NLP research by & for local communities

While at EMNLP 2022, Daniel got a chance to sit down with an amazing group of researchers creating NLP technology that actually works for their local language communities. Just Zwennicker (Universiteit van Amsterdam) discusses his work on a machine translation system for Sranan Tongo, a creole language that is spoken in Suriname. Andiswa Bukula (SADiLaR), Rooweither Mabuya (SADiLaR), and Bonaventure Dossou (Lanfrica, Mila) discuss their work with Masakhane to strengthen and spur NLP research in African languages, for Africans, by Africans. The group emphasized the need for more linguistically diverse NLP systems that work in scenarios of data scarcity, non-Latin scripts, rich morphology, etc. You don’t want to miss this one! Featuring: Just Zwennicker – LinkedIn https://www.linkedin.com/in/just-zwennicker-1929171Andiswa Bukula – X https://x.com/andiebukulaRooweither Mabuya – X https://x.com/RoowyMBonaventure Dossou – Website https://bonaventuredossou.github.io, GitHub https://github.com/bonaventuredossou, LinkedIn https://www.linkedin.com/in/bonaventuredossou, X https://x.com/bonadossouDaniel Whitenack – Website https://www.datadan.io/, GitHub https://github.com/dwhitena, X https://x.com/dwhitenaShow Notes: EMNLP 2022 papers from the guests: Towards a general purpose machine translation system for Sranantongo https://arxiv.org/abs/2212.06383MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition https://arxiv.org/abs/2210.12391AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages https://arxiv.org/abs/2211.03263Other links relevant to the discussion: Masakhane https://www.masakhane.io/Lanfrica https://lanfrica.com/The South African Centre for Digital Language Resources (SADiLaR) https://sadilar.org/index.php/en/Upcoming Events: Register for upcoming webinars here https://practicalai.fm/webinars!

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I can relate to just, I thought that I knew the language, but then it feels like, okay, I actually don't know anything. And I don't know, they've been that interesting curve. It's called a curve of like David something, where technically showed that, okay, when you think that you know something, you have high confidence. And that's actually when you actually don't know anything. But then when you start learning and then you are adopting more of yourself, it's technically like that process of acknowledging and like learning more things. And then like the curve like goes up at some point again.

• 0:41Speaker 01

  Welcome to Practical AI, a weekly podcast making artificial intelligence practical, productive and accessible to everyone. Subscribe now. If you haven't already, head to practicalai.fm for all the ways. Special thanks to our partners at Fastly for delivering our shows super fast to wherever you listen. Check them out at fastly.com and to our friends at fly.io. We deploy our app servers close to our users and you can too. Learn more at fly.io.

• 1:17Daniel Whitenack?

  Welcome to another episode of the Practical AI Podcast. This is Daniel Whitenack. I'm a data scientist with SIL International and I'm at the EM NLP Conference in Abu Dhabi. And I've got some old friends, some new friends here with me, a very exciting community show that we have for you today. Why don't I just have everyone just give a brief introduction of who they are and where they're coming from?

• 1:43Speaker 03

  Hi, everyone. My name is Andi Swabukula from South Africa. I work for the South African Centre for Digital Language Resources as an Isikosa researcher. Isikosa being one of the 11 official languages spoken in South Africa.

• 1:59Speaker 04

  Hi everyone, I am Ruweza Mabuya, better known as Ru. I am also from South Africa. I work with Andy Swa at the South African Centre for Digital Language Resources. I work as an NISI Zulu researcher. It's also part of the 11 official languages of the country. Thank you.

• 2:15Speaker 05

  Hi all, my name is Juss Veniker. I've been working as a data engineer for over 20 years. Recently, I wanted to switch towards data science, so I did a master's in that direction. For my thesis, I created a translation system for Sanantongo, which is a Creole-based, English-based Creole language from Suriname, where my father is from, and I'm of mixed origins. So my mother is from the Netherlands and my father from Suriname, and I've been born and raised in the Netherlands.

• 2:44Speaker 00

  Okay, hi. My name is Bonaventure Dosu. I'm originally from Benin, but I'm also known as the citizen of the world, travelling around conferences. I am soon to be a PhD student at the Quebecia Institute and also at McGill. And I work on like low resource languages, African low resource languages. I mean focusing on formality language, but extending to other languages as well. And I'm also interested in machine learning for healthcare, like drug discovery, therapy, medical imaging, all those type of things.

