Classification-Based Approach for Hybridizing Statistical and Rule-Based Machine Translation

Statistical Machine Translation Adding Rule-based Machine Translation

Statistical Machine Translation with Rule based Machine Translation

We have evaluated the two-stage machine translation (MT) system. The first stage is a state-of-the-art trial rule-based machine translation system. The second stage is a normal statistical machine translation system. For Japanese-English machine translation, first, we used a Japanese-English rule-based MT, and we obtained "ENGLISH" sentences from Japanese sentences. Second, we used a standard s...

Fast Translation Rule Matching for Syntax-based Statistical Machine Translation

In a linguistically-motivated syntax-based translation system, the entire translation process is normally carried out in two steps, translation rule matching and target sentence decoding using the matched rules. Both steps are very timeconsuming due to the tremendous number of translation rules, the exhaustive search in translation rule matching and the complex nature of the translation task it...

A Study of Translation Rule Classification for Syntax-based Statistical Machine Translation

Recently, numerous statistical machine translation models which can utilize various kinds of translation rules are proposed. In these models, not only the conventional syntactic rules but also the non-syntactic rules can be applied. Even the pure phrase rules are includes in some of these models. Although the better performances are reported over the conventional phrase model and syntax model, ...

Rule-based Reordering Space in Statistical Machine Translation

In Statistical Machine Translation (SMT), the constraints on word reorderings have a great impact on the set of potential translations that are explored. Notwithstanding computationnal issues, the reordering space of a SMT system needs to be designed with great care: if a larger search space is likely to yield better translations, it may also lead to more decoding errors, because of the added a...