This paper proposes a nonparametric Bayesian method for inducing Part-of-Speech (POS) tags in dependency trees to improve the performance of statistical machine translation (SMT).
we extend the monolingual infinite tree model (Finkel et al., 2007) to a bilingual scenario: each hidden state (POS tag) of a source-side dependency tree emits a source word together with its aligned target word, either jointly (joint model), or independently (independent model).