 So, everybody, and welcome to and time gobel who is our speaker today and she's going to tell us all about her latest book. And I think it's very relevant to the linguistics career launch, which has theme run one of our running themes is about voice user interfaces. So, and take it away. I can ask you questions. Well, first tell us about your background. I mean, I think that's helpful if people know how you got to the place where you could write. That's great. Yeah, totally. So I actually so I grew up in Sweden. And I came over here first for a year abroad in college. And you know that's what happens I'm still here really long year. And right. Yeah, exactly. And actually the first time I heard so sort of first quick forward. I stayed obviously I ended up getting a PhD in linguistics and cognitive science from your CSD. Nancy's element. And Robin from session. Yeah, cool. And, but the first time I heard about linguistics I remember because we had actually an exchange student from LA when I was in high school came and stayed with us. And she was basically a year ahead of me and she just started college and she said she was going to major in linguistics and what is this thing. You know, why have I not heard of this. I love languages. So then when I went to my year abroad and stuck around I basically ended up doing linguistics. And I actually the great thing about that in college I went to Washington State, and they didn't have a linguistics department but they had people spread around in different departments who were associated to make this program. So it was, you know, sort of languages, computer science philosophies I called you know, they expect what you would expect as a combination of programs and I think that was really great because to me I like that sort of broad background because of course it touches so many things I mean everything feeds into each other. I don't like the siloing. And, and so then UCSD was really great because of the cogside department. And there was a lot of interdisciplinary connections and, you know, so on. And while I was in grad school, I started working. I was part-time, first doing phonetic marking for the King database it was it. And so very low level phonetic marking because I was really fondling of phonetics I mean I just took to that right away. Then eventually I got another job that then turned into what I did after I finished grad school. Do I want to do the academic thing or do I want to continue this way where they're going to, you know, contain they'll take care of everything including these as at the time. So I started working for this little startup which was a language related sort of small R&D company. I worked for them for a while and then eventually ended up at Nuance and was at Nuance for many years like many other people at the time. That was kind of, you know, the place that many of us met and they're still in touch right from there. And it's funny because I remember one point while I was there my roommate and my office mate at the time and I were talking about, you know, this is probably the only job that we can have that uses linguistics and industry. Back then it felt like that's like, oh lucky us we ended up doing this kind of thing. And now of course it's, you know, wow lucky us to pick such a direction of doing something that we actually find really interesting being linguistics and related things and ending up being able to do a lot of it with it whether we want to stay in academia or some other things. I took a couple other, you know, places that was at Amazon for a bit, early Alexa, pre-release Alexa Alexa and some startups, you know, it's an interesting thing to be at small companies and big companies and compare, you know, the pros and cons of course, both. And now I'm at a little startup again. And then I called that my yo-yo career. Yeah, exactly. Okay, that's pretty much it. Small company, big companies, small. Exactly. Big companies and small companies that become bigger companies. Exactly. So I tend to like the smaller companies, but they're pros and cons. But yeah, so here I am. The book that we're talking about today is not your first book, and not even your first book in this domain, right? That's my first book. Oh, okay. Other than transcribing and sort of self-publishing a thing about my dad's history during the 50s and everything like that. Okay, good. I just have a look of an experienced author, I guess. The multi volume author. I like writing. Good. So tell us about the book that you've written called Mastering. Yeah. So the, you know, I mentioned earlier, not liking silos, right? And realizing, especially during the new ones years, realizing how important it is to kind of have your fingers and everything in a way. So we were lucky at the start of that time in that everybody kind of talked to each other and it was kind of we figured things out as we were going, right? So we had access to, oh, there's Christopher joining. We have access to things that most people don't have access to now, but we did not have access to things that are common. All right, so I mean, now it's super easy for people who are not in a company where academic setting right to have access to voice technology. And it was really hard back then in the sort of early 2000s, right? That was a very limited set of people who could do it. But because we actually were in that, you know, we could access data, we could make changes to all kinds of parameters or have people change it for us. And, you know, actually see the result of it. So there are all these things that we learned then that we kind of miss now I guess in a way, because like, oh, if only we could actually do these things then experiences