Accuracy evaluation model of oral English translation based on semantic analysis

Abstract

In order to solve the problem of low semantic feature extraction accuracy and evaluation efficiency in traditional oral English translation accuracy evaluation model, this paper proposes and constructs an oral English translation accuracy evaluation model based on semantic analysis. Semantic analysis method combined with word frequency weight is used to construct word frequency feature matrix, and singular value decomposition method is used to solve the feature matrix to obtain semantic features. According to the result of word score calculation, the weight of oral English translation words is calculated. According to the results of vocabulary weight calculation, the translation accuracy evaluation model is constructed to complete the evaluation of oral English translation accuracy. Experimental results show that, compared with the traditional evaluation model, this model has higher semantic feature extraction accuracy and accuracy evaluation efficiency, so the evaluation performance of the text model is stronger.