Professor B: So the other , uh , Aurora thing maybe is I I dunno if any of this is gonna  come in in time to be relevant , but , uh , we had talked about , uh , {comment} Guenter playing around , uh , uh , over in Germany
PhD D: Mm - hmm .
Professor B: and and , @ @ {comment} uh , possibly coming up with something that would , uh , uh , fit in later . Uh , I saw that other mail where he said that he  uh , it wasn't going to work for him to do CVS .
PhD D: Yeah . Yeah . So now he has a version of the software .
Professor B: So he just has it all sitting there . Yeah .
PhD D: Yeah . Um Mm - hmm .
Professor B: So if he 'll he might work on improving the noise estimate or on some histogram things , or PhD D: Yeah . Mm - hmm .
Professor B: Yeah . I just saw the Eurospeech We we didn't talk about it at our meeting but I just saw the just read the paper . Someone , I forget the name , {comment} and and Ney , uh , about histogram equalization ? Did you see that one ?
PhD D: Um , it was a poster . Or Professor B: Yeah . I mean , I just read the paper .
PhD D: Yeah .
Professor B: I didn't see the poster .
PhD D: Yeah . Um  It was something similar to n on - line normalization finally I mean , in the idea of of normalizing Professor B: Yeah . But it 's a little more it it 's a little finer , right ? So they had like ten quantiles
PhD D: Yeah .
Professor B: and  and they adjust the distribution .
PhD D: Right .
Professor B: So you you have the distributions from the training set ,
PhD D: N
Professor B: and then , uh So this is just a a histogram of of the amplitudes , I guess . Right ? And then  Um , people do this in image processing some .
PhD D: Mm - hmm .
Professor B: You have this kind of  of histogram of of levels of brightness or whatever . And and and then , when you get a new new thing that you you want to adjust to be better in some way , you adjust it so that the histogram of the new data looks like the old data .
PhD A: Hmm .
Professor B: You do this kind of piece - wise linear or , uh , some kind of piece - wise approximation . They did a uh one version that was piece - wise linear and another that had a power law thing between them  between the points . And , uh , they said they s they sort of see it in a way as s for the speech case {comment} as being kind of a generalization of spectral subtraction in a way , because , you know , in spectral subtraction you 're trying to get rid of this excess energy . Uh , you know , it 's not supposed to be there . Uh  and , uh , this is sort of  adjusting it for for a lot of different levels . And then they have s they have some kind of , uh , a floor or something ,
Grad E: Hmm .
Professor B: so if it gets too low you don't don't do it .
PhD A: Hmm .
Professor B: And they they claimed very nice results ,
PhD D: Mm - hmm .
PhD A: So is this a histogram across different frequency bins ?
Professor B: and PhD A: Or ?
Professor B: Um , I think this i You know , I don't remember that . Do you remember ?
PhD D: I think they have , yeah , different histograms . I uh Something like one per frequency band ,
Professor B: One PhD A: So , one histogram per frequency bin .
Professor B: One per critical PhD D: or But I did Yeah , I guess .
PhD A: And that 's PhD D: But I should read the paper . I just went through the poster quickly ,
Professor B: Yeah .
PhD A: So th
Professor B: And I don't remember whether it was filter bank things
PhD A: Oh .
PhD D: and I didn't Professor B: or whether it was FFT bins
PhD A: Huh .
Professor B: or PhD A: And and that that , um , histogram represents the different energy levels that have been seen at that frequency ?
Professor B: I don't remember that . And how often they you 've seen them . Yeah .
PhD A: Uh - huh .
Grad E: Hmm .
Professor B: Yeah . And they do they said that they could do it for the test So you don't have to change the training . You just do a measurement over the training . And then , uh , for testing , uh , you can do it for one per utterance . Even relatively short utterances . And they claim it it works pretty well .
PhD A: So they , uh Is the idea that you you run a test utterance through some histogram generation thing and then you compare the histograms and that tells you what to do to the utterance to make it more like ?
Professor B: I guess in pri Yeah . In principle .
PhD A: I see .
Professor B: I didn't read carefully how they actually implemented it ,
PhD A: Hmm . Yeah .
Professor B: whether it was some , uh , on - line thing , or whether it was a second pass , or what . But but they  That that was sort of the idea .
PhD A: Hmm .
Professor B: So that that seemed , you know , different . We 're sort of curious about , uh , what are some things that are , u u um , @ @ {comment} conceptually quite different from what we 've done .
PhD A: Mm - hmm .
Professor B: Cuz we you know , one thing that w that , uh , Stephane and Sunil seemed to find , uh , was , you know , they could actually make a unified piece of software that handled a range of different things that people were talking about , and it was really just sort of setting of different constants . And it would turn , you know , one thing into another . It 'd turn Wiener filtering into spectral subtraction , or whatever . But there 's other things that we 're not doing . So , we 're not making any use of pitch , uh , uh , which again , might might be important , uh , because the stuff between the harmonics is probably a schmutz . And and the , uh , transcribers will have fun with that . Uh  And , um , the , uh , stuff at the harmonics isn't so much . And and , uh And we there 's this overall idea of really sort of matching the the hi distributions somehow . Uh , not just , um , um not just subtracting off your estimate of the noise . So . So I guess , uh , Guenter 's gonna play around with some of these things now over this next period ,
PhD D: Uh , I dunno .
Professor B: or ?
PhD D: I don't have feedback from him , but
Professor B: Yeah .
PhD D: I guess he 's gonna , maybe Professor B: Well , he 's got it anyway , so he can .
PhD D: Yeah .
Professor B: So potentially if he came up with something that was useful , like a diff a better noise estimation module or something , he could ship it to you guys u up there
PhD D: Uh - huh .
Professor B: and
PhD D: Yeah .
Professor B: we could put it in .
PhD D: Mm - hmm . Mm - hmm .