Neural machine translation (NMT) has been prominent in many machine translation tasks.
However, in some domain-specific tasks, only the corpora from similar domains can improve …

Unsupervised word sense disambiguation (WSD) methods are an attractive approach to all-
words WSD due to their non-reliance on expensive annotated data. Unsupervised estimates …

We present novel models for domain adaptation based on the neural network joint model
(NNJM). Our models maximize the cross entropy by regularizing the loss function with …

Joint models have recently shown to improve the state-of-the-art in machine translation (MT).
We apply EM-based mixture modeling and data selection techniques using two joint models …

This article aims to explore the features, mechanisms, and applications of bilingual cognition
in international communication activities. Our main idea is: First, clarify the mother tongue of …

In this paper, we propose two extensions to the vector space model (VSM) adaptation
technique (Chen et al., 2013b) for statistical machine translation (SMT), both of which result …

The objective of this thesis is to directly incorporate comparable corpora into the estimation
of end-to-end statistical machine translation (SMT) models. Typically, SMT models are …

Machine Translation (MT) has made significant progress in the recent years and continues
to improve. Today, MT is successfully used in many contexts, including professional …

Previously, statistical machine translation (SMT) models have been estimated from parallel
corpora, or pairs of translated sentences. In this thesis, we directly incorporate comparable …

Provided with a sentence in an input language, a human translator produces a sentence in
the desired target language. The advances in artificial intelligence in the 1950s led to the …