Integrating Pronunciation into Chinese-Vietnamese Statistical Machine Translation

• 来源期刊: 清华大学学报自然科学版（英文版）
• 年，卷（期）: 2018,（6）
• 页码范围: 715-723
• 页数: 9页
• 语种: 英文
• DOI: 10.26599/TST.2018.9010006

摘要

Statistical machine translation for low-resource language suffers from the lack of abundant training corpora.Several methods,such as the use of a pivot language,have been proposed as a bridge to translate from one language to another.However,errors will accumulate during the extensive translation pipelines.In this paper,we propose an approach to low-resource language translation by exploiting the pronunciation correlations between languages.We find that the pronunciation features can improve both Chinese-Vietnamese and Vietnamese-Chinese translation qualities.Experimental results show that our proposed model yields effective improvements,and the translation performance (bilingual evaluation understudy score) is improved by a maximum value of 1.03.