Improvement in Machine Translation from English to Punjabi by Identifying the Morpheme Boundaries

We discuss about language distinct and an unsupervised approach for Morphological Analysis. The algorithm is based on probability that uses the distance, frequency and length of the strings. In future it would solve problems of large corpora and agglutinative languages as well. We perform the algorithm on English data as well as Punjabi data and get the results as follows, as the number of morphemes recognized are more in English than in Punjabi language due to the fluctuations in random behavior showing smaller segmentations in small data sizes. There will be always a room for change ahead as the language grows.