基于人机交互和特征提取的英汉翻译系统研究

为了提高英汉翻译系统的翻译精度,提出一种基于人机交互和特征提取的英汉翻译系统模型。首先,为了实现翻译特征语境特征的提取,通过特征提取算法提取语义翻译语境矩阵和非语义翻译语境矩阵;其次,为度量同一翻译环境下的两个语义向量之间的相似度,选择余弦相似度函数计算翻译相似度。将翻译相似度引入英汉翻译系统模型,通过比较两个语义向量之间的翻译相似度实现英汉之间的翻译。与SOA、SCA和SLA对比可知,基于人机交互和特征提取的英汉翻译具有更高的准确率、精确率和召回率,为英语翻译提供新的方法和途径。

Study on English-Chinese Translation System Based on Human-Computer Interaction and Feature Extraction

In order to improve the translation accuracy of English-Chinese translation system, combining feature extraction and human-computer interaction, an English-Chinese translation system model based on human-computer interaction and feature extraction is proposed. Firstly, in order to extract the context features of translation features, the semantic translation context matrix and non-semantic translation context matrix are extracted by feature extraction algorithm. Secondly, in order to measure the similarity between two semantic vectors in the same translation environment, the cosine similarity function is chosen to calculate the translation similarity. The translation similarity is introduced into the English and Chinese translation system model, and the translation similarity between the two semantic vectors is compared. Compared with SOA, SCA, and SLA, English-Chinese translation based on human-computer interaction and feature extraction has higher accuracy and recall rates, hence, it provides new methods and approaches for English translation.