シラバス参照

開講年度(Academic Year) 2021 
科目コード/科目名
(Course Code / Course Title)
VV306/通訳翻訳テクノロジー論
(Technologies for Translators and Interpreters) 
テーマ/サブタイトル等
(Theme / Subtitle)
Theoretical and Practical Foundation for Advanced Technologies in Translation and Interpretation  
担当者 (Instructor) 山田 優(YAMADA MASARU) 
時間割 (Class Schedule) 春学期 (Spring Semester) 木曜日(Thu) 5時限(Period 5) 8503(Room)
単位 (Credit) 2単位(2 Credits) 
科目ナンバリング
(Course Number)
ICC6243 
使用言語
(Language)
その他
(Others) 
備考 (Notes)  
テキスト用コード (Text Code) VV306 



授業の
目標
Course
Objectives
This course aims at equipping students with basic knowledge and experiences of technologies utilized by linguists such as professional translators and project managers. The technologies to be covered in the course are Neural Machine Translation, including customization of it, post-editing and pre-editing tourniquets, orthodox CAT tools such as translation memory, terminology management tools, subtitling tools. Through the course, students are also expected to learn how to use technologies for research purposes, techniques such as corpus analysis, text mining, translation process research data collection methods.  
 
授業の
内容
Course
Contents
The course consists of a) understanding of the basic mechanism of AI-related NMT such as RNN, Transformer, word embedding, b) mastering CAT tools including translation memory, terminology management tools, including effective practice in post-editing and pre-editing, c) being familiar with customizing machine translation, including domain adaptation and corpus data cleansing, d) being knowledgeable of project management and localization tool. The theme also covers post-editing, controlled language, speech recognition, data analyses, and privacy protection.
Throughout the course, students will be asked to read relevant articles, join a discussion, and complete assignments as specified. This course will be interactive and participative, in which students will be requested to study actively each subject and reflect what they learn onto their translation projects to be assigned in classes.  
 
授業計画
Course
Schedule
1. Introduction 
2. CAT tools 1 
3. CAT tools 2 
4. Post-editing 1 
5. Post-editing 2 
6. Machine translation 1: History 
7. Machine translation 2 Theory 
8. Machine translation 3: Domain adaptation 
9. Terminology management and Project Management 
10. Data cleansing, data mining, corpus analysis 
11. Data-driven research and translation process research 1 
12. Data-driven research and translation process research 2 
13. Total workbench environment 
14. Review 
授業時間外
(予習・復習
等)の学習
Study
Required
Outside
of Class
Reading assignments will be given respectively. Students will be asked to join discussions on the assigned articles. 
成績評価
方法・基準
Evaluation
種類(Kind) 割合(%) 基準(Criteria)
平常点(In-class Points) 100  %
Reflection paper(20%) 、Homework assignments(30%) 、Project-based assignement(50%)
テキスト
Textbooks
Articles and handouts will be provided in class.
参考文献
Readings
No 著者名
(Author/Editor)
書籍名
(Title)
出版社
(Publisher)
出版年
(Date)
ISBN/ISSN
1. Minako O'Hagan  The Routledge Handbook of Translation and Technology   Routledge  2019  9781138232846 
2. 坂西優・山田優  『自動翻訳大全』   三才ブックス  2020  4866731931 
3. ティエリー・ポイボー, 中澤 敏明  『機械翻訳:歴史・技術・産業』   森北出版  2020  4627851812 
その他(Others)
その他
(HP等)
Others
(e.g. HP)
https://researchmap.jp/yamada_trans 
注意事項
Notice
 


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