Applying Support Vector Machines to POS tagging of the Ainu Language

Authors

  • Karol Nowakowski Kitami Institute of Technology
  • Michal Ptaszynski Kitami Institute of Technology
  • Fumito Masui Kitami Institute of Technology
  • Yoshio Momouchi Hokkai-Gakuen University

DOI:

https://doi.org/10.33011/computel.v2i.449

Abstract

We describe our attempt to apply a state-of-the-art sequential tagger – SVMTool – in the task of automatic part-of-speech annotation of the Ainu language, a critically endangered language isolate spoken by the native inhabitants of northern Japan. Our experiments indicated that it performs better than the custom system proposed in previous research (POST-AL), especially when applied to out-of-domain data. The biggest advantage of the model trained using SVMTool over the POST-AL tagger is its ability to guess part-of-speech tags for OoV words, with the accuracy of up to 63%.

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Published

2019-02-26