15. A processing arrangement system to perform maximum entropy modeling in which one or more candidate features derived from a corpus of data are incorporated into a model that predicts linguistic behavior, the system comprising: a gain computation arrangement to determine gains for the candidate features; a feature ranking arrangement to rank the features based on the determined gain; a feature selection arrangement to select a feature with a highest gain; a parameter estimation arrangement to estimate weighting factors for each selected feature; and a model adjustment arrangement to adjust the model using the selected feature based on a level of uncertainty regarding the feature; wherein at least one of the feature selection arrangement, the parameter estimation arrangement, and the model adjustment arrangement incorporates a soft feature.
15. A processing arrangement system to perform maximum entropy modeling in which one or more candidate features derived from a corpus of data are incorporated into a model that predicts linguistic behavior, the system comprising: a gain computation arrangement to determine gains for the candidate features; a feature ranking arrangement to rank the features based on the determined gain; a feature selection arrangement to select a feature with a highest gain; a parameter estimation arrangement to estimate weighting factors for each selected feature; and a model adjustment arrangement to adjust the model using the selected feature based on a level of uncertainty regarding the feature; wherein at least one of the feature selection arrangement, the parameter estimation arrangement, and the model adjustment arrangement incorporates a soft feature. 16. The system of claim 15 , wherein the soft feature can vary continuously in an interval from 0 to 1, in which values near 1 indicate a confident score and values near 0 indicate a non-confident score.