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  6. CS50AD: Natural Language Generation

CS50AD: NATURAL LANGUAGE GENERATION (2015-2016)

Last modified: 25 Mar 2016 11:39


Course Overview

The aim of the course is to introduce students who have some background in computing to (1) the varied aims for which Natural Language Generation (NLG) is pursued, (2) the main rule based and statistical methods that are used in NLG, and (3) some of the main NLG algorithms and systems. The course will cover NLG both as a theoretical enterprise (e.g., for constructing models of language production) and as practical language engineering, paying particular attention to the link between NLG and data science. Some programming experience is expected.

Course Details

Study Type Postgraduate Level 5
Term First Term Credit Points 15 credits (7.5 ECTS credits)
Campus Old Aberdeen Sustained Study No
Co-ordinators
  • Dr Advaith Siddharthan
  • Professor Kees Van Deemter

Qualification Prerequisites

None.

What courses & programmes must have been taken before this course?

  • Computing Science (CS) (Studied)
  • Any Postgraduate Programme (Studied)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The course will cover topics including:
1. Introduction: the varied aims of NLG; some examples of practical NLG systems
2. The classic NLG pipeline
3. The revised Data2Text pipeline, including data analysis and interpretation
4. Highlight: Data analysis and interpretation
5. Highlight: Generation of Referring Expressions
6. Highlight: Grammars and Linguistic Realisation
7. Evaluation methods for NLG algorithms and systems
8. Algorithmic models of human language production
9. Links with neighbouring areas of NLP: visualisation; summarisation; machine translation; dialogue

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

1st Attempt: 1 two-hour written examination (75%); continuous assessment (25%)

Resit: Candidates only resit those components (written examination, continuous assessment) which the failed at first attempt. Written examination at resit is 1 two-hour paper.

Formative Assessment

There are no assessments for this course.

Feedback

None.

Course Learning Outcomes

None.
 

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