PhD A: OK , we 're on .
Professor C: OK , what are we talking about today ?
PhD B: I don't know . Do you have news from the conference talk ? Uh , that was programmed for yesterday {disfmarker} I guess .
Professor C: Uh {disfmarker}
PhD D: Yesterday
Professor C: Uh {disfmarker}
PhD D: Yesterday morning on video conference .
Professor C: Uh ,
PhD B: Well
Professor C: oh , I 'm sorry .
Grad E: Oh . Conference call .
Professor C: I know {disfmarker} now I know what you 're talking about . No , nobody 's told me anything .
PhD B: Alright .
PhD A: Oh , this was the , uh , talk where they were supposed to try to decide {disfmarker}
PhD B: To {disfmarker} to decide what to do ,
PhD A: Ah , right .
PhD B: yeah .
PhD D: Yeah .
Professor C: Yeah . No , that would have been a good thing to find out before this meeting , that 's . No , I have no {disfmarker} I have no idea . Um , Uh , so I mean , let 's {disfmarker} let 's assume for right now that we 're just kind of plugging on ahead ,
PhD B: Yeah .
Professor C: because even if they tell us that , uh , the rules are different , uh , we 're still interested in doing what we 're doing . So what are you doing ?
PhD B: Mm - hmm . Uh , well , we 've {disfmarker} a little bit worked on trying to see , uh , what were the bugs and the problem with the latencies .
PhD D: To improve {disfmarker}
PhD B: So , We took {disfmarker} first we took the LDA filters and , {vocalsound} uh , we designed new filters , using uh recursive filters actually .
Professor C: So when you say " we " , is that something Sunil is doing or is that {disfmarker} ?
PhD B: I 'm sorry ?
Professor C: Who is doing that ?
PhD B: Uh , us . Yeah .
Professor C: Oh , oh . Oh , OK .
PhD B: So we took the filters {disfmarker} the FIR filters {vocalsound} and we {comment} designed , uh , IIR filters that have the same frequency response .
PhD D: But {disfmarker}
Professor C: Mm - hmm .
PhD B: Well , similar , but that have shorter delays .
Professor C: Mm - hmm .
PhD B: So they had two filters , one for the low frequency bands and another for the high frequency bands . And so we redesigned two filters . And the low frequency band has sixty - four milliseconds of delay , and the high frequency band filter has something like eleven milliseconds compared to the two hundred milliseconds of the IIR filters . But it 's not yet test . So we have the filters but we still have to implement a routine that does recursive filtering
Professor C: OK .
PhD B: and {disfmarker}
Professor C: You {disfmarker} you had a discussion with Sunil about this though ?
PhD B: No . No .
Professor C: Uh - huh . Yeah , you should talk with him .
PhD B: Yeah , yeah .
Professor C: Yeah . No , I mean , because the {disfmarker} the {disfmarker} the {disfmarker} the whole problem that happened before was coordination ,
PhD B: Mm - hmm .
Professor C: right ? So {disfmarker} so you need to discuss with him what we 're doing ,
PhD B: Yeah .
Professor C: uh , cuz they could be doing the same thing and {disfmarker} or something .
PhD B: Mm - hmm . Uh , I {disfmarker} yeah , I don't know if th that 's what they were trying to {disfmarker} They were trying to do something different like taking , uh {disfmarker} well , using filter that takes only a past
Professor C: Right .
PhD B: and this is just a little bit different . But I will I will send him an email and tell him exactly what we are doing , so .
Professor C: Yeah , yeah . Um ,
PhD B: Um ,
Professor C: I mean {disfmarker} We just {disfmarker} we just have to be in contact more . I think that {disfmarker} the {disfmarker} the fact that we {disfmarker} we did that with {disfmarker} had that thing with the latencies was indicative of the fact that there wasn't enough communication .
PhD B: Mm - hmm .
Professor C: So .
PhD B: Alright .
Professor C: OK .
PhD B: Um , Yeah . Well , there is w one , um , remark about these filters , that they don't have a linear phase . So ,
Professor C: Right .
PhD B: Well , I don't know , perhaps it {disfmarker} perhaps it doesn't hurt because the phase is almost linear but . Um , and so , yeah , for the delay I gave you here , it 's {disfmarker} it 's , uh , computed on the five hertz modulation frequency , which is the {disfmarker} mmm , well , the most important for speech so . Uh , this is the first thing .
Professor C: So that would be , uh , a reduction of a hundred and thirty - six milliseconds ,
PhD D: The low f f
PhD B: Yeah .
Professor C: which , uh {disfmarker} What was the total we ended up with through the whole system ?
PhD B: Three hundred and thirty .
Professor C: So that would be within {disfmarker} ?
PhD B: Yeah , but there are other points actually , uh , which will perhaps add some more delay . Is that some other {disfmarker} other stuff in the process were perhaps not very {disfmarker} um perf well , not very correct , like the downsampling which w was simply dropping frames .
Professor C: Yeah .
PhD B: Um , so we will try also to add a nice downsampling having a filter that {disfmarker} that {disfmarker}
Professor C: Uh - huh .
PhD B: well , a low - pass filter at {disfmarker} at twenty - five hertz . Uh , because wh when {disfmarker} when we look at the LDA filters , well , they are basically low - pass but they leave a lot of what 's above twenty - five hertz .
Professor C: Yeah .
PhD B: Um , and so , yeah , this will be another filter which would add ten milliseconds again .
Professor C: Yeah .
PhD B: Um , yeah , and then there 's a third thing , is that , um , basically the way on - line normalization was done uh , is just using this recursion on {disfmarker} on the um , um , on the feature stream ,
Professor C: Yeah .
PhD B: and {disfmarker} but this is a filter , so it has also a delay . Uh , and when we look at this filter actually it has a delay of eighty - five milliseconds . So if we {disfmarker}
Professor C: Eighty - five .
PhD B: Yeah . If we want to be very correct , so if we want to {disfmarker} the estimation of the mean t t to {disfmarker} to be {disfmarker} well , the right estimation of the mean , we have to t to take eighty - five milliseconds in the future . Mmm .
Professor C: Hmm ! That 's a little bit of a problem .
PhD B: Yeah . Um , But , well , when we add up everything it 's {disfmarker} it will be alright . We would be at six so , sixty - five , plus ten , plus {disfmarker} for the downsampling , plus eighty - five for the on - line normalization . So it 's
Professor C: Uh ,
PhD B: plus {disfmarker} plus eighty for the neural net and PCA .
Professor C: yeah , but then there 's {disfmarker} Oh .
PhD B: So it would be around two hundred and forty {disfmarker} so , well ,
Professor C: Just {disfmarker} just barely in there .
PhD B: plus {disfmarker} plus the frames , but it 's OK .
PhD A: What 's the allowable ?
Professor C: Two - fifty , unless they changed the rules .
PhD B: Hmm .
Professor C: Which there is {disfmarker} there 's some discussion of .
PhD A: What were they thinking of changing it to ?
Professor C: But {disfmarker}
PhD B: Yeah .
Professor C: Uh , well the people who had very low latency want it to be low {disfmarker} uh , very {disfmarker} {vocalsound} very very narrow , uh , latency bound . And the people who have longer latency don't . So .
PhD A: Huh .
PhD B: So , yeah .
Professor C: Unfortunately we 're the main ones with long latency , but
PhD A: Ah !
Professor C: But , uh ,
PhD B: Yeah , and basically the best proposal had something like thirty or forty milliseconds of latency .
Professor C: you know , it 's {disfmarker} Yeah .
PhD B: So . Well .
Professor C: Yeah , so they were basically {disfmarker} I mean , they were more or less trading computation for performance and we were , uh , trading latency for performance . And they were dealing with noise explicitly and we weren't , and so I think of it as complementary , that if we can put the {disfmarker}
PhD A: Think of it as what ?
Professor C: Complementary .
PhD A: Hmm .
Professor C: I think the best systems {disfmarker} so , uh , everything that we did in in a way it was {disfmarker} it was just adamantly insisting on going in with a brain damaged system , which is something {disfmarker} actually , we 've done a lot over the last thirteen years . Uh , {vocalsound} which is we say , well this is the way we should do it . And then we do it . And then someone else does something that 's straight forward . So , w th w this was a test that largely had additive noise and we did {disfmarker} we adde did absolutely nothing explicitly to handle ad additive noise .
PhD A: Right .
Professor C: We just , uh , you know , trained up systems to be more discriminant . And , uh , we did this , uh , RASTA - like filtering which was done in the log domain and was tending to handle convolutional noise . We did {disfmarker} we actually did nothing about additive noise . So , um , the , uh , spectral sub subtraction schemes a couple places did seem to seem to do a nice job . And so , uh , we 're talking about putting {disfmarker} putting some of that in while still keeping some of our stuff . I think you should be able to end up with a system that 's better than both but clearly the way that we 're operating for this other stuff does involved some latency to {disfmarker} to get rid of most of that latency . To get down to forty or fifty milliseconds we 'd have to throw out most of what we 're doing . And {disfmarker} and , uh , I don't think there 's any good reason for it in the application actually . I mean , you 're {disfmarker} you 're {disfmarker} you 're speaking to a recognizer on a remote server and , uh , having a {disfmarker} a {disfmarker} a quarter second for some processing to clean it up . It doesn't seem like it 's that big a deal .
PhD A: Mm - hmm .
Professor C: These aren't large vocabulary things so the decoder shouldn't take a really long time , and .
PhD A: And I don't think anybody 's gonna notice the difference between a quarter of a second of latency and thirty milliseconds of latency .
Professor C: So . No . What {disfmarker} what does {disfmarker} wa was your experience when you were doing this stuff with , uh , the {disfmarker} the {disfmarker} the surgical , uh , uh , microscopes and so forth . Um , how long was it from when somebody , uh , finished an utterance to when , uh , something started happening ?
PhD A: Um , we had a silence detector , so we would look for the end of an utterance based on the silence detector .
Professor C: Mm - hmm .
PhD A: And I {disfmarker} I can't remember now off the top of my head how many frames of silence we had to detect before we would declare it to be the end of an utterance .
Professor C: Mm - hmm . Mm - hmm .
PhD A: Um , but it was , uh , I would say it was probably around the order of two hundred and fifty milliseconds .
Professor C: Yeah , and that 's when you 'd start doing things .
PhD A: Yeah , we did the back trace at that point to get the answer .
Professor C: Yeah . Of course that didn't take too long at that point .
PhD A: No , no it was pretty quick .
Professor C: Yeah .
