As one of the most important Chinese cultural classics, the study of English translation of The Analects of Confucius is also a hot research topic in the field. Based on statistical machine translation, which is a mainstream method in machine translation, this paper combines two methods of obtaining word vector space representations and word embedding representations, namely, Point Mutual Information (PMI) and Word2vec, to construct a translation model based on word semantic distributions, which provides technical support for the English translation of The Analects of Confucius. The English translation model of this paper is used to integrate and analyze the philosophical connotation of the word “Body” in the Analects, and to explore the acceptability of the English translation results to the readers. The main philosophical connotation of the word “body” in the Analects is to be self-oriented and Tao-oriented. The former is to start all moral practice from self-reflection and cultivation, while the latter is to the individual’s “body” beyond the ego and finally integrate into the Confucian order with “benevolence” and “propriety” as the core. The mean syntactic acceptability of Chinese and foreign readers is 3.25 and 3.12 respectively, and the mean main idea acceptability is 3.32 and 3.15 respectively, all of which are in the range of 2.5~3.5, presenting a basically acceptable attitude.
