Linguistic filters in statistical machine translation models

The paper focuses on the problems of linguistic filters development for statistical machine translation and advancement of parallel texts alignment methods for enhancing precision and adequacy of translations. Statistical and heuristic models of alignment and translation are considered. The solutions proposed are based on the hybrid grammar formalism comprising the linguistic rules and probability characteristics of language structures.