• 3:15Daniel Whitenack?

  Great, yeah, thank you all. Thank you all for taking time to do this. This is so great. I mean, one of the really encouraging things about being in this room with you all is that, you know, so many talks here at EMNLP are great talks, but they'll say things like massively multilingual, or like this works for all languages, or something like that. And that's definitely one perspective that's not totally accurate. So maybe if we start with Ru and Andy, what from your perspective are you passionate about? What is the area that you're working? And maybe just highlight some of those things that maybe are another perspective of either linguistics or NLP that are important for people to understand in terms of the world's languages.

• 4:00Speaker 04

  Okay, so I'm, my passion is working on making sure that SSulu is also a language of teaching and learning, because currently in South Africa, um, English is the predominant um, language that is used in media governance and also in, in higher education. So, um, what we're doing now is ensuring that our languages are also at a level where they are at par with English, in terms of developing it in tools, um, in human language technologies, in machine learning, etc. So we also want to have that privilege, if I can put it like that, in ensuring that our languages are also more accessible even online. I'm, I've been working on looking at specific literature materials, but you find that I can't find those online.

• 4:42Speaker 04

  I literally have to scan the book if I wanna do an analysis of a particular morphological structure that I'm working on currently. But then you find that all the Shakespearean books, for example, are readily available online. So that's, that's my passion, in ensuring that even African scholars can do research in their own, um, languages with writers or authors that are like them, that, that writes in, in the languages that we're interested in looking at, so that we also have those readily available and they can be used for research throughout, um, for posterity.

• 5:14Speaker 03

  And I think for me, also for the institution that we are working with or working for, is that we're trying to also build a, a bridge, a gap between NLP practitioners and linguists, because it's also, it's always a matter of linguists are doing their projects on their own side, and NLP practitioners are doing their own project on the side. But I feel like if we can work together, because you need to, for you to understand the lang, the, the language that you're working on, you should collaborate with the linguists. And for us to understand how these language technologies work, we, we need to work with the NLP practitioners, because now in South Africa, NLP is not a big field. Uh, that's why our institutions are able to send us to such conferences, so that we

• 5:55Speaker 03

  know what other people are doing, so that when we go back to our institutions and going back to actually assisting the universities in the country, we can impart that knowledge to them. Because currently, really, how we're doing research is still a bit traditional, and time is Moving, technology is advancing, we don't wanna be left behind. So I think our greatest passion is to make sure that our languages, because you keep saying that under-resourced, under-resourced, until what? Like, we've been saying that our languages have been under-resourced for many years now, that now we have the opportunity to actually be sitting in a room like this with people who are actually doing the things that we've always heard of, but never knew were possible for our languages. So we're basically here to say, collaborate with us, assist us to get our languages to a level

• 6:39Speaker 03

  where there are languages of teaching and learning, and our data is also easily accessible. Because the other issue we have is accessibility of data. We don't have a lot of data in our languages, because we don't digitize the material that we have. But at least now, we know that, we know what the possibilities are. So, yeah.

• 6:57Daniel Whitenack?

  That's great. And just to follow up on one of the things that you mentioned, you mentioned this sort of idea of linguists and NLP people collaborating together, and you kind of mentioned the problem of the availability of data, the scarcity of data. Are there any either misconceptions or things that you would like to highlight in terms of, you know, a lot of times what we see are these models, NLP models, getting bigger and bigger and bigger and requiring more and more and more data to train. But the reality is, for a lot of languages of the world, like you said, we either kind of have just a small amount of data and it's not growing quickly, and, you know, those models are getting further and further away from being applicable in those scenarios.

• 7:41Daniel Whitenack?

  So anything you'd like to highlight or point out there?

• 7:43Speaker 03

  Yeah, I think, yeah, that's the issue that I don't really know who builds the models. Because I wanted to refer specifically to the people who build the models, is that when they're building them, it's like they don't have the idea of the structures of the languages that they're building the models for. Because we also have in our repository certain models that we're using, but as soon as we train them with data from our languages, the accuracy levels are always very poor, because it's like the systems or the technologies do not understand that, for instance, my languages are glutinous. So when they're being built, hence the collaboration, it's like also take into consideration the languages that you're building the systems for. Because I feel like the systems are always built for specific structured languages.

• 8:26Speaker 03

  So that's always an issue, because now we do have access to the languages, but there's so little that we can do with them, because they don't understand the structures of our languages. Hence, again, I will re- emphasize.

