Overview of Neural Machine Translation for English-Hindi

S. Singh, H. Darbari, Ajai Kumar, Shikha Jain, Anu Lohan
{"title":"Overview of Neural Machine Translation for English-Hindi","authors":"S. Singh, H. Darbari, Ajai Kumar, Shikha Jain, Anu Lohan","doi":"10.1109/ICICT46931.2019.8977715","DOIUrl":null,"url":null,"abstract":"Artificial intelligence is getting shrewd in real time with massive amounts of computational power and high in demand in last quarter more than billion dollars. The Intensification of Neural Networks in Machine learning playing major revolution in Machine Translation (MT). Looking same aspect, we have prepared a paper on Machine Translation for Hindi using Neural Machine Translation techniques. The Basis of this paper is to translate the source language into target language with the help of sentence structure for source language (English sentence) and corresponding reordering rules for target language (Hindi sentence) using a deep neural network (DNN).When the source input that is English sentences are exactly matched with the target language database then the suitable translation for related input is directly fetched from the database. The fuzzy matching between the input sentence and the sample sentence in the database is done with cosine similarity between the sentence structure of input sentence and the sample sentence and then the reordering rule of the most alike sentence to the input sentence is used for translation.Extracting the structure of the source language sentence and extracting the reordering rule for target sentence is the core part of the translator. Reordering of words in spite of that remains one of the complex problems.It is exciting to implement Deep Neural Network and fuzzy logic to build intelligent reordering rules machine learning system.","PeriodicalId":412668,"journal":{"name":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT46931.2019.8977715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Artificial intelligence is getting shrewd in real time with massive amounts of computational power and high in demand in last quarter more than billion dollars. The Intensification of Neural Networks in Machine learning playing major revolution in Machine Translation (MT). Looking same aspect, we have prepared a paper on Machine Translation for Hindi using Neural Machine Translation techniques. The Basis of this paper is to translate the source language into target language with the help of sentence structure for source language (English sentence) and corresponding reordering rules for target language (Hindi sentence) using a deep neural network (DNN).When the source input that is English sentences are exactly matched with the target language database then the suitable translation for related input is directly fetched from the database. The fuzzy matching between the input sentence and the sample sentence in the database is done with cosine similarity between the sentence structure of input sentence and the sample sentence and then the reordering rule of the most alike sentence to the input sentence is used for translation.Extracting the structure of the source language sentence and extracting the reordering rule for target sentence is the core part of the translator. Reordering of words in spite of that remains one of the complex problems.It is exciting to implement Deep Neural Network and fuzzy logic to build intelligent reordering rules machine learning system.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
英语-印地语神经机器翻译综述
人工智能正变得越来越精明,拥有巨大的计算能力,上个季度的需求超过了10亿美元。神经网络在机器学习中的强化在机器翻译领域掀起了一场重大革命。同样,我们准备了一篇关于使用神经机器翻译技术进行印地语机器翻译的论文。本文的基础是利用深度神经网络(deep neural network, DNN),利用源语言(英语句子)的句子结构和目标语言(印地语句子)相应的重排规则,将源语言翻译成目标语言。当源输入(即英语句子)与目标语言数据库完全匹配时,则直接从数据库中获取相关输入的合适翻译。首先利用输入句子的句子结构与样本句子的余弦相似度对数据库中的输入句子与样本句子进行模糊匹配,然后利用最相似句子与输入句子的重排规则进行翻译。提取源语言句子的结构和提取目标句子的重排规则是翻译工作的核心部分。尽管如此,单词的重新排序仍然是一个复杂的问题。利用深度神经网络和模糊逻辑来构建智能重排序规则机器学习系统是令人兴奋的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Fraud Detection During Money Transaction and Prevention Stockwell Transform Based Algorithm for Processing of Digital Communication Signals to Detect Superimposed Noise Disturbances Exploration of Deep Learning Techniques in Big Data Analytics Acquiring and Analyzing Movement Detection through Image Granulation Handling Structured Data Using Data Mining Clustering Techniques
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1