B: Right .
A: Mm - hmm .
G: It 's gonna be too hard to do it without a G: Yeah ,
B: Yeah .
G: forget it .
B: Yeah .
F: You won't be able to align .
A: Yeah .
H: So H: no , I mean , the B: Absolutely .
G: You won't be able to get grants .
B: I agree .
F: You won't be able to segment .
B: Yeah .
F: You won't be able to do anything .
B: Yeah .
B: Yeah .
G: You won't be able to get funding .
A: So F: Right !
G: No ,
G: I 'm serious .
H: Hang on , hang on !
B: Yeah .
G: I mean , you won't be able to show any results .
B: Mmm .
G: So .
H: Oh , right , right , right .
A: And with this with this you 're saying , you are also in that situation ?
H: I mean th
F: Well , I mean , we haven't done the the detail experiment
F: but just from listening to it , it 's pretty bad ,
G: It was pretty bad .
A: Yeah .
A: Yeah .
G: It takes off quite a lot .
F: whereas these are m are very good .
C: Well , yeah , I mean , that 's really like having one of these almost ,
F: I mean , that 's why That 's why if you if you use DragonDictate or or ViaVoice , or any of those others to do dictation you need to use these .
C: so .
B: Hmm .
A: Yeah , yeah , yeah .
B: Hmm .
A: Yeah .
F: There 's just no other way around it .
G: Somebody will design a comfortable close talking mike .
G: I mean it 's there are too many applications to for them not to not do that .
A: Mm - hmm .
F: Well , and as I said , I find this one G: I mean , it may not look like this
G: but .
F: I find this one is no problem at all .
F: The only thing is <nonvocalsound> a little bit of audio a a little bit of audio degradation in one ear ,
G: Yeah .
H: Yeah it 's y
G: Yeah , this one 's fine .
A: Yeah , yeah , yeah , yeah .
G: Right .
F: and I get a little bit of peripheral vision ,
F: but other than that , it 's not bad at all .
H: Yeah .
B: Hmm .
F: Those , on the other hand , are very uncomfortable .
G: I
D: We could G: Yeah ,
G: those are pretty bad .
A: Yeah ,
A: those are really bad .
F: So .
D: Can can't we buy an expander that you just B: Uh B: I 'm actually finding this quite comfortable now that I 've got it I 've got it just right .
F: That 's right .
E: I 'm surviving .
H: It depends ,
H: yeah I 've A: I think you have , you know , he would .
E: Yeah , I uh
B: It 's just C: I think he 's about to pass out .
C: That 's why B: U i
E: You guys gave up too soon .
B: It must have numbed the areas .
E: I think you just get used to it after five minutes .
F: So I I guess F: you know , maybe the problem is we got the kid 's version .
G: Yeah .
C: Yeah .
H: No , we got a Japanese version ,
H: you know that 's that 's it ,
G: Sorry .
A: And so and what about this one ?
H: yeah .
A: I mean , this thing wearing sideway that that can ?
H: Uh the F: It 's wired .
H: It 's funny , I li I kind of like this .
H: So it actually gets most of its strength from <comment> from you know , the fact this thing 's stuck in your ear .
G: Oh , this would drive me crazy .
B: Mmm .
H: And , yeah ,
A: Oh .
G: I absolutely A: D uh does it have a speaker ?
H: uh I and originally G: people are very picky about this .
A: Does it have a speaker
E: Mmm .
A: or ?
H: Oh yeah , it does .
H: When I bought those things I originally got this version , cuz Plantronics makes uh you know , an in - the - ear one .
A: Uh Uh - huh .
A: Mm - hmm .
H: And I really liked it
H: but , other people didn't .
H: So it just depends .
H: I guess , you know , I 've been using in - the - ear Walkman headphones , for you know , a long time ,
A: Yeah .
B: Mmm .
H: so I 'm kind of used to that weird sensation having something stuck in my ear .
H: But if , uh ,
G: But that 's painful .
F: Whereas I used speech recognition for about four years using one of these ,
H: If you 're not used G: I can't F: so I 'm used to this .
A: You do .
F: I don't use it anymore .
A: Y
F: Uh , my hands got better
A: Uh - huh .
F: so I stopped using it .
A: OK .
F: But , uh .
F: So , for about four years I used DragonDictate and NaturallySpeaking
A: OK .
C: Really ?
C: So you could actually produce like code
F: to do all my work .
A: Oh , you 're a C: or ?
F: Yeah .
C: Yeah ?
F: It was really a pain .
B: Code !
B: Right .
F: Yeah ,
F: but I didn't have a choice .
C: Wow .
F: I mean , I couldn't type .
B: That 's an interesting language model I 'm sure .
