Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation

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.

• Type: Journal
• Year: 2012
• Where: ACL
• Authors: Benjamin Börschinger, Mark Johnson
• Keywords: ACL 2012, Computational Linguistics, Goldwater, Segmentation Problem, Word Segmentation