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China Terminology ›› 2022, Vol. 24 ›› Issue (1): 14-25.doi: 10.12339/j.issn.1673-8578.2022.01.002

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Bilingual Terminology Alignment Based on Chinese-English Monolingual Terminological Bank

XIANG Lu1,2(), ZHOU Yu1,2,3(), ZONG Chengqing1,2()   

  • Received:2021-07-30 Revised:2021-10-09 Online:2022-01-05 Published:2021-12-27

Abstract:

Bilingual terminologies are essential resources in natural language processing, which are of great significance for many multilingual applications such as cross-lingual information retrieval and machine translation. Bilingual terminology pairs are usually obtained by either human translation or automatic extraction from a bilingual parallel corpus. However, human translation requires professional knowledge and is time-consuming and labor-intensive. Besides, it is not easy to have a large bilingual parallel corpus in a specific domain. But the monolingual terminology banks of various languages in the same domain are relatively easy to obtain. Therefore, this paper proposes a novel method to extract bilingual terminology pairs by automatically aligning terms from monolingual terminology banks of two languages. Firstly, multiple online machine translation engines are adopted to generate the target pseudo terminology through a voting mechanism. Secondly, the target pseudo terminology is used to retrieve from the target terminology bank to obtain the candidate set of target terminologies. Finally, a mBERT-based semantic matching model is used to re-rank the candidate set and obtain the final bilingual terminology pair. Experimental results of Chinese-English bilingual terminology alignment on three domains, including computer science, civil engineering, and medicine, show that our proposed method can effectively improve the accuracy of bilingual terminology extraction.

Key words: bilingual terminology, monolingual terminological bank, terminology alignment, semantic matching

CLC Number: