A machine translation system for translating a source language text fragment to a target language text fragment, comprising: a decoder configured to receive as an input, a source language dependency tree, indicative of syntactic dependencies in the source language text fragment, and a plurality of matching treelet translation pairs, each of the matching treelet translation pairs matching at least a portion of the source language dependency tree, the decoder being configured to generate a target language dependency tree, indicative of the target language text fragment, based on the source language dependency tree and the matching treelet translation pairs by scoring different combinations of target language portions of the matching treelet translation pairs, wherein a language dependency tree has a plurality of different levels, each level having one or more nodes that represent language words, wherein the decoder is configured to generate the target language dependency tree using matching treelet translation pairs having a plurality of different sizes, wherein the decoder is configured to rank the treelet translation pairs, and wherein the decoder is configured to only keep the top ranked translation pairs with the same input node, the machine translation system being characterized in that the decoder is configured to generate the target language dependency tree based on the source language dependency tree and the matching treelet translation pairs by scoring different combinations of target language portions of the matching treelet translation pairs with a log-linear combination of statistical models, wherein the statistical models comprise an order model and a channel model, wherein the order model statistically calculates a score for different orders of the target language words on each individual level of the target language dependency tree to statistically predict an order of dependency of the target language words on each individual level of the target language dependency tree, relative to an ancestor word represented by a node from which the target language words depend in the target language dependency tree, a structure of the language dependency tree indicates whether a language word represented by a given node on one level is ordered before or after a language word represented by a node from which the given node depends, and the decoder is configured to rank the treelet translation pairs first by size, then by the channel model score and then by another model score. a decoder configured to receive as an input, a source language dependency tree, indicative of syntactic dependencies in the source language text fragment, and a plurality of matching treelet translation pairs, each of the matching treelet translation pairs matching at least a portion of the source language dependency tree, the decoder being configured to generate a target language dependency tree, indicative of the target language text fragment, based on the source language dependency tree and the matching treelet translation pairs by scoring different combinations of target language portions of the matching treelet translation pairs, wherein a language dependency tree has a plurality of different levels, each level having one or more nodes that represent language words, wherein the decoder is configured to generate the target language dependency tree using matching treelet translation pairs having a plurality of different sizes, wherein the decoder is configured to rank the treelet translation pairs, and wherein the decoder is configured to only keep the top ranked translation pairs with the same input node, the machine translation system being characterized in that the decoder is configured to generate the target language dependency tree based on the source language dependency tree and the matching treelet translation pairs by scoring different combinations of target language portions of the matching treelet translation pairs with a log-linear combination of statistical models, wherein the statistical models comprise an order model and a channel model, wherein the order model statistically calculates a score for different orders of the target language words on each individual level of the target language dependency tree to statistically predict an order of dependency of the target language words on each individual level of the target language dependency tree, relative to an ancestor word represented by a node from which the target language words depend in the target language dependency tree, a structure of the language dependency tree indicates whether a language word represented by a given node on one level is ordered before or after a language word represented by a node from which the given node depends, and the decoder is configured to rank the treelet translation pairs first by size, then by the channel model score and then by another model score.