Abstract: A system and methods of language identification of natural language text are presented. The system includes stored expected character counts and variances for a list of characters found in a natural language. Expected character counts and variances are stored for multiple languages to be considered during language identification. At run-time, one or more languages are identified for a text sample based on comparing actual and expected character counts. The present methods can be combined with upstream analyzing of Unicode ranges for characters in the text sample to limit the number of languages considered. Further, n-gram methods can be used in downstream processing to select the most probable language from among the languages identified by the present system and methods.

Abstract: A computer implemented method of suggesting replacement words for words of a string. In the method, an input string of input words is received. The input words are then matched to subject words of a candidate table. Next, candidate replacement words and scores from the candidate table corresponding to the matched subject words are extracted. Each score is indicative of a probability that the input word should be replaced with the corresponding candidate replacement word. Finally, replacement of the input words with their corresponding candidate replacement words is selectively suggested based on the scores for the replacement words. Another aspect of the present invention is directed to a spell checking system that is configured to implement the method.