摘要
在融合翻译记忆和统计机器翻译的整合式模型的基础上,该文提出在解码过程中进一步地动态加入翻译记忆中新发现的短语对。它在机器翻译解码过程中,动态地加入翻译记忆片段作为候选,并利用翻译记忆的相关信息,指导基于短语的翻译模型进行解码。实验结果表明该方法显著提高了翻译质量:与翻译记忆系统相比,该方法提高了21.15个BLEU值,降低了21.47个TER值;与基于短语的翻译系统相比,该方法提高了5.16个BLEU值,降低了4.05个TER值。
Under a framework of combining translation memory （TM） and statistical machine translation （SMT）, this paper proposes to further dynamically add new phrase-pairs found in TM. During decoding, the integrated mod- el adds those TM matched segments into the SMT phrase table as candidates dynamically, and incorporates corresponding TM information for each hypothesis to guide SMT decoding. Our exPerimental results show that the proposed approach improves translation quality significantly： compared with TM system, the integrated model achieves 21.15 BLEU points improvements and 21.47 TER points reduction; compared with SMT system, the integrated model achieves 5.16 BLEU points improvements and 4.05 TER points reduction.
出处
《中文信息学报》
CSCD
北大核心
2015年第2期87-94,102,共9页
Journal of Chinese Information Processing
基金
国家自然科学基金(61402478)
关键词
统计机器翻译
基于短语的翻译模型
翻译记忆
模型融合
动态加入翻译记忆短语对
statistical machine translation
phrase-based machine translation, translation memory
model integration
dynamically adding phrase-pairs