could be so much better. But for various reasons it's harder to do sometimes, right? And so Charles, who's my co-author, who's an MIT engineer, who was at Nuance then we were at one of the startups together too. We said, you know, we have all these experiences that we'd like to share, but what we really want to share also is the importance of kind of not thinking in silos, right? But to really see how do you, you know, there are books and writing for the designers, there's books and writing for the developers, but what about that interface, right? So we really tried to do things, kind of, in each chapter it's, we try really hard to sort of web those things together and, you know, things for program managers, product managers, whoever, right? You don't have to be, definitely don't have to be a hardcore coder to read this stuff, right? You skip over the code or look at it, but I mean it all ties together. So it's a lot of, you know, here's why you should do this, you know, a lot of in-depth of do this because if you don't then this happens or here's some experience we had possibly kind of hidden a little bit to not call out the guilty parties or including ourselves, right? But you know, here's an experience and here's why that happened, things like that. So you structured this for, I mean, you wrote this book with the intention that it was not only linguists who are going to look at it. That's right. And not only developers in the voice space, but a much broader audience. So was it hard to think that way? I mean, was it hard to write that way? No, not really. I think that part was easy in a way. I mean, what I tended to do was I did most of the sort of prose writing, I guess, and Charles wrote about how to fit in. I mean, I was kind of, I would go first, you know, sort of like does the music or the lyrics come first, you know, different people do it different ways. Right. I would sort of do it first and say, here, put something in here that shows this and then Charles would come in and do that and then we'd sort of make sure that it fit together. So, and that's, that worked pretty well. I mean, there was this, you know, pandemic thing, of course, spread out a little bit. But in general, that worked pretty well. But you know, you really, it depends on your, you know, if you can have a co-author, it depends on how you work together. Right. Right, right. So then the related question is, I have a slight awareness that you switched publishers in midstream. Is that true? Yeah, pandemic. Pandemic? Is that what happened? Yeah, basically. Okay, we can break. Blame COVID. Why not? Yeah, totally. And well, I'm happy to open this to other people. But if you have some, I'd love to hear a little piece of this as a little example, you know, if you've come up with one. Well, I will get you a better example because this is actually not one sort of from our work experience per se, but it's one actually just from home life. I don't want to call out, you know, we don't, if we have any, if we've worked in the field, or if we even, you know, listen to no virtual assistants or anything, I know how, I mean, it's hard, right? So one of the reasons that we kind of hid some of the examples that I don't want to call anybody out, right? It's just difficult. But I just want to share this example that happened in our house a while back, which is, you know, a home assistant who allows you to do shopping on it, shall we say. But we don't do that. We don't have it set up. And I, my husband left, walked out of the kitchen and said, you know, turn off the under cabinet light or something like that, which is kind of the main thing we use it for and it said something like, okay, I put blah, blah, blah kitchen pools in your shopping cart. And I have this example in the book first, but it's such a great example because it just shows this kind of catastrophic fail when things aren't quite lining up. For example, this was a very poor audio capture, it probably should have just been rejected. Instead, it tried to make sense of it. And it just kind of went down the path that was very odd one. So it was sort of, whoa, that shouldn't happen. It's a useful example because it helps us understand sort of a level at which you are calling things out, and that you're drawing people's attention to what counts as a failure. Yeah, and, you know, this is an example of where it is a lot harder in some ways today because, you know, a designer may or may not see this and say, hey, you know, we have to be sure that this doesn't happen. And things are so, again, siloed and so separated that things like this fall in the cracks. And because it's just kind of harder to go in and fix them and not break something else in the process and things like that, right? And yeah. So you're mostly then in this book talking about speech to something. Not only you mean as opposed to text to speech. Yeah, or some of the other ways that we interpret voice user interfaces these days. That's mainly, yeah, I mean either one of the points is that it doesn't really matter so much if you're doing something for a home assistant or sort of call center IVR kind of thing, or in car or whatever it is right on some level I mean details of course right So it's users that should be able to talk like users and shouldn't have to be taught to say certain things, but and how to make sure that this catastrophic failure and things like that. And also we talked about, you know, the importance of privacy and trust and, and you know, good audio output you know whether it's synthesis or a recorded voice talent and things like that but Good. Okay. And I noticed in the chat men the saying Alexa doesn't like my accent. She always says, I'm not sure