Title: Training Machine Translation with a Second-Order Taylor Approximation of Weighted Translation Instances
Speaker: Aaron Phillips
When: Tuesday, September 13, 12:00 Noon to 1:00pm.
Where: GHC 6501
Abstract: The Cunei Machine Translation Platform is an open-source MT system designed to model instances of translation. One of the challenges to this approach is effective training. We describe two techniques that improve the training procedure and allow us to leverage the strengths of instance-based modeling. First, during training we approximate our model with a second-order Taylor series. Second, we discount models based on the magnitude of their approximation. By reducing error in training, our model now consistently outperforms the standard SMT model with gains ranging from 0.51 to 3.77 BLEU on German-English and Czech-English test sets.