Enhancing the quality of machine translation system using cross lingual word embedding models
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Enhancing the quality of machine translation system using cross lingual word embedding models
Enhancing the quality of machine translation system using cross lingual word embedding models
Enhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology Univer Enhancing the quality of machine translation system using cross lingual word embedding models rsity of Engineering and Technology Vietnam National University, HanoiSupervised byAssociate Professor. Nguyen Phuong ThaiA thesis submitted in fulfillment of the requirements for the degree ofMaster of Science in Computer Science43405ORIGINALITY STATEMENT'I hereby declare that this submission is my Enhancing the quality of machine translation system using cross lingual word embedding models own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of maEnhancing the quality of machine translation system using cross lingual word embedding models
terial which have been accepted for the award of any other degree or diploma at University of Engineering and Technology (UET/Coltech) or any other edEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology Univer Enhancing the quality of machine translation system using cross lingual word embedding models d at UET/Coltech or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic express Enhancing the quality of machine translation system using cross lingual word embedding models ion is acknowledged.’Hanoi, November 15rt, 2018Signed ...............................iiABSTRACTIn recent years, Machine Translation has shown promisinEnhancing the quality of machine translation system using cross lingual word embedding models
g results and received much interest of researchers. Two approaches that have been widely used for machine translation are Phrase-based Statistical MaEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology Univer Enhancing the quality of machine translation system using cross lingual word embedding models which require much effort and financial support. The lack of bilingual data leads to a poor phrase-table, which is one of the main components of PBSMT, and the unknown word problem in NMT. In contrast, monolingual data are available for most of the languages. Thanks to the advantage, many models of Enhancing the quality of machine translation system using cross lingual word embedding models word embedding and cross-lingual word embedding have been appeared to improve the quality of various tasks in natural language processing. The purposEnhancing the quality of machine translation system using cross lingual word embedding models
e of this thesis is to propose two models for using cross-lingual word embedding models to address the above impediment. The first model enhances the Enhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology Univer Enhancing the quality of machine translation system using cross lingual word embedding models -Hien Vu, Phuong-Thai Nguyen and Chi-Mal Luong. Enhancing the quality of Phrase-table In Statistical Machine Translation for Less-Common and Low-Resource Languages. In the 2018 International Conference on Asian Language Processing (IALP 2018).iiiACKNOWLEDGEMENTSI would like to express my sincere gra Enhancing the quality of machine translation system using cross lingual word embedding models titude to my lecturers in university, and especially to my supervisors - Assoc.Prof. Nguyen Phuong Thai, Dr. Nguyen Van Vinh and MSc. Vu Huy Hien. TheEnhancing the quality of machine translation system using cross lingual word embedding models
y are my inspiration, guiding me to get the better of many obstacles in the completion this thesis.I am grateful to my family. They usually encourage,Enhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology Univer Enhancing the quality of machine translation system using cross lingual word embedding models inh Luyen, Hoang Cong Tuan Anh, for giving me many useful advices and supporting my thesis, my studying and my living.Finally, I sincerely acknowledge the Vietnam National University, Hanoi and especially, TC.02-2016-03 project named "Building a machine translation system to support translation of d Enhancing the quality of machine translation system using cross lingual word embedding models ocuments between Vietnamese and Japanese to help managers and businesses in Hanoi approach Japanese market" for supporting finance to my master study.Enhancing the quality of machine translation system using cross lingual word embedding models
To my family VivEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology UniverEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology UniverGọi ngay
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