Design of Machine Translation Algorithm for English Long Sentences Based on Artificial Neural Network

Machine translation (MT) is a key research area within natural language processing and artificial intelligence, focusing on utilizing computers to facilitate the conversion between distinct languages. The widespread application of neural networks in natural language processing stems from their proficiency in comprehending and analyzing semantics. In this study, we leverage artificial neural networks (ANN) to refine the MT algorithm for complex, long English sentences characterized by their intricate syntactic structures and professional nuances. Our approach hinges on semantic relationships to enhance translation quality. Simulation outcomes reveal that our refined algorithm for translating lengthy English sentences exhibits substantial improvements compared to the conventional ID3 algorithm. Specifically, we observe a notable decrease in mean absolute error (MAE) by approximately 20% and an increase in recall rate by roughly 15%. These findings underscore the algorithm's efficacy in enhancing the translation of intricate English sentences.