This unit entry is for students who completed this unit in 2016 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

ATS3672 - Computational linguistics: An introduction

6 points, SCA Band 1, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Arts

Organisational Unit

Linguistics

Coordinator(s)

Dr Simon Musgrave

Offered

Not offered in 2016

Synopsis

This unit introduces students to the field of computational linguistics, an increasingly important area within linguistics. The course will include an overview of the development of the field and its relation to other developments in linguistics and outside of it. The main approaches used, both rule-based and probabilistic will be discussed and the basic techniques in each approach will be studied and practised. The major applications of computational techniques in linguistics, including machine translation, data mining and corpus linguistics will also be examined along with current achievements in these areas.

Outcomes

On completion of this unit, students will have gained an understanding of:

the history of the use of computers in linguistics
the intellectual context of such work
the computational implementation of rules in phonology, morphology and syntax
the principles of probabilistic analysis of language
and the application of computational techniques to various real-world problems.

Students will also have gained experience in:

using simple software for linguistic analysis including parsing
using software for quantitative analysis of large bodies of language data
and designing and implementing a small research project using computational techniques.

Students will also develop their skills in:

rigorous analysis of language data
critical thinking
and developing research projects.

In addition, students at level 3 will develop their skills in presenting the results of their work.

Assessment

Within semester assessment: 100%

Workload requirements

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. A unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.