{"title":"The Design of English Translation Software Based on Machine Learning Technology","authors":"Xiaoshan Zeng","doi":"10.1109/ACMLC58173.2022.00014","DOIUrl":null,"url":null,"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.","PeriodicalId":375920,"journal":{"name":"2022 5th Asia Conference on Machine Learning and Computing (ACMLC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th Asia Conference on Machine Learning and Computing (ACMLC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACMLC58173.2022.00014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.