Computer Models of Language and Applications

Postgraduate course

Course description

Objectives and Content

The content of the course may vary with the lecturer, but will focus on theories and methods based on Artificial Intelligence for the development of linguistic models and applications. Examples of relevant topics in modeling are machine learning and classification algorithms based on rule induction, neural networks, nearest neighbor, etc. Examples of language technology applications are interfaces between human and machine, machine translation, proofreading, information retrieval, and information technology aids for persons with disabilities.

This course is also suitable for students in e.g. information science and digital humanities.

Learning Outcomes

Knowledge

The candidate can ...

  • state principles and methods for modeling of linguistic categories and linguistic processing
  • state principles and methods for digital natural language processing

Skills

The candidate can...

  • build and test models for language processes and for applications, based on linguistic data and existing algorithms

General competence

The candidate can...

  • report on a modeling experiment, including design, data collection, tool selection, production of results, interpretation and conclusion
  • critically evaluate the utility of models for insight into human language processing and for practical applications in society.

ECTS Credits

15

Level of Study

Master

Semester of Instruction

Fall

Place of Instruction

Bergen
Required Previous Knowledge
Basic knowledge and programming skills in Python.
Recommended Previous Knowledge
LING123 and DASPSTAT or equivalents are strongly advised.
Credit Reduction due to Course Overlap
DASP303 (15 credits), DASP304 (15 credits)
Access to the Course
Open to all who have been admitted to study at master's level at UiB.
Teaching and learning methods
Lectures, independent exercises on computers and supervision.
Compulsory Assignments and Attendance

Supervision in connection to the writing of the term paper is obligatory, and must consist of at least one meeting with the supervisor, who must be given access to a draft and a literature list a week in advance.

Mandatory activities are valid in the teaching semester.

Forms of Assessment
Supervised term paper reporting on an individual modeling or programming task. The paper should have about 5000 words (not counting references, appendices etc.)
Grading Scale
A-F
Assessment Semester
Fall. Assessment only in the teaching semester.
Reading List
The litterature consists consists of an introduction to modeling methods that are used in this field, with a special emphasis on cognitive modeling and machine learning and with regard to possible applications. Computers are used in the exercises.
Course Evaluation
Course evaluation will be conducted in accordance with the University of Bergen's quality assurance system.
Examination Support Material
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Programme Committee
Programme Committee for Linguistics
Course Coordinator
Programme Committee for Linguistics
Course Administrator
Department of Linguistic, Literary and Aesthetic Studies.