UNL based machine translation system for punjabi language

Abstract

Machine Translation (MT) has been an area of immense interest among researchers during last couple of decades. This area has witnessed a few lows and highs during its life span and has also witnessed integration of research works from different fields including linguistics, computer science, artificial intelligence, statistics, mathematics, philosophy and others. Researchers have proposed different paradigms for machine translation across natural languages with reasonable success. Universal Networking Language (UNL) based MT is also an effort in this direction. The UNL programme was launched in 1996 in Institute of Advanced Studies (IAS) of United Nations University (UNU), Tokyo, Japan. The approach in UNL revolves around the development of an EnConverter and a DeConverter for a natural language. The EnConverter is used to convert a given sentence in natural language to an equivalent UNL expression; and the DeConverter is used to convert a given UNL expression to an equivalent natural language sentence. In the work carried out in this PhD project, these two components, namely, EnConverter and DeConverter have been developed for Punjabi language. The PhD thesis on the work carried out in this project is divided into seven chapters. These chapters are: Introduction, Review of Literature; UNL Framework and Creation of Punjabi-Universal Word Lexicon; Punjabi-UNL EnConverter; UNL-Punjabi DeConverter; Results and Discussions; Conclusion and Future Scope of the work. First chapter contains introduction to Machine Translation and its need in the age of Information Technology. In this chapter, the challenges of MT, approaches of MT, objectives of this research, methodology adopted to achieve these objectives and the features of Punjabi language have been presented. Machine Translation approaches that can be classified into four categories, namely, direct MT, rule-based MT, corpus-based MT and knowledge-based MT, have also been discussed in this chapter.