日本語 English
| 開講年度/ Academic YearAcademic Year |
20242024 |
| 科目設置学部/ CollegeCollege |
異文化コミュニケーション研究科/Graduate School of Intercultural CommunicationGraduate School of Intercultural Communication |
| 科目コード等/ Course CodeCourse Code |
VV306/VV306VV306 |
| テーマ・サブタイトル等/ Theme・SubtitleTheme・Subtitle |
Theoretical and Practical Foundation for Advanced Technologies in Translation and Interpretation |
| 授業形態/ Class FormatClass Format |
対面（一部オンライン）/Face-to-face (partially online)Face-to-face (partially online) |
| 授業形態（補足事項）/ Class Format (Supplementary Items)Class Format (Supplementary Items) |
オンライン会議の機能を通してしか得られないサービス（リアルタイム翻訳、文字起こし等）の実践と理論を学ぶために全授業回のうち2回はオンラインで実施する（7・8回目の授業）。 なお、オンライン実施回に変更が生じる場合は、授業内またはCanvas LMS等で周知する。 |
| 授業形式/ Class StyleCampus |
演習・ゼミ/SeminarSeminar |
| 校地/ CampusCampus |
池袋/IkebukuroIkebukuro |
| 学期/ SemesterSemester |
秋学期/Fall semesterFall semester |
| 曜日時限・教室/ DayPeriod・RoomDayPeriod・Room |
木5･8301/Thu.5･8301 Thu.5･8301 |
| 単位/ CreditCredit |
22 |
| 科目ナンバリング/ Course NumberCourse Number |
ICC6243 |
| 使用言語/ LanguageLanguage |
その他/OthersOthers |
| 履修登録方法/ Class Registration MethodClass Registration Method |
科目コード登録/Course Code RegistrationCourse Code Registration |
| 配当年次/ Grade (Year) RequiredGrade (Year) Required |
配当年次は開講学部のR Guideに掲載している科目表で確認してください。配当年次は開講学部のR Guideに掲載している科目表で確認してください。 |
| 先修規定/ prerequisite regulationsprerequisite regulations |
|
| 他学部履修可否/ Acceptance of Other CollegesAcceptance of Other Colleges |
履修登録システムの『他学部・他研究科履修不許可科目一覧』で確認してください。 |
| 履修中止可否/ course cancellationcourse cancellation |
－（履修中止制度なし/ No system for cancellation) |
| オンライン授業60単位制限対象科目/ Online Classes Subject to 60-Credit Upper LimitOnline Classes Subject to 60-Credit Upper Limit |
|
| 学位授与方針との関連/ Relationship with Degree PolicyRelationship with Degree Policy |
各授業科目は、学部・研究科の定める学位授与方針（DP）や教育課程編成の方針（CP）に基づき、カリキュラム上に配置されています。詳細はカリキュラム・マップで確認することができます。 |
| 備考/ NotesNotes |
2024.3.25付シラバス変更（曜日時限） 【変更前】春学期 2024.4.20付シラバス変更（担当者） 【変更前】未定 2024.4.26付シラバス変更（曜日時限） 【変更前】未定 |
| テキスト用コード/ Text CodeText Code |
VV306 |
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.
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.
※Please refer to Japanese Page for details including evaluations, textbooks and others.
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.
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.
| 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 |
板書 /Writing on the Board
スライド（パワーポイント等）の使用 /Slides (PowerPoint, etc.)
上記以外の視聴覚教材の使用 /Audiovisual Materials Other than Those Listed Above
個人発表 /Individual Presentations
グループ発表 /Group Presentations
ディスカッション・ディベート /Discussion/Debate
実技・実習・実験 /Practicum/Experiments/Practical Training
学内の教室外施設の利用 /Use of On-Campus Facilities Outside the Classroom
校外実習・フィールドワーク /Field Work
上記いずれも用いない予定 /None of the above
Reading assignments will be given respectively. Students will be asked to join discussions on the assigned articles.
| 種類 (Kind) | 割合 (%) | 基準 (Criteria) |
|---|---|---|
| 平常点 (In-class Points) | 100 |
Reflection paper(20%) Homework assignments(30%) Project-based assignments(50%) |
| 備考 (Notes) | ||
| その他 (Others) | |||||
|---|---|---|---|---|---|
| Articles and handouts will be provided in class. |
| 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 |
https://researchmap.jp/yamada_trans
全授業回のうち3回のみオンライン実施（実施回については「Canvas LMS」で指示する）。