Binary Semantic Pattern Rules for Chinese-English Machine Translation Based on Machine Learning Algorithms

Abstract

With the increase of internationalization and the exponential growth of intercultural communication, the importance of interlingual translation has become increasingly prominent. Machine translation has been a booming area of research as technology has advanced. Due to the complexity of language ability and limited understanding of language laws, there are challenges for machine translation. This paper focused on how to construct and apply binary semantic pattern rules through machine learning to improve the translation effect in Chinese-English machine translation. The research results of this paper would contribute to the further development and improvement of Chinese-English machine translation technology. In order to produce high-quality translation results, research in machine translation has recognized the need to analyze and understand the semantics of natural language. To address the important issue of lexical and syntactic ambiguity, representations of binary semantic pattern rules have been developed to formally describe these rules. Based on this, this paper designed and implemented a corpus-based binary semantic rule extraction and optimization algorithm, which used machine learning algorithms to automatically detect the semantic rules of two or more than two phrases in the Chinese corpus, and then automatically optimized and converted them according to the statistical results, and realized the design of Chinese-English machine translation system. The article evaluated the quality of machine translation to test the effectiveness of machine translation binary semantic pattern rules based on machine learning algorithms. The study found that compared with the rule set A, the rule sets B and C obtained automatically by the rule mining algorithm had significantly improved accuracy, both reaching more than 90%. This showed that the binary semantic pattern rule mining algorithm and optimization algorithm proposed in this paper were reasonable.