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| 交互式机器翻译综述 | |
| 引用本文： | 廖兴滨,秦小林,张思齐,钱杨舸. 交互式机器翻译综述[J]. 计算机应用, 2023, 43(2): 329-334. DOI: 10.11772/j.issn.1001-9081.2021122067 |
| 作者姓名： | 廖兴滨 秦小林 张思齐 钱杨舸 |
| 作者单位： | 中国科学院 成都计算机应用研究所,成都 610213 中国科学院大学 计算机科学与技术学院,北京 101408 |
| 基金项目： | 四川省科技计划项目（2019ZDZX0006）; |
| 摘 要： | 随着深度学习的发展和成熟,神经机器翻译的质量也越来越高,然而仍不完美,为了达到可接受的翻译效果,需要人工进行后期编辑。交互式机器翻译（IMT）是这种串行工作的一个替代,即在翻译过程中进行人工互动,由用户对翻译系统产生的候选翻译进行验证,并且,如有必要,由用户提供新的输入,系统根据用户当前的反馈生成新的候选译文,如此往复,直到产生一个使用户满意的输出。首先,介绍了IMT的基本概念以及当前的研究进展;然后,分类对一些常用方法和前沿工作加以介绍,并简述每个工作的背景和创新之处;最后,探讨了IMT的发展趋势和研究难点。 |
| 关 键 词： | 机器翻译 交互式机器翻译 交互式统计机器翻译 交互式神经机器翻译 强化学习 自然语言处理 |
| 收稿时间： | 2021-12-09 |
| 修稿时间： | 2022-05-03 |
Review of interactive machine translation |
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| Xingbin LIAO,Xiaolin QIN,Siqi ZHANG,Yangge QIAN. Review of interactive machine translation[J]. Journal of Computer Applications, 2023, 43(2): 329-334. DOI: 10.11772/j.issn.1001-9081.2021122067 | |
| Authors: | Xingbin LIAO Xiaolin QIN Siqi ZHANG Yangge QIAN |
| Affiliation: | Chengdu Institute of Computer Applications,Chinese Academy of Sciences,Chengdu Sichuan 610213,China School of Computer Science and Technology,University of Chinese Academy of Sciences,Beijing 101408,China |
| Abstract: | With the development and maturity of deep learning, the quality of neural machine translation has increased, yet it is still not perfect and requires human post-editing to achieve acceptable translation results. Interactive Machine Translation （IMT） is an alternative to this serial work, that is performing human interaction during the translation process, where the user verifies the candidate translations produced by the translation system and, if necessary, provides new input, and the system generates new candidate translations based on the current feedback of users, this process repeats until a satisfactory output is produced. Firstly, the basic concept and the current research progresses of IMT were introduced. Then, some common methods and state-of-the-art works were suggested in classification, while the background and innovation of each work were briefly described. Finally, the development trends and research difficulties of IMT were discussed. |
| Keywords: | machine translation Interactive Machine Translation (IMT) Interactive Statistical Machine Translation (ISMT) Interactive Neural Machine Translation (INMT) Reinforcement Learning (RL) Natural Language Processing (NLP) |
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