about that. Right. So I did. That's a great comment right. Yeah. And of course, the thing that most people have issues with with all speech stuff is sort of. I don't understand and whatever the reason is the feeling of it's the way I talk in terms of accent or how I express myself in terms of the words and so on right and, of course, it's, it's a hard task and of course, it has to be better. I'm not picking on Alexa at all, but all the integrations that it's, there's a lot of that low hanging fruit that have not been picked and eaten, and the hard stuff is still there right. It's a favorite thing I want to say with people that well you know there's music asking for music that simple that's done right, not at all. Right, because if you want to find out how it breaks. You just have to ask for specific things and see how easy it is to break something like that. And that's something that also worked on for a few years for another company was, you know, understanding music requests right, which is very tricky, actually. So what's the tricky part for that. So, for example, there's so the, the band massive attack has a song named rising sun. Okay, but it's spelled in a kind of unusual way. So there are many ways that this can go wrong. And depending on, you know, how does it interpret because of course there's this interpretation right you say something. If it will be interpreted as text, then does the text actually match the search in the database of music, and then is the music there. Is there some kind of ownership issue, or does one company try to push something and not something else. Is it a song or an album, you know, there are all these different places where it can go wrong. So like, because you don't want to ask people, did you mean this one, do you want the song with the album, what do you want, because it's just like, how do you decide if you should just give people something and they say no that's wrong. Try again. Yeah, how far do you back up. Yeah, exactly wrong about it. Okay, I can fix it. Right. And like doesn't matter it's just a song, oh you meant to buy the song well then you probably want to make sure that it's the right thing. You just want to hear it. Oh you didn't want to hear the cover version okay. Didn't want to hear the disco version okay. Right, right, right. Other people have questions or comments of anybody in the audience had a chance to pick up and both yet. And are you going to show it to you can you show us the cover so we can. Oh because I'm like trying to find a good example in there. Yeah. Excellent. All right. So, Adriana. Adriana, do you want to. I'm not saying your name right but anyway, do you want to come off mute and ask your question directly. I can try. Okay. Well, thank you so much I'm never familiar with what happens with boys interfaces, and I'm curious about what, what is really going on. Do you need to be a connotation or phonologist to work and what are the main aspects that need to be worked on for voice interfaces like the groups of people in a company like how do you divide the work in like, so I will maybe on the words that can be recognized or like the sounds how does it work. Great question. And you know that probably also depends on where you are with company and so on. And if you're one of the larger companies, you're probably going to be more specialized and if you're a smaller company, but I would say, there's such one way to answer it is there's such a demand for college whatever conversation designer, design or whoever. Speech scientists, there's such a demand that, and there isn't no real official training until very recently right, even for any kind of stuff like this, that I would say that there's necessarily going to be, Oh, while you're a phonetician so you know you have to do this thing right that's not at all. If you have an interest in the stuff and what I always say to people when I talk about questions about doing this kind of work is the very best way I think to practice doing anything in this field is to really just like, listen to people with speech technology, and do it like a study right like, right. Record the thing, transcribe it, see what went wrong or went right, figure out, you know, how it can be done better. This also would be something that if you interview someplace you can then show oh I did this thing. That's always interesting to people. In the nuanced days, let's say for on the design side people had all kinds of background those linguistics psychology. Computer science engineering. There was just the general interest in in language right and these days I'd say if you're doing the movie design. Unless you're a super technical person right now like, you know, really NLP anything coder person. The super coder technical focus people tend to these days be more the sort of speech science like we're going to figure out how to make the actual recognition work better. So I guess the design side tends to be more, you know, the linguists. You know, whoever psychologist, whatever UX. In terms of how it's broken up the sort of standard way of doing this kind of work will be first there's kind of a concept okay where this is the area we're going to create something for and so you'd start out with how big an area might you define what it's going to be it is a, you know, a music finding app is that banking is a general knowledge, you know, that sort of thing. And you know if it's, it's easier of course if it's a little bit more specific like kind of cut down a little bit so that if you do general knowledge like Alexa or Google right it's the whole different things so to put that aside a little bit. If it's a little bit more defined, you're going to first start by well