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Hits 1 – 2 of 2
1
Adding More Languages Improves Unsupervised Multilingual Part-of-Speech Tagging: A Bayesian Non-Parametric Approach
Barzilay, Regina
;
Naseem, Tahira
;
Snyder, Benjamin
;
Eisenstein, Jacob
In: MIT web domain (2009)
Abstract:
We investigate the problem of unsupervised part-of-speech tagging when raw parallel data is available in a large number of languages. Patterns of ambiguity vary greatly across languages and therefore even unannotated multilingual data can serve as a learning signal. We propose a non-parametric Bayesian model that connects related tagging decisions across languages through the use of multilingual latent variables. Our experiments show that performance improves steadily as the number of languages increases. ; National Science Foundation (U.S.) (CAREER grant IIS-0448168) ; National Science Foundation (U.S.) (CAREER grant IIS- 0835445)
URL:
http://hdl.handle.net/1721.1/58926
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2
Multilingual Part-of-Speech Tagging Two Unsupervised Approaches
Naseem, Tahira
;
Snyder, Benjamin
;
Eisenstein, Jacob
...
In: JAIR (2009)
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