微型电脑应用

英语翻译过程中,语义越相似,则相关度越大,容易造成不同语境下的理解错误,给翻译工作带来困难。基于此,从英汉句子双语料入手,建立基于语义词典和语料库相结合的相似度计算模型。在建立的语料库条件下,确定相关语义提取规则和依存关系,通过英语句子相似度算法,采用向量空间模型标准,将计算的相似度作为向量元素,寻找到语句的差异化程度,区别语句和单词词性、句法、时态多方面内容。研究结果表明:系统在语句翻译过程中具备较高的准确度和召唤率,尤其是在介词、虚词、时态方面的英译过程中,具有更高的翻译效率和准确度。

In the process of English translation, the more similar the semantics is, the greater the correlation. It can easily cause understanding errors in different contexts, and bring difficulties to the translation work. Based on this, this paper establishes a similarity calculation model based on the combination of semantic dictionary and corpus. Under the condition of the established corpus, the relevant semantic extraction rules and dependencies are determined. Through the English sentence similarity algorithm, using the vector space model standard, the calculated similarity is used as the vector element to find the degree of differentiation of the sentence, distinguish the sentence from the word part of speech, syntax, tense, and many aspects of the content. The results show that the translation process has higher accuracy and call rate, especially in the translation of prepositions, function words, tenses, with higher translation efficiency and accuracy.