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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 2
432-435

Separate structure machine translation model based on fusion of CNN and Transformer

Ge Junwei
Tu Zhaohao
Fang Yiqiu
College of Software Engineering, Chongqing University of Posts & Telecommunications, Chongqing 400065, China
DOI: 10.19734/j.issn.1001-3695.2021.07.0274

Abstract

To address the problems of inefficient operation, excessive computational parameters, and high computational complexity in the Transformer-based machine translation model, this paper proposed a separate structure machine translation model based on fused CNN and Transformer. Firstly, for the problems of inefficient operation and excessive computational parameters, this paper used the structure of separating computational attention module and normalization module to ensure the reusability of stacked multilayer structure, improve the operation efficiency and reduce the computational parameters. Secondly, the model introduced the convolutional computation module and the original self-attentive module for fusion. This paper used the original self-attentive module to calculate the global contextual semantic relations and the convolutional computation module to calculate the local contextual semantic relations to reduce the complexity of the model. Experimental comparisons with other machine translation models on the same dataset show that the model has the lowest computational parameters and performs better than other models.

Foundation Support

国家自然科学基金面上项目(62072066)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.07.0274
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Algorithm Research & Explore
Pages: 432-435
Serial Number: 1001-3695(2022)02-018-0432-04

Publish History

[2021-09-19] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

葛君伟, 涂兆昊, 方义秋. 基于融合CNN和Transformer的分离结构机器翻译模型 [J]. 计算机应用研究, 2022, 39 (2): 432-435. (Ge Junwei, Tu Zhaohao, Fang Yiqiu. Separate structure machine translation model based on fusion of CNN and Transformer [J]. Application Research of Computers, 2022, 39 (2): 432-435. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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