Abstract
Facebook/ Metaverse is a world-leading social networking platform that is equally popular in the world that is equally popular globally Due to the diversity of its users, Facebook is dedicated to improving its Machine Translation (MT) to refine the communication process and remove linguistic hurdles for efficient communication. Recently, Metaverse has started Neural Machine Translation (NMT) for the improvement of translation. NMT uses artificial neural networks to predict a more appropriate word choice and sequence. This research investigates the efficiency of Neural Machine Translation (NMT) in translating text from Urdu to the English language. The Oxford Urdu English Dictionary and FARHANG E AASFIA dictionaries have been used as validation parameters in translation. The semantic and syntactic errors have been segregated and categorized with Antoine Berman’s Twelve Deforming Tendencies for rectification. Major findings reveal that the most frequent errors result from transliteration that damages the semantic and syntactic structure of the text.
Authors
1-Zafar Ullah Instructor, Virtual University, Islamabad, Pakistan.2-Muhammad Farooq Alam Assistant Professor, University of NUML, Rawalpindi, Punjab, Pakistan.3-Wishma Ihsan MPhil English Scholar, University of NUML, Islamabad, Pakistan.
Keywords
Facebook/ Metaverse, Machine Translation (MT), Neural Machine Translation (NMT), Artificial Neural Networks
DOI Number
10.31703/glr.2022(VII-II).05
Page Nos
55 ‒ 66
Volume & Issue
VII - II