英汉机器音译系统对比研究
A Comparative Study on English-Chinese Machine Transliteration

摘要 针对机器音译的两种主要方法 —— 传统的基于统计的方法和目前流行的基于深度神经网络的方法, 分别使用两种典型系统进行研究。实验结果显示, 基于统计的方法和基于深度神经网络的方法取得的音译质量在评测指标上相当, 但在具体音译结果上各系统间呈现不一致的输出。使用系统融合的方法来实现各系统间的优势互补。实验结果显示, 系统融合的方法显著优于单系统的音译质量。
Abstract With the aim to study the two main methods on machine transliteration: traditional statistical method and the current prevalent deep neural network method, the authors carry out the comparative study on them with two typical systems per method The experiments show that traditional statistical method and deep neural network method perform comparatively regarding evaluation metrics, while manifest difference on individual transliteration result. A system combination method is proposed to balance the strengths of all systems. Experimental results show that system combination significantly improves the transliteration quality over single system.