In recent years, natural language processing (NLP) has got great development with deep
learning techniques. In the sub-field of machine translation, a new approach named Neural …

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

Quite surprisingly, exact maximum a posteriori (MAP) decoding of neural language
generators frequently leads to low-quality results. Rather, most state-of-the-art results on …

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

We present and compare various methods for computing word alignments using statistical or
heuristic models. We consider the five alignment models presented in Brown, Della Pietra …

We propose a new phrase-based translation model and decoding algorithm that enables us
to evaluate and compare several, previously proposed phrase-based translation models …

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 …

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We present a framework for statistical machine translation of natural languages based on
direct maximum entropy models, which contains the widely used source-channel approach …