Russian Neural Machine Translation System Integrating Translation Memory and Improved Reverse Translation

As the artificial intelligence and intelligent algorithms rapidly develop in the field of natural language processing, Neural Machine Translation (NMT) technology has become an important tool for cross linguistic communication. In order to improve the accuracy and fluency of translation systems, a Russian neural machine translation system that integrates translation memory and improved reverse translation has been proposed. The system utilizes translation memory to better remember and reuse historical translation knowledge, and adopts a data filtering strategy based on perplexity to improve the reverse translation mechanism, in order to solve the problem of sparse Russian data. The outcomes denoted that the translation accuracy and BLEU score of the research system reached 98.45% and 42.61, respectively, showing significant improvement compared to other advanced translation systems. Under high concurrent user numbers, the maximum throughput of the system is 3306.44, and the average request waiting time for users is 448.51 ms, effectively improving the smoothness of the system. In summary, the Russian translation system that integrates translation memory with improved reverse translation strategies significantly improves the accuracy and fluency of Russian translation, providing a reference for translation research in other low resource languages.