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EMNLP
2007
13 years 9 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 5 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 9 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 10 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 11 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