Statistical machine translation

Statistical Machine Translation

Statistical Machine Translation (SMT) deals with automatically mapping sentences in one human language (for example French) into another human language (such as English). The first language is called the source and the second language is called the target. This process can be thought of as a stochastic process. There are many SMT variants, depending upon how translation is modelled. Some approa...

On Statistical Machine Translation and Translation Theory

The translation process in statistical machine translation (SMT) is shaped by technical constraints and engineering considerations. SMT explicitly models translation as search for a target-language equivalent of the input text. This perspective on translation had wide currency in mid-20th century translation studies, but has since been superseded by approaches arguing for a more complex relatio...

Improving Pronoun Translation for Statistical Machine Translation

Machine Translation is a well–established field, yet the majority of current systems translate sentences in isolation, losing valuable contextual information from previously translated sentences in the discourse. One important type of contextual information concerns who or what a coreferring pronoun corefers to (i.e., its antecedent). Languages differ significantly in how they achieve coreferen...

Statistical Machine Translation Adding Rule-based Machine Translation

Neural Machine Translation Advised by Statistical Machine Translation

Neural Machine Translation (NMT) is a new approach to machine translation that has made great progress in recent years. However, recent studies show that NMT generally produces fluent but inadequate translations (Tu et al. 2016; He et al. 2016). This is in contrast to conventional Statistical Machine Translation (SMT), which usually yields adequate but non-fluent translations. It is natural, th...