1. A method comprising: translating source language content in a source natural language to a target natural language using statistical machine translation (SMT) employing a conditional translation probability conditioned on the source language content; and optimizing values of parameters of the conditional translation probability by an iterative optimization process operating on a translation pool, the optimizing including adding candidate aligned translations to the translation pool by sampling available candidate aligned translations for a source language sentence in accordance with the conditional translation probability; wherein the conditional translation probability is quantitatively equivalent to: P ⁡ ( e , a | f ) = exp ⁡ ( ∑ k = 1 K ⁢ λ k ⁢ h k ⁡ ( e , a , f ) ) ∑ ( e ′ , a ′ ) ∈ L ⁢ exp ⁡ ( ∑ k = 1 K ⁢ λ k ⁢ h k ⁡ ( e ′ , a ′ , f ) ) where f denotes the source language sentence, L denotes the set of available candidate aligned translations, (e, a) denotes a candidate aligned translation for which the conditional probability is computed, h k (.. .), k=1,. .. , K denotes a set of K feature functions, and λ k , k=1,. .. , K denotes the parameters of the conditional translation probability; wherein the sampling comprises: selecting a sampled candidate aligned translation by traversing a translation lattice representing the available candidate aligned translations for the source language sentence from its root node to its final node wherein each transition from a current node to a next node is selected based on conditional translation probabilities σ ⁡ ( e i ) = ∑ k = 1 K ⁢ λ k ⁢ h k ⁡ ( e i ) of the available edges e i leading away from the current node; wherein the SMT and the optimizing are implemented by a SMT system embodied by at least one digital processor.