , is so that the person who 's extracting the digits , meaning me , will know where to look in the meeting , to try to find the digits . professor c: Why What what were you putting in ? postdoc b: Oh , well , I was saying if we started the meeting at two thirty , phd e: Yeah . postdoc b: I 'd put two thirty , and I guess d e everyone was putting two thirty , professor c: Oh . postdoc b: and I didn't realize there was "  oh I 'm about to read this and I should " grad a: Actually it 's about one third each . About one third of them are blank , about one third of them are when the digits are read , and about one third of them are when the meeting starts . postdoc b: This would be a radical suggestion but grad a: I could put instructions ? Nah . postdoc b: Ei - either that or maybe you could maybe write down when people start reading digits on that particular session . grad a: But if I 'm not at the meeting , I can't do that . professor c: For some reason he doesn't want to sit through every meeting that 's grad a: Yep , but that is the reason Name , Email and Time are where they are . phd e: " use only " postdoc b: Actually you could Well that does raise another question , which is why is the " Professional use only " line not higher ? Why doesn't it come in at the point of Date and Seat ? Oh . grad a: What ? professor c: What ? postdoc b: Well , because If y your your professional use , you 're gonna already have the date , and the s grad a: What which form are you talking about ? postdoc b: Well I 'm comparing the new one with the old one . grad a: The digit form doesn't The digit postdoc b: Oh ! I wasn't supposed to phd e: Yeah . grad a: So on the digits form , everything above the line is a fill - in form postdoc b: Sorry about that . Alright s but I didn't mean to derail our discussion here , so you really wanted to start with this other form . grad a: No , either way is fine I just You just started talking about something , and I didn't know which form you were referring to . postdoc b: Alright yeah , I was comparing so th this is So I was looking at the change first . So it 's like we started with this and now we 've got a new version of it wi with reference to this . professor c: So the main thing that the person fills out  is the name and email and time ? phd e: Yeah . postdoc b: What And there 's an addition of the native language , which is a bit redundant . grad a: That 's because the one , the digit form that has native language is the old form not the new form . professor c: " South Midland , North Midland " postdoc b: That 's the old and that 's the new . grad a: Yeah this was the problem with these categories , I I picked those categories from TIMIT . phd d: Actually , the only way I know is from working with the database and having to figure it out . grad a: So , I was gonna ask phd e: What i professor c: So is South Midland like Kansas ? grad a: wh w  . grad a: So so what accent are we speaking ? Western ? professor c: By definition ? phd e: And for simple for for me ? professor c: Well , phd d: Probably Western , yeah . phd e: Is mean my native language Spanish Spanish ? eh The original is the center of Spain and the beca grad a: Yeah ,  you could call it whatever you want . phd e: Because is different , the Span -  the Spanish language from the the north of Spain , of the south , of the west and the grad a: Sure . grad a: So I 'm not sure what to do about the Region field for English variety . You know , when I wrote I was writing those down , I was thinking , " You know , these are great if you 're a linguist " . grad a: But I don't know how to I don't know how to I don't know how to categorize them . professor c: If you 're if e if y phd d: This wasn't developed by th these regions weren't professor c: if you 're a TI or MIT from nineteen eighty - five . grad a: Yeah So I guess my only question was if if you were a South Midland speaking region , person ? Would you know it ? professor c: Yeah . grad a: Is that what you would call yourself ? phd d: I don't know . professor c: You know , I think if you 're talking if you 're thinking in terms of places , as opposed to names different peop names people have given to different ways of talking , I would think North Midwest , and South Midwest would be more common than saying Midland , right , I I went to s phd d: Yeah . Now the usage Maybe we can give them a li like a little map ? with the regions and they just No , I 'm serious . phd d: Because it takes less time , and it 's sort of cute phd e: i at this in that side in that side of the the paper . phd d: Well just a little You know , it doesn't have all the detail , but you sort of professor c: But what if you moved five times and and  postdoc b: Well , I was thinking you could have ma multiple ones and then the amount