PhD A: So {disfmarker}
Professor C: Yeah , so you {disfmarker} you {disfmarker} so you had a
PhD A: this w
Professor C: so you had a {disfmarker} a quarter second delay before , uh , plus some little processing time ,
PhD A: Right .
Professor C: and then the {disfmarker} the microscope would start moving or something .
PhD A: Right .
Professor C: Yeah .
PhD A: Right .
Professor C: And there 's physical inertia there , so probably the {disfmarker} the motion itself was all {disfmarker}
PhD A: And it felt to , uh , the users that it was instantaneous . I mean , as fast as talking to a person . It {disfmarker} th I don't think anybody ever complained about the delay .
Professor C: Yeah , so you would think as long as it 's under half a second or something .
PhD A: Yeah .
Professor C: Uh , I 'm not an expert on that
PhD A: Yeah .
Professor C: but .
PhD A: I don't remember the exact numbers but it was something like that .
Professor C: Yeah .
PhD A: I don't think you can really tell . A person {disfmarker} I don't think a person can tell the difference between , uh , you know , a quarter of a second and a hundred milliseconds , and {disfmarker} I 'm not even sure if we can tell the difference between a quarter of a second and half a second .
Professor C: Yeah .
PhD A: I mean it just {disfmarker} it feels so quick .
Professor C: Yeah . I mean , basically if you {disfmarker} yeah , if you said , uh , um , " what 's the , uh , uh {disfmarker} what 's the shortest route to the opera ? " and it took half a second to get back to you ,
PhD A: Yeah .
Professor C: I mean , {vocalsound} it would be f I mean , it might even be too abrupt . You might have to put in a s a s {vocalsound} a delay .
PhD A: Yeah . I mean , it may feel different than talking to a person
Professor C: Yeah .
PhD A: because when we talk to each other we tend to step on each other 's utterances . So like if I 'm asking you a question , you may start answering before I 'm even done .
Professor C: Yeah .
PhD A: So it {disfmarker} it would probably feel different
Professor C: Right .
PhD A: but I don't think it would feel slow .
Professor C: Right . Well , anyway , I mean , I think {disfmarker} we could cut {disfmarker} we know what else , we could cut down on the neural net time by {disfmarker} by , uh , playing around a little bit , going more into the past , or something like that . We t we talked about that .
PhD A: So is the latency from the neural net caused by how far ahead you 're looking ?
Professor C: Mm - hmm .
PhD B: Mm - hmm .
Professor C: And there 's also {disfmarker} well , there 's the neural net and there 's also this , uh , uh , multi - frame , uh , uh , KLT .
PhD A: Wasn't there {disfmarker} Was it in the , uh , recurrent neural nets where they weren't looking ahead at all ?
Professor C: They weren't looking ahead much . They p they looked ahead a little bit .
PhD A: A little bit . OK .
Professor C: Yeah . Yeah , I mean , you could do this with a recurrent net . And {disfmarker} and then {disfmarker} But you also could just , um , I mean , we haven't experimented with this but I imagine you could , um , uh , predict a , uh {disfmarker} um , a label , uh , from more in the past than in {disfmarker} than {disfmarker} than in the future . I mean , we 've d we 've done some stuff with that before . I think it {disfmarker} it works OK .
PhD B: Mm - hmm .
PhD A: We 've always had {disfmarker} usually we used the symmetric windows
Professor C: So .
PhD A: but I don't think {disfmarker}
Professor C: Yeah , but we 've {disfmarker} but we played a little bit with {disfmarker} with asymmetric , guys .
PhD A: Yeah .
Professor C: You can do it . So . So , that 's what {disfmarker} that 's what you 're busy with , s messing around with this ,
PhD B: Uh , yeah .
Professor C: yeah . And , uh ,
PhD D: Also we were thinking to {disfmarker} to , uh , apply the eh , spectral subtraction from Ericsson
PhD B: Yeah .
Professor C: Uh - huh .
PhD D: and to {disfmarker} to change the contextual KLT for LDA .
PhD A: Change the what ?
PhD D: The contextual KLT .
PhD A: I 'm missing that last word . Context
Professor C: K {disfmarker} KLT .
PhD A: KLT .
PhD D: KLT {disfmarker}
Grad E: Oh . KLT .
PhD A: Oh , KLT .
Professor C: Mm - hmm .
PhD A: Uh - huh .
PhD D: KLT , I 'm sorry . Uh , to change and use LDA discriminative .
PhD B: Yeah .
Professor C: Uh - huh .
PhD D: But {disfmarker} I don't know .
Professor C: Uh ,
PhD A: What is the advantage of that ?
PhD D: Uh {disfmarker}
PhD B: Well , it 's that by the for the moment we have , uh , something that 's discriminant and nonlinear . And the other is linear but it 's not discriminant at all . Well , it 's it 's a linear transformation , that {disfmarker} Uh {disfmarker}
Professor C: So at least just to understand maybe what the difference was between how much you were getting from just putting the frames together and how much you 're getting from the discriminative , what the nonlinearity does for you or doesn't do for you . Just to understand it a little better I guess .
PhD B: Mmm . Well {disfmarker} uh {disfmarker} yeah . Actually what we want to do , perhaps it 's to replace {disfmarker} to {disfmarker} to have something that 's discriminant but linear , also . And to see if it {disfmarker} if it improves ov over {disfmarker} over the non - discriminant linear transformation .
PhD A: Hmm .
PhD B: And if the neural net is better than this or , well . So .
Professor C: Yeah , well , that 's what I meant , is to see whether {disfmarker} whether it {disfmarker} having the neural net really buys you anything .
PhD B: Ye Mmm .
Professor C: Uh , I mean , it doe did look like it buys you something over just the KLT .
PhD B: Yeah .
Professor C: But maybe it 's just the discrimination and {disfmarker} and maybe {disfmarker} yeah , maybe the nonlinear discrimination isn't necessary .
PhD D: S maybe .
PhD B: Yeah . Mm - hmm .
Professor C: Could be .
PhD D: Maybe .
Professor C: Good {disfmarker} good to know . But the other part you were saying was the spectral subtraction , so you just kind of , uh {disfmarker}
PhD B: Yeah .
Professor C: At what stage do you do that ? Do you {disfmarker} you 're doing that , um {disfmarker} ?
PhD B: So it would be on the um {disfmarker} on {disfmarker} on the mel frequency bands ,
PhD D: We was think
PhD B: so . Yeah , be before everything .
Professor C: OK ,
PhD D: Yeah ,
Professor C: so just do that on the mel f
PhD D: we {disfmarker} no {disfmarker} nnn We {disfmarker} we was thinking to do before after VAD or
PhD B: Yeah ,
PhD D: Oh , {comment} we don't know exactly when it 's better .
PhD B: um {disfmarker}
PhD D: Before after VAD or {disfmarker}
Professor C: So {disfmarker} so you know that {disfmarker} that {disfmarker} that the way that they 're {disfmarker}
PhD D: and then
PhD B: Um .
Professor C: uh , one thing that would be no {disfmarker} good to find out about from this conference call is that what they were talking about , what they 're proposing doing , was having a third party , um , run a good VAD , and {disfmarker} and determine boundaries .
PhD D: Yeah .
Professor C: And then given those boundaries , then have everybody do the recognition .
PhD D: Begin to work .
Professor C: The reason for that was that , um , uh {disfmarker} if some one p one group put in the VAD and another didn't , uh , or one had a better VAD than the other since that {disfmarker} they 're not viewing that as being part of the {disfmarker} the task , and that any {disfmarker} any manufacturer would put a bunch of effort into having some s kind of good speech - silence detection . It still wouldn't be perfect but I mean , e the argument was " let 's not have that be part of this test . " " Let 's {disfmarker} let 's separate that out . " And so , uh , I guess they argued about that yesterday and , yeah , I 'm sorry , I don't {disfmarker} don't know the answer but we should find out . I 'm sure we 'll find out soon what they , uh {disfmarker} what they decided . So , uh {disfmarker} Yeah , so there 's the question of the VAD but otherwise it 's {disfmarker} it 's on the {disfmarker} the , uh {disfmarker} the mel fil filter bank , uh , energies I guess ?
PhD D: Mm - hmm .
PhD B: Mmm , yeah .
Professor C: You do {disfmarker} doing the {disfmarker} ?
PhD D: Mm - hmm .
Professor C: And you 're {disfmarker} you 're subtracting in the {disfmarker} in the {disfmarker} in the {disfmarker} I guess it 's power {disfmarker} power domain , uh , or {disfmarker} or magnitude domain . Probably power domain , right ?
PhD B: I guess it 's power domain , yeah .
Professor C: why
PhD B: I don't remember exactly .
Professor C: Yeah ,
PhD D: I don't remember .
PhD B: But {disfmarker} yeah , so it 's before everything else ,
Professor C: yep .
PhD B: and {disfmarker}
Professor C: I mean , if you look at the theory , it 's {disfmarker} it should be in the power domain but {disfmarker} but , uh , I 've seen implementations where people do it in the magnitude domain
PhD B: Yeah .
Professor C: and {disfmarker}
PhD B: Mmm .
Professor C: I have asked people why and they shrug their shoulders and say , " oh , it works . " So .
PhD B: Yeah .
Professor C: Uh , and there 's this {disfmarker} I guess there 's this mysterious {disfmarker} I mean people who do this a lot I guess have developed little tricks of the trade . I mean , there 's {disfmarker} there 's this , um {disfmarker} you don't just subtract the {disfmarker} the estimate of the noise spectrum . You subtract th that times {disfmarker}
PhD B: A little bit more and {disfmarker} Yeah .
Professor C: Or {disfmarker} or less , or {disfmarker}
PhD A: Really ?
PhD B: Yeah .
PhD A: Huh !
Professor C: Yeah .
PhD B: And generated this {disfmarker} this ,
Professor C: Uh .
PhD B: um , so you have the estimation of the power spectra of the noise , and you multiply this by a factor which is depend dependent on the SNR . So . Well .
PhD D: Hmm , maybe .
PhD A: Hmm !
PhD B: When the speech lev when the signal level is more important , compared to this noise level , the coefficient is small , and around one . But when the power le the s signal level is uh small compared to the noise level , the coefficient is more important . And this reduce actually the music musical noise ,
PhD A: Oh !
PhD B: uh which is more important during silence portions ,
PhD A: Uh - huh .
PhD B: when the s the energy 's small .
PhD A: Hmm !
PhD B: So there are tricks like this but , mmm .
PhD A: Hmm !
Professor C: Yeah .
PhD B: Yeah .
Professor C: So .
PhD A: Is the estimate of the noise spectrum a running estimate ? Or {disfmarker}
PhD B: Yeah .
