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    <abstract>Numerous machine translation systems have been proposed since the appearance of this task. Nowadays, new large language model-based algorithms show results that sometimes overcome human ones on the rich-resource languages. Nevertheless, it is still not the case for the low-resource languages, for which all these algorithms did not show equally impressive results. In this work, we want to compare 3 generations of machine translation models on 7 low-resource languages and make a step further by proposing a new way of automatic parallel data augmentation using the state-of-the-art generative model.</abstract>
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%0 Conference Proceedings
%T The Only Chance to Understand: Machine Translation of the Severely Endangered Low-resource Languages of Eurasia
%A Mosolova, Anna
%A Smaili, Kamel
%S Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F mosolova-smaili-2022-chance
%X Numerous machine translation systems have been proposed since the appearance of this task. Nowadays, new large language model-based algorithms show results that sometimes overcome human ones on the rich-resource languages. Nevertheless, it is still not the case for the low-resource languages, for which all these algorithms did not show equally impressive results. In this work, we want to compare 3 generations of machine translation models on 7 low-resource languages and make a step further by proposing a new way of automatic parallel data augmentation using the state-of-the-art generative model.
%U https://aclanthology.org/2022.loresmt-1.4
%P 23-34

Markdown (Informal)

[The Only Chance to Understand: Machine Translation of the Severely Endangered Low-resource Languages of Eurasia](https://aclanthology.org/2022.loresmt-1.4) (Mosolova & Smaili, LoResMT 2022)

• The Only Chance to Understand: Machine Translation of the Severely Endangered Low-resource Languages of Eurasia (Mosolova & Smaili, LoResMT 2022)

ACL

• Anna Mosolova and Kamel Smaili. 2022. The Only Chance to Understand: Machine Translation of the Severely Endangered Low-resource Languages of Eurasia. In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022), pages 23–34, Gyeongju, Republic of Korea. Association for Computational Linguistics.