Construction of a Multimedia Instructional Effect Assessment System of College Foreign Language Translation Based on Artificial Intelligence

Abstract

The teaching evaluation module is an important guarantee of teaching effectiveness, and as an important part of the multimedia teaching system, it needs special attention. This paper combines artificial intelligence and multimedia teaching effect evaluation, proposes a foreign language translation multimedia teaching effect evaluation model based on improved support vector machine (SVM) algorithm, and provides theoretical support for the construction of foreign language translation multimedia teaching effect evaluation system. The results show that the accuracy of this assessment algorithm is improved by 22.18% compared with the traditional assessment algorithm. Therefore, it is theoretically feasible to use the improved SVM to analyse the application effect of multimedia teaching mode in foreign language translation teaching. It can be found that the automatic acquisition of model data, the cumulative search of spatial knowledge and the adaptive control of the search phase of the optimised SVM algorithm have also been significantly improved, and conclusions drawn are more reliable.