12. A computer-implemented method comprising: determining word probability values associated with words in a word corpus; determining a weight based on a type of the word corpus, the weight indicating a degree of reliability for updating an existing input method editor dictionary using the word corpus; determining candidate segmentations of sentences of documents in a document corpus, each candidate segmentation having one or more segments that define words forming the sentence; iteratively determining a segmentation probability value for each candidate segmentation of each sentence based on the word probability values associated with the words in the candidate segmentation; determining a weighted segmentation probability value for each segmentation probability value based on the weight; determining, in a data processing apparatus, a soft-count value for each word in the word corpus based on the weighted segmentation probability values of the candidate segmentations in which the word appears and a number of occurrences of the word in the candidate segmentations in which the word appears; iteratively adjusting the word probability value for each word in the word corpus based on the soft-count for the word; and updating the existing input method editor dictionary by iteratively adding a plurality of words from the word corpus and their respective associated word probability values to the existing input method editor dictionary, wherein the plurality of words from the word corpus are words having the highest associated word probability values.
13. The method of claim 12 , further comprising accumulating a count for each word based on the weighted segmentation probability values of the segmentations that include the word.