This paper describes the application of discriminative reranking techniques to the problem of machine translation. For each sentence in the source language, we obtain from a basel...
Recent research has shown that a balanced harmonic mean (F1 measure) of unigram precision and recall outperforms the widely used BLEU and NIST metrics for Machine Translation evalu...
Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is on...
We describe a methodology for rapid experimentation in statistical machine translation which we use to add a large number of features to a baseline system exploiting features from...
Franz Josef Och, Daniel Gildea, Sanjeev Khudanpur,...
Automatic evaluation metrics are fast and cost-effective measurements of the quality of a Machine Translation (MT) system. However, as humans are the end-user of MT output, human ...