Professor C: Yeah .
PhD B: Yeah .
Professor C: Well , that 's {disfmarker} I mean , that 's what differs from different {disfmarker} different tasks and different s uh , spectral subtraction methods .
PhD A: Hmm !
Professor C: I mean , if {disfmarker} if you have , uh , fair assurance that , uh , the noise is {disfmarker} is quite stationary , then the smartest thing to do is use as much data as possible to estimate the noise , get a much better estimate , and subtract it off .
PhD A: Mm - hmm .
Professor C: But if it 's varying at all , which is gonna be the case for almost any real situation , you have to do it on - line , uh , with some forgetting factor or something .
PhD A: So do you {disfmarker} is there some long window that extends into the past over which you calculate the average ?
Professor C: Well , there 's a lot of different ways of computing the noise spectrum . So one of the things that , uh , Hans - Guenter Hirsch did , uh {disfmarker} and pas and other people {disfmarker} actually , he 's {disfmarker} he wasn't the only one I guess , was to , uh , take some period of {disfmarker} of {disfmarker} of speech and in each band , uh , develop a histogram . So , to get a decent histogram of these energies takes at least a few seconds really . But , uh {disfmarker} I mean you can do it with a smaller amount but it 's pretty rough . And , um , in fact I think the NIST standard method of determining signal - to - noise ratio is based on this .
PhD A: A couple seconds ?
Professor C: So {disfmarker} No , no , it 's based on this kind of method ,
PhD A: Hmm .
Professor C: this histogram method . So you have a histogram . Now , if you have signal and you have noise , you basically have these two bumps in the histogram , which you could approximate as two Gaussians .
PhD A: But wh don't they overlap sometimes ?
Professor C: Oh , yeah .
PhD A: OK .
Professor C: So you have a mixture of two Gaussians .
PhD A: Yeah .
Professor C: Right ? And you can use EM to figure out what it is . You know .
PhD A: Yeah .
Professor C: So {disfmarker} so basically now you have this mixture of two Gaussians , you {disfmarker} you n know what they are , and , uh {disfmarker} I mean , sorry , you estimate what they are , and , uh , so this gives you what the signal is and what the noise e energy is in that band in the spectrum . And then you look over the whole thing and now you have a noise spectrum . So , uh , Hans - Guenter Hirsch and others have used that kind of method . And the other thing to do is {disfmarker} which is sort of more trivial and obvious {comment} {disfmarker} is to , uh , uh , determine through magical means that {disfmarker} that , uh , there 's no speech in some period , and then see what the spectrum is .
PhD A: Mm - hmm .
Professor C: Uh , but , you know , it 's {disfmarker} that {disfmarker} that {disfmarker} that 's tricky to do . It has mistakes . Uh , and if you 've got enough time , uh , this other method appears to be somewhat more reliable . Uh , a variant on that for just determining signal - to - noise ratio is to just , uh {disfmarker} you can do a w a uh {disfmarker} an iterative thing , EM - like thing , to determine means only . I guess it is EM still , but just {disfmarker} just determine the means only . Don't worry about the variances .
PhD A: Mm - hmm .
Professor C: And then you just use those mean values as being the {disfmarker} the , uh uh signal - to - noise ratio in that band .
PhD A: But what is the {disfmarker} it seems like this kind of thing could add to the latency . I mean , depending on where the window was that you used to calculate {pause} the signal - to - noise ratio .
PhD B: Yeah , sure . But {disfmarker} Mmm .
Professor C: Not necessarily . Cuz if you don't look into the future , right ?
PhD A: OK , well that {disfmarker} I guess that was my question ,
Professor C: if you just {disfmarker} yeah {disfmarker}
PhD A: yeah .
Professor C: I mean , if you just {disfmarker} if you {disfmarker} you , uh {disfmarker} a at the beginning you have some {disfmarker}
PhD A: Guess .
Professor C: esti some guess and {disfmarker} and , uh , uh {disfmarker}
PhD B: Yeah , but it {disfmarker}
Professor C: It 's an interesting question . I wonder how they did do it ?
PhD B: Actually , it 's a mmm {disfmarker} If - if you want to have a good estimation on non - stationary noise you have to look in the {disfmarker} in the future . I mean , if you take your window and build your histogram in this window , um , what you can expect is to have an estimation of th of the noise in {disfmarker} in the middle of the window , not at the end . So {disfmarker}
Professor C: Well , yeah ,
PhD B: the {disfmarker} but {disfmarker} but people {disfmarker}
Professor C: but what does {disfmarker} what {disfmarker} what {disfmarker} what does Alcatel do ?
PhD D: Mm - hmm .
Professor C: And {disfmarker} and France Telecom .
PhD B: The They just look in the past . I guess it works because the noise are , uh pret uh , almost stationary
Professor C: Pretty stationary .
Grad E: Pretty stationary ,
PhD B: but , um {disfmarker}
Professor C: Well , the thing , e e e e
Grad E: yeah .
Professor C: Yeah , y I mean , you 're talking about non - stationary noise but I think that spectral subtraction is rarely {disfmarker} is {disfmarker} is not gonna work really well for {disfmarker} for non - stationary noise ,
PhD B: Well , if y if you have a good estimation of the noise ,
Professor C: you know ?
PhD B: yeah , because well it it has to work .
Professor C: But it 's hard to {disfmarker}
PhD B: i
Professor C: but that 's hard to do .
PhD B: Yeah , that 's hard to do . Yeah .
Professor C: Yeah . So {disfmarker} so I think that {disfmarker} that what {disfmarker} what is {disfmarker} wh what 's more common is that you 're going to be helped with r slowly varying or stationary noise .
PhD B: But {disfmarker} Mm - hmm .
Professor C: That 's what spectral subtraction will help with , practically speaking .
PhD B: Mm - hmm . Mm - hmm .
Professor C: If it varies a lot , to get a If {disfmarker} if {disfmarker} to get a good estimate you need a few seconds of speech , even if it 's centered , right ?
PhD B: Mm - hmm .
Professor C: if you need a few seconds to get a decent estimate but it 's changed a lot in a few seconds , then it , you know , i it 's kind of a problem .
PhD B: Yeah .
Professor C: I mean , imagine e five hertz is the middle of the {disfmarker} of the speech modulation spectrum ,
PhD B: Mmm .
Professor C: right ? So imagine a jack hammer going at five hertz .
PhD B: Yeah , that 's {disfmarker}
Professor C: I mean , good {disfmarker} good luck . So ,
PhD B: So in this case , yeah , sure , you cannot {disfmarker}
Professor C: Yeah .
PhD B: But I think y um , Hirsch does experiment with windows of like between five hundred milliseconds and one second . And well , five hundred wa was not so bad . I mean and he worked on non - stationary noises , like noise modulated with well , wi with amplitude modulations and things like that ,
PhD A: Were his , uh , windows centered around the {disfmarker}
PhD B: and {disfmarker} But {disfmarker} Um , yeah . Well , I think {disfmarker} Yeah . Well , in {disfmarker} in the paper he showed that actually the estimation of the noise is {disfmarker} is delayed . Well , it 's {disfmarker} there is {disfmarker} you {disfmarker} you have to center the window , yeah .
Professor C: Yeah .
PhD B: Mmm .
Professor C: No , I understand it 's better to do but I just think that {disfmarker} that , uh , for real noises wh what {disfmarker} what 's most likely to happen is that there 'll be some things that are relatively stationary
PhD B: Mmm .
Professor C: where you can use one or another spectral subtraction thing
PhD B: Yeah .
Professor C: and other things where it 's not so stationary and {disfmarker} I mean , you can always pick something that {disfmarker} that falls between your methods ,
PhD B: Hmm .
Professor C: uh , uh , but I don't know if , you know , if sinusoidally , uh , modul amplitude modulated noise is {disfmarker} is sort of a big problem in {disfmarker} in in {disfmarker} practice .
PhD B: Yeah .
Professor C: I think that {vocalsound} it 's uh {disfmarker}
PhD A: We could probably get a really good estimate of the noise if we just went to the noise files , and built the averages from them .
Professor C: Yeah . Well .
PhD B: What {disfmarker} What do you mean ?
Professor C: Just cheat {disfmarker} You 're saying , cheat .
PhD B: But if the {disfmarker} if the noise is stationary perhaps you don't even need some kind of noise estimation algorithm .
Professor C: Yeah . Yeah .
PhD B: We just take th th th the beginning of the utterance and
Professor C: Oh , yeah , sure .
PhD B: I I know p I don't know if people tried this for Aurora .
PhD D: It 's the same .
PhD B: Well , everybody seems to use some kind of adaptive , well , scheme
Professor C: But {disfmarker} but {disfmarker}
PhD D: Yeah .
PhD B: but ,
PhD D: A dictionary .
PhD B: is it very useful
Professor C: you know , stationary {disfmarker}
PhD A: Very slow adaptation .
PhD B: and is the c
PhD A: th
Professor C: Right , the word " stationary " is {disfmarker} has a very precise statistical meaning . But , you know , in {disfmarker} in signal - processing really what we 're talking about I think is things that change slowly , uh , compared with our {disfmarker} our processing techniques .
PhD B: Mm - hmm .
Professor C: So if you 're driving along in a car I {disfmarker} I would think that most of the time the nature of the noise is going to change relatively slowly . It 's not gonna stay absolute the same . If you {disfmarker} if you check it out , uh , five minutes later you may be in a different part of the road
PhD B: Mm - hmm .
Professor C: or whatever . But it 's {disfmarker} it 's {disfmarker} i i i using the local characteristics in time , is probably going to work pretty well .
PhD B: Mm - hmm .
Professor C: But you could get hurt a lot if you just took some something from the beginning of all the speech , of , you know , an hour of speech and then later {disfmarker}
PhD B: Yeah .
Professor C: Uh , so they may be {disfmarker} you know , may be overly , uh , complicated for {disfmarker} for this test but {disfmarker} but {disfmarker} but , uh , I don't know . But what you 're saying , you know , makes sense , though . I mean , if possible you shouldn't {disfmarker} you should {disfmarker} you should make it , uh , the center of the {disfmarker} center of the window . But {disfmarker} uh , we 're already having problems with these delay , uh {disfmarker} {vocalsound} delay issues .
PhD B: Yeah , so .
Professor C: So , uh , we 'll have to figure ways without it . Um ,
PhD A: If they 're going to provide a , uh , voice activity detector that will tell you the boundaries of the speech , then , couldn't you just go outside those boundaries and do your estimate there ?
