It is the field of machine learning deployed in voice-to-text platforms like Otter, and voice assistants like Google Assistant, Siri and Alexa.
However, natural language processing is as immediately practical as modern complex technologies can be. Ogueji and Ahia’s six-page paper might give you a mild headache. Practically though, what’s this useful for?īeing an intersection of computer science, mathematics and statistics, lots of AI jargon is dizzying. Thanks to frameworks like Word2vec and Google’s transformer, their ambition had a solid foundation to build on. Quality research data is scarce or too raw where available. It didn’t help that AI development is at an embryonic stage in Nigeria. But this project was the first Natural Language Processing (NLP) project ever to be done on pidgin English by anyone. He has been interested in working on languages since encountering Google Translate on his first android device in 2014. Essentially, they created a pidgin-English catalogue of word pairs from scratch, scraping 56,695 pidgin sentences and 32,925 unique words from a couple of websites. It would lead them to train an Unsupervised Neural Machine Translation (UNMT) model. Orevaoghene Ahia and Kelechi Ogueji worked on their translation model for three months Comment ça va : How are you, etc.īut with little pidgin English used online in writing – there’s no Wikipedia Pidgin – finding data for a decent translation project proved to be the first major hindrance. To build an English-French translator, for example, you need a corpus – tons of sentence pairs for both languages.
A shame given the objective and symbolic importance of this work in showing Africans’ competence to identify and solve local problems. The project is published and was accepted – after peer review – at this year’s NeurIPS conference, the world’s largest gathering of artificial intelligence researchers and enthusiasts, which held last week.ĭubious visa standards by the Canadian embassy denied them the honour of being in Vancouver to hold the world’s attention. “It’s insane that most technologies we build these days are for very high-resource language speakers,” Ahia tells me.įrom June to August this year, Ogueji and Ahia – colleagues at the Nigerian office of InstaDeep, an AI research and solutions firm – successfully developed a model for the translation. So when Kelechi Ogueji, 23, suggested a pidgin-to-English machine translation project, acceptance was easy.
Though Ahia’s pidgin isn’t as intense as her mum’s waffi dialect, she regards it an indispensable feature of her formative years. Her mum, an Isoko woman bred in Nigeria’s Niger Delta area, is fluent in three languages but favours pidgin English for conversations with family, friends and customers. Twenty-one-year old Orevaoghene Ahia speaks good English and writes tons of code in python.
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