mlsanityData to 14 Oct 2026

Does Generative AI speak Nigerian-Pidgin?: Issues about Representativeness and Bias for Multilingualism in LLMs

arXiv 2404.19442 ↗First posted 30 Apr 2024cs.CLcited by 5

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Abstract (arXiv)

Nigeria is a multilingual country with 500+ languages. Naija is a Nigerian Pidgin spoken by approximately 120M speakers and it is a mixed language (e.g., English, Portuguese, Yoruba, Hausa and Igbo). Although it has mainly been a spoken language until recently, there are some online platforms (e.g., Wikipedia), publishing in written Naija as well. West African Pidgin English (WAPE) is also spoken in Nigeria and it is used by BBC to broadcast news on the internet to a wider audience not only in Nigeria but also in other West African countries (e.g., Cameroon and Ghana). Through statistical analyses and Machine Translation experiments, our paper shows that these two pidgin varieties do not represent each other (i.e., there are linguistic differences in word order and vocabulary) and Generative AI operates only based on WAPE. In other words, Naija is underrepresented in Generative AI, and it is hard to teach LLMs with few examples. In addition to the statistical analyses, we also provide historical information on both pidgins as well as insights from the interviews conducted with volunteer Wikipedia contributors in Naija.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 10 of its 42 references that are in the map. First posted on arXiv 30 Apr 2024.

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10 of 42 references.

References · 10

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  2. 2021MasakhaNER: Named Entity Recognition for African Languagescited by 155
  3. 2022A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translationcited by 98
  4. 2022NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysiscited by 64
  5. 2023A Survey of Code-switching: Linguistic and Social Perspectives for Language Technologiescited by 59
  6. 2021The Effect of Domain and Diacritics in Yor`ub'a-English Neural Machine Translationcited by 38
  7. 2022What a Creole Wants, What a Creole Needscited by 27
  8. 2022Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?cited by 24
  9. 2023Representativeness as a Forgotten Lesson for Multilingual and Code-switched Data Collection and Preparationcited by 16
  10. 2024Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgincited by 3

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Citing papers per year: 2025: 2; 2026: 3.

5 papers.