Papers with decipherment-based approach

1 papers
A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages (N19-1)

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Challenge: Unsupervised part of speech (POS) tagging is often framed as a clustering problem, but taggers need to ground their clusters as well.
Approach: They propose an approach for low-resource unsupervised part of speech (POS) tagging that yields fully grounded output and requires no labeled training data.
Outcome: The proposed method achieves reasonable performance across languages, including Sinhalese and Kinyarwanda, with no labeled training data.

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