2021/04/12 by Felermino D. M. A. Ali, Ali, Felermino D. M. A., Andrew Caines +3
Arts and Humanities · Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Language, Discourse, Communication Strategies #Natural Language Processing Techniques #Speech and dialogue systems
paper · pdf · doi:10.48550/arxiv.2104.05753
openalex publication_date 2021/04/12 · openalex created_date 2021/04/26 · openalex updated_date 2026/07/28
Major advancement in the performance of machine translation models has been made possible in part thanks to the availability of large-scale parallel corpora. But for most languages in the world, the existence of such corpora is rare. Emakhuwa, a language spoken in Mozambique, is like most African languages low-resource in NLP terms. It lacks both computational and linguistic resources and, to the best of our knowledge, few parallel corpora including Emakhuwa already exist. In this paper we describe the creation of the Emakhuwa-Portuguese parallel corpus, which is a collection of texts from the Jehovah's Witness website and a variety of other sources including the African Story Book website, the Universal Declaration of Human Rights and Mozambican legal documents. The dataset contains 47,415 sentence pairs, amounting to 699,976 word tokens of Emakhuwa and 877,595 word tokens in Portuguese. After normalization processes which remain to be completed, the corpus will be made freely available for research use.