of time phd d: No , but you 're categorized . You could say , you know " ten years on the east coast , five years on the west coast " or something or other . grad a: Well , We I think we don't want to get that level of detail at this form . phd d:  I As I said , I don't think there 's a huge benefit to this region thing . It it gets The problem is that for some things it 's really clear and usually listening to it you can tell right away if it 's a New York or Boston accent , but New York and Boston are two well , I guess they have the NYC , but New England has a bunch of very different dialects and postdoc b:   grad a: Yeah , so I picked these regions cuz we had talked about TIMIT , and those are right from TIMIT . And so these would be satisfying like a speech research community if we released the database , grad a: So . phd d: but as to whether subjects know where they 're from , I 'm not sure because  I know that they had to fill this out for Switchboard . phd d: Also Northwest you 've got Oreg - Washington and Oregon now which  y people don't know if it 's western or northern . phd d: It 's like Northwest grad a: Am I speaking Am I speaking Western ? professor c: Oh , what is Northern ? Well and what and what 's Northern ? phd d: I think originally it was North Northwest grad a: Northwest ? phd d: But phd e: Yeah . And and so I would think I would say , I 've I 've got a mix of California and Ohio . grad a: I c I think at the first level , for example , we speak the same . grad a: a techno - speak accent ? phd d: Yeah , you know ? phd e: A techno grad a: A a geek region ? phd d: Well it 's  I you can sort of identify postdoc b: Geek region . phd d: it f It 's it 's not not that that 's phd e: Is different . phd d: but but maybe that maybe we could leave this and see what people See what people choose and then  let them just fill in if they don't  I don't know what else we can do , cuz That 's North Midland . postdoc b: I 'm wondering about a question like , " Where are you from mostly ? " phd e: Yeah . professor c: But I I 'm s I 'm now that you mentioned it though , I am really am confused by " Northern " . professor c: If you 're i if you 're postdoc b: Scandinavian , the Minnesota area 's north . professor c: right ? postdoc b:  professor c: And and and Oregon and and Oregon and Washington are are Western , but they 're also Northern . professor c: Maybe Maybe we Maybe we should put a little map and say " put an X on where you 're from " , phd d: No , that 's phd e: And is in those grad a: Yeah really . phd e: And if you put postdoc b: It 'd be pretty simple , yeah . If you put eh the state ? grad a: Well well we sort of postdoc b: Where are you from mostly ? phd d: We we went we went around this and then a lot of people ended up saying that it phd e:  - huh . grad a: Well , I like the idea of asking " what variety of English do you speak " as opposed to where you 're from Because th if we start asking where we 're from , again you have to start saying , " well , is that the language you speak or is that just where you 're from ? " phd e: Yeah . phd d:  it gives us good information on where they 're from , but that doesn't tell us anything grad a: And professor c: We could always ask them if they 're from phd d: well , enough about their grad a:  . So so I would say Germany phd d: like grad a: You know am I speaking with German accent postdoc b: Oh . postdoc b: Well , see , I 'm thinking " Where are you from mostly " phd d: Right . postdoc b: because , you know , then you have some some kind of subjective amount of time factored into it . grad a:  there 's not a lot of r of room professor c: I 'd say , " Boston , New York City , the South and Regular " . grad a: I think of those , Northern is the only one that I don't even know what they 're meaning . phd e: And And  And usually here people here know what is their kind of mmm lang English language ? professor c: That 's a joke . Right ? We can make up our own So we can say " Northwest " , " Rest of West " or something . postdoc b: I professor c: " Do you come from the Louisiana Purchase ? " phd d: So we could take out " North " " Northern " . phd e: eh here Is easy for people to know ? phd d: That 's Yeah , w It 's In It 's it 's harder in America anywhere else , basically . postdoc b: I can't do it , but phd e: Or Boston ? professor c: Yeah . phd d: They know they don't speak the same as the grad a: But is Boston New England ? postdoc b: And they 're proud of it . phd e:  phd d: But that 's why they have New York City but postdoc b: Well , we ca Well , why can't we just say characterize something like char characterize your accent professor c: Well , Boston 's @ @ , too . " postdoc b: and and so I would say , " I don't know " . Right , which probably means you have a