Papers by Ana Valeria González-Garduño

1 papers
Unsupervised Induction of Linguistic Categories with Records of Reading, Speaking, and Writing (N18-1)

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Challenge: a few researchers have shown that data traces from human processing can be used to improve NLP models.
Approach: They propose to use data readily available for most languages to improve unsupervised induction . they find that english unsupervised POS induction achieves an error reduction of 1.5% .
Outcome: The proposed model improves on Ontonotes domains with a word embeddings.

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