Application of ELAN in Human-Machine Mutual Translation of English for the News

Abstract

The translation of English news means the process of converting news articles published in English into another language. These articles may also be referred to as English news. This process comprises understanding the substance of the source article and accurately translating its tone and intent into the target language. A human translator or machine translation software can be used to perform the translation manually. In the disciplines of software globalization and technological translation, the Human-Machine Mutual Translation technique has grown significantly with the advancement of civilization and the quickening growth of research and innovation. Because of this practical need, translators have begun to focus more on machine translation and have conducted some productive research in this area. As a result, we suggested the EUDICO Linguistic Annotator (ELAN) in Human-Machine mutual translation of English for the news. EUDICO stands for European Distributed Corpora Project. The Max Planck Institute for Psycholinguistics created the EUDICO Linguistic Annotator as a software program for the linguistic annotation of language data. For this study, the English news dataset was used. The data were pre-processed by using normalization. The results were evaluated using performance metrics such as translation quality, precision, BLEU, recall, and computation time. The findings show that the recommended procedure provides an accurate translation of English news when compared to previously used methods. The results demonstrated that translation quality and computation time of proposed model are 95% and 60s respectively.