Lexical, semantic and pragmatic equivalence gaps in google machine translation software

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dc.contributor.authorJustin, Naomi
dc.date.accessioned2017-12-26T05:35:40Z
dc.date.available2017-12-26T05:35:40Z
dc.date.issued2017
dc.descriptionSupervised By:Dr. Nadia Anwaren_US
dc.description.abstractThis research investigates the lexical, semantic and pragmatic equivalence issues faced while translating Urdu into English language using Google Machine Translation (GMT) software. I have used content analysis technique of qualitative research to validate my corpus in isolation and with reference to the context. This has helped me to identify the equivalence issues in the translation process of GMT and its impact on the translated product. The corpus selected for analysis belongs to different chapters of Zaviya 2 written by the well renowned intellect Ashfaq Ahmed. During the validation process, it has been identified that Google Machine Translation software has its limitations at lexical, semantic and pragmatic levels while translating from Urdu to English language. It fails to analyze the word and hence unable to transfer it equivalently and due to these limitations, at certain occurrences it remains ineffective to restructure the sentence correctly. Other than identifying these limitations, I have also suggested some recommendations which will help GMT software to improve its translation quality. I believe this research will contribute to help GMT software overcome these issues at lexical, semantic and pragmatic level and help in producing more accurate translation.en_US
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/2339
dc.language.isoenen_US
dc.publisherUniversity of Management and Technology Lahoreen_US
dc.subjectMachine translationen_US
dc.subjectlexical, semanticen_US
dc.titleLexical, semantic and pragmatic equivalence gaps in google machine translation softwareen_US
dc.typeThesisen_US
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