Learning Bilingual Word Representations by Marginalizing Alignments

Tomáš Kočiský; Karl Moritz Hermann; Phil Blunsom

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arXiv · 1405.0947

Learning Bilingual Word Representations by Marginalizing Alignments

Tomáš Kočiský·Karl Moritz Hermann·Phil Blunsom

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Abstract

We present a probabilistic model that simultaneously learns alignments and distributed representations for bilingual data. By marginalizing over word alignments the model captures a larger semantic context than prior work relying on hard alignments. The advantage of this approach is demonstrated in a cross-lingual classification task, where we outperform the prior published state of the art.

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Tomáš Kočiský, Karl Moritz Hermann, Phil Blunsom. 2014-05-05. Learning Bilingual Word Representations by Marginalizing Alignments. https://arxiv.org/abs/1405.0947

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