• 8:40Speaker 03

  Emphasize the collaboration between N O P practitioners and linguists. Yeah.

• 8:45Speaker 04

  Just to add on, a case in example is when looking at Google Translate, for example. It has improved quite a lot now, but previously you'd find that you'd want to translate something from my language into English or vice versa, the results were poor. But I think now because there's data that is available and they're doing something to ensure that there's an improvement in there, then you actually can see the positive results. But still, you find that in some other tools, even now, you still find that the accuracy levels are still very low. And as you said, that it's the fact that when the tools are being built or created, it's like they don't have the language structure in mind. I feel like it's a matter of, okay, we've built this, so it should work for every other

• 9:30Speaker 04

  language, which is not the case. Each languages have a unique structure, we have a unique morphology, even though they're spoken maybe, for like the case in South Africa, we have nine indigenous languages, but their structure is not the same. So the people that actually build tools or create tools need to have that in mind and need to also work collaboratively with linguists, people that are trained in these languages, to ensure that the structure is also represented when the tools are created.

• 9:57Daniel Whitenack?

  Yeah, that's such a, that's such an amazing point. I'm glad you brought that up. I know even in our work, you know, encountering tools that are very popular, you know, things like word segmenters or subword packages where maybe it doesn't work quite right for like an Arabic script language or a right to left language or whatever it is, just because that was never envisioned, you know, from the beginning. On that same theme of kind of the types of languages that people are building language technology for, I wanted to ask you just about Creole languages. Maybe people listening to this podcast aren't that familiar with Creole languages or understand kind of how they're used around the world or what they are. Could you describe that a little bit and then also a little bit about your language and the language you've been working with?

• 10:42Speaker 05

  Yeah, sure. So a Creole language is basically a language that emerges in places where people of different cultural backgrounds come together. So in the case of Suriname, that is during slavery time, basically the 17th century, people were brought from Africa to Suriname. Also, people from Europe came there to, you know, basically, you know what they did? All kinds of horrible stuff. But they needed a means to communicate amongst each other. And basically, it's a language that has characteristics from the different languages that participate, from the people that participated in those communities, like English, Portuguese, Dutch, and some African languages. So it's basically a melting pot of languages.

• 11:27Speaker 05

  I don't know if I can say, put it that way, but usually it's grammatically a bit simpler and it's easier to learn a language, let's put it that way.

• 11:37Daniel Whitenack?

  Yeah, and one of the things you were mentioning to me in our discussions even previous to this is that for some of those reasons that you've mentioned, you know, maybe Creole languages weren't and aren't always treated sort of at the same status of other languages. Could you speak to that a little bit?

• 11:54Speaker 05

  Yeah, definitely that's the case. So when I started this project, I found that this was really low resource. I was even amazed to find out that I couldn't find a single book or novel written in Stranantongo. And that's because there's a lot of stigmatization going on with that language. So for instance, in school, the, so it's a form, the Suriname is a former colony of the Netherlands. The first language still, to this day, they're independent since 1975. The first language still is, and the official language is Dutch, spoken in Suriname. Stranantongo is the second language. So there's basically no sources available in Stranantongo. And it wasn't, it was for a long time forbidden to speak the language in schools, for instance.

• 12:38Speaker 05

  Also, parents often discourage their children to speak the language. So that's stigmatization caused the low availability that we are dealing with now.

• 12:49Daniel Whitenack?

  Yeah, and describe a little bit about sort of your vision, I guess, for this project that you're working on and how it fits into maybe some of the needs of the language community that you're aware about just from being part of that community and how that shaped your view of the project and what you're actually working on in your project.

• 13:08Speaker 05

  Yeah, so I have two sons. My youngest son asked me a couple of, last year he asked me why I hadn't taught him how to speak Stranantongo. And that gave me actually the idea to build a translating system. So that there's a lot of people living in the Netherlands with Surinamian roots. Like I just explained, like in 1975, they became independent. So around that time, lots of people migrated from Suriname to the Netherlands. So that's first generation is mostly fluent in Swanang Tonga. I myself am a second generation. Before starting this project, I thought I was pretty okay in the Swanang Tonga. Maybe eighty, ninety percent. So I now would say maybe fifty percent, sixty percent after studying the language better.

