Dialog and Natural Language Generation (P00883)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : INF-P-DNLG

This course will provide: -An introduction to the theory and practice of computational approaches to natural language generation. The course will cover common approaches to content selection and organization, sentence planning, and grammar formalisms and algorithms for content realisation. The course will cover both symbolic, knowledge based approaches to generation, as well as more recent statistical techniques. -Exposure to techniques and tools used to develop practical systems that can communicate with users; -Insight into many open research problems in applications of natural language generation, e.g., summarization, machine translation, and response generation for dialogue systems. -An understanding of evaluation methods used in this field.

Entry Requirements

? Pre-requisites : Introduction to Computational Linguistics For Informatics PG students only, or by special permission of the School. Programming Experience useful, but not mandatory.

? Co-requisites : Data Intensive Linguistics is recommended (but not required).

Subject Areas

Home subject area

Language Processing, (School of Informatics, Schedule O)

Other subject areas

Speech Processing, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
07/01/2008	10:00	10:50			4 Buccleuch Place, Conference Suite

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	10:00	10:50	Central
Lecture	Thursday	10:00	10:50	Central

Summary of Intended Learning Outcomes

It is anticipated that students who successfully complete DNLG will be able to:
-Select and apply the theories and techniques covered in the module to solve natural language generation problems that occur in practical applications.
-Critically appraise the strengths and weaknesses of approaches described in current research papers and express their ideas coherently and logically in classroom discussion
-Structure a presentation on a course topic and communicate their comprehension of key issues and concepts by giving an oral presentation to peers
-Define a research question and undertake an extended practical project and produce a written report.
-The ability to apply the algorithms and techniques developed in the module to develop new methods in natural language generation.