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EMNLP
2007
13 years 6 months ago
A Systematic Comparison of Training Criteria for Statistical Machine Translation
We address the problem of training the free parameters of a statistical machine translation system. We show significant improvements over a state-of-the-art minimum error rate tr...
Richard Zens, Sasa Hasan, Hermann Ney
EMNLP
2009
13 years 3 months ago
Feasibility of Human-in-the-loop Minimum Error Rate Training
Minimum error rate training (MERT) involves choosing parameter values for a machine translation (MT) system that maximize performance on a tuning set as measured by an automatic e...
Omar Zaidan, Chris Callison-Burch
ACL
2008
13 years 6 months ago
Beyond Log-Linear Models: Boosted Minimum Error Rate Training for N-best Re-ranking
Current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. We present BoostedMERT, a nove...
Kevin Duh, Katrin Kirchhoff
ACL
2012
11 years 7 months ago
Akamon: An Open Source Toolkit for Tree/Forest-Based Statistical Machine Translation
We describe Akamon, an open source toolkit for tree and forest-based statistical machine translation (Liu et al., 2006; Mi et al., 2008; Mi and Huang, 2008). Akamon implements all...
Xianchao Wu, Takuya Matsuzaki, Jun-ichi Tsujii
ICASSP
2011
IEEE
12 years 9 months ago
Combination of stochastic understanding and machine translation systems for language portability of dialogue systems
In this paper, several approaches for language portability of dialogue systems are investigated with a focus on the spoken language understanding (SLU) component. We show that the...
Bassam Jabaian, Laurent Besacier, Fabrice Lefevre