the utterances are very short And so gonna be talking beep number yes beep number no Well if if it saves time Yeah yeah and u I think it would I Actually I thi I like And that when I they think transcribe this meeting Yeah really impossible W saying beep Yeah Yeah yep Yeah for instance But see that would that would definitely keep not a bad idea Yeah Keep things from getting out of sequence If they heard it over again they would know It would be obvious from their transcript whether they did that one or not It might actually would help help them get terms synchronized holding Yeah And Yeah it might be helpful to them in terms of d act think it would be because plenty know of their digits place so Yeah They would know We their place darn it Know Those Oh transcriptionists need to know their place no no no sounds no like a k a a a short conversation with Brian might be Yeah might be helpful to get a sense him of an Yeah the numbers are a good going idea on Yeah OK just other than lengthening the transcript I think it would be very helpful Just instead of the sequential number for perhaps just the speaker ID or something Just say speaker one or spea or just one two three four for four speakers or something Pppt Could i helpful Yeah you don't have to you could keep them short by Yeah not s or Yeah just go one through ten Yeah one through ten one through Yep ten or one through twenty And then also if we I mean I don't know what their setup is but your template idea might be a way of of of We could actually build the numbers into a template Yep Well talk to Brian and see what he Yeah single digit numbers That Yeah also appeals idea me So that you don't have to Very simple know One hundred Yeah Well th Beep although One thousand three hundred saying i about an hour meeting and there were a hundred and I don't remember Chuck was saying minutes was more than that Hmm More beeps minutes than for that that one I was thinking there was on the order of fifteen hundred segments but maybe There must be Because otherwise should possible more whole That was at least minutes right right Was it that many I it just don't recall minutes shortest meeting we have Most of them are double that or Yep Well I was just so wondering what the average length Oh of a was of a segment that hearing Yeah I don't know Hmm interesting Easy Uh know enough to figure out So if Yeah are all in that the data in the hundreds and thou or thousands of these It must be in the high hundreds of them at least So right So i getting a little cumbersome for them to type Yeah like Well with just one five digit hundred I think Well if they recycle through we if Yeah did mod ten then Right but my point was you know if a big difference to me if a thousand or a hundred If a thousand then that means that this is only happening three times out of a thousand Which means you know even just splitting it up into a few files would probably take You know nearly all the time there Yeah no W if a hundred then you know not the issue but if a hundred then the average length of each one is pretty pretty long and so having a little thing at the front of it is no big deal So right It why had curious more than that I mean it was a minute meeting so Right And it certainly was not a minute a chunk it was a few seconds a chunk what I Yeah so So be just lot of overhead to type just Oh I So Well and the other thing is maybe the numbers would help them keep their place in the transcript and It speed make process transcript Yeah mean I A quick conversation with Brian would be good Yeah so OK And other than that Actually if it is u I mean not a bad idea to try the alignment Um if only like three of them then if you align the first point at which things get messed up is sort of the location of the first problem And then the second p I mean you could do it that way or you could it would be able to handle any errors So if they Right make on the average that many and it costs them more time to do something different than what doing which I don't know but if it does then we could try doing that as a and um have a student or a transcriber run this alignment or Yep we can do it and You know actually what all that then we you can would iteratively figure out where the problems are You know Liz It all take we a would little re work but not any real human not Right lot of human work mean what we if want in to terms avoid the alignment actually all we would need is we wouldn't even need words We would need a general speech model and a beep model Cuz all really concerned about is missing beeps or too many beeps Well So the if we for had the a forced alignment will run fa otherwise take forever I mean to really Well run recognition guess what thinking Or of is that w that a lot of times there will be put in question marks that represent some Right unknown amount of speech so gonna have to have some kind of Yeah then we just map it to a reject model In and in fact what we do now Cuz Right cases even after Jane listens where you know we have an expert can't even tell what talking about Yeah Um so OK Just Right map that to I reject map and all the speech to the reject model And then you have Yeah beep model But Yeah that still won't talking because forced al The forced alignment might not work then although we can try it Um Well but all Well with the get models is really have really g The it beep be model good is Right So match like so really well really just doing yeah a keyword like a spotting But for beep with grab the next beep in other words be get back another offset Um I mean I was thinking of then I and then I realized Well the recognizer will just go along and line up all the beeps and then be all the extra beeps at the end if there were more beeps then you wanted you need So you But need need word text you need the word to c to sort it of where control wrong Yeah relative No