The Design of English Translation Software Based on Machine Learning Technology

Xiaoshan Zeng
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Abstract

With the increasing frequency of our country’s international communication and the popularization and penetration of mobile Internet into people’s work and life styles in modern society, the level of social informatization has also increased. In order not to be eliminated by this era, people must follow the pace of development of this era, always keep an eye on and receive the latest information from all over the world. Most of these materials are published on the Internet in foreign languages. Therefore, language has become the biggest obstacle for people to obtain information. As machine translation technology is restricted in terms of convenience and cost control, people’s need for machine translation or machine translation technology has become more and more urgent. This paper studies the design of English translation software (ETS) based on machine learning technology (MLT). By introducing MLT into ETS, a new neural machine translation method is proposed, and related experiments are used to test the effectiveness of the translation method. The designed translation software has been evaluated for translation quality. The experimental results show that as the arc length distribution increases, the translation quality (TTQ) decreases. The English translation software designed in this paper is of great importance to the research and development of machine translation.
基于机器学习技术的英语翻译软件设计
随着我国国际交流的日益频繁,以及移动互联网在现代社会中对人们工作和生活方式的普及和渗透,社会信息化水平也不断提高。为了不被这个时代淘汰,人们必须跟上这个时代的发展步伐,时刻关注和接收来自世界各地的最新信息。这些材料大多以外语发布在互联网上。因此,语言成为人们获取信息的最大障碍。由于机器翻译技术在便利性和成本控制方面受到限制,人们对机器翻译或机器翻译技术的需求变得越来越迫切。本文研究了基于机器学习技术的英语翻译软件(ETS)的设计。通过将MLT引入ETS,提出了一种新的神经网络机器翻译方法,并通过相关实验验证了该方法的有效性。对所设计的翻译软件进行了翻译质量评价。实验结果表明,随着弧长分布的增大,平移质量(TTQ)降低。本文设计的英语翻译软件对机器翻译的研究和发展具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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