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Towards neural machine translation for African languages

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dc.contributor.author Abbott, JZ
dc.contributor.author Martinus, Laura JB
dc.date.accessioned 2019-02-24T10:24:42Z
dc.date.available 2019-02-24T10:24:42Z
dc.date.issued 2018-12
dc.identifier.citation Abbott, J.Z. and Martinus, L.J.B. 2018. Towards neural machine translation for African languages. NIPS 2018 Workshop on Machine Learning for the Developing World, December 2018, Montreal, Canada en_US
dc.identifier.uri https://arxiv.org/html/1812.10398
dc.identifier.uri http://hdl.handle.net/10204/10726
dc.description Paper presented at the NIPS 2018 Workshop on Machine Learning for the Developing World, December 2018, Montreal, Canada en_US
dc.description.abstract Given that South African education is in crisis, strategies for improvement and sustainability of high-quality, up-to-date education must be explored. In the migration of education online, inclusion of machine translation for low-resourced local languages becomes necessary. This paper aims to spur the use of current neural machine translation (NMT) techniques for low-resourced local languages. The paper demonstrates state-of-the-art performance on English-to-Setswana translation using the Autshumato dataset. The use of the Transformer architecture beat previous techniques by 5.33 BLEU points. This demonstrates the promise of using current NMT techniques for African languages. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;21984
dc.subject Neural machine translation en_US
dc.subject NMT en_US
dc.subject Transformer architecture en_US
dc.title Towards neural machine translation for African languages en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Abbott, J., & Martinus, L. J. (2018). Towards neural machine translation for African languages. http://hdl.handle.net/10204/10726 en_ZA
dc.identifier.chicagocitation Abbott, JZ, and Laura JB Martinus. "Towards neural machine translation for African languages." (2018): http://hdl.handle.net/10204/10726 en_ZA
dc.identifier.vancouvercitation Abbott J, Martinus LJ, Towards neural machine translation for African languages; 2018. http://hdl.handle.net/10204/10726 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Abbott, JZ AU - Martinus, Laura JB AB - Given that South African education is in crisis, strategies for improvement and sustainability of high-quality, up-to-date education must be explored. In the migration of education online, inclusion of machine translation for low-resourced local languages becomes necessary. This paper aims to spur the use of current neural machine translation (NMT) techniques for low-resourced local languages. The paper demonstrates state-of-the-art performance on English-to-Setswana translation using the Autshumato dataset. The use of the Transformer architecture beat previous techniques by 5.33 BLEU points. This demonstrates the promise of using current NMT techniques for African languages. DA - 2018-12 DB - ResearchSpace DP - CSIR KW - Neural machine translation KW - NMT KW - Transformer architecture LK - https://researchspace.csir.co.za PY - 2018 T1 - Towards neural machine translation for African languages TI - Towards neural machine translation for African languages UR - http://hdl.handle.net/10204/10726 ER - en_ZA


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