Applying Neural Networks to English-Chinese Named Entity Transliteration

Abstract

This paper presents the machine transliteration systems that we employ for our participation in the NEWS 2016 machine transliteration shared task. Based on the prevalent deep learning models developed for general sequence processing tasks, we use convolutional neural networks to extract character level information from the transliteration units and stack a simple recurrent neural network on top for sequence processing. The systems are applied to the standard runs for both English to Chinese and Chinese to English transliteration tasks. Our systems achieve competitive results according to the official evaluation.