In the KL divergence framework, the extended language modeling approach has a critical problem estimating a query model, which is the probabilistic model that encodes user’s inf...
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
We propose a translation recommendation framework to integrate Statistical Machine Translation (SMT) output with Translation Memory (TM) systems. The framework recommends SMT outp...
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...
Several recent efforts in statistical natural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; ...
Stephen Della Pietra, Mark Epstein, Salim Roukos, ...