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A Comparative Study on English-Chinese Machine Transliteration
Enting GAO, Xiangyu DUAN
Acta Scientiarum Naturalium Universitatis Pekinensis    2017, 53 (2): 287-294.   DOI: 10.13209/j.0479-8023.2017.039
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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.

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