| Introduction | Early work in statistical machine translation Viewed translation as a noisy channel process comprised of a translation model, which functioned to posit adequate translations of source language words, and a target language model, which guided the fluency of generated target language strings (Brown et al., |
| Introduction | Drawing on earlier successes in speech recognition, research in statistical machine translation has effectively used n-gram word sequence models as language models. |
| Related Work | speech recognition and statistical machine translation focus on the use of n-grams, which provide a simple finite-state model approximation of the target language. |
| Related Work | priate algorithmic fit for incorporating syntax into phrase-based statistical machine translation , since both process sentences in an incremental left-to-right fashion. |