Improving historical spelling normalization with bi-directional LSTMs and multi-task learning

Contribution for newspaper or weekly magazine, Preprint English OPEN
Bollmann, Marcel; Søgaard, Anders;
  • Subject: Computer Science - Computation and Language

Natural-language processing of historical documents is complicated by the abundance of variant spellings and lack of annotated data. A common approach is to normalize the spelling of historical words to modern forms. We explore the suitability of a deep neural network a... View more
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    Inferred by OpenAIRE
    norma software on GitHub
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