Performance evaluation of various training data in English-Persian Statistical Machine Translation

Globalization and the continued increase in international travel and commerce have made automatic translation systems an attractive area of research and development. Even as technology opens up e-commerce opportunities, companies must overcome language barriers to reach new potential customers and business partners. With the advent of Web2.0 technologies, machine translation and tools like Google Translate have made the web more accessible. Machine translation is usually employed to translate text from one language into another. Statistical Machine Translation has been used for translation between many language pairs contributing to its popularity in recent years. It has however not been used for the English/Persian language pair. This paper presents the first such attempt and describes the problems faced in creating a corpus and building a base line system. Our experience with the construction of a parallel corpus during this ongoing study and the problems encountered especially with the process of alignment are discussed in this paper. The prototype constructed and its evaluation is briefly described and results are analyzed. In the final part of the paper, conclusions are drawn and work planned for the future is discussed.