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Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution)

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dc.contributor.author Sharma, Yashvardhan
dc.date.accessioned 2024-11-14T10:56:28Z
dc.date.available 2024-11-14T10:56:28Z
dc.date.issued 2021
dc.identifier.uri https://biblio.ugent.be/publication/8709864/file/8719511.pdf
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16384
dc.description.abstract This paper describes the team ("Tamalli")’s submission to AmericasNLP2021 shared task on Open Machine Translation for low resource South American languages. Our goal was to evaluate different Machine Translation (MT) techniques, statistical and neural-based, under several configuration settings. We obtained the second-best results for the language pairs “Spanish-Bribri", “Spanish-Asháninka", and “Spanish-Rarámuri" in the category “Development set not used for training". Our performed experiments will serve as a point of reference for researchers working on MT with low-resource languages. en_US
dc.language.iso en en_US
dc.publisher Association for Computational Linguistics (ACL) en_US
dc.subject Computer Science en_US
dc.subject Machine Translation (MT) en_US
dc.subject Neural Machine Translation (NMT) en_US
dc.title Open machine translation for low resource South American languages (AmericasNLP 2021 shared task contribution) en_US
dc.type Article en_US


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