Local String Transduction as Sequence Labeling

Joana Ribeiro, Shashi Narayan, Shay Cohen, Xavier Carreras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We show that the general problem of string transduction can be reduced to the problem of sequence labeling. While character deletions and insertions are allowed in string transduction, they do not exist in sequence labeling. We show how to overcome this difference. Our approach can be used with any sequence labeling algorithm and it works best for problems in which string transduction imposes a strong notion of locality (no long range dependencies). We experiment with spelling correction for social media, OCR correction, and morphological inflection, and we see that it behaves better than seq2seq models and yields state-of-the-art results in several cases.
Original languageEnglish
Title of host publication27th International Conference on Computational Linguistics (COLING 2018)
Place of PublicationSanta Fe, New-Mexico, USA
PublisherAssociation for Computational Linguistics (ACL)
Number of pages12
ISBN (Electronic)978-1-948087-50-6
Publication statusPublished - 31 Aug 2018
Event27th International Conference on Computational Linguistics - Sante Fe, United States
Duration: 20 Aug 201825 Aug 2018


Conference27th International Conference on Computational Linguistics
Abbreviated titleCOLING 2018
Country/TerritoryUnited States
CitySante Fe
Internet address


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