0150 - 語料庫語言學與自然語言處理 英授 Taught in English

Corpus linguistics and Natural Language Processing

教育目標 Course Target

Corpus Linguistics (CL) is a scientific method of language analysis using electronic tools. It requires knowledge of linguistic theories, quantitative statistics and data processing. Natural Language Processing (NLP), combining the power of artificial intelligence, computational linguistics and computer science, could help computers read text by simulating the human ability to understand language.
The application of methodologies of NLP has led to advances in fields such as lexicography or corpus linguistics, descriptive grammar, and language teaching and learning. In other words, NLP is not only about mathematics, but also about linguistics. Meanwhile, corpora play an essential role in a wide range of linguistic investigations as well as NLP research.
This course aims to help students understand the importance and trends of Corpus Linguistics and Natural Language Processing fields. In addition to providing an overview of both the theoretical foundation of Corpus Linguistics and the fundamental methods of Natural Language Processing (NLP), this cross disciplinary course places more emphasis on hands-on learning. Students will be introduced existing major corpora, software packages and analyzing methodologies. Students will learn to examine practical examples by using some of the most common techniques in corpus analysis. Importantly, students will learn some basic computer programming skills. Eventually, students will have opportunities to build their own corpora using NLP methods as well as practically apply corpora in language analysis and learning.

Corpus Linguistics (CL) is a scientific method of language analysis using electronic tools. It requires knowledge of linguistic theories, quantitative statistics and data processing. Natural Language Processing (NLP), combining the power of artistic intelligence, computer linguistics and computer science, could help computers read text by simulating the human ability to understand language.
The application of methods of NLP has led to advances in fields such as lexicography or corpus linguistics, descriptive grammar, and language teaching and learning. In other words, NLP is not only about mathematics, but also about linguistics. Meanwhile, corpora play an essential role in a wide range of linguistic investigations as well as NLP research.
This course aims to help students understand the importance and trends of Corpus Linguistics and Natural Language Processing fields. In addition to providing an overview of both the theoretical foundation of Corpus Linguistics and the fundamental methods of Natural Language Processing (NLP), this cross discipline course places more emphasis on hands-on learning. Students will be introduced existing major corporate, software packages and analyzing methods. Students will learn to examine practical examples by using some of the most common techniques in corpus analysis. Importantly, students will learn some basic computer programming skills. Eventually, students will have opportunities to build their own corpora using NLP methods as well as practically apply corpora in language analysis and learning.

參考書目 Reference Books

No textbooks are required for this course. Online resources and handouts will be provided for topics to be covered in the course. Some additional readings will be supplemented.

Sample important studies:
Steven Bird, Ewan Klein & Edward Loper. 2009. Natural Language Procesing with Python. O’Reilly Media.
Kilgarriff, Adam. 2005. Language is never, ever, ever, random. Corpus Linguistics and Linguistic Theory, 1(2). 263–275.
Luke Curtis Collins. 2019. Corpus linguistics for online communication- a guide for research. London: Routledge.
McEnery, Tony & Andrew Hardie. 2012. Corpus Linguistics: Method, Theory and Practice. Cambridge University Press.
Scott, Mike & Christopher Tribble. 2006. Textual Patterns: Key words and corpus analysis in language education. John Benjamins.
Weisser, Martin. 2016. Practical Corpus Linguistics: An Introduction to Corpus-Based Language Analysis. Oxford: Wiley Blackwell.
William Crawford & Eniko Csomay. 2016. Doing Corpus Linguistics. London: Routledge.

No textbooks are required for this course. Online resources and handsets will be provided for topics to be covered in the course. Some additional readings will be supplemented.

Sample important studies:
Steven Bird, Ewan Klein & Edward Loper. 2009. Natural Language Procesing with Python. O’Reilly Media.
Kilgarriff, Adam. 2005. Language is never, ever, ever, random. Corpus Linguistics and Linguistic Theory, 1(2). 263–275.
Luke Curtis Collins. 2019. Corpus linguistics for online communication- a guide for research. London: Routledge.
McEnery, Tony & Andrew Hardie. 2012. Corpus Linguistics: Method, Theory and Practice. Cambridge University Press.
Scott, Mike & Christopher Tribble. 2006. Textual Patterns: Key words and corpus analysis in language education. John Benjamins.
Weisser, Martin. 2016. Practical Corpus Linguistics: An Introduction to Corpus-Based Language Analysis. Oxford: Wiley Blackwell.
William Crawford & Eniko Csomay. 2016. Doing Corpus Linguistics. London: Routledge.

評分方式 Grading

評分項目
Grading Method
配分比例
Percentage
說明
Description
Attendance and participation
Attendance and participation
15
Group presentations
Group presentations
40 20% group & 20% individual
Peer feedback & Activities
Peer feedback & Activities
20
Final project
Final project
25 (Note: The percentage of the course evaluation is subject to possible adjustments.)

授課大綱 Course Plan

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課程資訊 Course Information

基本資料 Basic Information

  • 課程代碼 Course Code: 0150
  • 學分 Credit: 3-0
  • 上課時間 Course Time:
    Tuesday/7,8,9[LAN010]
  • 授課教師 Teacher:
    陳玫樺
  • 修課班級 Class:
    外文系3,4
  • 選課備註 Memo:
    網路選課
選課狀態 Enrollment Status

目前選課人數 Current Enrollment: 32 人

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