In this paper, we present a survey on the application of recurrent neural networks to the task
of statistical language modeling. Although it has been shown that these models obtain good …

MT aims to find for the source language sentence the most probable target language
sentence that shares the most similar meaning. Essentially, MT is a sequence-to-sequence …

Many NLP applications can be framed as a graph-to-sequence learning problem. Previous
work proposing neural architectures on this setting obtained promising results compared to …

We describe an open-source toolkit for statistical machine translation whose novel
contributions are (a) support for linguistically motivated factors,(b) confusion network …

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 only a loose …

The Handbook of Natural Language Processing, Second Edition presents practical tools
and techniques for implementing natural language processing in computer systems. Along …

We present a statistical phrase-based translation model that uses hierarchical phrases—
phrases that contain subphrases. The model is formally a synchronous context-free …

We present a statistical machine translation model that uses hierarchical phrases—phrases
that contain subphrases. The model is formally a synchronous context-free grammar but is …

Prediction of human physical traits and demographic information from genomic data
challenges privacy and data deidentification in personalized medicine. To explore the …

Statistical machine translation (SMT) treats the translation of natural language as a machine
learning problem. By examining many samples of human-produced translation, SMT …