Three paradigms have dominated machine translation (MT)--rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). These paradigms differ in the way they handle the three fundamental processes in MT--analysis, transfer, and generation (ATG). In its pure form, RBMT uses rules, while SMT uses data. EBMT tries a combination--data supplies translation parts that rules recombine to produce translation.

Machine Translation compares and contrasts the salient principles and practices of RBMT, SMT, and EBMT. Offering an...

This contributed volume discusses in detail the process of construction of a WordNet of 18 Indian languages, called Indradhanush (rainbow) in Hindi. It delves into the major challenges involved in developing a WordNet in a multilingual country like India, where the information spread across the languages needs utmost care in processing, synchronization and representation. The project has emerged from the need of millions of people to have access to relevant content in their native languages, and it provides a common interface for information sharing and reuse across the Indian...