Machine Transliteration has come out to be an emerging and a very important
research area in the field of machine translation. Transliteration basically
aims to preserve the phonological structure of words. Proper transliteration of
name entities plays a very significant role in improving the quality of machine
translation. In this paper we are doing machine transliteration for
English-Punjabi language pair using rule based approach. We have constructed
some rules for syllabification. Syllabification is the process to extract or
separate the syllable from the words. In this we are calculating the
probabilities for name entities (Proper names and location). For those words
which do not come under the category of name entities, separate probabilities
are being calculated by using relative frequency through a statistical machine
translation toolkit known as MOSES. Using these probabilities we are
transliterating our input text from English to Punjabi.

本文采用基于规则的方法对英 - 旁遮普语进行机器音译，通过计算名实体和非名实体的概率以及使用统计机器翻译工具包 MOSES 计算相对频率来提高机器翻译的质量，同时进行音节划分。