Generating Learner-Like Morphological Errors in Russian

Markus Dickinson

Proceedings of COLING'10.

To speed up the process of categorizing learner errors and obtaining data for languages which lack error-annotated data, we describe a linguistically-informed method for generating learner-like morphological errors, focusing on Russian. We outline a procedure to select likely errors, relying on guiding stem and suffix combinations from a segmented lexicon to match particular error categories and relying on grammatical information from the original context.

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Bibtex entry:

  author =       {Markus Dickinson},
  title =        {Generating Learner-Like Morphological Errors in Russian},
  booktitle =    {Proceedings of the 23nd International Conference on Computational Linguistics (COLING-10)},
  pages=         {},
  address =      {Beijing},
  url =          {\url{}},
  year =         {2010}