Grad A: OK . We seem to be recording .
Professor G: Alright !
Grad A: So , sorry about not Professor G: We 're not crashing .
PhD D: Number four .
Grad A: not pre - doing everything . The lunch went a little later than I was expecting , Chuck .
PhD E: Hmm ?
Professor G: OK .
PhD B: Chuck was telling too many jokes , or something ?
Grad A: Yep . Pretty much .
PhD E: Yeah .
Professor G: OK . Does anybody have an agenda ?
Grad A: No .
Postdoc F: Well , I 'm I sent a couple of items . They 're they 're sort of practical .
Professor G: I thought somebody had .
Postdoc F: I don't know if you 're Professor G: Yeah , that 's right .
Postdoc F: if if that 's too practical for what we 're focused on .
Grad A: I mean , we don't want anything too practical .
Professor G: Yeah , we only want th useless things .
Grad A: Yeah , that would be Professor G: Yeah . No , why don't we talk about practical things ?
Postdoc F: OK .
Professor G: Sure .
Postdoc F: Well , um , I can give you an update on the transcription effort .
Professor G: Great .
Postdoc F: Uh , maybe {nonvocalsound} raise the issue of microphone , uh , um procedures with reference to the cleanliness of the recordings .
Professor G: OK , transcription , uh , microphone issues Postdoc F: And then maybe {nonvocalsound} ask , th uh , these guys . The we have great great , uh , p steps forward in terms of the nonspeech - speech pre - segmenting of the signal .
Professor G: OK .
Grad A: Well , we have steps forward .
PhD C: Yeah .
Postdoc F: Well , it 's a it 's a big improvement .
PhD C: I would prefer this .
Professor G: Yes . Yeah , well . OK . Uh PhD D: We talk about the  the results of
Professor G: You have some Yeah .
Grad A: I have a little bit of IRAM stuff
Professor G: OK .
PhD D: use Grad A: but I 'm not sure if that 's of general interest or not .
Professor G: Uh , bigram ?
Grad A: IRAM .
PhD D: IRAM .
Professor G: IRAM .
Grad A: IRAM , bigram ,
Professor G: Well , m maybe .
PhD D: Bi - Bigram .
Grad A: you know .
Professor G: Yeah , let 's let 's see where we are at three - thirty .
PhD B: Hmm .
Professor G: Um PhD B: Since , uh since I have to leave as usual at three - thirty , can we do the interesting stuff first ?
Postdoc F: I beg your pardon ?
Professor G: Well PhD C: Which is ?
Grad A: What 's the interesting stuff ?
Postdoc F: I beg your pardon ?
PhD D: Yeah .
Professor G: Yeah . Th - now you get to tell us what 's the interesting part .
PhD E: Please specify .
Professor G: But PhD B: Well , uh , I guess the work that 's been done on segmentation would be most PhD C: Yeah .
Postdoc F: I think that would be a good thing to start with .
PhD B: Yeah .
Professor G: OK . Um , and , um , the other thing , uh , which I 'll just say very briefly that maybe relates to that a little bit , which is that , um , uh , one of the suggestions that came up in a brief meeting I had the other day when I was in Spain with , uh , Manolo Pardo and Javier , uh , Ferreiros , who was here before , was , um , why not start with what they had before but add in the non - silence boundaries . So , in what Javier did before when they were doing , um h he was looking for , uh , speaker change points .
PhD D: Mm - hmm .
Professor G: Um . As a simplification , he originally did this only using silence as , uh , a putative , uh , speaker change point .
PhD C: Yeah .
Professor G: And , uh , he did not , say , look at points where you were changing broad sp uh , phonetic class , for instance . And for Broadcast News , that was fine . Here obviously it 's not .
PhD D: Yeah .
Professor G: And , um , so one of the things that they were pushing in d in discussing with me is , um , w why are you spending so much time , uh , on the , uh , feature issue , uh , when perhaps if you sort of deal with what you were using before
PhD D: Uh - huh .
Professor G: and then just broadened it a bit , instead of just ta using silence as putative change point also ?
