Semi-automatic acquisition of two-level morphological rules for iban language

  • Authors:

  • Suhaila Saee;Lay-Ki Soon;Tek Yong Lim;Bali Ranaivo-Malançon;Enya Kong Tang

  • Affiliations:

  • Faculty of Computer Science and IT, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia,Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia;Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia;Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia;Faculty of Computer Science and IT, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia;School of Computer Science and Information Technology, Linton University College, Mantin, Negeri Sembilan, Malaysia

  • Venue:
  • CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
  • Year:
  • 2013

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Abstract

We describe in this paper a semi-automatic acquisition of morphological rules for morphological analyser in the case of under-resourced language, which is Iban language. We modify ideas from previous automatic morphological rules acquisition approaches, where the input requirements has become constraints to develop the analyser for under-resourced language. This work introduces three main steps in acquiring the rules from the under-resourced language, which are morphological data acquisition, morphological information validation and morphological rules extraction. The experiment shows that this approach gives successful results with 0.76 of precision and 0.99 of recall. Our findings also suggest that the availability of linguistic references and the selection of assorted techniques for morphology analysis could lead to the design of the workflow. We believe this workflow will assist other researchers to build morphological analyser with the validated morphological rules for the under-resourced languages.