• 13:53Speaker 05

  My son, who's a third generation, really wants to connect with his culture. So when we visit Suriname, for instance, and we're meeting with family members, he wants to know what they're saying. So I see this need within the Netherlands that people from the second and third generation, they want to connect with the culture, but they don't speak the language. So I hope that this translation system will support them in reconnecting with their culture.

• 14:19Daniel Whitenack?

  Awesome, yeah. So I want to maybe ask Bona a couple of questions. I feel like I've been trying to get you on the podcast for a while now. So I'm glad you're actually here and...

• 14:29Speaker 00

  I was actually already on.

• 14:32Daniel Whitenack?

  So yeah, I wonder, one of the things that we were chatting about just before this is that people view Masakane and some of the things that are going on there with a lot of respect and because of the momentum it has and how so much has been done. And I know you're part of some of the things that are being presented here with Masakane. Could you describe maybe, we've actually mentioned Masakane on the podcast before, but for those that aren't familiar, could you describe what it is?

• 15:00Speaker 00

  Okay, I hope I will do justice to everyone. So I'll just describe, I would describe Masakane as a grassroots organization, NLP movement that wants to build NLP on language technologies for African languages by Africans. And as everyone talked about, as everyone said earlier here, you know, like we need more people speaking those languages to be more involved in the like... Building of those language technologies. Because someone, for instance, who works in a big company and be like, oh, okay, I found maybe this data on, uh, let me say, Oscar or like on like Flores or any uh dataset that is said to be

• 15:45Speaker 00

  high quality and like multilingual. You know, he is just like trains a model on it and then assume that everything is supposed to be working, you know. But while at the beginning, those like language models like SLM, those type of thing have been created like for for like high resource languages like what, like English, Chinese, you know. Even like in those initial paper, you can see that the downstream task, they evaluated those tasks, those models on um languages like French, English, Chinese, those type of thing. So uh there's the assumption that, okay, we train those massive pre-trained language models and well, they can just like, we can just do like some transfer learning to low resource settings,

• 16:26Speaker 00

  which is not always true, which is one of the idea and paper that I presented here, talking about active learning for uh language modeling. So as everyone has been saying, this is important and like that's the the gap. Uh like also um Andy said and like Ru said and uh just said, they, we need to like reduce that gap between language and like people who are are like practitioners or NLP practitioners. You know, we need domain expertise, domain knowledge and of course, like as an NLP researcher, I can have those, but language also have to come in to be able to say, okay, whatever this model model is like predicting is like rubbish or like is it makes sense.

• 17:09Speaker 00

  And I think as the most recent like ongoing stuff like on Twitter and all, models actually don't understand language. They understand data distribution, they understand words, you know. But then we need, again, as I'm emphasizing, we need that expert knowledge to be able to make sense of whatever those model produce, to be able to say, okay, this is actually something useful. And yeah, that's what Masakane is trying to like build a community of like NLP, not, I want to say NLP research, a community of like, let me say, people Africans who are

• 17:47Speaker 00

  working on African technologies. So it includes linguists, it includes people who have theoretical, like NLP mathematical background like me and like you. You're also part of the community. We have also like Sebastian, we have people who actually are not Africans, but who have like interest in like building, in like accompanying like that, that effort. And that's like what the community is all about, putting forward and like representing, bringing more people like us at this, at this type of like big NLP conference, let me say, to the world or to the map or however, like increasing like representation and making sure like our languages are preserved through those technologies, which are inevitable today because somehow,

• 18:32Speaker 00

  um, everything we're doing now is like based on needs somehow. So, yeah.

• 18:37Daniel Whitenack?

  Yeah, that's great. And I can speak, as you mentioned, I've had the great privilege to interact with a lot of people from Masakane and, you know, on a, on a few small areas, but even in those, those small things, I would just encourage researchers out there that have an interest in what's being discussed here to engage with those communities, engage with local language communities and speakers of those languages as you're building these technologies. Cause you do, you know, I am benefited so much by getting to interact with Masakane and the things that I learn and, and, you know, getting to have these sorts of discussions to have better awareness and understand how I can join and partner with people in the building of language technology. So as we kind of have, have gone around and

• 19:19Daniel Whitenack?

  talked about various things, I'm wondering if you all could maybe share, there, there's probably people, a lot of people listening to this podcast that are actually listening to it in English, but are maybe have a mother tongue, their English is their second language, and they're thinking, hey, I wonder what I could do in, in my mother tongue, in my, in my first language. Um, I know it's not well supported in language technology. Any encouragements from any of you of like, if you're a language speaker and you, you're wanting to sort of get into this somehow and, and kind of partner together, collaborate with others to help build, um, you know, more language, a higher level of digital language support for your language, what would you say?

