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» Bidirectional Decoding for Statistical Machine Translation
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ACL
2009
13 years 4 months ago
Efficient Minimum Error Rate Training and Minimum Bayes-Risk Decoding for Translation Hypergraphs and Lattices
Minimum Error Rate Training (MERT) and Minimum Bayes-Risk (MBR) decoding are used in most current state-of-theart Statistical Machine Translation (SMT) systems. The algorithms wer...
Shankar Kumar, Wolfgang Macherey, Chris Dyer, Fran...
EMNLP
2007
13 years 8 months ago
Large Language Models in Machine Translation
This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 t...
Thorsten Brants, Ashok C. Popat, Peng Xu, Franz Jo...
ACL
2010
13 years 4 months ago
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models
We present cdec, an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based m...
Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonatha...
ACL
2009
13 years 4 months ago
Quadratic-Time Dependency Parsing for Machine Translation
Efficiency is a prime concern in syntactic MT decoding, yet significant developments in statistical parsing with respect to asymptotic efficiency haven't yet been explored in...
Michel Galley, Christopher D. Manning
NAACL
2010
13 years 4 months ago
Accurate Non-Hierarchical Phrase-Based Translation
A principal weakness of conventional (i.e., non-hierarchical) phrase-based statistical machine translation is that it can only exploit continuous phrases. In this paper, we extend...
Michel Galley, Christopher D. Manning