Automatic Correction of French to English Relative Pronoun Translations using Natural Language Processing and Machine Learning Techniques

Machine translation is an area of computational linguistics in which researchers have sought to make significant improvements. In particular, many researchers have focused their interest on statistical machine translation (SMT) models to obtain accurate translations from source languages to English. The use of SMT models may be attributed in large part to Brown et al. (1990), who developed an approach for the translation of single sentences using language and translation models. Since that time, the SMT approach has been modified and expanded by several researchers, including Marcu and Wong (2002) who developed a phrase-based translation model, and Yamada and Knight (2001) who proposed a syntax-based SMT model to include structural and syntactic aspects of language into the translation model.