PVBMT: A Principal Verb based Approach for English to Bangla Machine Translation

Abstract

This paper proposes principal verb based machine translation (PVBMT), a new approach of machine translation (MT) from English to Bangla (EtoB) that runs in both web-based and mobile applications. The key mechanism is to detect the principal verb from any form of English sentence and then to transform it into the simplest form of English sentence i.e, subject plus verb plus object; identical to rule based MT (RBMT). Also while a ‘prepositional phrase (PP)’ or an ‘idiom and phrase (I&P)’ exists in a sentence, PVBMT uses its own corpus to tag and bind it properly; identical to statistical MT (SMT). While only RBMT is employed, often it generates feeble output because it requires the matching of various forms of English sentences with established grammatical rules stored in the knowledge-base. Therefore PVBMT employs hybrid machine translation (HMT) paradigm, a hybrid of RBMT and SMT. Finally the performance of PVBMT has been compared with a number of existing on-line EtoB translators employing a syntactic and a semantic analyzer. The experimental result shows that PVBMT can translate any form of English sentence i.e, Interrogative, Imperative, Exclamatory, Active, Passive, Complex or Compound along with an ‘I&P’ or a ‘PP’ with better accuracy than others.