GRU neural network Mongolian-Chinese machine translation method

Abstract

The invention discloses a GRU neural network Mongolian-Chinese machine translation method. Firstly, a translation language is preprocessed; then, an Encoder-Decoder model is built and trained for a certain scale of Mongolian and Chinese bilingual; the Mongolian and Chinese bilingual linguistic data is subjected to coding unified processing; and finally, a translation result is obtained on the basis of an Encoder-Decoder model, wherein the Encoder-Decoder model is constructed by a neural network, one neural network is LSTM; the encoder is responsible for Encoder encoding, bidirectional coding setting, namely, forward encoding and reverse encoding are carried out on a source language; the source statement is converted into two vectors which are coded in different directions and have fixed lengths, the other neural network is a GRU and is in charge of Decoder decoding; the decoding is carried out from a forward direction and a reverse direction, namely, the context information is automatically integrated when decoding is carried out to output the target language, thus the length-fixed vector generated by encoding is converted into the target sentence. According to the method, the characteristics of the Mongolian and Chinese language are combined, so that the expression capability of a Mongolian and Chinese machine translation system is smoother and closer to human expression, andthe degrees of semantic loss and translation disorder in the translation process are reduced.

Description

technical field [0001] The invention belongs to the technical field of machine translation, relates to Mongolian-Chinese machine translation, in particular to a Mongolian-Chinese machine translation method with a GRU neural network. Background technique [0002] At this stage, with the rapid development of the Internet industry and the continuous rise of a series of IT industries including information technology, machine translation for natural language processing is playing a certain role in promoting the development of the entire Internet industry. Large-scale search service industries such as Google and Baidu have conducted large-scale scientific research in the field of machine translation in the face of industry development. Continuous research in order to continuously obtain higher quality translations. [0003] Although scientific research institutions are still making continuous efforts to obtain better translation results, machine translation still exposes more and...

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Problems solved by technology

[0006] In order to solve the problems of missed translation, mistranslation, and unregistered word processing in the translation process mainly existing in the above-mentioned prior art, the purpose of the present invention is to provide a kind of GRU neural network Mongolian-Chinese machine translation method, which utilizes CPU and GPU to work in parallel Processing the corpus in this way nearly doubles the speed, and learning the corpus through the set learning rate can effectively alleviate the local optimal problem in the process of learning the semantic expression of the corpus and the problem of low coding quality caused by rapid convergence. , to improve the quality of the overall system by setting special structures and algorithms

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