First, we develop four novel cohesive soft constraints for a phrase-based decoder namely exhaustive interruption check, interruption count, exhaustive interruption count, and rich interruption constraints. To ensure the robustness and effectiveness of the proposed constraints, we conduct experiments on four different language pairs, including English-{Iraqi, Spanish} and {Arabic, Chinese}-English. The improvements are in between 0.4 and 1.8 BLEU points. These experiments also cover a wide range of training corpus sizes, ranging from 500K sentence pairs up to 10 million sentence pairs. Furthermore, to show the effectiveness of our proposed methods we apply them to systems using a 2.7 billion words 5-gram LM, different reordering models and dependency parsers. 