Professor C: Oh , yeah . You bet . Yeah . So I {disfmarker} I imagine that 's what they 're doing , right ? Is they 're {disfmarker} they 're probably looking in nonspeech sections and getting some , uh {disfmarker}
PhD B: Yeah , they have some kind of threshold on {disfmarker} on the previous estimate , and {disfmarker} So . Yeah . I think . Yeah , I think Ericsson used this kind of threshold . Yeah , so , they h they have an estimate of the noise level and they put a threshold like six or ten DB above , and what 's under this threshold is used to update the estimate . Is {disfmarker} is that right
PhD D: Yeah .
PhD B: or {disfmarker} ?
PhD D: I think so .
PhD B: So it 's {disfmarker} it 's {disfmarker}
PhD D: I have not here the proposal .
PhD B: Yeah . It 's like saying what 's under the threshold is silence ,
Professor C: Does France Telecom do this {disfmarker}
PhD B: and {disfmarker}
Grad E: Hmm .
Professor C: Does France Telecom do th do the same thing ? More or less ?
PhD B: I d I {disfmarker} Y you know , perhaps ?
PhD D: No . I do I have not here the proposal .
Professor C: OK . Um , OK , if we 're {disfmarker} we 're done {disfmarker} done with that , uh , let 's see . Uh , maybe we can talk about a couple other things briefly , just , uh , things that {disfmarker} that we 've been chatting about but haven't made it into these meetings yet . So you 're coming up with your quals proposal , and , uh {disfmarker} Wanna just give a two three minute summary of what you 're planning on doing ?
Grad E: Oh , um , two , three , it can be shorter than that .
Professor C: Yeah .
Grad E: Um . Well , I 've {disfmarker} I 've talked to some of you already . Um , but I 'm , uh , looking into extending the work done by Larry Saul and John Allen and uh Mazin Rahim . Um , they {disfmarker} they have a system that 's , uh , a multi - band , um , system but their multi - band is {disfmarker} is a little different than the way that we 've been doing multi - band in the past , where um {disfmarker} Where we 've been @ @ {comment} uh taking {pause} um {pause} {vocalsound} sub - band features and i training up these neural nets and {disfmarker} on {disfmarker} on phonetic targets , and then combining them some somehow down the line , um , they 're {disfmarker} they 're taking sub - band features and , um , training up a detector that detects for , um , these phonetic features for example , um , he presents um , uh , a detector to detect sonorance . And so what {disfmarker} what it basically is {disfmarker} is , um {disfmarker} it 's {disfmarker} there 's {disfmarker} at the lowest level , there {disfmarker} it 's {disfmarker} it 's an OR ga I mean , it 's an AND gate . So , uh , on each sub - band you have several independent tests , to test whether um , there 's the existence of sonorance in a sub - band . And then , um , it c it 's combined by a soft AND gate . And at the {disfmarker} at the higher level , for every {disfmarker} if , um {disfmarker} The higher level there 's a soft OR gate . Uh , so if {disfmarker} if this detector detects um , the presence of {disfmarker} of sonorance in any of the sub - bands , then the detect uh , the OR gate at the top says , " OK , well this frame has evidence of sonorance . "
PhD A: What are {disfmarker} what are some of the low level detectors that they use ?
Grad E: And these are all {disfmarker} Oh , OK . Well , the low level detectors are logistic regressions . Um , and the , uh {disfmarker}
Professor C: So that , by the way , basically is a {disfmarker} is one of the units in our {disfmarker} in our {disfmarker} our neural network .
Grad E: the one o
Professor C: So that 's all it is . It 's a sig it 's a sigmoid ,
Grad E: Yeah .
Professor C: uh , with weighted sum at the input ,
PhD A: Hmm .
Professor C: which you train by gradient {pause} descent .
Grad E: Right . Yeah , so he uses , um , an EM algorithm to {disfmarker} to um train up these um parameters for the logistic regression .
Professor C: Well , actually , yeah ,
Grad E: The {disfmarker}
Professor C: so I was using EM to get the targets . So {disfmarker} so you have this {disfmarker} this {disfmarker} this AND gate {disfmarker} what we were calling an AND gate , but it 's a product {disfmarker} product rule thing at the output . And then he uses , uh , i u and then feeding into that are {disfmarker} I 'm sorry , there 's {disfmarker} it 's an OR at the output , isn't it ? Yeah ,
Grad E: Mm - hmm .
Professor C: so that 's the product . And then , um , then he has each of these AND things . And , um , but {disfmarker} so they 're little neural {disfmarker} neural units . Um , and , um , they have to have targets . And so the targets come from EM .
PhD A: And so are each of these , low level detectors {comment} {disfmarker} are they , uh {disfmarker} are these something that you decide ahead of time , like " I 'm going to look for this particular feature or I 'm going to look at this frequency , " or {disfmarker} What {disfmarker} what {disfmarker} what are they looking at ?
Grad E: Um {disfmarker}
PhD A: What are their inputs ?
Grad E: Uh Right , so the {disfmarker} OK , so at each for each sub - band {comment} there are basically , uh , several measures of SNR and {disfmarker} and correlation .
PhD A: Ah , OK , OK .
Grad E: Um , um and he said there 's like twenty of these per {disfmarker} per sub - band . Um , and for {disfmarker} for every s every sub - band , e you {disfmarker} you just pick ahead of time , um , " I 'm going to have like five {pause} i independent logistic tests . "
PhD A: Mm - hmm .
Grad E: And you initialize these parameters , um , in some {disfmarker} some way and use EM to come up with your training targets for a {disfmarker} for the {disfmarker} the low - level detectors .
PhD A: Mm - hmm .
Grad E: And then , once you get that done , you {disfmarker} you {disfmarker} you train the whole {disfmarker} whole thing on maximum likelihood . Um , and h he shows that using this {disfmarker} this method to detect sonorance is it 's very robust compared to , um {disfmarker} {vocalsound} to typical , uh , full - band Gaussian mixtures um estimations of {disfmarker} of sonorance .
PhD A: Mm - hmm . Mm - hmm .
Grad E: And , uh so {disfmarker} so that 's just {disfmarker} that 's just one detector . So you can imagine building many of these detectors on different features . You get enough of these detectors together , um , then you have enough information to do , um , higher level discrimination , for example , discriminating between phones
PhD A: Mm - hmm .
Grad E: and then you keep working your way up until you {disfmarker} you build a full recognizer .
PhD A: Mm - hmm .
Grad E: So , um , that 's {disfmarker} that 's the direction which I 'm {disfmarker} I 'm thinking about going in my quals .
PhD A: Cool .
Professor C: You know , it has a number of properties that I really liked . I mean , one is the going towards , um , using narrow band information for , uh , ph phonetic features of some sort rather than just , uh , immediately going for the {disfmarker} the typical sound units .
PhD A: Right .
Professor C: Another thing I like about it is that you t this thing is going to be trained {disfmarker} explicitly trained for a product of errors rule , which is what , uh , Allen keeps pointing out that Fletcher observed in the twenties ,
PhD A: Mm - hmm .
Professor C: uh , for people listening to narrow band stuff . That 's Friday 's talk , by the way . And then , um , Uh , the third thing I like about it is , uh , and we 've played around with this in a different kind of way a little bit but it hasn't been our dominant way of {disfmarker} of operating anything , um , this issue of where the targets come from . So in our case when we 've been training it multi - band things , the way we get the targets for the individual bands is , uh , that we get the phonetic label {disfmarker} for the sound there
PhD A: Mm - hmm .
Professor C: and we say , " OK , we train every {disfmarker} " What this is saying is , OK , that 's maybe what our ultimate goal is {disfmarker} or not ultimate but penultimate {vocalsound} goal is getting these {disfmarker} these small sound units . But {disfmarker} but , um , along the way how much should we , uh {disfmarker} uh , what should we be training these intermediate things for ? I mean , because , uh , we don't know uh , that this is a particularly good feature . I mean , there 's no way , uh {disfmarker} someone in the audience yesterday was asking , " well couldn't you have people go through and mark the individual bands and say where the {disfmarker} where it was sonorant or not ? "
PhD A: Mm - hmm .
Professor C: But , you know , I think having a bunch of people listening to critical band wide , {vocalsound} uh , chunks of speech trying to determine whether {disfmarker} {comment} I think it 'd be impossible .
Grad E: Ouch .
Professor C: It 's all gonna sound like {disfmarker} like sine waves to you , more or less .
PhD A: Mm - hmm .
Professor C: I mean {disfmarker} Well not I mean , it 's g all g narrow band uh , i I m I think it 's very hard for someone to {disfmarker} to {disfmarker} a person to make that determination . So , um , um , we don't really know how those should be labeled . It could sh be that you should , um , not be paying that much attention to , uh , certain bands for certain sounds , uh , in order to get the best result .
PhD A: Mm - hmm .
Professor C: So , um , what we have been doing there , just sort of mixing it all together , is certainly much {disfmarker} much cruder than that . We trained these things up on the {disfmarker} on the , uh the final label . Now we have I guess done experiments {disfmarker} you 've probably done stuff where you have , um , done separate , uh , Viterbis on the different {disfmarker}
Grad E: Yeah . Forced alignment on the sub - band labels ?
Professor C: Yeah .
Grad E: Yeah .
Professor C: You 've done that . Did {disfmarker} did that help at all ?
Grad E: Um , it helps for one or t one iteration but um , anything after that it doesn't help .
Professor C: So {disfmarker} so that may or may t it {disfmarker} that aspect of what he 's doing may or may not be helpful because in a sense that 's the same sort of thing . You 're taking global information and determining what you {disfmarker} how you should {disfmarker} But this is {disfmarker} this is , uh , I th I think a little more direct .
PhD A: How did they measure the performance of their detector ?
Professor C: And {disfmarker} Well , he 's look he 's just actually looking at , uh , the confusions between sonorant and non - sonorant .
PhD A: Mm - hmm .
Professor C: So he hasn't applied it to recognition or if he did he didn't talk about it . It 's {disfmarker} it 's just {disfmarker} And one of the concerns in the audience , actually , was that {disfmarker} that , um , the , uh , uh {disfmarker} he {disfmarker} he did a comparison to , uh , you know , our old foil , the {disfmarker} the nasty old standard recognizer with {vocalsound} mel {disfmarker} mel filter bank at the front , and H M Ms , and {disfmarker} and so forth . And , um , it didn't do nearly as well , especially in {disfmarker} in noise . But the {disfmarker} one of the good questions in the audience was , well , yeah , but that wasn't trained for that . I mean , this use of a very smooth , uh , spectral envelope is something that , you know , has evolved as being generally a good thing for speech recognition but if you knew that what you were gonna do is detect sonorants or not {disfmarker} So sonorants and non - sonorants is {disfmarker} is {disfmarker} is almost like voiced - unvoiced , except I guess that the voiced stops are {disfmarker} are also called " obstruents " . Uh , so it 's {disfmarker} it 's {disfmarker} uh , but with the exception of the stops I guess it 's pretty much the same as voiced - unvoiced ,
PhD A: Mm - hmm .