PhD D: Nnn , yeah .
Professor G: So then you 've got you already have the super - structure with Gaussians and H - you know , simple H M Ms and so forth . And you you might So there was a there was a little bit of a a a a difference of opinion because I I thought that it was it 's interesting to look at what features are useful .
PhD D: Yeah .
Professor G: But , uh , on the other hand I saw that the they had a good point that , uh , if we had something that worked for many cases before , maybe starting from there a little bit Because ultimately we 're gonna end up with some s su kind of structure like that ,
PhD D: Yeah .
Professor G: where you have some kind of simple HMM and you 're testing the hypothesis that , uh , there is a change .
PhD D: Yeah .
Professor G: So so anyway , I just reporting that .
PhD D: OK .
Professor G: But , uh , uh So . Yeah , why don't we do the speech - nonspeech discussion ?
Postdoc F: Yeah . Do I I hear you you didn't PhD C: Speech - nonspeech ? OK .
Postdoc F: Uh - huh . Yeah .
PhD C: Um , so , uh , what we basically did so far was using the mixed file to to detect s speech or nonspeech portions in that .
Professor G: Mm - hmm .
PhD C: And what I did so far is I just used our old Munich system , which is an HMM - ba based system with Gaussian mixtures for s speech and nonspeech . And it was a system which used only one Gaussian for silence and one Gaussian for speech . And now I added , uh , multi - mixture possibility for  for speech and nonspeech .
Professor G: Mm - hmm . Mm - hmm .
PhD C: And I did some training on on one dialogue , which was transcribed by Yeah . We we did a nons s speech - nonspeech transcription .
PhD D: Jose .
PhD C: Adam , Dave , and I , we did , for that dialogue and I trained it on that . And I did some pre - segmentations for for Jane . And I 'm not sure how good they are or what what the transcribers say . They they can use it or ?
Postdoc F: Uh , they they think it 's a terrific improvement . And , um , it real it just makes a a world of difference .
Professor G: Hmm .
Postdoc F: And , um , y you also did some something in addition which was , um , for those in which there {nonvocalsound} was , uh , quiet speakers in the mix .
PhD C: Yeah . Uh , yeah . That that was one one one thing , uh , why I added more mixtures for for the speech . So I saw that there were loud loudly speaking speakers and quietly speaking speakers .
Professor G: Mm - hmm .
PhD C: And so I did two mixtures , one for the loud speakers and one for the quiet speakers .
Grad A: And did you hand - label who was loud and who was quiet , or did you just ?
PhD C: I did that for for five minutes of one dialogue
Grad A: Right .
PhD C: and that was enough to to train the system .
PhD B: W What ?
PhD D: Yeah .
PhD C: And so it it adapts , uh , on while running . So .
PhD B: What kind of , uh , front - end processing did you do ?
PhD C: Hopefully .
PhD D: OK .
PhD C: It 's just our our old Munich , uh , loudness - based spectrum on mel scale twenty twenty critical bands and then loudness .
PhD B: Mm - hmm .
PhD C: And four additional features , which is energy , loudness , modified loudness , and zero crossing rate . So it 's twenty - four twenty - four features .
PhD B: Mmm .
Professor G: Mm - hmm .
Postdoc F: And you also provided me with several different versions ,
PhD C: Yeah .
Postdoc F: which I compared .
PhD C: Yeah .
Postdoc F: And so you change {nonvocalsound} parameters . What do you wanna say something about the parameters {nonvocalsound} that you change ?
PhD C: Yeah . You can specify the minimum length of speech or and silence portions which you want . And so I did some some modifications in those parameters , basically changing the minimum minimum length for s for silence to have , er to have , um yeah to have more or less , uh , silence portions in inserted . So .
Grad A: Right . So this would work well for , uh , pauses and utterance boundaries and things like that .
PhD D: Yeah .
PhD C: Yeah . Yeah .
Grad A: But for overlap I imagine that doesn't work at all ,
PhD C: Yeah .
PhD D: Yeah .
Grad A: that you 'll have plenty of s sections that are PhD C: Yeah .
