Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation

Benjamin Börschinger, Mark Johnson

Abstract: We present a novel extension to a recently proposed incremental learning algorithm for the word segmentation problem originally introduced in Goldwater (2006). By adding rejuvenation to a particle filter, we are able to considerably improve its performance, both in terms of finding higher probability and higher accuracy solutions.