Climbing the Tower of Babel: Unsupervised Multilingual Learning
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.
Cite
Text
Snyder and Barzilay. "Climbing the Tower of Babel: Unsupervised Multilingual Learning." International Conference on Machine Learning, 2010.Markdown
[Snyder and Barzilay. "Climbing the Tower of Babel: Unsupervised Multilingual Learning." International Conference on Machine Learning, 2010.](https://mlanthology.org/icml/2010/snyder2010icml-climbing/)BibTeX
@inproceedings{snyder2010icml-climbing,
title = {{Climbing the Tower of Babel: Unsupervised Multilingual Learning}},
author = {Snyder, Benjamin and Barzilay, Regina},
booktitle = {International Conference on Machine Learning},
year = {2010},
pages = {29-36},
url = {https://mlanthology.org/icml/2010/snyder2010icml-climbing/}
}