Professor C: right ? So {disfmarker} so {disfmarker} Um . So , um , if you knew you were doing that , if you were doing something say for a {disfmarker} a , uh {disfmarker} a {disfmarker} a Vocoder , you wouldn't use the same kind of features . You would use something that was sensitive to the periodicity and {disfmarker} and not just the envelope . Uh , and so in that sense it was an unfair test . Um , so I think that the questioner was right . It {disfmarker} it was in that sense an unfair test . Nonetheless , it was one that was interesting because , uh , this is what we are actually using for speech recognition , these smooth envelopes . And this says that perhaps even , you know , trying to use them in the best way that we can , that {disfmarker} that {disfmarker} that we ordinarily do , with , you know , Gaussian mixtures and H M Ms {comment} and so forth , you {disfmarker} you don't , uh , actually do that well on determining whether something is sonorant or not .
PhD A: Didn't they {disfmarker}
Professor C: Which means you 're gonna make errors between similar sounds that are son sonorant or obstruent .
PhD A: Didn't they also do some kind of an oracle experiment where they said " if we {pause} could detect the sonorants perfectly {pause} and then show how it would improve speech recognition ? I thought I remember hearing about an experiment like that .
Professor C: The - these same people ?
PhD A: Mm - hmm .
Professor C: I don't remember that .
PhD A: Hmm .
Professor C: That would {disfmarker} that 's {disfmarker} you 're right , that 's exactly the question to follow up this discussion , is suppose you did that , uh , got that right . Um , Yeah .
PhD A: Hmm .
PhD B: What could be the other low level detectors , I mean , for {disfmarker} {comment} Other kind of features , or {disfmarker} ? in addition to detecting sonorants or {disfmarker} ? Th - that 's what you want to {disfmarker} to {disfmarker} to go for also
Grad E: Um {disfmarker}
PhD B: or {disfmarker} ?
Grad E: What t Oh , build other {disfmarker} other detectors on different {pause} phonetic features ?
PhD B: Other low level detectors ? Yeah .
Grad E: Um , uh Let 's see , um , Yeah , I d I don't know . e Um , um , I mean , w easiest thing would be to go {disfmarker} go do some voicing stuff but that 's very similar to sonorance .
PhD B: Mm - hmm .
Grad E: Um ,
PhD A: When we {disfmarker} when we talked with John Ohala the other day we made a list of some of the things that w
Grad E: Yeah .
PhD A: like frication ,
Grad E: Oh ! OK .
PhD A: abrupt closure ,
Grad E: Mm - hmm . Mm - hmm .
PhD A: R - coloring , nasality , voicing {disfmarker} Uh .
Professor C: Yeah , so there 's a half dozen like that that are {disfmarker}
Grad E: Yeah , nasality .
Professor C: Now this was coming at it from a different angle but maybe it 's a good way to start . Uh , these are things which , uh , John felt that a {disfmarker} a , uh {disfmarker} a human annotator would be able to reliably mark . So the sort of things he felt would be difficult for a human annotator to reliably mark would be tongue position kinds of things .
Grad E: Oh , OK . Placing stuff ,
PhD A: Mm - hmm .
Professor C: Yeah .
Grad E: yeah .
PhD A: There 's also things like stress .
Professor C: Uh {disfmarker}
PhD A: You can look at stress .
Professor C: But stress doesn't , uh , fit in this thing of coming up with features that will distinguish words from one another ,
Grad E: Mm - hmm .
Professor C: right ? It 's a {disfmarker} it 's a good thing to mark and will probably help us ultimate with recognition
PhD A: Yeah , there 's a few cases where it can like permit {comment} and permit .
Professor C: but {disfmarker}
PhD A: But {disfmarker} that 's not very common in English . In other languages it 's more uh , important .
Professor C: Well , yeah , but i either case you 'd write PERMIT , right ? So you 'd get the word right .
PhD A: No , I 'm saying , i i e I thought you were saying that stress doesn't help you distinguish between words .
Professor C: Um ,
PhD A: Oh , I see what you 're saying . As long as you get {disfmarker} The sequence ,
Professor C: We 're g if we 're doing {disfmarker} if we 're talking about transcription as opposed to something else {disfmarker}
PhD A: right ? Yeah . Yeah , yeah , yeah . Yeah . Right .
Professor C: Yeah .
PhD A: So where it could help is maybe at a higher level . Yeah .
Professor C: Right .
Grad E: Like a understanding application .
PhD A: Understanding , yeah . Exactly .
Professor C: Yeah .
Grad E: Yeah .
Professor C: But that 's this afternoon 's meeting . Yeah . We don't understand anything in this meeting . Yeah , so that 's {disfmarker} yeah , that 's , you know , a neat {disfmarker} neat thing and {disfmarker} and , uh {disfmarker} So .
Grad E: S so , um , Ohala 's going to help do these , uh {pause} transcriptions of the meeting data ?
PhD A: Uh , well I don't know . We d we sort of didn't get that far . Um , we just talked about some possible features that could be marked by humans and , um ,
Grad E: Hmm .
PhD A: because of having maybe some extra transcriber time we thought we could go through and mark some portion of the data for that . And , uh {disfmarker}
Professor C: Yeah ,
Grad E: Hmm .
Professor C: I mean , that 's not an immediate problem , that we don't immediately have a lot of extra transcriber time .
PhD A: Yeah , right .
Professor C: But {disfmarker} but , uh , in the long term I guess Chuck is gonna continue the dialogue with John and {disfmarker} and , uh , and , we 'll {disfmarker} we 'll end up doing some I think .
PhD A: I 'm definitely interested in this area , too , f uh , acoustic feature stuff .
Professor C: Uh - huh .
Grad E: OK .
PhD A: So .
Professor C: Yeah , I think it 's an interesting {disfmarker} interesting way to go .
Grad E: Cool .
Professor C: Um , I say it like " said - int " . I think it has a number of good things . Um , so , uh , y you want to talk maybe a c two or three minutes about what we 've been talking about today and other days ?
Grad F: Ri Yeah , OK , so , um , we 're interested in , um , methods for far mike speech recognition , um , {pause} mainly , uh , methods that deal with the reverberation {pause} in the far mike signal . So , um , one approach would be , um , say MSG and PLP , like was used in Aurora one and , um , there are other approaches which actually attempt to {pause} remove the reverberation , instead of being robust to it like MSG . And so we 're interested in , um , comparing the performance of {pause} um , a robust approach like MSG with these , um , speech enhancement or de - reverber de - reverberation approaches .
PhD B: Mm - hmm .
Grad F: And , um , {vocalsound} it looks like we 're gonna use the Meeting Recorder digits data for that .
PhD B: And the de - reverberation algorithm , do you have {disfmarker} can you give some more details on this or {disfmarker} ? Does it use one microphone ?
Grad F: o o
PhD B: Several microphones ? Does it {disfmarker} ?
Grad F: OK , well , um , there was something that was done by , um , a guy named Carlos , I forget his last name , {comment} who worked with Hynek , who , um ,
Professor C: Avendano .
Grad F: OK .
Professor C: Yeah .
Grad F: Who , um ,
PhD B: Mm - hmm .
Grad F: um , it was like RASTA in the sense that of it was , um , de - convolution by filtering um , except he used a longer time window ,
PhD B: Mm - hmm .
Grad F: like a second maybe . And the reason for that is RASTA 's time window is too short to , um include the whole , um , reverberation {disfmarker} um , I don't know what you call it the reverberation response . I if you see wh if you see what I mean . The reverberation filter from my mouth to that mike is like {disfmarker} it 's t got it 's too long in the {disfmarker} in the time domain for the um {disfmarker} for the RASTA filtering to take care of it . And , um , then there are a couple of other speech enhancement approaches which haven't been tried for speech recognition yet but have just been tried for enhancement , which , um , have the assumption that um , you can do LPC um analysis of th of the signal you get at the far microphone and the , um , all pole filter that you get out of that should be good . It 's just the , um , excitation signal {comment} that is going to be distorted by the reverberation and so you can try and reconstruct a better excitation signal and , um , feed that through the i um , all pole filter and get enhanced speech with reverberation reduced .
PhD B: Mm - hmm . Mm - hmm .
Professor C: There 's also this , uh , um , uh , echo cancellation stuff that we 've sort of been chasing , so , uh we have , uh {disfmarker} and when we 're saying these digits now we do have a close microphone signal and then there 's the distant microphone signal . And you could as a kind of baseline say , " OK , given that we have both of these , uh , we should be able to do , uh , a cancellation . " So that , uh , um , we {disfmarker} we , uh , essentially identify the system in between {disfmarker} the linear time invariant system between the microphones and {disfmarker} and {disfmarker} and {disfmarker} and re and invert it , uh , or {disfmarker} or cancel it out to {disfmarker} to some {disfmarker} some reasonable approximation
PhD B: Mm - hmm .
Professor C: through one method or another . Uh , that 's not a practical thing , uh , if you have a distant mike , you don't have a close mike ordinarily , but we thought that might make {disfmarker} also might make a good baseline . Uh , it still won't be perfect because there 's noise . Uh , but {disfmarker} And then there are s uh , there are single microphone methods that I think people have done for , uh {disfmarker} for this kind of de - reverberation . Do y do you know any references to any ? Cuz I {disfmarker} I w I was {disfmarker} w w I {disfmarker} I lead him down a {disfmarker} a bad path on that .
PhD B: Uh , I g I guess {disfmarker} I guess when people are working with single microphones , they are more trying to do {disfmarker}
Professor C: But .
PhD B: well , not {disfmarker} not very {disfmarker} Well , there is the Avendano work ,
Professor C: Right .
PhD B: but also trying to mmm , uh {disfmarker} trying to f t find the de - convolution filter but in the um {disfmarker} not in the time domain but in the uh the stream of features uh I guess . Well , @ @ {comment} there {disfmarker} there 's someone working on this on i in Mons
Professor C: Yeah , OK .
PhD B: So perhaps , yeah , we should try t to {disfmarker} He 's working on this , on trying to {disfmarker}
Professor C: Yeah .
PhD B: on re reverberation , um {disfmarker}
Professor C: The first paper on this is gonna have great references , I can tell already .
