English to Pakistan sign language - machine translation

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dc.contributor.authorTayyaba Zainab
dc.contributor.authorAbdul Rehman
dc.date.accessioned2017-11-01T05:20:09Z
dc.date.available2017-11-01T05:20:09Z
dc.date.issued2016
dc.descriptionSupervised by:Nabeel Sabir Khan Blochen_US
dc.description.abstractIn this thesis a Text to PakistanSign Language Automation System has been proposed. To conquer any hindrance between deaf and an ordinary individual, we need to think of a framework which can make an interpretation of one dialect to another. Till now interpreters were doing this work for us however now we are going to mechanize it as a result of constrained assets. Keeping in perspective the difference of sentence structure, there is a need to study PakistanSign Language's sentence structure with the goal that we could make an interpretation of as per the PSL linguistic use. Without linguistic use, sentences can't pass on their appropriate implications. In the wake of archiving the punctuation we now need to mechanize the capacity of changing over English sentence into its PakistanSign Language proportional sentence. For this we have proposed a system which takes an English sentence as an input and will produce its comparable PakistanSign Language's sentence. Our proposed framework uses a few tools which parse the offered sentence to give English language lexicons along with their parts of speech and dependency tags, in the form of a tree. The yielded tree, alongside our documented sentence structure is passed to our proposed parser which then change the given tree hubs in light of those linguistic use rules. Last but not the least a PSL sentence is created from the modified tree.en_US
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/2187
dc.language.isoenen_US
dc.publisherUniversity of Management and Technology Lahoreen_US
dc.subjectInterpretersen_US
dc.subjectPakistanSign Language'sen_US
dc.subjectBS Thesisen_US
dc.titleEnglish to Pakistan sign language - machine translationen_US
dc.titleEnglish to Pakistansign language - machine translationen_us
dc.typeThesisen_US
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