People relatively use machine translation to learn any textual knowledge beyond their native language. There is already robust such as Google translate. However, the language list has only covered high resource English, France, etc., but not for Kawi Language one of local languages used in Bali's old works literature. Therefore, it necessary study development from more active user Indonesian ma...

Researchers have long been interested in the synergy between portability and computing power but had been limited by unwieldy, uncommonly used devices. The latest generation of mobile phones, i.e. ‘smartphones’, are equipped with hardware powerful enough to develop novel, interesting applications with allow users to directly interact with the world around them. This paper describes a multimodal...

This paper attempts to compare between the advancements in the productivity of Arabic into English Machine Translation Systems between two years, 2008 and 2013. It also aims to evaluate the progress achieved by various systems of Arabic into English electronic translation between the two years. For tracing such advancement, a comparative analysis of translated texts taken from previous studies ...

Although neural machine translation has made significant progress recently, how to integrate multiple overlapping, arbitrary prior knowledge sources remains a challenge. In this work, we propose to use posterior regularization to provide a general framework for integrating prior knowledge into neural machine translation. We represent prior knowledge sources as features in a log-linear model, wh...

In this paper we provide the largest published comparison of translation quality for phrase-based SMT and neural machine translation across 30 translation directions. For ten directions we also include hierarchical phrase-based MT. Experiments are performed for the recently published United Nations Parallel Corpus v1.0 and its large six-way sentencealigned subcorpus. In the second part of the p...

The problem of rare and unknown words is an important issue in Uyghur-Chinese machine translation, especially using neural machine translation model. We propose a novel way to deal with the rare and unknown words. Based on neural machine translation of using pointers over input sequence, our approach which consists of preprocess and post-process can be used in all neural machine translation mod...

We propose a multimodal neural machine translation (MNMT) method with semantic image regions called region-attentive (RA-NMT). Existing studies on MNMT have mainly focused employing global visual features or equally sized grid local extracted by convolutional networks (CNNs) to improve performance. However, they neglect the effect of information captured inside features. This study utilizes obj...