what are the kinds of thing you sort of start with requirements right. What does it do. How do people do it today. This is all kind of stuff that any kind of like UX or similar background you might have. It's perfect for that right. So you just go and observe kind of who does what how does it done now if it's done or what's missing today. And then you start basically laying out the flow of what's going to happen in here what are some dialogue example dialogues we talked about that. Here's the sort of image of the wireframe of what the conversation should be like the sort of best case and here's some sample things of one little stuff goes wrong what should happen. And then you kind of dig into details more and more and this is all kind of what you know, this is perfect stuff for a linguist right because we think about language things. And how people communicate and so on. And then, at some point, of course you want to actually be and be working with the technical folks at the same time I guess you don't want to propose something that is going to be not possible to exactly not feasible within you know a reasonable time or with the current technology, because it's better to have something that actually works and something that's kind of mediocre right. And then you, you'll specify very clearly, these are exactly the kinds of things that people say it's very important right to, if there's things like the key words, you know, buy buy isn't bad on right. People say buy, or did the stock apps, you don't want to say something buy and suddenly you bought some stock right because. Yeah, sure it looks different and text but not when you say other. And so basically, want to lay out exactly the, the, the flow the dialogues and so on the into those details, and then, you know it's implemented and so on. Now if you're in someplace we actually have access to what the users do and say and get the data from that. That's the really, this is also a place where linguists are great right and linguists really love doing this work right to sort of speech science work where you sort of decide. Oh look, those people weren't recognized those people weren't recognized because they said this thing and that's not handled right. So you have to then feed back into the recognition and say, Oh, you know, look, we didn't take into account that people might phrase it this way or use these words that can also mean this other thing sometimes and you sort of just dig into this kind of like field methods or it's really fun. I really like that. In some places, you know, it's all very statistical based, and there's still also ways to make voice applications or systems that are very rule based. So you can kind of specify that these are things that people will say. This is especially if you're doing things like, you know, health related stuff or financial stuff we really have to make sure you know what people said because if it was wrong that bad things happen. So sometimes having rule based stuff where you're matching to specific things that people like names of drugs or something. It's really important to have that and I think it's, that's another thing that as a linguist is really fun right because it's really kind of looking at exactly how do people phrase things. So I'm kind of babbling a bit and I'm not sure if I'm answering your question. Yeah, thank you so much. Right, sometimes you're so far in it, you forget, you know, like not to be in it. Right. Exactly. Other people have questions for and so I'm going to I'm going to ask how did you organize the book I mean what's what's your sense of the flow through the understanding. Yeah, sure. The sort of overall was kind of start to finish over projects actually, you know, who goes into a little bit the layout of how I responded to the other question that sort of starting from how what happens first in a project like the overall organization is kind of start to finish the things that come up, but there's like sections right so starting with how do you gather information. And actually this is kind of a good example I think. I know I was going to think of an example eventually, which is this small startup that Charles now we're at was a healthcare related thing. And we, somebody actually wanted us to do a voice recognition thing for urine sample collection at the hospital, because you don't. It seems like it's a good idea right have you don't have to touch anything because your hands are busy doing other things and you don't want that what the problem that they were trying to solve was that they had a lot of samples that got contaminated, thank you contaminated. So there's a well speech will be good way to do it's like that sounds kind of a cool idea right. So we started kind of looking at that and laid out this flow and everything. And then said well do you have any pictures of what the, the restrooms look like. Okay, well let me start looking at that and then we realized actually, which really need us a table. Because there was no place for people to put anything and probably that's why I think so I contaminated because they have to, you know, touch all kinds of furniture and whatever. And the reason I mentioned this is because I really want people also to think about, you know, that whole thing to the man with a hammer you know everything looks like a nail. Because there are many places where voice is not the right thing right so pushing people into having a voice solution also isn't a good idea. I don't just be unhappy. No, I love this example. This is a fabulous example because it really talks to the UX side. Exactly. Paulina I'll be there in just one minute. That is to say some of the client asked for something they thought