This study enhances the conventional English-Chinese bilingual teaching mode by incorporating the continuous digital twin technology into its design. In addition to the typical video and audio transmission teaching functions, the English-Chinese bilingual distant education system also includes a number of interactive capabilities. The approach described in this study is mostly utilized for bilingual instruction in colleges and universities, and the instruction is enhanced by digital twin technology. In this work, the system performance test focuses primarily on the evaluation of teaching quality and teaching satisfaction. Among these are the evaluation of teaching quality by questionnaires, the evaluation of this paper’s system by a number of senior teachers, and the calculation of student satisfaction through teaching experiments. The results of the study indicate that the strategy described in this work has a particular effect.

In order to explore the correlation between college English teacher behavior and teaching effects, this paper applies data mining technology to related research. Moreover, this paper uses Bloom Filter to represent the efficiency of insert queries and space usage of dynamic data sets and designs a multichannel balanced matrix Bloom Filter. In addition, this paper uses the longest prefix matching filling algorithm when selecting the element insertion position in multiple candidate Bloom Filters, and uses this algorithm to process the college teacher behavior and teaching effect data. Finally, this paper combines investigation and experiment to conduct research. Through the investigation, it can be seen that the teaching behavior of college English teachers will have a certain impact on students, and the positive behavior of teachers can effectively improve the teaching effect, which can be used as a reference for the formulation of subsequent teaching plans.

This work offers an enhanced intelligent picture text recognition algorithm based on the intelligent image text recognition method to increase the impact of English image text translation. Texture blocks of adaptable size are used to successfully increase the accuracy and efficiency of restoration due to the varying texture information present in various photos. Furthermore, the repair sequence is altered as a result of the improved priority calculation algorithm, and the weight of the structural information is enhanced at the same time. In addition, in order to reduce the overall structural complexity and calculation amount of the system, the gated loop unit is also selected as the RNN structure. Finally, this article constructs an English translation system based on intelligent image text recognition according to the requirements of intelligent image text recognition and designs experiments to evaluate the performance of the system constructed in this article. The experimental statistical results show that the English translation system constructed in this article can basically meet the needs of English image text recognition.