Machine Translation of Electrical Terminology Constraints

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Information (Switzerland) Pub Date : 2023-09-20 DOI:10.3390/info14090517
Zepeng Wang, Yuan Chen, Juwei Zhang
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引用次数: 0

Abstract

In practical applications, the accuracy of domain terminology translation is an important criterion for the performance evaluation of domain machine translation models. Aiming at the problem of phrase mismatch and improper translation caused by word-by-word translation of English terminology phrases, this paper constructs a dictionary of terminology phrases in the field of electrical engineering and proposes three schemes to integrate the dictionary knowledge into the translation model. Scheme 1 replaces the terminology phrases of the source language. Scheme 2 uses the residual connection at the encoder end after the terminology phrase is replaced. Scheme 3 uses a segmentation method of combining character segmentation and terminology segmentation for the target language and uses an additional loss module in the training process. The results show that all three schemes are superior to the baseline model in two aspects: BLEU value and correct translation rate of terminology words. In the test set, the highest accuracy of terminology words was 48.3% higher than that of the baseline model. The BLEU value is up to 3.6 higher than the baseline model. The phenomenon is also analyzed and discussed in this paper.
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电气术语约束的机器翻译
在实际应用中,领域术语翻译的准确性是评估领域机器翻译模型性能的重要标准。针对英语术语短语逐字翻译造成的短语不匹配和翻译不当问题,构建了电气工程领域术语短语词典,并提出了三种将词典知识整合到翻译模型中的方案。方案1替换源语言的术语短语。方案2在替换术语短语后在编码器端使用剩余连接。方案3对目标语言采用字符分割和术语分割相结合的分割方法,并在训练过程中增加了损失模块。结果表明,三种方案在BLEU值和术语词的正确翻译率两个方面都优于基线模型。在测试集中,术语词的最高准确率比基线模型高48.3%。BLEU值比基线模型高3.6。本文还对这一现象进行了分析和探讨。
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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来源期刊
Information (Switzerland)
Information (Switzerland) Computer Science-Information Systems
CiteScore
6.90
自引率
0.00%
发文量
515
审稿时长
11 weeks
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