Text Auto-Correction via N-Grams

Abstract

An input text string is received that contains characters or words. The input text string can be completed or corrected using contact scores based on n-grams. In addition, a subsequent text string and a preceding text string for the input text string are also identified, again using n-gram scores. A corrected text string is created by inserting the preceding text string before the input text string and appending the subsequent text string after the input text string.

1 . A system for text auto-correction, the system comprising:
 a text input interface device to receive an input text string from a user;   a semantic processing module in communication with the text input device to evaluate the input text string and to extend the input text string in at least two directions by identifying a subsequent text string comprising a plurality of words forming a subsequent phrase and a preceding text string comprising a plurality of words forming a preceding phrase for the input text string and creating a corrected text string by inserting the preceding phrase before the input text string and appending the subsequent phrase after the input text string; and   a user interface in communication with the text input interface and the semantic processing module to display the corrected text string to the user for approval.   
     
     
         2 . The system of  claim 1 , wherein the text input device comprises a computer keyboard, a speech recognition device, a computer touch screen, a handwriting input device or combinations thereof. 
     
     
         3 . The system of  claim 1 , wherein the semantic processing module further comprises:
 a content score generator to generate content scores and to associate the content scores with text strings, the content scores expressing a probability of accuracy of content within a given text string;   a content score evaluator in communication with the content score generator to evaluate and to compare content scores associated with text strings; and   a text string modifier in communication with the content score evaluator to create the corrected input text string only if a corrected input text string content score is higher than the input text string content score.   
     
     
         4 . The system of  claim 3 , wherein the content scores comprise N-gram scores for an input text string comprising N characters. 
     
     
         5 . The system of  claim 1 , wherein the semantic processing module further comprises a substitute input text string generator in communication with the content score generator to generate candidate substitute input text strings. 
     
     
         6 . The system of  claim 5 , wherein the substitute input text string generator comprises:
 a sub-phrase identifier to identify sub-phrases in the input text string, each sub-phrase comprising a number of characters less than a plurality of characters forming the input text string;   a substitute sub-phrase generator to generate a plurality of substitute sub-phrases, each substitute sub-phrase associated with one of the sub-phrases in the input text string; and   a substitute sub-phrase assembly module to form a plurality of candidate substitute input data strings, each candidate substitute input data string comprising a unique combination of the input data string and at least one of the plurality of substitute sub-phrases.   
     
     
         7 . The system of  claim 1 , wherein the semantic processing module further comprises a text string expansion module in communication with the content score generator to generate the subsequent text string and the preceding text string for the corrected input text string. 
     
     
         8 . The system of  claim 1 , wherein the semantic processing module further comprises a language translator.