People with motor impairments often have difficulty typing using desktop keyboards. We developed TrueKeys, a system that combines models of word frequency, keyboard layout, and typing error patterns to automatically identify and correct typing mistakes. In this paper, we describe the TrueKeys algorithm, compare its performance to existing correction algorithms, and report on a study of TrueKeys with 9 motor-impaired and 9 non-impaired participants. Running in non-interactive mode, TrueKeys performed more corrections than popular commercial and open source spell checkers. Used interactively, both motor-impaired and non-impaired users performed typing tasks significantly more accurately with TrueKeys than without. However, typing speed was reduced while TrueKeys was enabled.