PhD D: Yeah .
PhD C: That 's it . Yeah .
Postdoc F: Mm - hmm , mm - hmm .
PhD D: Yeah .
Grad A: But Postdoc F: That 's true . But {nonvocalsound} it it saves so much time the the {nonvocalsound} transcribers
Professor G: Um Grad A: Yep .
Postdoc F: just enormous , enormous savings . Fantastic .
Professor G: That 's great . Um , just qu one quickly , uh , still on the features . So you have these twenty - four features .
PhD C: Yeah .
Professor G: Uh , a lot of them are spectral features . Is there a a transformation , uh , like principal components transformation or something ?
PhD C: No .
Grad A: Yeah . It was IS two .
PhD C: No . W w we originally we did that
Professor G: Just PhD C: but we saw , uh , when we used it , uh , f for our close - talking microphone , which yeah , for our for our recognizer in Munich we saw that w it 's it 's not it 's not so necessary . It it works as well f with with without , uh , a LDA or something .
Professor G: OK . OK . No , I was j curious .
PhD C: Yeah .
Postdoc F: Mm - hmm .
Professor G: Yeah , I don't think it 's a big deal for this application ,
PhD C: Yeah .
PhD D: Right .
Professor G: but but Yeah , it 's a Postdoc F: Mm - hmm . OK . But then there 's another thing that also Thilo 's involved with , which is , um OK , and and also Da - Dave Gelbart . So there 's this this problem of and w and so we had this meeting . Th - the {nonvocalsound} also Adam , before the the before you went away . Uh we , um regarding the representation {nonvocalsound} of overlaps , because at present , {nonvocalsound} um , because {nonvocalsound} of the limitations of th the interface we 're using , overlaps are , uh , not being {nonvocalsound} encoded by {nonvocalsound} the transcribers in as complete {nonvocalsound} and , uh , detailed a way as it might be , and as might be desired I think would be desired in the corpus ultimately .
Professor G: Mm - hmm .
Postdoc F: So we don't have start and end points {nonvocalsound} at each point where there 's an overlap . We just have the the {nonvocalsound} overlaps {nonvocalsound} encoded in a simple bin . Well , OK . So {nonvocalsound} @ @ the limits of the {nonvocalsound} over of of the interface are such that we were at this meeting we were entertaining how we might either expand {nonvocalsound} the the interface or find other tools which already do what would be useful . Because what would ultimately be , um , ideal in my my view and I think I mean , I had the sense that it was consensus , is that , um , a thorough - going musical score notation would be {nonvocalsound} the best way to go . Because {nonvocalsound} you can have multiple channels , there 's a single time - line , it 's very clear , flexible , and all those nice things .
Professor G: Mm - hmm .
Postdoc F: OK . So , um , um , I spoke I had a meeting with Dave Gelbart on on and he had , uh , excellent ideas on how the interface could be modified to to do this kind of representation . But , um , he in the meantime you were checking into the existence of already , um , existing interfaces which might already have these properties . So , do you wanna say something about that ?
PhD C: Yes . Um , I talked with , uh , Munich guys from from Ludwi - Ludwig Maximilians University , who do a lot of transcribing and transliterations .
Professor G: Mm - hmm .
PhD C: And they basically said they have they have , uh , a tool they developed themselves and they can't give away , uh , f it 's too error - prone , and had it 's not supported , a a a and Professor G: Yeah .
PhD C: But , um , Susanne Bur - Burger , who is at se CMU , he wa who was formally at in Munich and w and is now at with CMU , she said she has something which she uses to do eight channels , uh , trans transliterations , eight channels simultaneously ,
Professor G: Excuse me .
PhD C: but it 's running under Windows .
Postdoc F: Under Windows .
PhD C: So I 'm not sure if if if we can use it .
Postdoc F: Mm - hmm .
PhD C: She said she would give it to us .
Postdoc F: Mm - hmm .
PhD C: It wouldn't be a problem . And I 've got some some kind of manual down in my office .
Grad A: Well , maybe we should get it and if it 's good enough we 'll arrange Windows machines to be available .