基于机器辅助的高校英语专有名词自动翻译研究

Based on the Auxiliary Machine Automatic College English Proper Nouns Translation Study

常规方法匹配输入名词和翻译名词关联语义时,译文组合关联程度达不到最优,造成名词翻译召回率和准确率较低。提出基于机器辅助的高校英语专有名词自动翻译方法。预处理英语专有名词文件,建立英语平行语料库,为机器辅助提供语料,分割用户输入名词和语料库检索名词语义,根据关联系数和编辑距离,匹配语义关联的输入名词和检索名词,建立语义匹配评价体系,选取最优匹配译文组合作为翻译译文。采用英语专有名词实体集设置对比实验,结果表明,该方法提高了翻译召回率和准确率,以及两项指标调和均值,专有名词翻译结果更加准确。

Conventional methods match nouns and noun translation relation semantics, input matching to reach the optimal combination of correlation degree, make the recall rate and the noun translation accuracy is low. Therefore, colleges and universities based on machine auxiliary English proper nouns automatic translation method. English proper noun files are preprocessed, English parallel corpus is established, corpus is provided for machine assistance, noun semantics are retrieved by segmenting user input nouns and corpus, semantic matching evaluation system is established according to correlation coefficient and editing distance, and optimal matching translation combination is selected as translation. Acquisition of English proper nouns entity set, set the contrast experiment, the results show that the design method to improve the recall rate and accuracy, and the two indicators harmonic mean,proper nouns translation results more accurate.