10. The computer-implemented method of claim 1 , further comprising performing a learning phase that computes values of a probability matrix used to compute the first probability, wherein the values of the probability matrix are computed based at least in part on observed user behavior, wherein the probability matrix is an N by N matrix where N is a number of keys represented by the input device; and wherein an entry at position (I, J) in the probability matrix is a probability that the J th key was intended when the I th key was pressed.
1. A computer-implemented method for text input, the method comprising: receiving a sequence of input characters corresponding to a user actuating multiple areas of an input device; computing a first probability for a candidate word of multiple words in a dictionary, wherein the first probability for the candidate word is computed by combining multiple character difference probabilities, wherein each character difference probability is computed, for each selected character in the sequence of input characters, by applying a probability distribution that indicates, for the selected character, that a character of multiple characters of the candidate word was intended when the area of the input device corresponding to the selected character was actuated; obtaining a second probability for the candidate word, wherein the second probability for the candidate word indicates a likelihood, independent of the sequence of input characters, of occurrence of the candidate word; and in response to receiving the sequence of input characters, selecting the candidate word, using one or more processors, based on a combination of the first probability for the candidate word and the second probability for the candidate word.