A high performance computing technology powered multimedia fusion model in university English translation

Abstract

Various forms of materials, such as pictures, videos and texts, have rapidly brought the college English translation teaching model into the era of multimedia integration. This makes it difficult for English teachers to improve college English translation by using unique materials, so as to form their own unique teaching style. In view of this, a multimedia comprehensive English translation framework based on the combination of big data technology and multimedia teaching mode is proposed. At the same time, the idea of building the framework is introduced from two perspectives: the integration of big data technology and multimedia, and the integration of multimedia and English teaching process. Then, a recursive neural network algorithm based on ant colony optimization algorithm is proposed and tested. Finally, the simulation results show that the proposed method has significantly improved the accuracy and retention rate, indicating the effectiveness of the framework.