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dc.contributor.advisor Fernando S
dc.contributor.advisor Sumathipala S
dc.contributor.author Sandaruwan HGD
dc.date.accessioned 2021
dc.date.available 2021
dc.date.issued 2021
dc.identifier.citation Sandaruwan, H.G.D. (2021). Neural machine translation approach for Singlish to English translation [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21470
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21470
dc.description.abstract This dissertation is for a research that aimed at proposing a language model to translate texts written in Singlish to English. Singlish is an alternative writing system for Sinhala language that uses Latin scripts (English Alphabet) instead of using native Sinhala alphabet. This had been a requirement for long period, since many Sri Lankans use this writing method to write product reviews, social media posts and comments etc. This has been tried since couple of years by many research students but the main challenge was to find a proper data set to evaluate deep learning models for this Natural Language Processing (NLP) task. Hence, traditional statistic, rulebased models has been proposed with less data. This research addresses the challenge of preparing a data set to evaluate a deep learning approach for this machine translation activity and also to evaluate a seq2seq Neural Machine Translation (NMT) model. The proposed seq2seq model is purely based on the attention mechanism, as it has been used to improve NMT by selectively focusing on parts of the source sentence during translation. The proposed approach can achieve 24.13 BLEU score on Singlish-English by seeing ~0.15 M parallel sentence pairs with ~50 K word vocabulary. en_US
dc.language.iso en en_US
dc.subject SINGLISH en_US
dc.subject NMT en_US
dc.subject LANGUAGE PROCESSING en_US
dc.subject SEQ2SEQ en_US
dc.subject ATTENTION MODEL en_US
dc.subject WORD EMBEDDING en_US
dc.subject INFORMATION TECHNOLOGY -Dissertation en_US
dc.subject COMPUTATIONAL MATHEMATICS -Dissertation en_US
dc.subject ARTIFICIAL INTELLIGENCE -Dissertation en_US
dc.title Neural machine translation approach for Singlish to English translation en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty IT en_US
dc.identifier.degree MSc in Artificial Intelligence en_US
dc.identifier.department Department of Computational Mathematics en_US
dc.date.accept 2021
dc.identifier.accno TH5006 en_US


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