Exploration for Polish-* bi-lingual translation equivalents from comparable and quasi-comparable corpora

In contemporary world, translation becomes a critical need of the time. Parallel dictionaries have now become a most accessible source by humans, but confines are there as they do not offer good quality translation function, because of neologisms and words that are out of vocabulary. To overcome this problem in the usage of statistical translation systems is becoming more and more important in maintaining the eminence and quantity of the training data. But due to the limitations in these systems they have very limited availability for few languages and very limited narrow text areas. The purpose of this research is to bring calculation time up gradation via GPU acceleration, tuning script introduction and the enhancement and improvements in the methodologies of the contemporary comparable corpora mining through re-implementation of analogous algorithms through Needleman-Wunch algorithm. Experiments have been conducted on multiple language data which were extracted on numerous domains from Wikipedia. For the sake of Wikipedia, multiple cross-lingual contrasts and comparison were established. Optimistic impact on the both quantity and quality of mined data was observed due to such changes and adaptation. The solution is language independent and highly practical especially for under-resourced languages.