voice was the solution. You went in and did your expectation about the flow of the process you're going to receive a two little whatever. Yeah, we worked it all out. So you wrapped the cup so that you can put the urine in there and la la la you know so that you knew what the steps were that people take and not get in trouble. And then you looked at the situation of use and realized, oh my God, there's no table. And so you get to give the feedback that voice may be an excellent add on to this, but a more pragmatic and immediate solution let's see if we can avoid contamination by putting a physical table in the room in the bathroom with exactly. Yeah, so this is great. I mean this is definitely a UX example, as well as a voice example. Thank you exactly. Yes, please. Yes. Hi, I have a question about when when somebody's writing we normally tend in mind, like an ideal reader. So I was wondering who would be like this ideal reader for you. And as the second question, let's say, I might not feed your ideal reader I might just be an average person but I have interesting in your work. So who would be your suggestion if I steal. I don't, there's still things that I don't really understand or like your book doesn't really cover like what are, what kind of suggestion tools, extra tools you will recommend. Even now, you know there's a pretty limited set of books right even I mean there are there are a few, and they're the good ones right but it's still pretty limited. So each one has kind of its own real focus and so on. And I would say, for us it was. So one thing that we, I was doing one, many years ago at New Orleans was, we created this class for project managers to basically teach them about the newest technology and how to the sort of pitfalls of a speech project. And so it's almost like some of that was still kind of in the back of my mind so that it could be something here that anybody who just wants to dig into. Why is it like this, not just kind of the two liner of, oh, here, or here are the five tips of doing a speech thing right. I was like, okay, that's great. And why are you telling me that. So, I would say that the ideal reader is somebody who really wants to look into what's underneath what what's the reasoning for this without having, you know, it's not like, I said before it's not a technical book in that it's, you have to have a particular degree and any particular kind of technical field instead you can kind of pick through okay here's talking about error handling or something and here's some examples and why I said and one thing that we have throughout is a lot of little sort of from from the voice trenches examples and also examples of, you know, doing it this way might lead, excuse me, might lead to this and this other way so on purpose it could be you're just interested in finding out more about why things go wrong or how to make them work better, or you really want to look into some details about how design stuff is done or how to code up something. You know that would, that would run that would work. And so basically it's a little bit for everybody and not necessarily something that I would expect people to just sit and read cover to cover, but just look up. You know, why is it that they asked me these questions. Because there's a reference. Yeah, exactly. Yeah. Yeah, cool. Did I answer that question. The other. Yeah, I mean I had was affirmative even. And in terms of the other books, I mean, you know, like, I have a stack of, of books that I tend to recommend to people I don't want to leave anybody else, for example. And you know, and I mean some of the books that don't usually come up necessarily because they're not, you know, speech per se but I'm going to grab this thing right here. I really like Jeff Johnson stuff like this book. Also, Jeff Johnson is a really great guy. Yes, yes, yes, I recommended this one yesterday so great. Oh cool. And it's like super easy to read. Yeah, I'm going to get a book off my shelf so I can show it to you. This is another one that I like. Oh yeah, I forgot. Who wrote Oh, David Travis. Okay. But yeah, there are those two, but anyways in the chat. Yeah, they're just like, yeah, I can make a list. Are you familiar with Isaac's and Walendowski it's a little bit older. I'm not sure what's the name of it. It's called designing from both sides of the screen so it's Ellen. Yeah, it's it's a wonderful book because it sounds like it's much like yours. I often recommend it, because it's a UX person and a computer scientist talking to one another about how to work on a project. I totally want that. I'll show you hold on one second I'll be right back. And there's of course Cliff NASA's book, which I'm sure has been mentioned. Cliff NASA's an awesome guy. And I worked with him a little bit. And then there's also this which is has been around for a while but is still very relevant. A lot of the stuff. Cool. We should make a list of it. And then there's this one. Which is also. Who's that one. I'm trying to get it into here. Yeah, yeah, good. So, and of course Kathy purpose. Yes, Kathy Pearl, right. Yeah, sorry, I said her name on. Yeah, I knew you meant the new ones alone. Right now Kathy is interestingly not a linguist. I think she has come to appreciate linguists. Sure. And I mean she's she's also. Undergraded UCSD. And that's just computer science. Yeah, exactly. Right, right. And interestingly, I don't know if you. I don't know if she's written this up, but you know, Abby Jones. She's at in health at Google now. For a little while she was still, she was earlier at Google in a voice position when she had to. She gave a presentation and so on, which was great. Her background I think is English literature