Design and Development of Intelligent Detection of Japanese Vocabulary Translation Errors based on Improved GLR Algorithm

Precise translation of Japanese words is a major challenge because Japanese has a complex grammatical structure, contextual dependence, and multiple meanings of words. Current translation error detection systems tend to adopt rule-based approaches or static dictionaries, which are incapable of dealing with syntactic ambiguity and dynamic sentence structures well. Conventional methods fare poorly in the detection of minor vocabulary mistakes, particularly when word usage is highly dependent on sentence context. In order to overcome these constraints, this research introduces an intelligent detection system based on the Improved Generalized Left-to-right Rightmost derivation (I-GLR) algorithm. The I-GLR parser can process ambiguous and intricate grammatical structures, supporting more accurate detection of syntactic errors and word misuse in translated sentences. The proposed system combines the principles of GLR-based syntactic parsing with an error detection component that alerts against deviations from proper grammatical structures. Relative to traditional rule-based methods, the model provides more flexibility and precision in detecting translation aberrations. In particular, the system produced a 97.5% accuracy score in evaluation, attesting to its ability to identify vocabulary translation mistakes. This research shows syntactic parsing–based intelligent systems can enhance the quality and reliability of Japanese language translation tools and justifies further research in natural language processing applications for educational and professional purposes.