计算机工程 ›› 2017, Vol. 43 ›› Issue (12): 179-183.doi: 10.3969/j.issn.1000-3428.2017.12.033

• 人工智能及识别技术 • 上一篇    下一篇

融合主题的汉越冶金领域统计机器翻译方法

周珂,余正涛,高盛祥   

  1. (昆明理工大学 信息工程与自动化学院,昆明 650500)
  • 收稿日期:2016-11-14 出版日期:2017-12-15 发布日期:2017-12-15
  • 作者简介:周珂(1991—),男,硕士研究生,主研方向为机器翻译;余正涛,教授、博士生导师;高盛祥(通信作者),博士。
  • 基金项目:
    国家自然科学基金(61672271,61761026,61732005);昆明理工大学校人才培养项目(省级)(KKSY201703005)。

Statistical Machine Translation Method Integrating Topic for Chinese-Vietnamese Metallurgy Field

ZHOU Ke,YU Zhengtao,GAO Shengxiang   

  1. (School of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)
  • Received:2016-11-14 Online:2017-12-15 Published:2017-12-15

摘要: 为有效利用领域知识提高汉越冶金领域的机器翻译效果,利用术语与主题的分布关系约束术语的选择,提出融合主题的统计机器翻译方法。建立术语翻译模型,抽取短语概率表时将术语对源语言文档的主题信息融入到翻译概率表中,利用主题分布描述术语与主题之间的关系,同时使用冶金领域语料训练翻译模型,将2个模型融合到基于短语的汉越翻译系统解码过程中,指导选择出最符合领域特性的术语及译文。融合模型前后的对比实验结果表明,与基于短语的机器翻译方法相比,该方法可有效提高汉越冶金领域的翻译性能。

关键词: 冶金领域, 统计机器翻译, 主题模型, 术语, 联合翻译模型

Abstract: In order to effectively use domain knowledge to improve the effect of Chinese-Vietnamese metallurgy field translation,this paper proposes a method of statistical machine translation,which uses the terms and topics’ distribution relation to constrain the choice of terms.It constructs term translation model in the process of phrase probability table extraction,the topic information of the source language document for the term pair is incorporated into the translation probability table,and the relationship between the term and the topic is described by topic distribution.Based on the translation model of metallurgy field corpus training,the two models are integrated into the decoding process of Chinese-Vietnamese phrase-based translation system to guide the selection of terms and translations that best match the domain characteristics.The contrastive experiments are carried out before and after the fusion model.The results show that,compared with the phrase-based machine translation method,the proposed method can increase translation performance in the Chinese-Vietnamese metallurgy field effectively.

Key words: metallurgy field, statistical machine translation, topic model, term, united translation model

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