very postdoc b: But someone from Boston with a really strong coloration would know . And so would an R - less Maine or something , phd d: And that 's actually good . phd d: I was I was thinking of something along that line professor c: How postdoc b: Good . phd d: because if you don't know , then , you know , ruling out the fact that you 're totally inept or something , postdoc b:  . phd d: if somebody doesn't know , it probably means their accent isn't very strong compared to the sort of midwest standard . professor c: Well , it wasn't that long ago that we had somebody here who was from Texas who was absolutely sure that he didn't have any accent left . I I would say more more sweepingly , " how would you characterize your accent ? " phd e: Yeah . grad a: So you want to change the instructions also not just say region ? phd d: W postdoc b: Well , I think this discussion has made me think that 's s something to consider . grad a: I don't know if I if I read this form , I think they 're going to ask it they 're going to answer the same way if you say , " What 's variety of English do you speak ? Region . " as if you say " what variety of region region do you speak ? Please characterize your accent ? " They 're going to answer the same way . grad a: Well what we talked about with that is is so that they would understand the granularity . postdoc b: Yes , but if , as Liz is suggesting , people who have strong accents know that they do grad a:  that 's what I had before , and you told me to list the regions to list them . phd d:  we we professor c: Yeah last week last week I was sort of r arguing for having it wide open , but then everybody said " Oh , no , but then it will be hard to interpret because some people will say Cincinnati and some will say Ohio " . phd d: What if we put in both ? grad a: That 's what the " Other " is for . phd d: And Would people No ,  what if we put in both ways of asking them ? So . One is Region and the another one is " if you had to characterize yourself your accent , what would you say ? " grad a: Won't they answer the same thing ? phd d: Well they might only answer only one of the questions but if postdoc b: Yeah that 's fine . postdoc b: They might say " Other " for Region because they don't know what category to use phd d: Actually postdoc b: but they might have something phd d: Right . phd d: It just And we we might learn from what they say , as to which one 's a better way to ask it . professor c: W This is just a small thing phd d: But I Cuz I really don't know .  professor c: but  It says " Variety " and then it gives things that e have American as one of the choices . But then it says " Region " , but Region actually just applies to  , US , grad a: Right . professor c: right ? grad a:  that 's why I put the " Other " in . We just We sort of thought , " yes , " y y  professor c: S postdoc b: At the last meeting , my recollection was that we felt people would have  less that that there are so many types and varieties of these other languages and we are not going to have that many subjects from these different language groups grad a: Yep . grad a: So  , I  the way I had it last time was Region was blank , postdoc b: That 's what I thought . grad a: And and I think that that 's the best way to do it , postdoc b: Yeah . grad a: because because of the problems we 're talking about but what we said last week , was no , put in a list , so I put in a list . grad a: Well , certainly dropping " Northern " I think is right , because none of us know what that is . phd d: Cuz ,  And keeping " Other " , and then maybe this North Midland , we call it " North Midwest " . Does that make sense ? phd e: South Midwest ? phd d: That would help me professor c: U unless you 're from Midland , Kansas . phd d: I don't know where Midland is professor c: There 's a Or Midland Midland grad a: Is " Midwest " one word ? professor c: Is it Midland Midland Midland , Texas or Midland , Kansas ? I forget . It 's just one big shebang , where , of course , you have huge variation in dialects , grad a: But that 's true of New England too . I was going to say the only one that doesn't have a huge variety is New York City . I I would think that these categories would be more w would be easier for an an analyst to put in rather than the subject himself . professor c: U grad a: I think that that was what happened with TIMIT , was that it was an analyst . Where does Where does d w Where Where 's where does  New New York west of west of  New York City and Pennsylvania  and  phd d: Yeah , I don't know how it came from . Pennsylvania is not grad a: " Other " , it goes under " Other " , definitely under " Other " . phd d: Well , you know , Pennsylvania has a pretty strong dialect and it 's totally different than professor c: Pennsylvania Yeah . and  New Jersey is not New England and Maryland is not New England and none of those are the South . Rather than have circle fill in forms , say " Region , open paren , E G Southern comma Western comma close paren colon . grad a: Is that a real accent ? postdoc b: Sure , yeah ! grad a: How do you spell it ? phd e: Yeah . Because that get 's at both of the things we were trying to do , professor c: OK . grad a: the granularity , and the person can just self - assess and we don't have to argue about what these regions are . postdoc b: So you have native language , you have region , and then you have time spent in English speaking country . Now , I wonder if it might be useful to have another open field saying " which one parenthesis S paren closed parenthesis " . postdoc b: It doesn't have to be ex all at all exact , just in the same open field format that you have .  s e Any any other  open mike topics or should we go right to the digits ? grad a: did you guys get my email on the multitrans ? That OK . postdoc b: So you this is n Dan 's patches , Dan Ellis 's patches . grad a: The what the ones I applied , that you can actually do are Dan 's , because it doesn't slow it down . phd d: M postdoc b: Fantastic ! grad a: Just uses a lot of memory . phd d: So when you say " slow " , does that mean to grad a: No , the the one that 's installed is fine . Which , instead of having the one pane with the one view , It has multiple panes with the views . grad a: But the problem with it is the drawing of those waveforms is so slow that every time you do anything it just crawls . phd d: It 's So , it it 's the redrawing of the w postdoc b: That 's a consideration . postdoc b: And this 'll be a hav having the multiwave will be a big help cuz in terms of like disentangling overlaps and things , that 'll be a big help . postdoc b: e so you e the patches that you grad a: No , he suggested that , but he didn't It 's not installed . phd d: So is there any hope for actually displaying the wave form ? grad a: not if we 're going to use Tcl - TK At least not if we 're going to use Snack . And it 's useful to have the grad a: Why don't we we see how Dan 's works and if it If we really need the display phd d: Yeah . And it 's just , you know , a a uni - dimensional feature , varying in time . phd d: Right ? grad a: We we could do that but that would mean changing the code . grad a: This is a program that we got from someone else , and we 've done patches on . professor c: If there was some Is there some way to have someone write patches in something faster and and link it in , or something ? phd d: That 's grad a: Not easily . grad a: Let 's try it with Dan 's and if that isn't enough , we can do it otherwise . grad a: I think it is , cuz when I was playing with it , the mixed signal has it all in there . And so it 's really It 's not too bad to find places in the in the stream where things are happening . postdoc b: And it 's also also the case that that  this multi - wave thing is proposed to the phd e:  ? postdoc b: So . postdoc b: They said that the only reason they hadn't had the multi the parallel  stream one before was simply that they hadn't had time to do it . grad a: And if if professor c: They may well have not had much demand for it . You mean they could they could do it and it would be fast enough if they do it ? phd e: Yeah . I just mean I just mean that it 's that that his phd d: Or ? phd e: Oh . This one that we now have does have the status of potentially being incorporated l likely being incorporated into the central code . postdoc b: Now , tha Now , if we develop further then , y  , I don't grad a: I think if if if one of us sat down and coded it , so that it could be displayed fast enough I 'm sure they would be quite willing to incorporate it . postdoc b:  it 's I think it 's a nice feature to have it set that way . postdoc b: I just like the idea of it being something that 's , you know , tied back into the original , so that other people can benefit from it . I also understand that you can have widgets that are very useful for their purpose and that you don't need to always go that w route . Let 's do digits , and then we 'll turn off the mikes , and then I have one other thing to discuss . phd d: so I can Well , I can wait for the digits but I can't stay for the discussion grad a: Well , you want to go first ? Or . postdoc b: Well , should we e should we switch off the g professor c: Well , we 'll talk to you about it  grad a: Do you wanna go do digits or do you wanna just skip digits ? phd d:  . phd d: But if there 's something on the rest of the I 'm I 'll be around just have to make call before quarter of . postdoc b: Ke grad a: Why don't you read the digits ? professor c: Yeah , why don't you read the digits and then you can go