19. A system for determining a dropped pronoun from a source language, comprising: at least one distinct software module, each distinct software module being embodied on a tangible computer-readable medium; a memory; and at least one processor coupled to the memory and operative for: collecting parallel sentences from a source language and a target language; creating at least one word alignment between the parallel sentences in the source language and the target language; mapping at least one pronoun from the target language sentence onto the source language sentence; computing multiple features from the mapping, wherein the multiple features are extracted from both the source language and the at least one pronoun projected from the target language; using the multiple features to train a plurality of classifiers to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language; updating the plurality of classifiers based on user feedback provided in response to a prediction of position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language; and providing a graphical user interface to enable a user to select one of the plurality of classifiers to apply to a portion of the source language, wherein said plurality of classifiers are displayed to the user via the graphical user interface for selection and comprise (i) a conditional random field classifier, (ii) a tree-relabeling classifier, and (iii) a maximum entropy classifier.
19. A system for determining a dropped pronoun from a source language, comprising: at least one distinct software module, each distinct software module being embodied on a tangible computer-readable medium; a memory; and at least one processor coupled to the memory and operative for: collecting parallel sentences from a source language and a target language; creating at least one word alignment between the parallel sentences in the source language and the target language; mapping at least one pronoun from the target language sentence onto the source language sentence; computing multiple features from the mapping, wherein the multiple features are extracted from both the source language and the at least one pronoun projected from the target language; using the multiple features to train a plurality of classifiers to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language; updating the plurality of classifiers based on user feedback provided in response to a prediction of position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language; and providing a graphical user interface to enable a user to select one of the plurality of classifiers to apply to a portion of the source language, wherein said plurality of classifiers are displayed to the user via the graphical user interface for selection and comprise (i) a conditional random field classifier, (ii) a tree-relabeling classifier, and (iii) a maximum entropy classifier. 20. The system of claim 19 , wherein the at least one processor coupled to the memory is further operative for: creating a parse tree for each sentence in the source language and the target language.