Natural language processing employs computational techniques for the purpose of learning,
understanding, and producing human language content. Early computational approaches to …

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 …

The field of machine translation faces an under-recognized problem because of
inconsistency in the reporting of scores from its dominant metric. Although people refer to" …

We introduce the Multi30K dataset to stimulate multilingual multimodal research. Recent
advances in image description have been demonstrated on English-language datasets …

We propose a simple data augmentation protocol aimed at providing a compositional
inductive bias in conditional and unconditional sequence models. Under this protocol …

Recent work on end-to-end neural network-based architectures for machine translation has
shown promising results for En-Fr and En-De translation. Arguably, one of the major factors …

We propose minimum risk training for end-to-end neural machine translation. Unlike
conventional maximum likelihood estimation, minimum risk training is capable of optimizing …

We present the 1.0 release of our paraphrase database, PPDB. Its English portion, PPDB:
Eng, contains over 220 million paraphrase pairs, consisting of 73 million phrasal and 8 …

While end-to-end neural machine translation (NMT) has made remarkable progress
recently, NMT systems only rely on parallel corpora for parameter estimation. Since parallel …

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