PhD B: Mm - hmm .
Professor C: It 's always good to have references , especially when reviewers read it or {disfmarker} or one of the authors and , {vocalsound} feel they 'll " You 're OK , you 've r You cited me . "
PhD B: So , yeah . Well , he did echo cancellation and he did some fancier things like , uh , {vocalsound} {vocalsound} uh , training different network on different reverberation conditions and then trying to find the best one , but . Well .
Professor C: Yeah .
PhD B: Yeah .
Professor C: The oth the other thing , uh , that Dave was talking about earlier was , uh , uh , multiple mike things , uh , where they 're all distant . So , um , I mean , there 's {disfmarker} there 's all this work on arrays , but the other thing is , uh , {pause} what can we do that 's cleverer that can take some advantage of only two mikes , uh , particularly if there 's an obstruction between them , as we {disfmarker} as we have over there .
PhD B: If there is {disfmarker} ?
Professor C: An obstruction between them .
PhD B: Ah , yeah .
Professor C: It creates a shadow which is {disfmarker} is helpful . It 's part of why you have such good directionality with , {vocalsound} with two ears
PhD B: Mm - hmm .
Professor C: even though they 're not several feet apart . For most {disfmarker} for most people 's heads .
PhD A: That could help though .
Professor C: So that {disfmarker} Yeah , the {disfmarker} the head , in the way , is really {disfmarker} that 's what it 's for . It 's basically ,
PhD A: That 's what the head 's for ? To separate the ears ?
Professor C: Yeah , it 's to separate the ears . That 's right , yeah . Yeah . Uh , so . Anyway , O K . Uh , I think that 's {disfmarker} that 's all we have this week .
Grad E: Oh .
Professor C:  And , uh , I think it 's digit time .
PhD A: Actually the , um {disfmarker} For some reason the digit forms are blank .
Professor C: Yeah ?
PhD A: Uh , I think th that may be due to the fact that {comment} Adam ran out of digits , {comment} uh , and didn't have time to regenerate any .
Professor C: Oh ! Oh ! I guess it 's {disfmarker} Well there 's no real reason to write our names on here then ,
PhD A: Yeah , if you want to put your credit card numbers and , uh {disfmarker}
Professor C: is there ?
Grad E: Oh , no {disfmarker} ?
Professor C: Or do {disfmarker} did any {disfmarker} do we need the names for the other stuff ,
PhD A: Uh , yeah , I do need your names and {disfmarker} and the time , and all that ,
Professor C: or {disfmarker} ? Oh , OK .
PhD A: cuz we put that into the " key " files .
Professor C: Oh , OK .
PhD A: Um . But w
Professor C: OK .
PhD A: That 's why we have the forms , uh , even if there are no digits .
Professor C: OK , yeah , I didn't notice this . I 'm sitting here and I was {disfmarker} I was about to read them too . It 's a , uh , blank sheet of paper .
PhD A: So I guess we 're {disfmarker} we 're done .
Professor C: Yeah , yeah , I 'll do my credit card number later . OK .


Project Manager: Think we can first {disfmarker}
Industrial Designer: Mm .
User Interface: Right it was function F_ eight or something .
Industrial Designer: Tha
User Interface: This one right there .
Industrial Designer: Okay .
User Interface: Okay .
Industrial Designer: Who is gonna do a PowerPoint presentation ?
User Interface: Think we all {gap} {disfmarker}
Industrial Designer: You will as well ?
User Interface: Huh . Oh I thought we all were .
Industrial Designer: Okay .
User Interface: Yeah , I have one too , okay .
Project Manager: {gap} .
User Interface: S
Industrial Designer: Yep .
Marketing: {gap} .
User Interface: Whoops I forgot to put the thing on {vocalsound} {disfmarker}
Project Manager: Right . I just wanna {disfmarker} 'cause basically I can't re I've {disfmarker} really crap at remembering everyone's name so I just wanna {disfmarker} rather than going uh Miss Marketing and Miss this and Miss that {vocalsound} wanted to know your names again .
User Interface: Okay .
Industrial Designer: Okay I'm {disfmarker}
Project Manager: {gap} just gonna leave this up here 'cause I'll {vocalsound} you know . So {disfmarker}
Industrial Designer: Okay .
User Interface: Yeah . Sure , that's a good idea .
Industrial Designer: I'm Catherine with a C_ . C_A_T_H_ E_R_ I_N_E_ .
Project Manager: Okay , and
User Interface: Uh Gabriel .
Project Manager: Gabriel . E_L_ is it ?
User Interface: E_L_ .
Project Manager: 'Kay . And you're s r R_E_I_S_S_ {vocalsound} {gap}
Marketing: I am Reissa . R_E_I_S_S_A_ . Double S_ A_ , yeah {vocalsound} yeah . Sorry .
Project Manager: Okay .
Marketing: {vocalsound}
Project Manager: 'S just a bit nicer calling people by their names I think .
Industrial Designer: Right .
User Interface: {vocalsound}
Industrial Designer: True .
Project Manager: {vocalsound} Uh , right .
Marketing: Mm 'kay .
Project Manager: Okay , right , welcome to meeting B_ . Um this is gonna go a lot better than the last meeting , basically ,
Industrial Designer: {vocalsound}
User Interface: {vocalsound}
Project Manager: uh 'cause I know what I'm supposed to be doing now .
Industrial Designer: {vocalsound}
Marketing: {vocalsound}
Project Manager: {vocalsound} I am your Project Manager , and , uh yeah , I'm just here to
Industrial Designer: {vocalsound}
Project Manager: {gap} sort of liaise between the three of you and get things going , get people talking and and I'm gonna be making notes and sending them off to the powers that be and stuff basically . Um right , this {disfmarker} for the purposes of this meeting {disfmarker} what this meeting is all about is um I'm gonna have some presentations from all three of you , what you've been working on for the last wee while , when you haven't been getting hit with spam on your computers and and , you know , filling out silly questionnaires and things .
Industrial Designer: {vocalsound}
Marketing: {vocalsound}
Project Manager: But hopefully you've been {disfmarker} actually been doing something productive . So we're gonna {disfmarker} each of you gonna give us a litt a little presentation . {vocalsound} Um .
Marketing: Mm .
Project Manager: Then we're gonna {vocalsound} work , you know , from each of your presentations . We'll we'll uh talk about what we actually need as a final coming together of it all . Um and then we'll , yeah , we'll {gap} sort of conclude {gap} anything else comes up at the end of it .
Industrial Designer: How long is the meeting ?
Project Manager: This meeting it's not very long . It's uh probably down to about thirty five minutes now . So I want each of your presentations to not be too long , five five minutes , something like that .
Industrial Designer: Okay . {vocalsound} No problem . {vocalsound}
Project Manager: Um if you haven't done a PowerPoint thingy , it doesn't matter , it it just it just says that you {disfmarker} it's {disfmarker} that's just one particular medium . If you haven't had time to prepare one , you can draw stuff on the noteboard , you can talk to us , you can {disfmarker} you know however you want to do your little presentation , basically , you can . Don't feel pressurised into using this thing . 'Cause I don't .
Industrial Designer: {vocalsound}
Project Manager: {vocalsound} Uh okay . So um . You okay over there ? Reissa ,
Marketing: I'm fine . Yeah .
Project Manager: are you uh b are you joining in with this meeting here
Marketing: I uh yeah , yeah .
Project Manager: or are y or are y or are you are you just are you just uh doing some Internet shopping there ? {vocalsound}
User Interface: Think she's finishing up her presentation .
Marketing: D I mean , I I'm finishing off my presentation .
Industrial Designer: {vocalsound}
Marketing: No no . {vocalsound} Uh I'm done . Okay .
Project Manager: Okay , jolly good . Alright , let's have um {disfmarker} well , we all know that it's it's a remote control that we're gonna be dealing with .
Marketing: Mm .
Project Manager: I think the first thing we should look at is um {vocalsound} probably the um what it is that it is actually supposed to be . So that's gonna be you Catherine ,
Industrial Designer: Okay .
Project Manager: if we wanna hear from you first .
Industrial Designer: Okay . Um just connecting this .
Project Manager: You don't have to worry about screwing it in just {disfmarker}
Industrial Designer: Are we getting i Really ?
Project Manager: there you go .
Industrial Designer: Okay . Cool . Okay . So I've got a very quick uh {disfmarker} Uh . Okay .
Marketing: {vocalsound}
Industrial Designer: So the working design , I've got a very quick presentation on this , so um I've {disfmarker} oh no , you can't see a thing . {vocalsound} Oh well , I'm gonna draw it on the board then . It's in blue uh , and I couldn't change it .
User Interface: Oh . {vocalsound}
Project Manager: Ah .
Industrial Designer: We it's fine on my screen , but never mind . So um {vocalsound} the idea is that we've got the energy source um , which in our case will pr , oh well {disfmarker} okay , never mind . So um I think maybe uh two batteries , I dunno what they're called {gap} six , or something like that .
Project Manager: Mm-hmm .
Industrial Designer: Uh and then {vocalsound} um then on the uh remote control itself will have um the sender for the signal , which could be uh an infra-red signal , um which will be sent by an electronic chip . And uh the chip will be controlled by the user interface . So we'll hear about that later from Gabriel .
Project Manager: Mm-hmm .
Industrial Designer: And uh the sender will send to the telly itself an infra-red signal to tell it to switch on or switch channels . Um and that's it really for the working design .
Project Manager: Great . Okay .
Industrial Designer: Sorry the presentation wasn't very uh clear but {disfmarker}
Project Manager: I prefer the pe I prefer the human touch personally .
Industrial Designer: Really ? Cool .
Project Manager: Yeah .
Industrial Designer: Um , should I erase this or {disfmarker}
Project Manager: Do you wanna just give us a moment , I just wanna copy this down .
Industrial Designer: Okay .
Project Manager: Um I dunno if you guys have got any questions for Catherine on any of this ?
Industrial Designer: Fine . {vocalsound} Or suggestions ?
Marketing: Is a battery like the only way of {disfmarker}
Industrial Designer: Well , it's just , you don't want it plugged in really , s
User Interface: Yeah , alternate energy source , like win wind power or {disfmarker}
Project Manager: {vocalsound} Yeah , you blow on it and i {vocalsound}
Industrial Designer: In indoors . {vocalsound}
Marketing: No , no {disfmarker}
User Interface: {vocalsound} Bicycle power .
Marketing: No I meant like {disfmarker}
Industrial Designer: {vocalsound}
Marketing: No 'cause like cha 'cause {disfmarker} always changing um um batteries can get like annoying .
