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 ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information Techn Enhancing the quality of machine translation system using cross lingual word embedding models nology University of Engineering and Technology-Vietnam National University, HanoiSupervised by Associate Professor. Nguyen Phuong ThaiA thesis submitted in fulfillment of the requirements for the degree ofMaster of Science in Computer Science43405ORIGINALITY STATEMENT■| hereby declare that Illis su Enhancing the quality of machine translation system using cross lingual word embedding models bmission is my own work and to I he Iwst of my knowledge it contains no materials previously published or written by another person, or substantial prEnhancing the quality of machine translation system using cross lingual word embedding models
oportions of material which have been accepted lor the award of any ot her degree or diploma at University of Engineering and Technology (UET/Coltcch)Enhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information Techn Enhancing the quality of machine translation system using cross lingual word embedding models hom I have worked at UET/Coltcch 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 li Enhancing the quality of machine translation system using cross lingual word embedding models nguistic expression is acknowledged.’Hanoi, November 15"', 2018Signed................................1iiABSTRACTỉn recent years, Machine Translation hEnhancing the quality of machine translation system using cross lingual word embedding models
as shown promising results and received much interest of researchers. Two approaches that have been widely used for machine translation are Phrase-basEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information Techn Enhancing the quality of machine translation system using cross lingual word embedding models bilingual corpora 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 PBSM'T, and the unknown word problem in NMT. In contrast, monolingual data are available for most of the languages. Thanks to the advant Enhancing the quality of machine translation system using cross lingual word embedding models age, many models of wo/d embedding and cross-lingual word embedding have been appeared to improve the quality of various tasks in natural language proEnhancing the quality of machine translation system using cross lingual word embedding models
cessing. The purpose of this thesis is to propose two models for using cross-lingual word embedding models to address the above impediment. The first Enhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information Techn Enhancing the quality of machine translation system using cross lingual word embedding models n. Van-Tim Búi. Huy-liien Vu. Phuong-Thai Nguyen and Chi-Mai 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 (1ALP 2018).iiiACKNOWLEDGEMENTS1 would like to ex Enhancing the quality of machine translation system using cross lingual word embedding models press my sincere gratitude to my lecturers ill university, and especially to my supervisors - Assoc.Prof. Nguyen Phuong Thai, Dr. Nguyen Van Vinh andEnhancing the quality of machine translation system using cross lingual word embedding models
MSc. Vu Huy Hion. They are my inspiration, guiding mo to got the bettor of many obstacles in the completion this thesis.I am grateful to my family. ThEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information Techn Enhancing the quality of machine translation system using cross lingual word embedding models g, my friends, Iran Minh Luyon, Hoang Cong Tuan Anh, for giving mo many useful advices and supporting my thesis, my studying and my living.Finally, I sincerely acknowledge the Vietnam National University, Hanoi ami csjxaially. TC.02-2016-03 project named "Building a machine translation system to sup Enhancing the quality of machine translation system using cross lingual word embedding models port translation of documents between Vietnamese and Japanese to help managers ami businesses in Hanoi approach Japanese market” for supporting financEnhancing the quality of machine translation system using cross lingual word embedding models
e to my master study.To my family ỌivEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information TechnEnhancing the quality of Machine Translation System Using Cross-Lingual Word Embedding ModelsV UAI1JcongINguyen Minh ThuanFaculty of Information TechnGọi ngay
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