and she was a teacher America person before she found her way into UX. And so has some great perspectives then on ordinary language. I actually, I did finally come up with another example too. Okay. Quick before I forget. I mean, this has actually come up a couple of times in different shapes, but working with customers. This is the thing that we also try to really cover is working with customers or clients and use not end users per se but you know the people who pay the bill and want a specific thing, it can be really tricky right because, and that's why we also want to teach them as much as possible about how voice works right because the more they understand and I can ask for things that are crazy hopefully. And there has been an example of people saying, well, we don't want to recognize that because we don't want to deal with it this happened in a health care situation. And, you know, said, well, can we just like, don't basically say don't let people say that or if they do it or them or something. And we have to explain that you can't personal you can't make people do certain things and users right they will say whatever is relevant, or, you know, you shouldn't stop them you can't right. But you have a choice of what to do with it. And obviously, and we said, importantly, you also can't say, don't put this into the grammars or into the recognition right because then it will match with something else. Yeah, give me give me a yeah so let's say it's, it says the name of a drug raises this healthcare thing. Okay, so maybe it was a competitor's drug name. I mean that wasn't the case but it would be the same thing. And maybe this is well we don't want to recognize that because that's not our drugs. I was like, well, have you looked at drug names. First of all, people can't pronounce them because they're really complicated. And even if so then. And if you say something that sounds similar, but it's not the same and then it's going to match with that kind of like the kitchen pool example. So you have to deal with it. So, put it in. And then you can say, Oh, we don't have any information about that thing or something right you have to actually. Like, it's an attractor. Yeah, tend to be ignorant. Yeah, it'll be helpful right you can say well that's not something we work with or whatever the cases but you have to have something that's the correct attractor. So it doesn't match to something else and then runs off with it. So I would hope that can you put your the link to your book also in the chat. Yeah, I'll do that and all those other books. Marcus has been trying to keep up with us a little great. Thank you. And we'll see if there's anything. Okay, Paulina is your hand up for a new question or an old question. Just want to check just want to check. Anybody else have questions or comments for and I should say to that. I love talking to people who are interested in getting into this space I do that a lot so by all means you know figure out how to, you know, Nancy can tell people to get in touch me with her. And we're just paying me and find me on LinkedIn. With my last name that's pretty easy. You're pretty easy to find, right. Yeah, just remember it's and without a knee. That's right. Yeah, yeah, I can totally find me there and just send me a question or whatever. I'm always happy to talk to people and say, um, Yocelyn, are you ready. Okay, she's got a question. Oh yeah. Yes, I'm ready. Hello. I have a question. I'm very interested in this type of work but I don't know much about it so I'm definitely getting a book. Yeah, but my question is out of the blue I ended up, I do some coaching in Spanish or actors. And I ended up being called for a different project. And it ended up being that it's for a speech recognition device. I was just thinking the other day, can I add that to my resume as I worked for a voice interface, even though I was part, you know, training the actor to deliver in a certain. I mean, that that's part of what we designers do. If they work with voice talents. That's something we've done a lot. I mean, and that's a whole actually interesting field or area to look at. Do you use synthetic speech, where you just, you know, try and type something in and get it to come out the right way, or do you use for the voice actor and get them to say things a certain way and the pros and cons of those two right. But absolutely that's something we do a lot. You know, and the food designers are very good people to do their actual coaching because they know exactly what they have in mind, and where to stress things, and that is very much, you know, a great wedding of linguistics and voice technology. And so yeah, what kind of, if you can say what kind of device was it that you were working on. Okay, but it is like a home. Home thing. But yeah, yeah. So a general audience that you're looking for, you know, general and not a specific domain. Yes. So you because you mentioned there's the NLP department, which is a very technical coding side of it. And then does the designer and the speech science. Yeah, my, my experience being more on the design side of it. Yeah. You know, when, when I first started that new ones are for many of those years, we were very broad and that we, there were projects where basically did everything from start to finish because they were smaller and I mean like there was something for Norwegian. So, okay, I don't speak Norwegian but I, you know, speak Swedish and therefore it's, you know, I can write the grammars for it and then I put that's a, you know, another question of how do you think Swedish in itself is not enough to do voice design for it, right, because you also need to know about the culture and things like