Papers by Kelsey Ball

1 papers
Part-of-Speech Tagging for Code-Switched, Transliterated Texts without Explicit Language Identification (D18-1)

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Challenge: Code-switching is a challenge for NLP due to the lack of representative data for training models.
Approach: They propose a model that is trained exclusively on monolingual resources but can be applied to unseen code-switched text at inference time.
Outcome: The proposed model outperforms standard models on Hindi-English part-of-speech tagging and on unannotated code-switched text with alternate scripts.

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