prosodics are so much different s gonna be strange I mean the prosodics are not the same as for example Yeah So not sure how much of effect that will have What H do how mean do the prosodics Um just what we were talking about with grouping That with these the grouping no grouping at all and so just the only sort of discontinuity you have is at the beginning and the end So what are they doing in Aurora are they reading Aurora actual I don't phone know numbers I or what they a do in Aurora at a time or Uh Cuz not sure how no no I mean connected connected Connected digits yeah So But But also the not just the prosody but the cross the modeling is Right probably quite different But H in reading things like zip codes and phone numbers and things Right that so How do gonna do on different I don't remember I mean very good right Yeah I mean we were in One the and a half percent two percent something Uh that th no I think we got under a percent Oh but really was but OK but s The very best system that I saw in the literature was a point two five percent or something that somebody had at at Bell Labs or Alright Uh Hmm but But uh sort of pulling out all the stops But I think a lot of systems sort of get half a percent or Right a percent and in there somewhere But that I mean really mikes no noise clean signal just digits I mean Yeah every the everything beginning is of good time in Yes speech exactly recognition Yeah And only recently got it like to the anywhere near single human cell you prehistory the beginning of life yeah And still like an order of magnitude worse than what humans do Right Yeah So When When wide awake yeah Yeah Um coffee after coffee right Not after lunch OK so um what do then is go ahead and enter this data And then hand off to Jane and the transcribers to do the Yeah actual extraction of the digits Yeah One question I have that that I mean we wouldn't know the answer to now but Hmm might do some guessing but I was talking before about doing some model modeling of arti uh uh marking of articulatory features with overlap and so on And and um On some subset One thought might be to do this uh on on the digits or some piece of the digits Uh be easier uh and so forth The only thing is a little concerned that maybe the kind of phenomena in w i i The reason for doing it is because the the argument is that certainly with conversational speech the stuff that looked at here before um just doing the simple mapping from um the phone to the corresponding features that you could look up in a book uh isn't right It isn't actually right In fact these overlapping processes where some voicing some up and then some you know some nasality is comes in here and so forth And you do this gross thing saying Well I guess this phone starting there So uh the reasoning But It could be that when reading digits because for such a limited set that maybe maybe that phenomenon doesn't occur as much I don't know Di an anybody Do you have any Anybody have any opinion about that strikes me that there are more each of them is more informative because so random and that people might articulate more and you that might end up with more a closer correspondence Yeah Yeah I I agree That Sort of less just predictability and Yeah Well definitely true that when people are reading even if what they had said spontaneously that they have very different patterns Mitch showed that and some Right dissertations have shown that So the fact that reading first of all whether reading in a room of people or rea you know just the fact that reading will make a difference Yeah And depends what interested in Would this corpus really be the right one to even try that on See I don't know So may maybe the thing will be do to take some very small subset I mean not have a big program but take a small set uh subset of the conversational speech and a small subset of the digits and look and and just get a feeling for it Um just take a look Really H think anybody is I at least I don't know of anybody uh well I don't know That could could be You an hafta interesting design too cuz Hey have the com the comparison of the uh predictable speech versus the less predictable Yeah speech and maybe find that it worked in in the case Yeah the pr of the uh Hafta think about the particular acoustic features to mark too because I mean some things they wouldn't be able to mark like uh you know uh tense lax Some things are really difficult You know just think listening Ohala in to give us some advice Yeah that Also I thought you were thinking of a much more restricted set of features that Yeah but I I I I was like he said I was Yeah gonna sure John in and ask Sure John what he thought Yeah Right But I mean you want you want it be restrictive but you also want it to to to have coverage Right You know Yeah i you should It should be such that if you if you uh if you had o um all of the features determined that you that you were uh ch have chosen that that would tell you uh in the case uh the phone So um Even I guess with vowels that would be pretty hard wouldn't it To identify actually you know which one it is It would seem to me that the points of articulation would be m more g uh I mean I think about articulatory features I think about points of articulation which means uh Yeah rather than vowels Points of articulation What do you mean So is it uh bilabial or dental or is it you know palatal Which which are all like where where Uvular ar rest place of articulation Place Place Thank you what OK whatev whatever I s said Yeah really OK place see Yeah OK we got our jargon then OK Yeah Uh Well also really a difference between the pronunciation models in the dictionary and the pronunciations that people produce And so You get some of that information from work on the Right on Right labeling and it really I actually think that data should be used more That maybe although I think the meeting context is great that he has transcriptions that give you the actual phone sequence And you can go from not from that to the articulatory features but that would