Normalizing tweets with edit scripts and recurrent neural embeddings

@inproceedings{Chrupala2014NormalizingTW,
  title={Normalizing tweets with edit scripts and recurrent neural embeddings},
  author={Grzegorz Chrupala},
  booktitle={ACL},
  year={2014}
}
Tweets often contain a large proportion of abbreviations, alternative spellings, novel words and other non-canonical language. These features are problematic for standard language analysis tools and it can be desirable to convert them to canonical form. We propose a novel text normalization model based on learning edit operations from labeled data while incorporating features induced from unlabeled data via character-level neural text embeddings. The text embeddings are generated using an… CONTINUE READING
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