机器翻译中的共性?

IF 1.6 2区文学 0 LANGUAGE & LINGUISTICS

International Journal of Corpus Linguistics Pub Date : 2022-02-14 DOI:10.1075/ijcl.19127.luo

Jinru Luo, Dechao Li

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引用次数: 10

摘要

通过研究和比较中国最受欢迎的社交媒体平台（微信）的最新在线机器翻译应用微信翻译（WeChat Translate）制作的自建中英文翻译语料库中的语言模式，本研究探讨了简化和规范化（假设的翻译普遍性）在这些翻译中是否以及在多大程度上表现出来等问题。结果表明，虽然简化无法得到证实，但可以证实微信翻译中出现规范化的趋势。研究发现，这些结果是由机器翻译系统的运行机制引起的。某些显著的单词往往会使微信的机器翻译系统重复使用典型的语言模式，从而导致词块的过度使用。希望本研究能够为机器翻译系统的发展提供新的思路，并鼓励更多基于语料库的面向产品的机器翻译研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Universals in machine translation?

By examining and comparing the linguistic patterns in a self-built corpus of Chinese-English translations produced by WeChat Translate, the latest online machine translation app from the most popular social media platform (WeChat) in China, this study explores such questions as whether or not and to what extent simplification and normalization (hypothesized Translation Universals) exhibit themselves in these translations. The results show that, whereas simplification cannot be substantiated, the tendency of normalization to occur in the WeChat translations can be confirmed. The research finds that these results are caused by the operating mechanism of machine translation (MT) systems. Certain salient words tend to prime WeChat’s MT system to repetitively resort to typical language patterns, which leads to a significant overuse of lexical chunks. It is hoped that the present study can shed new light on the development of MT systems and encourage more corpus-based product-oriented research on MT.

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来源期刊

International Journal of Corpus Linguistics Multiple-

CiteScore

3.30

自引率

0.00%

发文量

期刊介绍： The International Journal of Corpus Linguistics (IJCL) publishes original research covering methodological, applied and theoretical work in any area of corpus linguistics. Through its focus on empirical language research, IJCL provides a forum for the presentation of new findings and innovative approaches in any area of linguistics (e.g. lexicology, grammar, discourse analysis, stylistics, sociolinguistics, morphology, contrastive linguistics), applied linguistics (e.g. language teaching, forensic linguistics), and translation studies. Based on its interest in corpus methodology, IJCL also invites contributions on the interface between corpus and computational linguistics.