Development of an Enhanced BP Neural Network-Based English Translation Evaluation System Integrating GLR Algorithm for Automated Judgment

This study proposes an advanced English Translation Scoring System (ETSS) designed to improve the reliability and accuracy of English translation evaluation using an enhanced BP neural network and an improved Generalized Maximum Probability Ratio Detection (GLR) algorithm.The system features a comprehensive three-phase approach involving text feature extraction, optimization, and interactive fusion to analyze and score translations effectively.Key enhancements include the integration of a wavelet packet decomposition method for feature vector analysis and the use of context-aware corrections to address structural ambiguities.Evaluation of the system demonstrates a significant improvement in translation judgment accuracy, reducing human intervention and error rates.The ETSS system achieves over 95% accuracy in identity detection and an overall system reliability of 92.3%, validating its effectiveness as an intelligent tool for automated English translation assessment.