{"title":"English to Hindi Translation using Transformer","authors":"Abhinav Y. Watve, Madhuri A. Bhalekar","doi":"10.1109/ICIDCA56705.2023.10100193","DOIUrl":null,"url":null,"abstract":"This study analyzes the effectiveness of transformer-based models for English to Hindi translation, as the lack of translation resources for this language pair poses challenges in various domains. Our literature review supports the remarkable success of transformer architecture in natural language processing tasks, including machine translation. Experiments were conducted on multiple datasets to evaluate the effectiveness of the transformer model, and the findings provide further evidence of its effectiveness for English to Hindi translation. The results contribute to the understanding of the effectiveness of the transformer architecture in machine translation for English to Hindi language pairs and the importance of developing and improving machine translation models for overcoming the challenges faced due to a lack of translation resources.","PeriodicalId":108272,"journal":{"name":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","volume":"665 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIDCA56705.2023.10100193","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
This study analyzes the effectiveness of transformer-based models for English to Hindi translation, as the lack of translation resources for this language pair poses challenges in various domains. Our literature review supports the remarkable success of transformer architecture in natural language processing tasks, including machine translation. Experiments were conducted on multiple datasets to evaluate the effectiveness of the transformer model, and the findings provide further evidence of its effectiveness for English to Hindi translation. The results contribute to the understanding of the effectiveness of the transformer architecture in machine translation for English to Hindi language pairs and the importance of developing and improving machine translation models for overcoming the challenges faced due to a lack of translation resources.