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    <abstract>Translating into low-resource languages is challenging due to the scarcity of training data. In this paper, we propose a probabilistic lexical translation method that bridges through lexical relations including synonyms, hypernyms, hyponyms, and co-hyponyms. This method, which only requires a dictionary like Wiktionary and a lexical database like WordNet, enables the translation of unknown vocabulary into low-resource languages for which we may only know the translation of a related concept. Experiments on translating a core vocabulary set into 472 languages, most of them low-resource, show the effectiveness of our approach.</abstract>
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%0 Conference Proceedings
%T Known Words Will Do: Unknown Concept Translation via Lexical Relations
%A Wu, Winston
%A Yarowsky, David
%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 wu-yarowsky-2022-known
%X Translating into low-resource languages is challenging due to the scarcity of training data. In this paper, we propose a probabilistic lexical translation method that bridges through lexical relations including synonyms, hypernyms, hyponyms, and co-hyponyms. This method, which only requires a dictionary like Wiktionary and a lexical database like WordNet, enables the translation of unknown vocabulary into low-resource languages for which we may only know the translation of a related concept. Experiments on translating a core vocabulary set into 472 languages, most of them low-resource, show the effectiveness of our approach.
%U https://aclanthology.org/2022.loresmt-1.3
%P 15-22

Markdown (Informal)

[Known Words Will Do: Unknown Concept Translation via Lexical Relations](https://aclanthology.org/2022.loresmt-1.3) (Wu & Yarowsky, LoResMT 2022)

• Known Words Will Do: Unknown Concept Translation via Lexical Relations (Wu & Yarowsky, LoResMT 2022)

ACL

• Winston Wu and David Yarowsky. 2022. Known Words Will Do: Unknown Concept Translation via Lexical Relations. In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022), pages 15–22, Gyeongju, Republic of Korea. Association for Computational Linguistics.