Deep learning is revolutionizing how machine translation systems are built today. This book
introduces the challenge of machine translation and evaluation-including historical …

The dream of automatic language translation is now closer thanks to recent advances in the
techniques that underpin statistical machine translation. This class-tested textbook from an …

In statistical machine translation, translation prediction considers not only the aligned source
word itself but also its source contextual information. Learning context representation is a …

This paper presents neural probabilistic parsing models which explore up to thirdorder
graph-based parsing with maximum likelihood training criteria. Two neural network …

This paper describes a discourse parsing system for our participation in the CoNLL 2016
Shared Task. We focus on the supplementary task: Sense Classification, especially the Non …

Although neural language models have emerged, n-gram language models are still used for
many speech recognition tasks. This paper proposes four methods to improve n-gram …

In the last years, deep learning algorithms have highly revolutionized several areas
including speech, image and natural language processing. The specific field of Machine …

It is very import for Chinese language processing with the aid of an efficient input method
engine (IME), of which pinyinto-Chinese (PTC) conversion is the core part. Meanwhile …

Since larger n-gram Language Model (LM) usually performs better in Statistical Machine
Translation (SMT), how to construct efficient large LM is an important topic in SMT. However …

Larger n-gram language models (LMs) perform better in statistical machine translation
(SMT). However, the existing approaches have two main drawbacks for constructing larger …