Abstract
Explicit length modelling has been previously explored in statistical pattern recognition with successful
results. In this paper, two length models along with two parameter estimation methods and two
alternative parametrisations for statistical machine translation (SMT) are presented. More precisely, we
incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an
additional feature function in order to prove the contribution of length information. Finally, a
systematic evaluation on reference SMT tasks considering different language pairs proves the benefits
of explicit length modelling.
