Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Most of the machine translation systems rely on a large set of translation rules. These rules are treated as discrete and independent events. In this short paper, we propose a novel method to model rules as observed generation output of a compact hidden model, which leads to better generalization capability. We present a preliminary generative model to test this idea. Experimental results show about one point improvement on TER-BLEU over a strong baseline in Chinese-to-English translation.
Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Michelle X. Zhou, Fei Wang, et al.
ICMEW 2013
Sudeep Sarkar, Kim L. Boyer
Computer Vision and Image Understanding
James E. Gentile, Nalini Ratha, et al.
BTAS 2009