Industrial Designer: {vocalsound}
Marketing: The battery's down and {disfmarker} maybe {vocalsound} , I dunno , solar charged ? {vocalsound}
Industrial Designer: I dunno , swi I th I th I think changing your batteries once every six months is not really a pain , but {disfmarker}
Project Manager: Yeah , it's worked for the last fifty years you know .
Marketing: Mm . Yeah .
User Interface: One question I have , and I don't know how much control we have over this is um , as far as the infra-red signal , do we have control over , you know , how far away you can be from the receiving unit , the the T_V_ , and still have it be operational ? I mean , maybe we want one with a strong signal stream .
Project Manager: How far away is your television ?
Industrial Designer: Yeah .
Project Manager: It's never gonna be more than it's never gonna be , you kno unless you've got a T_V_ the size of a football pitch , it's not {disfmarker} doesn't have to go that far ,
User Interface: Uh {disfmarker}
Industrial Designer: Well , the thing is uh you you don't {disfmarker}
Project Manager: does it ? Doesn't have to go through a wall , because you're not gonna be looking through a wall .
User Interface: That's true .
Marketing: Yeah , but if like you're on the phone in the other room and you need turn television off or something and you don't really want to go into the {disfmarker} put the telephone down , and go into the other room . {vocalsound}
Industrial Designer: Well , we can make the the signal strong enough to go through walls if if you fancy it . I didn't think about that but {disfmarker}
Marketing: How about Bluetooth ? {gap} Instead of using infra-red , use Bluetooth .
Industrial Designer: Why not ? I just think that it's it's gonna cost more
Marketing: Isn't that a better signal ?
Project Manager: Yeah , yeah I d it sounds like you {gap} you w don't wanna overcomplicate things .
Industrial Designer: and I'm I'm not sure it's {disfmarker} you're gonna use it .
Marketing: Mm {vocalsound} .
Project Manager: You know we don't need it .
Industrial Designer: It's a fancy idea uh it's quite nice , but then I don't th I dunno , either you {disfmarker} if you wanna watch the telly you're in the room ,
Project Manager: Yeah , exactly .
Industrial Designer: you are gonna {disfmarker}
Project Manager: Basically , we're we're desi we're designing and marketing a television remote control unit .
Industrial Designer: But {disfmarker}
Project Manager: We're not w w w w designing something that you can plug in a headset to and and you know connect to your laptop computer and stuff . It's uh {disfmarker}
Marketing: Mm .
Industrial Designer: Oh , we can we can keep the idea if you i We can see at a later stage , maybe , I don't {disfmarker}
Marketing: 'S just an idea .
Project Manager: Okay . Right , well done , Catherine . Um Gab Gabriel let's uh let's hear from you on on on such things .
User Interface: Okay .
Industrial Designer: Do you need the border ?
User Interface: Uh I'm just gonna use the PowerPoint uh .
Industrial Designer: Okay . {vocalsound} Sorry .
User Interface: Technical {gap} . Okay .
Marketing: {vocalsound} {vocalsound}
User Interface: Okay , so , while this is warming up ,
Marketing: Adjusting .
User Interface: there it is uh .
Marketing: Yeah .
User Interface: So I'm doing the user interface design .
Project Manager: Mm-hmm .
User Interface: Yeah , and basically uh , as far as methods , I was I was looking looking at looking at uh already existing remotes , trying to find some inspiration from designs that are already out there . Thinking of what we can retain , what we can do away with , uh what we what we can perfect a little bit as far as design um . {gap} we don't want to do something that's too radical of a change , I guess , I mean people want a remote that's familiar , that has their favourite functionalities um and and does the basics , but {disfmarker}
Project Manager: Mm yeah .
User Interface: Um so we can improve what's out there and maintain that , the basic functionality that people want . Um so things that {vocalsound} seem like absolute must-haves uh would be a volume control , um so up-down keys for that , uh channel keys up-down , but then also a numerical key pad so that they can just key directly to the channel that they want , rather than doing up-down , and uh a mute button . Uh one thing that I didn't include here , that I forgot that we talked about last time , was doing um some sort of lock uh function .
Project Manager: Okay .
User Interface: Uh , I don't I dunno , uh that's one possibility . And so in the research that I was doing there's basically two types of remotes , ones that are engineering centred and ones that are more user centred , which I don't know if I can access the web page from here , but I can show you {disfmarker} uh . Yeah . So this is a engineer centred one , so you see it's rather busy , but it also lets you play your movie , stop your movie , fast-forward , all this , um {vocalsound} freeze frame .
Project Manager: Mm-hmm .
User Interface: Uh and this is a user centred one . Uh it's it's easier to g just glance at this and see {vocalsound} what's possible to do ,
Project Manager: Yeah .
User Interface: you're not gonna be staring at it for five minutes .
Project Manager: Great .
User Interface: And I {disfmarker} judging from what what we all talked about during our last meeting I kind of gathered that that's what we were going after , uh or the direction we were going in at least . Um . So , the engineering centred ones uh provide a lot of functionality , but it can be a little bit overwhelming , so the user centred ones just focus on ease of use . Uh and this sort of overlaps with what the marketing person uh , Reissa ,
Marketing: {vocalsound}
User Interface: because uh we we need to find out what what people want before we make firm decisions on this .
Marketing: Mm .
Project Manager: Yeah .
Marketing: {gap} . {vocalsound}
User Interface: So uh , yeah , that's me .
Project Manager: Great . Okay . Now that's I just have a q a q question for you . This w um research that you've been doing looki looking at other , you know , existing units {gap} stuff . Um have you found that anyone else has do has looked into the locking function or {disfmarker}
User Interface: No that that that seemed like a novel idea as f as far as I know . I mean obviously another {disfmarker} {gap} exists {gap} like you like you said in in mobile phones .
Project Manager: Yeah .
User Interface: That was sort of the inspiration for it . Um I've never seen that with {disfmarker} in in all my years in in the remote business .
Project Manager: Yeah . {vocalsound} {vocalsound}
User Interface: I've , haven't I've never seen a locking functionality . I dunno , what uh do you guys have a a yea or nay on that {gap} a feeling about whether that's really necessary ?
Project Manager: Um {disfmarker} I would say it's {disfmarker} If it's simple to do , which I think it probably should be ,
User Interface: Yeah .
Project Manager: even if it's a physical , you know , a f a like a f a physical switch or a physical cover for the remote , even something like that , um then yes ,
User Interface: Mm-hmm . 'Kay .
Project Manager: it's {gap} like , you know , like s you said earlier on ab ab ab a flip thing , something like that ,
User Interface: Right .
Project Manager: but you know being physical . Look into . Um I've had word down from head office that something that we should be centred {vocalsound} well , something we should take into account is um we've gotta keep the corporate image within this remote control unit . It's gotta d look like it's in the R_ and R_ .
User Interface: Mm {vocalsound} .
Project Manager: You know , the the company it's it's , from what I can see from our other products , are yellow with blue writing on them . Um .
Marketing: {vocalsound} {vocalsound} Mm .
User Interface: Right . And our motto is is we put the fashion in electronics .
Project Manager: We put the fashion in electronics . There you go .
User Interface: I think I think we have to carry that mental .
Marketing: Mm .
Project Manager: So it's kinda gotta look it's gotta look new and s you know something fashionable . If if remote control {disfmarker} well , if telephones can be fashionable , then maybe remote control units can be .
User Interface: Mm .
Marketing: Mm .
User Interface: Well yeah these , I think , we can {disfmarker} so we talked about the layout in my presentation and what I didn't mention yet really is is the sort of like the ergonomic design .
Project Manager: Yeah . Because we need {disfmarker}
User Interface: I t I think we can make big improvements over these two that you see here , I mean .
Project Manager: {vocalsound} Yeah . Great .
Industrial Designer: {vocalsound}
User Interface: Uh , everything is going t ergonomic , you know , there's you know mice for your computers that are very ergonomic and keyboards and that could be one of our niches p sort of uh uh in the market , I guess . Um .
Project Manager: Okay , fantastic .
Marketing: Okay .
Project Manager: Right , well done , Gabriel .
Marketing: {gap} .
Project Manager: Um Reissa . Let's plug you in , baby .
Marketing: Where does it go into ?
User Interface: {gap} .
Marketing: Here ?
User Interface: Yeah .
Marketing: The blue thing .
User Interface: Uh , yeah , this is getting all {gap} .
Marketing: {vocalsound}
User Interface: Mm . {vocalsound}
Marketing: {gap} .
User Interface: Yeah , then you just have to do function F_ eight and it should come up .
Marketing: Well , function F_ eight . No {disfmarker}
Project Manager: Yeah , w it it just takes a wee while .
User Interface: Yeah , it just takes a second uh .
Marketing: oh . {vocalsound} Come on . Right . Okay . {gap} . Okay . Well , for our marketing report uh we observed remote control users in a usability lab , and also gave {disfmarker} so this is research {disfmarker} and we also gave participants um questionnaires to fill out . Um total number of people tested were a hundred just so you know , so that hundred people were tested and these were the findings . So seventy five per cent of users find the remote control ugly . Okay , so they don't like the look of the remote control . Um eighty f eighty per cent of them would spend more money if the rem remote control looked really cool and fancy . So I think we all agree with that . Um {vocalsound} current remote controls do not match well with the operating behaviour of the user . So , they don't like {disfmarker} like the way they operate it doesn't like match how people behave . Um {gap} per cent of the users say that they only use ten per cent of the buttons on a remote , so probably if you have like one , two , three , four , five , the whole up to z ten , they probably don't use those , they only use the up and down channel .
Project Manager: 'Cause we've only got five channels . {vocalsound}
Marketing: {gap} {vocalsound} exactly .
Industrial Designer: {vocalsound}
Marketing: {vocalsound} That's another thing . {vocalsound} Um seventy five per cent of users say they zap . Not quite sure what they mean , zap , goes like {vocalsound} .
Project Manager: I think that's k flicking quickly between channels .
User Interface: Yeah , you wanna navigate the channels quickly I guess .
Marketing: Yeah .
Project Manager: Yeah .
Marketing: Mm . Um takes too much time to learn how to use a new remote . I think especially for uh the older generation . I know my grandmother doesn't like mobile phones , takes ages to work how to use . Anyway um and they also {disfmarker} remotes often get lost in the room , so nobody can find them .
User Interface: Mm .
Marketing: {vocalsound} So maybe tracking devices is a good idea .
Project Manager: {vocalsound} Wow .
