A Phrase-Based Hidden Semi-Markov Approach to Machine Translation.
Jesús Andrés-Ferrer, Alfons Juan · 2009
Statistically estimated phrase-based models promised to further the state-of-the-art, however, several works reported a performance decrease with respect to heuristically estimated phrase-based models. In this work we present a latent variable phrase-based translation model inspired by the hidden semi-Markov models, that does not degrade the system. Experimental results report an improvement over the baseline. Additionally, it is observed that both Baum-Welch and Viterbi trainings obtain the very same result, suggesting that most of the probability mass is gathered into one single bilingual segmentation. 1