• 20:02Speaker 05

  Yeah, if I can add to that. So what you usually see, you need a lot of data to train a good translation system or any NLP application. And although there is not much data available in San Antono in my case, the thing that you can usually find are Bible translations. So in my case, I used the Jehovah Witness 300 corpus, which has a translation of 300,000 parallel sentences from Dutch into San Antono. And even in some smaller, even smaller languages spoken in Suriname like Saramakan and Akan, which is closer to some African languages. So that's a starting point. Of course, the idea would probably be that you create a general-purpose translation system.

• 20:47Speaker 05

  That was also my plan and still is my plan. So on top of that data, you would need some more data from a general domain, from different domains next to the religious domain. So it was funny, actually, to see that Daniel from SIL, I found online, I found a dictionary in San Antono, and it contains a lot of words and with those words, some example sentences. So before even knowing Daniel, I found his website of his company and was able to scrape 3,000 sentences from there. Yeah, hopefully next time you don't have to scrape it. Shoot me an email. Yeah, indeed. Good to know you now.

• 21:28Speaker 05

  And on top of that, what I did is basically scan some smaller sources and OCR them, basically, and then manually align sentences. So it's a lot of manual work, but I think also Bona has the same experience of doing a lot of manual work for his translation system. So now that I finally was able to get my first model up and running, I also built a translation system around it, a web app. So I'm now in the pilot phase where people are trying to, are starting to use some Spanish speakers as using the system. And evaluating the results. And so basically by just using it, they enter a sentence in Dutch.

• 22:12Speaker 05

  They get the Strandang translation back and they rate it. And if they don't think it's good, I ask them to enter a better translation. And they submit it and I collect that data in my database. So I hope in this way to collect more data from a more modern use of a Sranatong instead of the religious one. And collect enough data to eventually build a system that is more potent.

• 22:34Daniel Whitenack?

  Yeah, that's great. I think you highlight something that's definitely good for people to realize. This is also our colleague Colin Leong from the University of Dayton. He told me about this, that his parents, who are speakers of a local language in East Asia. He asked them, hey, give me all of the data you have for your language and I'll try to try to build something. And he showed me the folder and it included, you know, MP3 files and Word documents and, you know, images and PDFs and all of these things. So I think, yeah, that's something important for people to realize that, you know, not everything has a nicely curated dataset on hugging face. And even doing some, you know, being involved in some of that work to get that data put together is a hugely beneficial thing.

• 23:19Daniel Whitenack?

  So, yeah, anyone else, things you would want to highlight for people out there wanting to start some of this?

• 23:25Speaker 00

  Before leaving the floor to the ladies, yeah, I would like to just like second what just said. I also had the same, let me say, struggle with phone because I started and nobody was working on phone. Nobody knew about the language. And that was also something interesting and exciting, you know, like going into a direction where nobody's looking at and like unveiling it. So not to show off, but a lot of people nowadays just like quote me as the phone guy, you know, like when someone is talking about phone or whatever and there's dub, they just tag me on like Twitter or whatever. And yeah, I envision just to be the same like for Sranatongo.

• 24:06Speaker 00

  And, you know, the moral of the story is that you need to get started because there's always going to be a point where there's No data and someone has to do some little effort. You know, for instance, we have GW three hundred, but what if those people didn't do anything? We wouldn't have even, we would not even have a starting point, you know? So I started as with GW three hundred, then I tried to like manually like scrape from like with my friends and all through Google Forms. Uh, I created something like a twenty five thousand sentences. And then out of that, then I've been able to bring some proof of concept. And you know, like it grew up and like people are now more knowing about the language.

• 24:48Speaker 00

  Still is not, I mean, I built F F I Translate with Chris, uh, people are using it, people are like very like sending feedback, they are like happy. It helps them, artists, people, they're like, they are more like aware as people be willing to be uh more contributing, creating more content. It's not yet on something like a Google Translate or a centralized translation for those like African law resource language or law resource language in general. But I hope that something is going to be coming. So I'll just say just that, yeah, honestly, like my name says, I like adventures and I like good adventures. So I just like to go where nobody is focusing on and like unknown is exciting, like you bring something that people haven't been focusing on to light.