C: Uh .
F: So ,
A: So C: Huh .
F: uh .
H: Yeah .
A: The market is a captive market .
F: Yeah .
H: Right .
B: Mmm .
D: Mm - hmm ,
D: yeah .
F: In fact , when I first came back to grad school that was a project I wanted to work on ,
F: " voice environments for programmers " ,
F: but we couldn't get any funding for it and my hands got better .
F: So
F: that 's how I ended up working on this project instead .
H: Hmm .
G: Huh .
A: Good .
F: Anyway .
H: So , yeah .
F: So so what are you guys doing ?
H: I don't know .
H: Yeah .
F: What 's your project ?
A: Well , basically , the the the original project looks a lot like , you know , the the p your project .
A: I mean , basically we set up with this , uh , idea of the the the meeting the the mediated spaces idea in general
F: Mm - hmm .
A: and then incr incarnated in this room that will be mediated somehow by , you know , a computer to access information , to help along the meeting ,
A: and will be like two kind of eh , f main functions .
A: One is the interaction with the computer
F: Mm - hmm .
A: which , as you said , you know , is your interaction with the PDA in your case ,
A: where you kind of query it to ask for information , et cetera .
F: Mm - hmm .
A: At the same time , our process is somehow , you know , getting all this multi - channel information , doing some sort of , you know , cross , eh , channel , you know , cancellation and transcribing the individual streams ,
F: Mm - hmm .
B: Mmm .
A: not necessarily in real time .
A: And the idea is y you can eventually after the meeting query , you know , previous meetings
F: Right .
A: and A: and there is all this work on transcription ,
A: similar probably to what we do in Switchboard but with better bandwidth ,
F: Mm - hmm .
A: you know ,
A: but worse , you know , environmental conditions .
F: Worse acoustics .
F: Yeah .
A: An - and then , you know , there is , all all these issues about processing all this information , you know , transcription ,
F: Mmm .
A: but then using , you know , prosody information to better , you know , segment , endpoint .
A: Eh , also using topic segmentation to help better classification of information or extraction of information .
F: Mm - hmm .
A: I mean ,
A: we didn't dare to say it will be just in a PDA you throw in the middle of a meeting .
B: I 'm beginning to feel my heart beat now .
F: Yeah .
F: So .
F: Yeah .
F: This is this is A: That that was daring .
F: The PDA one is very , very ambitious .
A: Yeah .
F: And it 's also it 's depending on not only that B: Mmm .
F: Uh , not only does it depend on IRAM taping out and working as specified , it also depends on writing vectorized speech recognition algorithms
C: Hmm .
C: Mmm .
A: Yeah .
A: Yeah .
F: which is non - trivial .
A: Yeah .
A: Yeah .
F: So .
A: Yeah .
A: But , you know , uh let 's assume somehow the compu processor power is going to be there .
A: Whatever .
A: I mean , initially you may do a super - computer for the transcription , <comment> real time and then F: Right , I mean ,
F: so so one of our B: Mmm .
H: Right .
F: our back off policy on that if if there 's problems with IRAM is it 'll be a wireless link ,
A: Yeah .
A: Uh - huh .
F: right ?
F: You 'll dump the the dump the audio wirelessly to a network somewhere
A: Yeah .
A: Yeah .
A: I I mean , ou uh we we kind of set up this concept like a year and a half ago .
F: and you 'll do the recognition .
B: Mm - hmm .
F: Mm - hmm .
A: And at that time I said , you know , we said , " don't worry about the the compute power " .
A: I mean , it will be somewhere , <comment> you know .
F: Hmm .
H: Yeah .
F: Well , we we we 've had a lot of discussions about it
F: and I think
A: Mm - hmm .
F: maybe I think t to some extent it comes down to a religious issue .
F: My religion is personal computers are good and terminal mainframes are bad .
F: And so if you can get away with it , I don't want to have a terminal in my hand and a mainframe somewhere else .
A: Yeah .
A: Yeah , yeah .
F: Um , the too many things to cont can go wrong and you lack control .
A: Yeah .
A: Yeah .
F: I think the PC revolution has shown how good it is if you can have the power yourself .
A: Yeah , yeah .
F: And so the IRAM project provided us a method of having a very powerful thing in your hand .
A: Mm - hmm .
F: And so we wanna see what we can do with it
F: but we 'd also don't want the project to actually completely depend on it .
F: So ,
A: Yeah .
F: the project will go forward regardless of whether IRAM works or not .
A: I mean , our approach , somehow , I mean , I believe it 's probably , you know , complimentary in many ways , is to focus on the actual deep technology that we have somehow in speech . And basically , make progress on , you know , the algorithms .
