Climbing the tower of babel: Unsupervised multilingual learning
Author(s)Snyder, Benjamin; Barzilay, Regina
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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.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 27th International Conference on Machine Learning (ICML-10)
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.
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