Paper: Recurrent Continuous Translation Models

ACL ID D13-1176
Title Recurrent Continuous Translation Models
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013

We introduce a class of probabilistic con- tinuous translation models called Recur- rent Continuous Translation Models that are purely based on continuous representations for words, phrases and sentences and do not rely on alignments or phrasal translation units. The models have a generation and a condi- tioning aspect. The generation of the transla- tion is modelled with a target Recurrent Lan- guage Model, whereas the conditioning on the source sentence is modelled with a Convolu- tional Sentence Model. Through various ex- periments, we show first that our models ob- tain a perplexity with respect to gold transla- tions that is > 43% lower than that of state- of-the-art alignment-based translation models. Secondly, we show that they are remarkably sensitive to the word order, syntax, and...