Northwest Center for Public Health PracticeDepartment of Health ServicesUniversity of WashingtonSeattle, WAUnited States.
Northwest Center for Public Health PracticeHuman Centered Design & EngineeringUniversity of WashingtonSeattle, WAUnited States.
JMIR Public Health Surveill. 2015 Nov 17;1(2):e17. doi: 10.2196/publichealth.4779. eCollection 2015 Jul-Dec.
Chinese is the second most common language spoken by limited English proficiency individuals in the United States, yet there are few public health materials available in Chinese. Previous studies have indicated that use of machine translation plus postediting by bilingual translators generated quality translations in a lower time and at a lower cost than human translations.
The purpose of this study was to investigate the feasibility of using machine translation (MT) tools (eg, Google Translate) followed by human postediting (PE) to produce quality Chinese translations of public health materials.
From state and national public health websites, we collected 60 health promotion documents that had been translated from English to Chinese through human translation. The English version of the documents were then translated to Chinese using Google Translate. The MTs were analyzed for translation errors. A subset of the MT documents was postedited by native Chinese speakers with health backgrounds. Postediting time was measured. Postedited versions were then blindly compared against human translations by bilingual native Chinese quality raters.
The most common machine translation errors were errors of word sense (40%) and word order (22%). Posteditors corrected the MTs at a rate of approximately 41 characters per minute. Raters, blinded to the source of translation, consistently selected the human translation over the MT+PE. Initial investigation to determine the reasons for the lower quality of MT+PE indicate that poor MT quality, lack of posteditor expertise, and insufficient posteditor instructions can be barriers to producing quality Chinese translations.
Our results revealed problems with using MT tools plus human postediting for translating public health materials from English to Chinese. Additional work is needed to improve MT and to carefully design postediting processes before the MT+PE approach can be used routinely in public health practice for a variety of language pairs.
中文是美国英语水平有限的人群中第二常用的语言，但可用的中文公共卫生材料却很少。先前的研究表明，使用机器翻译（MT）加双语译员的后期编辑生成的译文质量与人工翻译相当，但时间和成本更低。
本研究旨在探讨使用机器翻译（MT）工具（如谷歌翻译）加人工后期编辑（PE）制作高质量中文公共卫生材料译文的可行性。
我们从州和国家公共卫生网站收集了 60 份已通过人工翻译从英文翻译成中文的健康促进文件。然后，使用谷歌翻译将这些文件的英文版本翻译成中文。分析机器翻译的翻译错误。选择部分 MT 文档由具有卫生背景的母语为中文的人员进行后期编辑。测量后期编辑时间。然后由双语母语中文质量评估员对后期编辑版本进行盲评，与人工翻译进行比较。
最常见的机器翻译错误是词义错误（40%）和词序错误（22%）。后期编辑人员以大约每分钟 41 个字符的速度纠正机器翻译。评估员在不知道翻译来源的情况下，始终选择人工翻译而不是 MT+PE。初步调查确定 MT+PE 质量较低的原因表明，MT 质量差、后期编辑人员缺乏专业知识以及后期编辑指令不足可能是制作高质量中文译文的障碍。
我们的研究结果显示，使用 MT 工具加人工后期编辑将公共卫生材料从英文翻译成中文存在问题。在 MT+PE 方法可在各种语言对的公共卫生实践中常规使用之前，需要进一步改进 MT，并精心设计后期编辑流程。
