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Separating Grains from the Chaff: Using Data Filtering to Improve Multilingual Translation for Low-Resourced African Languages., , , , , , , , , and 1 other author(s). CoRR, (2022)E KÚ MASK: Integrating Yorùbá cultural greetings into machine translation., , , , and . CoRR, (2023)BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpus., , , , , , , , , and 10 other author(s). INTERSPEECH, page 2383-2387. ISCA, (2022)Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages., , , , , , , , , and . SemEval@ACL, page 1311-1316. Association for Computational Linguistics, (2023)On the N-gram Approximation of Pre-trained Language Models., , and . CoRR, (2023)Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages., , , and . CoRR, (2022)MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition., , , , , , , , , and 35 other author(s). EMNLP, page 4488-4508. Association for Computational Linguistics, (2022)Cross-lingual Open-Retrieval Question Answering for African Languages., , , , , , , , , and 34 other author(s). EMNLP (Findings), page 14957-14972. Association for Computational Linguistics, (2023)Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi., , , and . CoRR, (2019)UdS-DFKI@WMT20: Unsupervised MT and Very Low Resource Supervised MT for German-Upper Sorbian., , , , and . WMT@EMNLP, page 1092-1098. Association for Computational Linguistics, (2020)