Climbing the tower of babel: Unsupervised multilingual learning
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Author(s) •
Snyder, Benjamin
Barzilay, Regina
Date Issued
June 2010
Journal
Proceedings of the 27th International Conference on Machine Learning (ICML-10)
Publisher
Omnipress
Citation
Snyder, Benjamin, and Regina Barzilay. “Climbing the Tower of Babel: Unsupervised Multilingual Learning.” Proceedings of the 27th International Conference on Machine Learning (ICML-10). Haifa, Israel:29-36.
Version
Author's final manuscript
Abstract
For centuries, scholars have explored the deep
links among human languages. In this paper,
we present a class of probabilistic models
that use these links as a form of naturally
occurring supervision. These models allow
us to substantially improve performance for
core text processing tasks, such as morphological
segmentation, part-of-speech tagging,
and syntactic parsing. Besides these traditional
NLP tasks, we also present a multilingual
model for the computational decipherment
of lost languages.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
http://www.icml2010.org/papers/905.pdf