Yeah But you know uh assume somehow the compu processor power is going to be there Whatever I mean initially you may do a for the transcription Mmm our time and Right back off policy on that if if problems with IRAM is be a wireless link right dump the the dump the Yeah wirelessly to a network somewhere I and I do mean recognition we we kind of set up this concept like a year and a half ago And at that time I said you know we said don't worry about the the compute power I mean it will be somewhere Hmm Yeah Well know we we had a lot of discussions about it and I think maybe I think t to some extent it comes down to a religious issue My religion is personal computers are good and terminal mainframes are bad And so if you can get away with it I don't want to have Yeah terminal in my hand and a mainframe somewhere else Yeah yeah Um the too many things to cont can go wrong Yeah you lack control Yeah think the PC revolution has shown how good it is if you can have the power yourself Yeah And yeah the IRAM project provided us a method of having a very powerful thing in your hand And so we wanna see what we can do with it but also don't want the project to actually completely depend on it So Yeah the project will go forward regardless of whether IRAM works or not I mean our approach somehow I mean I believe probably you know complimentary in many ways is to focus on the actual deep technology that we have somehow in speech And Right basically make progress on you know the algorithms And then you know it will run somewhere I mean as you said to I mean we So would w like the idea to have it there but but our focus is basically to develop the algorithms to push the state of the art on this transcription task And uh the other task probably is also you know challenging the comp Right the the querying uh the command control or you know I mean Right doing the that so natural us language the Meeting Recorder project has a very similar uh approach Me personally for my thesis sorta doing the other way and seeing how much speech recognition can I do on this little unit Oh I see You really are challenged to do that to put as much power as you can in the PDA Yep OK uh our approach is you know we do whatever is necessary to do it and you know some of it may go into something depending on you know your scalable the power As I said the Meeting Recorder project so we have people at Yeah UW people here working on robust algorithms that will be running on work stations They won't be running on IRAM And then what trying to do is see how much of it I can put on IRAM OK Hmm you Yeah know is not eventually y you will get all this you know sc eh higher and higher you know powers in these Yeah portable things So as long as you have enough algorithms and technology to do something better if you have more processing power Right mean the the situation now in the speech community is that you know there is some boundary some limit in the performance And no matter how much processing you throw right in even know what you do don't with get it We don't need any to Mmm better And so Right we are trying to push that Yeah Yeah then you have room to port whatever you can Yep to you know smaller devices You get Yeah the we wrong don't answer know quicker with their basically cycles don't Yeah you Yeah Right interrupt you We w I was gonna say that um you know in terms So Adam has a you know a particular agenda um but obviously there are lots of other things And you know the way that a project like this works so that a group like this where we have students coming in you know meant to be sort of a long term thing that will get us data and people will be able to come along and look at different aspects of it So not clear you know whether s someone at gonna look at um or whatever But you know goo a good property for us that there are a lot of different things you could do with it and Hmm Always haven't thought it through Yeah But yeah OK you know Like kind of Yeah example enough we had a visitor who was working on speaker ID acoustic Huh change detection Yeah yeah And he yeah a very yeah good system for that and and Yeah he Yeah use this corpus Mmm Exactly So mean one of the areas where Kemal Yeah going to Mmm like you know speaker tracking and speaker ID I mean you want to know I mean if you have the people wired individually it probably is easier Oh But but you know nice in about the other situation Yeah about getting this corpus is Yeah with the people wired you have a excellent baseline Yeah Hmm easy problem and you can get the right answer can get the Yeah ground truth Yeah ground truth very easily and then you can degrade it by using the Yeah Mmm degrade yeah further by using those things Yeah And and yeah really see what you can do with a real system So Yeah for example when you go to your PDA system uh really an awful open problem to determine how many speakers there are and where right change turns Mmm uh Yeah right actually being ad one of the problems being addressed at this evaluation uh really doing Mmm place an now unknown number Right You you do need good to figure out the number of speakers Which the uh Right waveform Evaluation of This is a NIST evaluation Um speaker ID Eh something right speaker verification the what wha So what has the data been What what what data are they using What is Uh the Switchboard Oh OK Switchboard and uh I I We Well I mean We will also run so some part of that uh evaluation too but probably not that segmentation part But I don't know if they are using a different data for that But I mean s While I say Switchboard s eh of course only two speakers Yeah But um I don't know how they uh actually went about Um Cuz they were saying some some some up to eight speakers Maybe they maybe some other data for that part right I mean just mixing it wouldn't work because the channel No characteristics are too no different Mmm Yeah So Right