Computer Science > Computation and Language
[Submitted on 5 Aug 2017]
Title:A Comparison of Neural Models for Word Ordering
View PDF HTML (experimental)Abstract:We compare several language models for the word-ordering task and propose a new bag-to-sequence neural model based on attention-based sequence-to-sequence models. We evaluate the model on a large German WMT data set where it significantly outperforms existing models. We also describe a novel search strategy for LM-based word ordering and report results on the English Penn Treebank. Our best model setup outperforms prior work both in terms of speed and quality.
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