HausaMT v1.0: Towards English-Hausa Neural Machine Translation

• URL: http://arxiv.org/abs/2006.05014v2
• Date: Sun, 14 Jun 2020 04:35:37 GMT
• Title: HausaMT v1.0: Towards English-Hausa Neural Machine Translation
• Authors: Adewale Akinfaderin
• Abstract summary: We build a baseline model for English-Hausa machine translation. The Hausa language is the second largest Afro-Asiatic language in the world after Arabic.
• Score: 0.012691047660244334
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Neural Machine Translation (NMT) for low-resource languages suffers from low performance because of the lack of large amounts of parallel data and language diversity. To contribute to ameliorating this problem, we built a baseline model for English-Hausa machine translation, which is considered a task for low-resource language. The Hausa language is the second largest Afro-Asiatic language in the world after Arabic and it is the third largest language for trading across a larger swath of West Africa countries, after English and French. In this paper, we curated different datasets containing Hausa-English parallel corpus for our translation. We trained baseline models and evaluated the performance of our models using the Recurrent and Transformer encoder-decoder architecture with two tokenization approaches: standard word-level tokenization and Byte Pair Encoding (BPE) subword tokenization.

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