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dc.coverage.spatialDevelopment and evaluation of hybrid machine translation systems for english to indian language under low resource conditions
dc.date.accessioned2023-04-19T07:00:03Z-
dc.date.available2023-04-19T07:00:03Z-
dc.identifier.urihttp://hdl.handle.net/10603/476964-
dc.description.abstractIndia is a multi-cultural and multilingual country with 22 official newlinelanguages belonging to different linguistic families. Since the time of British newlinecolonial rule in India, English has been used as the linguistic medium (L1 newlinelanguage) for administrative and higher education purposes. Postindependence, newlinethe use of regional languages (as L1 language) along with newlineEnglish (as L2 language) has been encouraged in the states across the country. newlineHowever, the usage of either L1 or L2 language varies among the common newlinepeople. Thus, it is essential to develop machine translation (MT) systems newlinefrom English-to-Indian languages for smoother transactions and newlinecommunication across the country. Among the seven linguistic families of newlineSouth Asia, Indo-Aryan and Dravidian languages account for over 90% of newlineIndian speakers. On this note, the current research work proposes to develop newlinean efficient statistical-based (SMT) and neural-based (NMT) machine newlinetranslation systems for translation from English to two Indian languages newlinenamely, Tamil (a Dravidian language) and Hindi (an Indo-Aryan language). newlineMost of the well-established data-driven approaches for developing newlineMT systems require huge amount of parallel text in the source and target newlinelanguage, to train an efficient translation model. Availability of such huge newlineparallel corpora between English and Indian languages is scarce. Further, newlinedomain-specific parallel corpora required to develop highly efficient and newlineapplication-oriented MT systems are also not available. The proposed work newlinemakes use of punctuation marks and re-ordering to augment the parallel data newlineavailable for training the SMT and NMT systems. newline
dc.format.extentxix,183p.
dc.languageEnglish
dc.relationp.169-182
dc.rightsuniversity
dc.titleDevelopment and evaluation of hybrid machine translation systems for english to indian language under low resource conditions
dc.title.alternative
dc.creator.researcherMrinalini Kannan
dc.subject.keywordBilingual Language
dc.subject.keywordMachine Translation
dc.subject.keywordParts-of-Speech
dc.description.note
dc.contributor.guideVijayalakshmi P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File22.31 kBAdobe PDFView/Open
02_prelim pages.pdf2.32 MBAdobe PDFView/Open
03_contents.pdf126.87 kBAdobe PDFView/Open
04_abstracts.pdf84.37 kBAdobe PDFView/Open
05_chapter1.pdf385.33 kBAdobe PDFView/Open
06_chapter2.pdf429.65 kBAdobe PDFView/Open
07_chapter3.pdf2.27 MBAdobe PDFView/Open
08_chapter4.pdf1.45 MBAdobe PDFView/Open
09_chapter5.pdf563.12 kBAdobe PDFView/Open
10_annexures.pdf111.21 kBAdobe PDFView/Open
80_recommendation.pdf95.19 kBAdobe PDFView/Open


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