Handling Normalization Issues for Part-of-Speech Tagging of Online Conversational Text - Archive ouverte HAL
Communication Dans Un Congrès Année : 2018

Handling Normalization Issues for Part-of-Speech Tagging of Online Conversational Text

Résumé

For the purpose of POS tagging noisy user-generated text, should normalization be handled as a preliminary task or is it possible to handle misspelled words directly in the POS tagging model? We propose in this paper a combined approach where some errors are normalized before tagging, while a Gated Recurrent Unit deep neural network based tagger handles the remaining errors. Word embeddings are trained on a large corpus in order to address both normalization and POS tagging. Experiments are run on Contact Center chat conversations, a particular type of formal Computer Mediated Communication data.
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Dates et versions

hal-01943391 , version 1 (03-12-2018)

Identifiants

  • HAL Id : hal-01943391 , version 1

Citer

Géraldine Damnati, Jeremy Auguste, Alexis Nasr, Delphine Charlet, Johannes Heinecke, et al.. Handling Normalization Issues for Part-of-Speech Tagging of Online Conversational Text. Eleventh International Conference on Language Resources and Evaluation (LREC 2018), 2018, Miyazaki, Japan. ⟨hal-01943391⟩
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