With the diversification of the world landscape and the accelerating process of higher education, Japanese is being valued as an important language, yet there are differences in the formal expression of the language due to different cultural backgrounds. The creation of a corpus of Japanese language culture and education is explored in this article, which contributes to language acquisition by non-native speakers. After collecting relevant information about Japanese language culture and education, the article takes it as a corpus and develops a corpus annotation system and specification further modifies the model and algorithm through machine learning, and finally realizes the construction of the system. By testing the usefulness and effectiveness of the Japanese language culture education corpus proposed in this paper, the paper concludes that in the analysis of the number and rate of bias of “了 (have done)” in subjects with different levels of Japanese language proficiency, the average rate of bias of the beginner level group is the highest at 24.65%, and the average rate of bias of the intermediate level group is the lowest at 14.6%. The “over-marking” bias rate of students’ use of “着(be doing)” reveals that the bias rate of students decreases by 0.64 from the beginner stage to the advanced stage, which indicates that the Japanese cultural education corpus proposed in this paper has a good effect on improving and facilitating the language acquisition of non-native speakers. It shows that the Japanese cultural education corpus proposed in this paper has a positive effect on improving and promoting language acquisition for non-native speakers.