A method for identification of a standard text token in a dictionary that corresponds to a non-standard token identified in text includes identification of a first standard token that is associated with the non-standard using a predetermined conditional random field (CRF) model and identification of a second standard token that is associated with the non-standard token using a spell checker. The method further includes identification of noisy channel scores using data from the CRF model and the spell checker for the first standard token and the second standard token, respectively. The method further includes presentation of one of the first and second standard tokens having the greatest identified noisy channel score to a user with a user interface device.
Broad-coverage normalization system for social media language