PidginUNMT: Unsupervised Neural Machine Translation from West African Pidgin to English
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Abstract (arXiv)
Over 800 languages are spoken across West Africa. Despite the obvious diversity among people who speak these languages, one language significantly unifies them all - West African Pidgin English. There are at least 80 million speakers of West African Pidgin English. However, there is no known natural language processing (NLP) work on this language. In this work, we perform the first NLP work on the most popular variant of the language, providing three major contributions. First, the provision of a Pidgin corpus of over 56000 sentences, which is the largest we know of. Secondly, the training of the first ever cross-lingual embedding between Pidgin and English. This aligned embedding will be helpful in the performance of various downstream tasks between English and Pidgin. Thirdly, the training of an Unsupervised Neural Machine Translation model between Pidgin and English which achieves BLEU scores of 7.93 from Pidgin to English, and 5.18 from English to Pidgin. In all, this work greatly reduces the barrier of entry for future NLP works on West African Pidgin English.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Dec 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 3; 2024: 4; 2025: 2.
11 papers.
- 2022What a Creole Wants, What a Creole Needscited by 27
- 2021On Language Models for Creolescited by 17
- 2024Cheetah: Natural Language Generation for 517 African Languagescited by 15
- 2024Krey`ol-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languagescited by 10
- 2023CreoleVal: Multilingual Multitask Benchmarks for Creolescited by 9
- 2025Where Are We? Evaluating LLM Performance on African Languagescited by 9
- 2023How Good are Commercial Large Language Models on African Languages?cited by 8
- 2023Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgincited by 5
- 2024A Systematic Review of NLP for Ghanaian Languages: Datasets, Models, and a Research Roadmapcited by 5
- 2024Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgincited by 3
- 2025Limited-Resource Adapters Are Regularizers, Not Linguistscited by 0
- 2025Limited-Resource Adapters Are Regularizers, Not Linguists30 May 2025
- 2025Where Are We? Evaluating LLM Performance on African Languages26 Feb 2025
- 2024A Systematic Review of NLP for Ghanaian Languages: Datasets, Models, and a Research Roadmap10 May 2024
- 2024Krey`ol-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages8 May 2024
- 2024Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin28 Apr 2024
- 2024Cheetah: Natural Language Generation for 517 African Languages2 Jan 2024
- 2023CreoleVal: Multilingual Multitask Benchmarks for Creoles30 Oct 2023
- 2023Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin1 Jul 2023
- 2023How Good are Commercial Large Language Models on African Languages?11 May 2023
- 2022What a Creole Wants, What a Creole Needs1 Jun 2022
- 2021On Language Models for Creoles13 Sep 2021