Paper: Distributed Language Modeling For $N$-Best List Re-Ranking

ACL ID W06-1626
Title Distributed Language Modeling For $N$-Best List Re-Ranking
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006

In this paper we describe a novel dis- tributed language model for N-best list re-ranking. The model is based on the client/server paradigm where each server hosts a portion of the data and provides information to the client. This model al- lows for using an arbitrarily large corpus in a very efficient way. It also provides a natural platform for relevance weighting and selection. We applied this model on a 2.97 billion-word corpus and re-ranked the N-best list from Hiero, a state-of-the- art phrase-based system. Using BLEU as a metric, the re-ranked translation achieves a relative improvement of 4.8%, signifi- cantly better than the model-best transla- tion.