Multilevel Text Normalization with Sequence-to-Sequence Networks and Multisource Learning

27 Mar 2019Tatyana RuzsicsTanja Samardžić

We define multilevel text normalization as sequence-to-sequence processing that transforms naturally noisy text into a sequence of normalized units of meaning (morphemes) in three steps: 1) writing normalization, 2) lemmatization, 3) canonical segmentation. These steps are traditionally considered separate NLP tasks, with diverse solutions, evaluation schemes and data sources... (read more)

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