Intelligent Calibrating Method of English Interpretation Based on Particle Swarm Optimization

Due to the increasing progress of IT such as artificial intelligence (AI), English interpretation with computers has gradually become one of the study fields. Due to the influence of algorithms and matching degree, there are still bottlenecks in English interpretation. The phrase and syntax-based English interpretation calibration method emphasizes precise adjustments but falls short in addressing contextual coherence issues. In this paper, a novel AI-based approach is introduced for calibrating English interpretations, comprising a seek module, an interpretation module, a calibration module, and a behavior log. Particle Swarm Optimization (PSO) is a kind of efficient stochastic swarm intelligence optimization method, which has been widely used in various fields of scientific research and engineering practice. Therefore, an English interpretation AI correction algorithm based on PSO is proposed. PSO has the characteristics of simple principle, few parameters, easy implementation and fast convergence. This method has wide adaptability to different types of problems, and is quickly and effectively applied in many fields. This method can extract the basic meaning, check with the subject information, and judge whether the interpretation result is reasonable through all-round query, replace the unreasonable interpretation result, and finally generate the interpretation result with high precision. The semantics of words is preliminarily determined through the seek module, and the user's behavior data is collected by using the behavior log. On the basis of the automatic calibration method of the improved phrase interpretation model, the correct words are determined in combination with the context. The AI calibrating method of English interpretation based on PSO proposed in this paper shows that the precision of the generated interpretation results is significantly improved compared with the precision of the interpretation without calibrating processing. This method can be used as an interpretation auxiliary tool.