Marketing: Um personal preferences . {vocalsound}
Project Manager: You are a child of technology , aren't you ? {vocalsound}
Marketing: {vocalsound} {vocalsound} Um so yeah um {vocalsound} I was thinking something easy to use , especially for older people . Um {vocalsound} has to look really cool , flashy groovy for people to buy it . And it's easy to find {vocalsound} , so I don't know whether maybe {disfmarker} and also we asked them whether they wanted {vocalsound} {disfmarker} whether they'd be interested in um {vocalsound} voice activating .
Industrial Designer: {vocalsound}
Marketing: So voice activation . So and this was what we came up with . Then if you look fifteen to twenty five {disfmarker} this is age , sorry , {gap} age groups . So fifteen to twenty five said like ninety two {disfmarker} ninety one per cent of them said yes .
Project Manager: So there you go , yeah .
Marketing: {vocalsound} Um {vocalsound} so basically the majority except for the forty five to fifty five year olds for some reason didn't want a voice activated one . And neither did the older generation , but the younger generation who we are catering for , like who have most of the money nowadays , do want a voice act speech recognition in a remote .
Industrial Designer: {vocalsound}
Project Manager: Uh but do the younger generation have the money ? They they don't .
User Interface: No I would I would say the older the older people , yeah .
Project Manager: It's older generation , they're the ones that have gone out and {disfmarker}
Marketing: Well the twenty five to thirty five year old , and thirty five , and the thirty five to forty five , forty five point seven per cent {gap} say no , so {disfmarker}
Project Manager: People people from the age of thirty f there's a big drop off there .
Marketing: {vocalsound}
Project Manager: For people up to the age of thirty five , you're kinda saying , yeah , they want it . Um but no they're not {gap} sort of {disfmarker} most people that have the money are people from the age of thirty five to fifty five ,
User Interface: Yeah , that would be my guess as well .
Project Manager: uh 'cause they're the ones that have been working for twenty years .
Marketing: So they don't {disfmarker}
Project Manager: Um {vocalsound} d and tha
Marketing: Well {disfmarker}
Project Manager: and that's a {vocalsound} that's quite a minority there , so yeah , it's not even like fifty fifty that's th thirty five per cent .
Marketing: These guys are growing up . {vocalsound}
User Interface: What about just from the the prospective of our manufacturing cost ? I mean if if it's twelve fifty per unit .
Project Manager: Yeah .
User Interface: I mean , okay , there's {disfmarker}
Marketing: {vocalsound} Voice activation might not be the best .
Project Manager: I would say scra I'd say scrap that straight off .
User Interface: Uh .
Marketing: Um also with um with buttons , {vocalsound} a thing called R_S_I_ , so wrist sense {vocalsound} {disfmarker}
User Interface: Repetitive strain uh rep repetitive strain injury
Marketing: Huh ?
User Interface: or like from doing {disfmarker}
Marketing: Yeah , repetitive strains injury , so they don't {disfmarker} I think people who watch T_V_ maybe too often , keep changing channel hurts their wrist .
Industrial Designer: {vocalsound} Well {vocalsound} maybe they shouldn't watch so much T_V_ then . {vocalsound}
Marketing: {vocalsound} I don't think so . {vocalsound}
Project Manager: So y so it's so it's so you got {disfmarker}
User Interface: {vocalsound}
Project Manager: so that's something we should have a look into then i when desi when designing the ergonomics of {disfmarker}
Marketing: Yeah {vocalsound}
User Interface: Mm .
Marketing: maybe not so hard .
User Interface: Mm .
Project Manager: see {vocalsound} have a look if um there's any w any medical background we can find out about this .
Industrial Designer: Maybe it could be , instead of pressing button it could be just touching a {disfmarker}
Marketing: Yeah .
Project Manager: Let's jus {gap}
Marketing: Maybe {disfmarker}
Project Manager: we just want {disfmarker} need to cover our arses so that people aren't gonna sue us in ten years' time , say your remote control gave me repetitive strain injury .
User Interface: Yeah , we should probably consult with our legal department uh .
Marketing: Mm .
Project Manager: Yeah . {vocalsound} They're having a lunch break at the moment , but {disfmarker} yeah .
Industrial Designer: {vocalsound}
Marketing: {vocalsound} Yeah .
Project Manager: I'll see if I can get {disfmarker} see if I can get hold of them for the next meeting .
User Interface: Yeah . I think we can do some really {disfmarker} in in that department , the the ergonomic department , we can make some some really good improvements .
Project Manager: Yeah .
Marketing: Mm . Maybe th the buttons not so high up so you don't have to press so much ,
User Interface: Mm .
Marketing: or we just like flat buttons , something . Yeah .
Project Manager: Okay .
Marketing: So that is me .
Project Manager: That's great , thank you very much for that , Reissa . {vocalsound} Um okay , so we've basically we've decide we've d we've decided that it's gonna be , you know uh , we're going for a basic television remote . It's gotta be safe to use , it's gotta look cool .
Marketing: Mm .
Project Manager: It's gotta be cheap . S um .
Marketing: Mm .
Project Manager: Now going back to the uh industrial design of it , you know , we were looking at whether to use maybe infra-red or Bluetooth . I think , we should just go with the simplest option on everything , uh and that would be infra-red , energy source , that would be batteries . Uh mean we we can look into using the s , you know , the little tiny weeny batteries , all like special long-lasting batteries . Um . {vocalsound} But a in {disfmarker} there's no I don't think there's any point in making a remote control unit that's gonna last for fifty years , because technology will have changed and , you know , we won't have televisions in ten years' time . {vocalsound} So {disfmarker}
Industrial Designer: Yep .
Project Manager: I think we're all um pretty sussed on that . Um anyone have any questions ? Everybody happy in their work ?
Marketing: Mm .
User Interface: Yeah , it seems like we're all on the {disfmarker} pretty much on the same page .
Project Manager: Now {gap} this is good , we've got a good structure going on . We all know where we're going to . {vocalsound} Have you been ge has {disfmarker} have any of you lot been getting loads of crap spam on your computers ?
User Interface: Oh it's probably just you , 'cause you're the project manager . {vocalsound}
Industrial Designer: {gap} .
Project Manager: {vocalsound}
Marketing: Well , just questionnaires .
Project Manager: Yeah .
User Interface: Sell {disfmarker} trying to sell your things {gap} . {vocalsound}
Project Manager: Yeah , {gap} stuff .
Marketing: {vocalsound}
Project Manager: Um okay . Do {disfmarker} oh {gap} have you guys found out if we can if we can e-mail stuff to each other ?
Marketing: Yeah , you can .
Project Manager: Right . Do all you all know my e-mail address ?
User Interface: Okay . No I don't . I {disfmarker}
Industrial Designer: Well , in the project announcement , you've got the addresses , I think .
Marketing: I think he's participant one , aren't you ?
Industrial Designer: So Project Manager , it's participant one at A_M_I_ . {vocalsound}
User Interface: Uh {disfmarker} Oh , it's just participant one oh okay . Yeah .
Project Manager: Can you all d e-mail me your e-mail addresses ?
Marketing: {vocalsound}
Project Manager: {vocalsound} {gap} .
Industrial Designer: You have them i you have them ,
User Interface: Well it's just w it's just it's just par participant one , participant two . {vocalsound}
Industrial Designer: but we'll send you an e-mail .
Project Manager: Send me , yeah
Industrial Designer: You want to have friends , don't you ?
Project Manager: {disfmarker} yeah , okay .
User Interface: {vocalsound} So are we headed towards like a b a big yellow and black remote as far as {gap} maybe that's our next meeting that we discuss that .
Project Manager: {vocalsound} Is it yellow and black or is it yellow and blue ? I I kind of thought it was blue writing on a yellow background , but I might be just going a bit {disfmarker}
User Interface: Well , it's like white on i white and blue on a black background with white {disfmarker} with yellow borders .
Project Manager: Okay .
User Interface: Maybe that's {vocalsound} like getting ahead of ourselves .
Project Manager: Well , maybe you can come up with a few {disfmarker} with a couple of different ideas ?
Industrial Designer: It wouldn't be {disfmarker}
User Interface: Mm .
Marketing: Can't we have different colours in the remotes , so somebody can choose different col
Project Manager: Well , see the thing is is we've gotta keep the company image .
Marketing: like does it have to be of a certain ?
User Interface: Mm .
Project Manager: It's gotta say {disfmarker} people have gotta look at this remote control and instantly recognise that it's a Real Reaction i product .
User Interface: Mm .
Marketing: But if it's a R_R_ , it would be Real Reaction ,
Project Manager: There's loads of companies that called R_R_ .
Marketing: like if it had a symbol on it .
User Interface: Mm .
Project Manager: This is slog {gap} but this is the slogan , this is the the the the type .
Marketing: Whoa .
User Interface: And this is something that came on down from from the higher ups ,
Project Manager: Yeah .
User Interface: so , I mean , we are sort of beholden to them .
Marketing: So we have to have it one colour .
Project Manager: Well , not necessarily . But we have to incorporate it .
User Interface: Not one colour , but the pattern needs to be recognisable .
Marketing: Mm .
Project Manager: Not necessarily even if i it just has to {disfmarker} ye but you have to look at the product and instantly know that it's one of our products
Industrial Designer: Well you could {disfmarker}
Project Manager: as opposed to a Sony product or a , you know , a Panasonic product .
Marketing: Mm .
Project Manager: It's got to {disfmarker} so maybe , so you can have a look at our our other products and see if they all follow a s similar vein , perhaps .
Industrial Designer: It could come {disfmarker} But it could come in different colours and have the R_R_ colours just somewhere
Project Manager: Yeah .
Industrial Designer: {vocalsound} like just around the lock button could be the R_R_ logo or colours and {disfmarker}
Project Manager: Yeah .
Marketing: Mm .
Industrial Designer: If {gap} .
Project Manager: Quite poss yeah . Well this is all your department . Mm okay . Well , well done everybody .
User Interface: {gap} .
Project Manager: And um , I think we uh stop for lunch now .
User Interface: Yeah , pretty soon I think , I guess that's now .
Marketing: Are we are we finished ahead of schedule ?
Project Manager: We might possibly have done .
Industrial Designer: Cool .
User Interface: Alright , see you all soon .
Project Manager: {vocalsound} If we've if we've finished at five minutes before the meeting's supposed to finish , then that means we get an extra five minutes for lunch .
Marketing: {vocalsound} 'Kay uh .
Project Manager: Yeah , there you go . Right . I just have to {disfmarker} there's a few little bits and pieces I have to write down , but {disfmarker} Take your headsets off , kick back , smoke 'em if you got 'em . {vocalsound}