CASIA OpenIR  > 自然语言处理团队
Input Method for Human Translators: a Novel Approach to Integrate Machine Translation Effectively and Imperceptibly
Huang, Guoping; Zhang, Jiajun; Zhou, Yu; Zong, Chengqing
Source PublicationACM Transactions on Asian and Low-Resource Language Information Processing
2019
Volume18Issue:1Pages:Article No. 4
Abstract

Computer-aided translation (CAT) systems are the most popular tool for helping human translators efficiently perform language translation. To further improve the translation efficiency, there is an increasing interest in applying machine translation (MT) technology to upgrade CAT. To thoroughly integrate MT into CAT systems, in this article, we propose a novel approach: a new input method that makes full use of the knowledge adopted by MT systems, such as translation rules, decoding hypotheses, and n-best translation lists. The proposed input method contains two parts: a phrase generation model, allowing human translators to type target sentences quickly, and an n-gram prediction model, helping users choose perfect MT fragments smoothly. In addition, to tune the underlying MT system to generate the input method preferable results, we design a new evaluation metric for the MT system. The proposed input method integrates MT effectively and imperceptibly, and it is particularly suitable for many target languages with complex characters, such as Chinese and Japanese. The extensive experiments demonstrate that our method saves more than 23% in time and over 42% in keystrokes, and it also improves the translation quality by more than 5 absolute BLEU scores compared with the strong baseline, i.e., post-editing using Google Pinyin.

KeywordMachine Translation
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23189
Collection自然语言处理团队
Affiliation中国科学院自动化研究所
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Huang, Guoping,Zhang, Jiajun,Zhou, Yu,et al. Input Method for Human Translators: a Novel Approach to Integrate Machine Translation Effectively and Imperceptibly[J]. ACM Transactions on Asian and Low-Resource Language Information Processing,2019,18(1):Article No. 4.
APA Huang, Guoping,Zhang, Jiajun,Zhou, Yu,&Zong, Chengqing.(2019).Input Method for Human Translators: a Novel Approach to Integrate Machine Translation Effectively and Imperceptibly.ACM Transactions on Asian and Low-Resource Language Information Processing,18(1),Article No. 4.
MLA Huang, Guoping,et al."Input Method for Human Translators: a Novel Approach to Integrate Machine Translation Effectively and Imperceptibly".ACM Transactions on Asian and Low-Resource Language Information Processing 18.1(2019):Article No. 4.
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