Training Data Selection and Optimization of English Translation System Based on Data-Driven Learning

Abstract

Systematic programming of translation and translation optimization is a translation method of system structure and function, and a translation criterion with general meaning. Relying on modern system theory, it studies the organic connection of elements, structures and functions of the semantic system from the aspects of structural form, functional process and optimization method, and constructs the translation route, translation scope, translation and optimization of the structure and function of the semantic system as a whole. Data-driven learning has opened up a new path for college English translation teaching, which is a new trend in college English teaching reform. This paper discusses the selection and optimization of training data for English translation systems based on data-driven learning, and analyzes the optimization principles of current college English translation systems. On this basis, this paper further illustrates the application case of data-driven learning in college English translation teaching, aiming at providing constructive suggestions for corpus-based data-driven college English translation teaching.