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The present paper attempts at exploring, classifying and resolving various types of divergence
patterns in the context of English-Urdu Machine Translation where English and Urdu are SL and
TL respectively. So far as the methodology is concerned, we have observed the English-Urdu pair
sentences and analyzed the translated output taking into consideration different areas of translational divergences. We have taken one thousand corpus of the ILCI English sentences for this study and analyzed the translated Urdu output in bulk taking into consideration different areas of translational divergences on web-based Machine Translation platforms namely, Bing and Google Translate. Dorr‟s (1994, 1995) theoretical framework has been adopted for the classification and resolution of the linguistic divergences in this undertaken study. Dorr has classified the divergences into two broad categories (lexical-semantic and syntactic divergences) and proposed Lexical Conceptual Structure-based resolution for them. This study would help identify, classify and resolve the underlying divergence patterns between these languages so as to develop MT systems
considering the divergence errors and enhance the performance of the MT.

Added on June 8, 2016


  More Details
  • Contributed by : Atul
  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : Sharmin Muzaffar, Pitambar Behera and Girish Nath Jha
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