Optimization of Dimension-Han Machine Translation Model Based on Neural Network

Abstract

Machine translation is a natural language (source language) converted into another natural language by computer processing. As the main branch of artificial intelligence, machine translation based on neural network has significantly exceeded the traditional statistical machine translation in small language translation. Resource-poor language has become a hot topic, such as Uygur translation, as a typical resource-poor language, although there are some achievements in Uygur information processing, its basic available tools are very limited. This paper first expounds the background of the topic, briefly introduces the background knowledge of machine translation and the language knowledge of related languages. This paper describes the machine translation method based on neural network, and analyzes the existing neural machine translation methods on Uygur-Chinese translation tasks. The analysis of Uygur, Turkish, Arabic and Japanese finally determines the transfer translation of Uygur in Japanese. The parallel corpus of Uygur-Chinese and Japanese-Chinese are used to experiment.