• 25:32Speaker 00

  I don't think I would have had the same maybe in part if I, for instance, started with Ebo. Because that project, the first F F I project that then like went on D B C or those type of things. We were doubting whether we should use for Ebo. So finally, Chris and I, we decided to go for phone because Ebo has at least some effort done already, but nobody heard about, found nothing was on phone like. Today, um, there are a lot of papers, people citing the work, it's been cited like in the paper that led to the extension of Google Translate to twenty twenty four. Or twenty more African languages or twenty four is being cited in like no language left behind of Meta.

• 26:10Speaker 00

  And you know, like also being part of the master candidate, you collaborate with people like Sibashon, with Julia, with Angela Fan, who work on N N L B, you know? So just get started and like people will know about it and then I would just keep supporting. Yeah, if you don't have support, just be yourself supporter. And at some point, like, you know, when people are seeing the effort, they will definitely enjoy it and then it will like take it up from there.

• 26:35Daniel Whitenack?

  Yeah, Ru or Andy, anything to add?

• 26:38Speaker 04

  I also share the same sentiments with the case for Isuzu. You find that people should just start, even though it's difficult because data is available, but people are not coming forth. They're not wanting to share their data. You find that, okay, you collect or you do whatever with it and then you just keep it to yourself. And then that now hinders the progress of the language or the development of the language in itself. I think it'd be a great idea if people get the understanding that when you are allowing your data to be accessible or make it open resource, you're not it's not a matter of I want to steal your idea. I can do something different than what you did with the data. And also just ensuring that it's more researchers have accessibility to it so that they can use it for whatever that they want to use it for.

• 27:23Speaker 04

  The only issue that I have with getting sure that the data is more is collected in a general sense because you find that newspaper articles are very much easily accessible, but in the case for Isuzu, you find that novels, you can't. You need to actually do OCR-ing and do the scans by hand, which takes a lot of time. So if we can find something that would work, that would be much quicker, we'd be grateful for it, so that at least we can get it to be at the level where we have enough data to train models and train tools with it.

• 27:54Speaker 03

  Yeah, what I would add is that language preservation is very important. Let's find ways in which we can preserve our languages in the sense that they do not go extinct. For instance, what we're doing now in South Africa is that because most of our languages have dialects and dialects, because they're not standard languages, they're not documented. So one of the projects that people can do if they're in similar situations is where you collect speech data of those dialects so that they can be accessible somewhere. So if in the next 10 years a dialect is not spoken, there is data available for people to hear that, okay, there was actually once a language like this spoken in a certain area. And yeah, I think more than anything, it's just preserving the language, creating more data.

• 28:35Speaker 03

  Because now for this Masakana project, we're able to access our data via our online newspapers. So if people can also digitize the work that they have, because it is true that it's so difficult to find material because it's not being not digitized, published, yes. Some books are out of publication now, so for that to not happen, we must digitize our literature, our text and everything else so that it can be easily accessible, so that we can actually run such projects.

• 29:03Daniel Whitenack?

  Great. Well, I really appreciate all of you getting to have a chance to join us here. I know it's a busy conference and there's a lot of great things to look at, but I'm so happy that we get to bring this conversation to a wider audience. And maybe, you know, if anyone wants to leave with a greeting in their language, please go ahead.

• 29:24Speaker 00

  So before finishing, I would do a little bit of like promotion.

• 29:29Daniel Whitenack?

  Yeah, please do.

• 29:30Speaker 00

  Regarding the language discoverability and other type of things, Chris and I have been working on LANFrica, which is an innovation, an idea of like putting out those like language resources for those African language resources that are not discoverable on the internet. So you can access like research papers, you can access data set, you can access tools like keyboard or those type of things and anything like dictionaries, anything, even sometime like YouTube videos. So people are doing great things like educating people, for instance, in Afra or those type of languages, languages I've never heard about before, and they are doing great effort, but then it's like on YouTube

• 30:12Speaker 00

  and like nobody knows. So on LANFrica, they can easily kind of access those resources. And if you also have a work like on mainly on African languages, but if it's on low resource languages, we have for instance LANFrica talk where people from all around the world, we got like people from like CMU, we got people from Google Research, we got people from like UCL, people from around the world, students, researchers, anybody who has been working, who's been working passionately about like low resource languages, NLP technologies, then to like come to and like give a talk for like people to know more about what they've been doing.

