Luận văn thạc sĩ 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: Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models
Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models
VIETNAM NATIONAL ƯNIVERISTY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYNGUYEN MINH THU ANEnhancing the quality of Machine Translation System Using Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models Cross-Lingual Word Embedding Models (Nâng cao chất lượng của hệ thống dịch máy dựa trên các mô hình vector nhúng biếu diễn từ giữa hai ngôn ngữ)Program: Computer ScienceMajor: Computer ScienceCode: 8480101.01MASTER THESIS: COMPUTER SCIENCESUPERVISOR: Assoc. Prof. NGUYEN PHUONG THAIHanoi - 11/2018En Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelshancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsNguyen Minh ThuanFaculty of Information Technology UniversiLuận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models
ty of Engineering and Technology Vietnam National University, HanoiSupervised byAssociate Professor. Nguyen Phuong ThaiA thesis submitted in fulfillmeVIETNAM NATIONAL ƯNIVERISTY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYNGUYEN MINH THU ANEnhancing the quality of Machine Translation System Using Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelsown work and to I he Iwst of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted lor the award of any ot her degree or diploma at University of Engineering and Technology (UET/Coltcch) or any other e Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelsducational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have workLuận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models
ed at UET/Coltcch or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product oVIETNAM NATIONAL ƯNIVERISTY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYNGUYEN MINH THU ANEnhancing the quality of Machine Translation System Using Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelssion is acknowledged.’Hanoi, November 15"', 2018Signed.................................1iiABSTRACTỉn recent years, Machine Translation has shown promising results and received much interest of researchers. Two approaches that have been widely used for machine translation are Phrase-based Statistical Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models Machine Translation (PBSMT) and Neural Machine Translation (NMT). During translation, both approaches rely heavily on large amounts of bilingual corpLuận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models
ora 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 VIETNAM NATIONAL ƯNIVERISTY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYNGUYEN MINH THU ANEnhancing the quality of Machine Translation System Using Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelsls of wo/d embedding and cross-lingual word embedding have been appeared to improve the quality of various tasks in natural language processing. The purpose of this thesis is to propose two models for using cross-lingual word embedding models to address the above impediment. The first model enhances Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models the quality of the phrase-table in SMT. and the remaining model tackles the unknown word problem in NMT.Publications:* Minh-Thuan Nguyen. Van-Tim BúiLuận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding models
. Huy-liien Vu. Phuong-Thai Nguyen and Chi-Mai Luong. Enhancing the quality of Phrase-table in Statistical Machine Translation for Less-Common and LowVIETNAM NATIONAL ƯNIVERISTY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYNGUYEN MINH THU ANEnhancing the quality of Machine Translation System Using Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelsre gratitude to my lecturers in university, and especially to my supervisors - Assoc. Prof. Nguyen Phuong Thai, Dr. Nguyen Van Vinh and MSc. Vu Huy Hien. They are my inspiration, guiding me to get the better of many obstacles in the completion this thesis. Luận văn thạc sĩ enhancing the quality of machine translation system using cross lingual word embedding modelsVIETNAM NATIONAL ƯNIVERISTY, HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYNGUYEN MINH THU ANEnhancing the quality of Machine Translation System UsingGọi ngay
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