Goals and Objectives
and you know how to take these differences into account when designing computational models of morphology.
Author(s)
Description of the Training Materials
(Sub)discipline, topic, language(s) |
computational morphology, finite-state methods English |
Keywords |
morphology, weighted finite-state networks, two-level rules, xfst, lexc, twolc |
CLARIN resources |
HFST: http://urn.fi/urn:nbn:fi:lb-20140730183 Kielipankki morphologies: http://urn.fi/urn:nbn:fi:lb-2018041703 |
Structure and duration | The course comprises seven lectures, based on the original course. The lectures are tutorial-like, showing how HFST tools can be used for implementing finite-state morphologies. There are assignments at the end of each lecture. This is a self-study course, so there are no time limits. Solutions to the assignments are not available, since the original course is still lectured each year. |
Target audience | Prerequisites include foundations of general linguistics and basic knowledge on how to use a computer. Some programming experience is desirable. Knowledge of Natural Language Processing ( ) is also a plus. |
Facilities required |
The course is accessible also at https://notebooks.csc.fi. Logging to the service requires Haka or CSC account or visitor account via CSC/SAFMORIL helpdesk. |
Format |
Self-study course containing seven lectures implemented as Jupyter notebooks. Tutorial-type lectures with assignments at the end. |
Course(s) in which the training material was used | The training material is taught as part of the “Computational Morphology” (LDA-T302) by Mathias Creutz in the Master’s programme Linguistic Diversity and Digital Humanities at the University of Helsinki for 5 ECTS. |
Licence and (re)use | CC BY 4.0: https://creativecommons.org/licenses/by/4.0/ |
Creation date |
First GitHub repository commit, Nov 29, 2018 |
Last modification date | A stable release was made on 25 June 2021 |
Experience with Using CLARIN Resources in Teaching
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Additional Information and Resources
See the info page of the course: http://urn.fi/urn:nbn:fi:lb-2021053003