that. But there's always an overlap right and there's certain things you can still do you can like check on other people's work and things like that. But so depending on where you're at, especially a smaller company, that's probably why I like smaller companies to like that. I like to do more. One thing, you know, one slice of the pie but I kind of like to taste all of the pie, you know, as much as possible because I also think that that leads to better implementations, better solutions because people kind of see what happens. You know, the in my experience, the buoy designers that I've had a chance to do some of the speech science and vice versa. They make better stuff, right, because you understand more of the big picture. So would you recommend coding experience on any of those. Yes, no matter what you do yes. Okay, and that's not you know it's definitely not my, my strong suits and if I came into the field now I, it would be. I mean I've done coding right fun. I'm very rusty I'm not that proficient in it, because it's not something I do I have other people do it so I never learned. But, but it's always a good thing of course you should know that absolutely. And in general, I mean the people say what language or what that's kind of, I mean, in general if you have to pick one probably Python, but because it comes up a lot in language situations but but always yes, learn to learn to code. It's always going to be good if nothing else you can use it. For things like manipulating text files is very good right if you because if you're doing anything that's kind of looking at data, being able to pull things out quickly, just like all things with this word or, you know, organize it in this way that kind of thing is very useful. So, I know, Chris since you're on the line that I don't know if you have any comments about that. If you're paying attention to jump in. Do you agree with that. Absolutely 100%. Okay, good answer. I without, you know, in language technology and an LP and that sort of world without coding in, but it will never hurt. Yeah, it will only help you. Exactly. I've had a lot of questions about like, well, I tried to do this intro to Python class and got bored, because you know just asked me to manipulate strings and stuff like that. But if that's the case, get a project, you know, find a project that you want to do like if you're unhappy with how, you know, some as our technology is not able to recognize your accident speech, you know, dig into it like figure out what what is the deal, can you make a contribution to the project. You know, this, you know, yeah, that's hard, but so is the work. I mean the work is very hard. And even if it doesn't work out anyway. It's also a great thing that if you're looking for job and you talk about what you've done, people would eat that up. Oh, you actually did that you actually try to fix something in recognition for this context that's awesome come work for us. I may simplify it a little bit, but you know, it's absolutely. It would be a great plus. Thank you. Sure. And thanks. And there's plenty of room for linguists. Thank you, Stuart, who's currently at Google to be able to talk to us about this. And I know your background is genetics, and if you've done a lot of things that require some amount of coding in recent years. Right, so I've gotten away with taking very flexible industry. Now job title computational linguists. I didn't study computational linguistics. The titles don't really mean a lot in this field right now is one thing. If you're looking for jobs to if you're looking for particular job you just have to read, try to read between lines or read what they're looking for but don't just say oh that title is not me. You know. Right, worth reading the description throwing your hat in the ring, and then getting to talk to somebody more about what the scope of their job. So don't let the job description turn you off. There's even like a quarter of absolutely that's worth that's attracted to you. And really push the linguistics thing. I mean really I would say, this is what if you don't know what linguistics is, you know you talk to me like, here's why linguists are great for this. We have a good language from that sort of object, you know, we can distance ourselves and that's something that a lot of people can't do, right. You say oh well I speak, blah blah blah I speak English I can make a skill for Alexa whatever like yeah there's more to it than that right. And, but that's kind of the attitude they always get so let's just language I speak it so how it can be. And, and that's the hardest part of working with customers really, because everybody gets so kind of into their way of thinking. And say well here as a linguist, we learn to study language more objectively from a distance whatever analyzing it and this is how it plays into this job. And I think we should all be seriously, you know, heavily banging our drums of when as linguists into any kind of technical job and say this is why you need me. I say to you because I don't talk like that myself, but it's still true. Great. Well, I'm going to say, everybody, you know this that Marcus added the evaluation form so that means we're getting to the end of our time. And if there are any last questions for and at the moment that you've thought of I'd be happy to entertain them otherwise. Please seek her out. And learn more. Yes, join us join us in the field. Yeah. We need strong languages. Totally. Cool. And we got some little party and clapping symbols. And I thank you and for sharing your morning with us. Absolutely. Good. My pleasure. I think it's awesome that you're doing this. Thank you. I do too. So everybody, go forth and be wonderful.