Applying Support Vector Machines to POS tagging of the Ainu Language


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



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%.