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• W2142523187 abstract "We describe a novel approach for inducing unsupervised part-of-speech taggers for languages that have no labeled training data, but have translated text in a resource-rich language. Our method does not assume any knowledge about the target language (in particular no tagging dictionary is assumed), making it applicable to a wide array of resource-poor languages. We use graph-based label propagation for cross-lingual knowledge transfer and use the projected labels as features in an unsupervised model (Berg-Kirkpatrick et al., 2010). Across eight European languages, our approach results in an average absolute improvement of 10.4% over a state-of-the-art baseline, and 16.7% over vanilla hidden Markov models induced with the Expectation Maximization algorithm." @default.
• W2142523187 created "2016-06-24" @default.
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• W2142523187 date "2011-06-19" @default.
• W2142523187 modified "2023-10-13" @default.
• W2142523187 title "Unsupervised Part-of-Speech Tagging with Bilingual Graph-Based Projections" @default.
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