F: Right .
A: And then , you know , it will run somewhere .
A: I mean ,
A: as you said , to I mean , we would like the idea to have it there
F: So w
A: but but our focus is basically to develop the algorithms , to push the state of the art on this transcription task .
F: Mm - hmm .
A: And , uh , the other task probably is also , you know , challenging the comp the the querying , uh , the command , control , or , you know , I mean , doing that in natural language .
F: So a
F: Right .
F: Mm - hmm .
F: Right ,
F: so the so for us the Meeting Recorder project has a very similar uh , approach .
A: Mm - hmm .
A: Uh - huh .
F: Me personally , for my P H D thesis , I 'm sorta doing the other way and seeing how much speech recognition can I do on this little unit .
A: Oh .
A: I see .
A: You really are challenged to do that ,
F: Yep .
A: to put as much power as you can in the PDA .
F: Yep .
A: OK ,
A: uh , our approach is , you know , we do whatever is necessary to do it
A: and , you know , some of it may go into something , depending on , you know , your scalable power .
F: That 's right .
F: So so the F: As I said , the Meeting Recorder project ,
F: so we have people at UW , people here working on robust algorithms that will be running on work stations .
A: Yeah .
F: They won't be running on IRAM .
A: Mm - hmm .
F: And then what I 'm trying to do is see how much of it I can put on IRAM .
A: OK .
B: Hmm .
H: Mmm .
A: Well , you know , is , eventually y you will get all this you know , sc eh , higher and higher , you know , powers in these portable things .
H: Yeah , it 's not F: Mm - hmm .
H: Yeah .
A: So as long as you have enough algorithms and technology to do something better if you have more processing power .
F: Right .
A: I mean , the the situation now in the speech community is that , you know , there is some boundary , some limit in the performance .
A: And no matter how much processing you throw in , you don't get any better .
F: That 's right ,
F: we don't even know what to do with it .
F: We don't need to n
B: Mmm .
A: And so we are trying to push that .
F: Right .
F: Yeah .
H: Yeah .
A: And then you have room to port whatever you can to , you know , smaller devices .
F: Yep .
B: You get the wrong answer quicker basically ,
F: Yeah , we don't even know what to do with their cycles .
B: don't you ?
A: Yeah .
B: Yeah .
H: Right .
A: Sorry I interrupt you .
F: We w
H: I was gonna say that , um , you know , in terms H: So , Adam has a you know , a particular agenda ,
H: um , but obviously there are lots of other things .
A: Mm - hmm .
H: And you know , it 's the way that a project like this works
H: so that a group like this where we have students coming in , you know It 's it 's meant to be sort of a long term thing that will get us data
A: Mm - hmm .
H: and people will be able to come along and look at different aspects of it .
H: So it 's not clear , you know , whether s someone at UW 's gonna look at , um , beam - forming or whatever .
H: But ,
H: you know ,
H: it 's goo it 's a good property for us that there are a lot of different things you could do with it ,
H: and so it 's We we haven't thought it through .
B: Hmm .
A: Yeah .
A: Always @ @ .
A: Yeah , yeah .
H: But that 's OK ,
H: you know , it 's kind of it 's fair enough .
F: Like A: Yeah .
F: As an example , we had a visitor who was working on speaker ID , acoustic change detection .
H: Yeah .
A: Huh .
A: Yeah , yeah , yeah , yeah .
F: And he has a very good system for that
F: and and he wants to use this corpus .
A: Yeah .
A: Yeah .
B: Mmm .
A: Exactly .
F: So .
A: I mean , it 's one of the areas where Kemal is going to work , like , you know , speaker tracking , and speaker ID .
F: Yeah .
B: Mmm .
C: Mm - hmm .
F: Mm - hmm .
A: I mean ,
A: you want to know .
A: I mean , if you have the people wired individually it probably is easier .
F: Oh , it th what 's nice about A: But but you know , in in the other situation , you know .
H: Yeah .
F: What 's nice about getting this corpus is , i with the people wired you have a excellent baseline .
A: Yeah .
A: Yeah .
F: Right ?
H: Yeah .
B: Hmm .
F: You have a very easy problem and you can get the right answer , to ground truth very easily
H: You can get the ground truth .
A: Yeah .
H: Yeah .
F: and then you can degrade it by using the P Z
A: Yeah , yeah .
B: Mmm .
F: you can degrade it further by using those things .
A: Yeah , yeah , yeah .
F: And and really see what you can do with a real system .
F: So .
C: Yeah , for example , when you go to your PDA system it 's , uh , really an awful open problem to determine how many speakers there are and where they change turns ,
F: That 's right .
B: Mmm .
C: uh .
