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AI时代神经网络翻译技术的飞速发展催生了一批视频译制平台。以“人人译视界”和“讯飞听见字幕”为研究对象，以动画作品《中华勤学故事》机翻字幕为研究素材，探究国内视频译制平台机翻字幕质量。基于FAR语际字幕评估模型提出了机翻字幕评估模型(FAR 2.0),从功能对等、接受程度、阅读体验三方面对机翻字幕的语义错误、术语翻译错误、译文冗余等问题进行了深入分析。根据研究结果，提出增强语音数据标注积累、加大机器翻译语料训练及强化翻译引擎的意群切分等三点优化建议。
Abstract：With the rapid development of neural machine translation technology in the AI era, a number of video translation platforms have emerged. In order to evaluate the quality of machine-generated subtitling, this paper takes “YSJ” and “Iflyrec” as the research objects, and the machine-generated subtitles of the cartoon “Chinese Stories of Study” as the material when doing the assessing. This study tries to propose a model for assessing machine-generated subtitle(FAR 2.0) based on the FAR model by Jan Pedersen, and analyses semantic error, term error, and redundancy phenomenon from three parameters: functional equivalence, acceptability and readability. This paper gives the following three suggestions for optimization: firstly, enhance the accumulation of speech data annotation; secondly, increase data training on the various corpus; thirdly, enhance the segmentation and combination ability of the translation engine.
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基本信息:
DOI：10.13744/j.cnki.cn21-1431/g4.2023.02.015
中图分类号:H085
引用信息:
[1]雷静,李明明.机翻字幕质量评估的模型构建研究——以“人人译视界”和“讯飞听见字幕”为例[J].大连民族大学学报,2023,25(02):176-182.DOI:10.13744/j.cnki.cn21-1431/g4.2023.02.015.
基金信息:
中央民族大学校级项目(2022QNYL14)
2023-03-15
2023-03-15