Overview
This course aims to
introduce students to the latest computer tools and translation software. In
this course, the focus is on three main topics: Corpus Generation, and website
localization. The course also aims to introduce students to the theories of
computer-based language teaching and different education technologies in
general and to train students to deal with other technologies, whether
computers or display devices. Or distance education media, and practically use them in teaching and learning languages. It introduces the concept of
machine translation to students. Highlight the need for machine
translation. It also discusses the achievements made in this field of
translation studies.
Intended learning outcomes
• Learn about the
theoretical and practical aspects of machine translation
• Learn how to use
examples of computer and Internet translation techniques
• Introducing the latest
technologies available worldwide
• Teaching the student
different aspects of machine translation.
• Teaching students how
to use computers and smartphones to search for information.
• The use of electronic
learning resources such as electronic dictionaries, encyclopedias, and the
automatic translation, and their role in language learning and translation
• Provide the student
with sufficient experience in the use of this multimedia in learning the
language after graduation.
Teaching and learning methods
Lecture, explanation and examples in the classroom.
A
theoretical presentation and then application on the computer aided software
and skills that can be used, accompanied by real examples and practical
exercises carried out by the student
Methods of assessments
Evaluation No. Evaluation method Duration
Weight %When (weeks)Remarks
First evaluation written translation exam 20 %40 After Week 4
Second evaluation translating a text by TM 20 %60 After Week 7
Final evaluation Report 60 %100 After
Week 14
Total 100 %100
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Main Content
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Reading /
References / Notes
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weeks
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Content
:Topics (subject matter)for each week
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1
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Introduction to machine
translation.
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2
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Basic concepts of machine
translation.
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3
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Misconceptions about machine
translation.
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4
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The
most important systems ofMT
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5
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Rule-based
Machine translation
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6
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Advantages & disadvantages of
rulebased MT
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7
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Transfer based machine
translation.
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8
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Advantages & disadvantages of the
program
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9
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Example based machine translation
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10
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Differences between Example&
Rule MTs
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11
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Statistical based MT
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12
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Neural
based MT
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John Hutchins (Latest Development in Machine Translation
Technology: Beginning a New Era in MT Research) (Reflections on the History and
Present State of Machine Translation) University of East Angila, Norwich,
England.
IJCSI International Journal of Computer Science Issues,
Vol. 11, Issue 5, No 2, September 2014
Kyunghyun Cho, Bart van Merrienboer, CaglarGulcehre,
FethiBougares, HolgerSchwenk, and YoshuaBengio. 2014. Learning phrase
representations using rnn encoder-decoder for statistical machinetranslation.
In Proceedings of the Empiricial Methods in Natural Language Processing (EMNLP2014),
October. to appear