• 30:53Speaker 00

  So it's pretty simple. You just go on like www.lanfrica.com and then like you can find all the information about languages and also how to assess the, or like how to book for a meeting for the LANFrica talk. So. That being said, like something basic in my language would be Ena Chenwe Kaka Daniel. That means, "Thank you so much, Daniel, for..." Oh, well, "Ena Chenwe Kaka Daniel." Well, I don't know about the foreign for this invitation, you know, and that's something like I can relate to just. I thought that I knew the language, but then it feels like, okay, I actually don't know anything.

• 31:37Speaker 00

  And I don't know, there've been that interesting curve. It's called a curve of like David something, where technically showed there, okay, when you think that you know something, you have high confidence, and that's actually when you actually don't know anything. But then when you start learning and then you are adopting more of yourself, it's technically like that process of acknowledging and like learning more things and then like the curve like goes up at some point again. So, yeah, I'll just stick to Ena Chenwe Kaka Daniel and I'll let Just and Andy and Ro finish in the languages.

• 32:11Speaker 04

  Thank you so much. I'd also just like to maybe just promote also the organization we're coming from, the South African Centre for Digital Language Resources. Any researchers that are working in any of the South African languages, they can check us out at sadealad.org.za. A parting word that I can say in my language is Ngulubwanga kulu, ngungipe inle, which means, "Thank you so much for listening to me."

• 32:34Speaker 03

  Nah, I don't know what I'm gonna say, but I'm gonna keep it very short. Ngosika kulu, which means, "Thank you very much."

• 32:41Speaker 05

  Um, yeah, before finishing, I must express that I'm actually a bit jealous of the Masakana community.

• 32:50Speaker 04

  Free of charge.

• 32:51Speaker 05

  Okay, no, okay, that's, that's good to know. Thank you very much for that invitation. Yeah, also, I wanted to add that maybe if there's other people listening who are into Creole languages, yeah, maybe give me a shout out. My name is Just Zweneke, [email protected]. So, yeah, I'm happy to join you guys, but I'm not sure if it fits in as being an African language, but...

• 33:16Speaker 00

  As we say, there's Daniel, for instance. There's Sebastian, there is Graham. You know, people actually who are not necessarily on from the continent or speaking those languages, but who just share the same vision. So like, well, many people, I'm sure that many people would be interested like in like, maybe like writing research papers or building language models or those type of things for Sana Tonga. So, I mean, as they say, alone you can do better or something like that, but like together with a bigger community, you can go definitely faster and like, you know. And like, that's how technical ideas come, you know.

• 33:58Speaker 00

  So, um, I'm definitely gonna share the link with you. I have your link in to join the Slack and...

• 34:04Daniel Whitenack?

  And we'll put it in our show notes as well, all the links to everything we've talked about, yeah.

• 34:09Speaker 00

  Okay, okay. So I'm definitely gonna share with you and you are free to just comment. I just wanna warn you, it's a big place. People find it messy. We usually work in this chaotic environment, but then...

• 34:21Daniel Whitenack?

  You mean, community is messy?

• 34:24Speaker 00

  Well, I won't say. I mean, it's just like...

• 34:26Daniel Whitenack?

  That means it's a real community. Yeah, yeah, yeah.

• 34:29Speaker 00

  So things are not like, don't wait for people to be like, okay, this, this, this, you know. Take ownership, take initiative, like on whatever you want to work on. And then like people will just like easily follow you. And yeah, I'm pretty sure it's gonna be beneficial. I may, I would like with pleasure, for instance, to share on the project with you. I speak what, French, a little bit of German, Russian, English, foreign a little bit. So it wouldn't hurt me to learn a sixth or fifth language, at least, you know. I learned a lot like working with people about, I mean, for working with Igbo people or those type of things. So let us not the African pass care you. Just join. It's a valuable resource in general.

• 35:14Speaker 05

  And I know there's even, for instance, in Nigeria, they have spoken Nigerian pidgin. Which I had some ideas of doing some pre-training, transfer learning from that land because I think there's some similarities going on there. So that already brings the connection to Masekana closer, I guess. So I would like to finish with just one word, "grantangi", which means "thank you" in San Tomo.

• 35:38Daniel Whitenack?

  Well, thank you all. This has been so much fun. Appreciate it. And we'll share links in our show notes for everything that we've talked about and all the great things that you've shared. So thank you all.

• 35:47Speaker 04

  Thank you.

• 35:48Speaker 05

  Thank you.

• 35:58Speaker 01

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