S. Singh, H. Darbari, Ajai Kumar, Shikha Jain, Anu Lohan
{"title":"英语-印地语神经机器翻译综述","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":"{\"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}","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}
Overview of Neural Machine Translation for English-Hindi
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.