Language Model and Grammar Extraction Variation in Machine Translation
BibTeX
@MISC{Eidelman_languagemodel,
author = {Vladimir Eidelman and Chris Dyer and Philip Resnik},
title = {Language Model and Grammar Extraction Variation in Machine Translation},
year = {}
}
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
This paper describes the system we developed to improve German-English translation of News text for the shared task of the Fifth Workshop on Statistical Machine Translation. Working within cdec, an open source modular framework for machine translation, we explore the benefits of several modifications to our hierarchical phrase-based model, including segmentation lattices, minimum Bayes Risk decoding, grammar extraction methods, and varying language models. Furthermore, we analyze decoder speed and memory performance across our set of models and show there is an important trade-off that needs to be made. 1
Citations
| 992 | BLEU: A Method for Automatic Evaluation of Machine Translation - Papineni, Roukos, et al. - 2002 |
| 805 | A systematic comparison of various statistical alignment models - Och, Ney - 2003 |
| 631 | J: An Empirical Study of Smoothing Techniques for Language Modeling - SF, Goodman - 1996 |
| 209 | Hierarchical phrase-based translation - Chiang - 2007 |
| 204 | A Study of Translation Edit Rate with Targeted Human Annotation - Snover, Dorr, et al. - 2006 |
| 93 | phrase-based translation - Statistical |
| 78 | Minimum Bayes-risk decoding for statistical machine translation - Kumar, Byrne - 2004 |
| 32 | rescoring: Faster decoding with integrated language models - Forest |
| 25 | Hierarchical phrase-based translation with suffix arrays - Lopez - 2007 |
| 23 | cdec: a decoder, alignment, and learning framework for finite-state and context-free translation models - Dyer, Weese, et al. - 2010 |
| 6 | The University of Maryland statistical machine translation system for the Fourth Workshop on Machine Translation - Dyer, Setiawan, et al. - 2009 |
