PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Complete Search Space Exploration for SITG Inside Probability
Guillem Gascó, Joan Andreu Sánchez and José Miguel Benedí
In: SSPR SPR 2010, August 18-20, Cesme,Izmir, Turkey.

Abstract

Stochastic Inversion Transduction Grammars are a very powerful formalism in Machine Translation that allow to parse a string pair with ecient Dynamic Programming algorithms. The usual parsing algorithms that have been previously dened cannot explore the complete search space. In this work, we propose important modications that consider the whole search space. We formally prove the correctness of the new algorithm. Experimental work shows important improvements in the probabilistic estimation of the models when using the new algorithm.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:7446
Deposited By:Alfons Juan
Deposited On:17 March 2011