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LDA-T3101 Computational Morphology, 5 cr 
Code LDA-T3101  Validity 01.01.2017 -
Name Computational Morphology  Abbreviation Computational M 
Scope5 cr   
TypeAdvanced studies
TypeCourse   
  GradingGeneral scale 
  no
    Can be taken more than onceno
Unit Master’s programme Linguistic Diversity in the Digital Age 

Teachers
Name
Mathias Creutz 

Description
Target group 

The course belongs to the MA Programme Linguistic Diversity in the Digital Age

  • study track: language technology
  • modules: Studies in Language Technology (LDA-T3100), Essentials in Language Technology (LDA-TA500), Comprehensive specialization in Language Technology (LDA-TB500)

This is an obligatory course for students of the study track in language technology, and elective for students of modules LDA-TA500 and LDA-TB500 

The course is available to students from other study tracks and degree programmes.

 

 

 
Timing 

Students are advised to take this course in year 1 (semester 2). The course is offered every year during the spring term in period III or IV

 
Learning outcomes 

After successfully completing the course

  • you can explain basic theory on finite-state automata and transducers,
  • you are able to design morphological lexica using finite-state technology,
  • you know how to write morpho-phonological rules in a finite-state framework,
  • you can apply machine learning methods to building models of morphology,
  • you understand the diversity of morphological structure in different languages and you know how to take these differences into account when designing computational models of morphology.
 
Completion methods 
  • The course comprises lectures and individual exercises.
  • You also complete your own project work, which you document and present in class.
  • Additionally, there may be a final exam.
  • Some sessions require student attendance.
 
Prerequisites 
  • Morphology and syntax or equivalent (BA level)
  • Programming for linguists or equivalent (BA level)
  • Mathematics for linguists or equivalent (BA level)
  • Machine learning for linguists or equivalent (BA level)
 
Recommended optional studies 
  • Linguistics in the digital age (MA level)
  • Computational Syntax (MA level)
  • Computational Semantics (MA level)
 
Contents 
  • This course teaches you models and methods for automatic morphological analysis and generation. Different frameworks will be studied, such as rule-based finite-state technology and supervised and unsupervised learning of morphology.
  • The diversity of morphological structure in different languages is demonstrated together with suggestions on how to take these differences into account when designing computational models of morphology.
 
Study materials and literature 
  • Kenneth Beesley & Lauri Karttunen, Finite State Morphology (CSLI Publications, 2003)
  • Web material and material distributed on the course
 
Activities and teaching methods in support of learning 
  • There are lectures and exercise sessions.
  • Learning is promoted through hands-on assignments, such as pre-planned exercises and a project work that can be tuned towards the student’s own interests.
  • Exercises, instructions and additional course material are published on a web-based learning platform (Moodle).
 
Assessment practices and criteria 

Grading follows the standard scale 0 – 5.

The following aspects are taken into account in grading

  • Performance in the exercises
  • Performance in the project work
  • Performance in the final exam
  • Activity during lectures and exercise sessions.
 


Current and future instruction
Functions Name Type cr Teacher Schedule
registration period has not begun Computational Morphology Computational Morphology  Course  Mathias Creutz 
15.01.20 -26.02.20 wed 12.15-13.45
17.01.20 -28.02.20 fri 08.15-09.45

Future examinations
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