H: Yeah .
F: That 's right .
C: That 's actually being ad That 's one of the problems that 's being addressed at this year 's evaluation ,
A: Mm - hmm .
C: uh ,
F: Oh , really ?
F: They 're doing an unknown number ?
C: which is taking place right now , actually .
D: Mmm .
C: Right .
C: You you do need to figure out the number of speakers in the waveform .
F: That 's good .
H: Which , uh Wha - Evaluation of B: Right .
C: This is a NIST evaluation .
C: Um .
H: Of the speaker ID or something ?
B: This i
C: Eh , right , speaker verification .
H: And what 's the what wha So what has the data been ?
H: What what what data are they using ?
H: What is the C: Uh , Switchboard .
H: Oh , OK .
C: Switchboard and , uh C: I I C: We C: Well , I mean C: We will also run so some part of that , uh , evaluation too
C: but probably not that segmentation part .
C: But I don't know if they are using a different data for that .
C: But I mean , it 's s While I say " Switchboard " , s eh , of course there 's only two speakers .
H: Yeah .
C: But , um , I don't know how they , uh , actually went about .
C: Um .
C: Cuz they were saying some some some up to eight speakers . Maybe they C: maybe some other data for that part ,
H: Uh - huh .
C: you 're right .
F: I mean , just mixing it wouldn't work because the channel characteristics are too different .
C: No , no .
B: Mmm .
C: Yeah .
F: So , uh , what we what we were working on here was parts of Broadcast News .
C: Right .
F: And so that that 's a slightly strange task because they tend to be long segments .
F: But they were they were parts that were interviews that he worked on .
A: Mm - hmm .
F: And , uh .
C: No .
C: We 've also , uh , s done some of that as , uh , eh ,
F: Right .
C: um , I mean , I have a so small , uh , hacked up system which sort of , for for the Broadcast News determines the approximate number of speakers and actually assigns some names to them .
F: Mm - hmm .
F: Mm - hmm .
C: This is something we did for the MAESTRO project , uh , for for Rick .
F: Mm - hmm .
C: But , um , uh ,
C: yeah , uh , for for Broadcast News it works much better actually .
C: It 's , uh ,
F: Yeah , he had he got very good results .
C: you do get eh , like in an interview , uh , nice long segments
F: Right .
C: and F: Right .
F: Yeah , so I I tried his on his system on the Meeting Recorder stuff ,
F: um ,
F: but of course we don't have any trained neural nets
F: or , uh F: So so his system was based on our hybrid neural net system that we use for speech recognition .
B: Hmm .
F: And so , uh , I was using the Broadcast News nets on this data .
A: Hmm .
F: So of course it didn't do didn't do t tremendously well .
F: And then the other problem also was that it doesn't handle overlap very well ,
F: his algorithm .
G: Yeah ,
G: I mean Broadcast News is for this third - party listener ,
F: Hmm ?
G: right ?
F: Right .
H: Right .
G: So they , you know if you were listening to an interview that sounded like this , you know , you 'd turn off your radio .
B: Yes .
F: That 's right , with all the i interrupts .
H: Right .
G: So it 's just got a d
G: it 's a lot easier .
F: Yes .
A: I think there are some programs in TV .
A: I 've been trying to get this from something like this from , you know , public cast
A: uh w eh eh .
D: There are there are some with a lot of overlap .
A: Um uh yeah ,
A: and they but they they do it somehow . They clean it up .
D: Yeah .
A: I notice that they they s they sa have some help with control of what person to pick up .
F: Mixing ,
F: yeah .
G: Mm - hmm .
A: I I mean there is some program at midnight somewhere .
A: It 's a bunch of , like , four people discussing
D: Well A: and they , it 's a lot clean .
F: Like
A: Yeah .
A: I yeah ,
D: But the but the worst the worst case is Politically Incorrect where they don't really make any adjustments at all .
A: probably .
F: But yeah , they they have G: Uh - huh .
D: And and it 's hard to even follow what they 're saying .
A: Uh - huh .
D: It 's just it 's truly totally overlapped .
B: Right .
A: Yeah .
A: Uh , yeah .
B: Yeah .
A: I 've heard that that that sometimes .
A: But it 's it 's OK , though .
F: I think in in B: It 's still in the forma it 's still in the format which is slightly more formal I think than , you know , completely informal conversational speech .
A: So you don't think they they fill it at all with any , you know D: OK .
H: Mm - hmm .
F: Oh , I 'm sure they do .
F: They I 'm sure they have an audio engineer in the back .
A: They B: They will do , a bit .
A: I am pretty sure they do .
B: Yeah .
A: I mean , it 's it 's it 's still , you know , understandable .