Method and device for error correction model training and text error correction

Abstract

A computer-implemented method is performed at a device having one or more processors and memory storing programs executed by the one or more processors. The method comprises: selecting a target word in a target sentence; from the target sentence, acquiring a first sequence of words that precede the target word and a second sequence of words that succeed the target word; from a sentence database, searching and acquiring a group of words, each of which separates the first sequence of words from the second sequence of words in a sentence; creating a candidate sentence for each of the candidate words by replacing the target word in the target sentence with each of the candidate words; determining the fittest sentence among the candidate sentences according to a linguistic model; and suggesting the candidate word within the fittest sentence as a correction.

What is claimed is: 
     
         1 . A computer-implemented method, comprising:
 at a device having one or more processors and memory storing programs executed by the one or more processors:
 selecting a target word in a target sentence by first predefined criteria; 
 from the target sentence, acquiring a first sequence of words that precede the target word and a second sequence of words that succeed the target word; 
 from a sentence database, searching and acquiring a group of words, each of which separates the first sequence of words from the second sequence of words in a sentence; 
 from the group of words, selecting candidate words whose similarity to the target word is above a pre-set threshold according to second predefined criteria; 
 creating a candidate sentence for each of the candidate words by replacing the target word in the target sentence with each of the candidate words; 
 determining the fittest sentence among the candidate sentences according to a linguistic model; and 
 suggesting the candidate word within the fittest sentence as a correction. 
   
     
     
         2 . The method of  claim 1 , further comprising:
 after suggesting the candidate word within the fittest sentence, replacing the target word in the target sentence with the suggested candidate word.   
     
     
         3 . The method of  claim 1 , wherein the first predefined criteria include whether a character string is a word based at least on Chinese grammar. 
     
     
         4 . The method of  claim 1 , wherein acquiring the first sequence of words comprises determining length of the first sequence of words based at least on meaning of the target word. 
     
     
         5 . The method of  claim 1 , wherein acquiring the second sequence of words comprises determining length of the second sequence of words based at least on meaning of the target word. 
     
     
         6 . The method of  claim 1 , wherein the length of the first sequence of words is pre-set. 
     
     
         7 . The method of  claim 1 , wherein the linguistic model includes criteria for grammar. 
     
     
         8 . The method of  claim 1 , wherein the linguistic model includes criteria for meaning of every candidate sentence. 
     
     
         9 . The method of  claim 1 , wherein at least one candidate word whose similarity to the target word is determined based on the pronunciation of the candidate word. 
     
     
         10 . The method of  claim 1 , wherein the sentence database is updated periodically by acquiring sentences from internet sources. 
     
     
         11 . A text-processing device, comprising:
 one or more processors;   memory; and   one or more program modules stored in the memory and configured for execution by the one or more processors, the one or more program modules including instructions for:
 selecting a target word in a target sentence by first predefined criteria; 
 from the target sentence, acquiring a first sequence of words that precede the target word and a second sequence of words that succeed the target word; 
 from a sentence database, searching and acquiring a group of words, each of which separates the first sequence of words from the second sequence of words in a sentence; 
 from the group of words, selecting candidate words whose similarity to the target word is above a pre-set threshold according to second predefined criteria; 
 creating a candidate sentence for each of the candidate words by replacing the target word in the target sentence with each of the candidate words; 
 determining the fittest sentence among the candidate sentences according to a linguistic model; and 
 suggesting the candidate word within the fittest sentence as a correction. 
   
     
     
         12 . The text-processing device of  claim 11 , further comprising:
 after suggesting the candidate word within the fittest sentence, replacing the target word in the target sentence with the suggested candidate word.   
     
     
         13 . The text-processing device of  claim 11 , wherein the first predefined criteria include whether a character string is a word based at least on Chinese grammar. 
     
     
         14 . The text-processing device of  claim 11 , wherein acquiring the first sequence of words comprises determining length of the first sequence of words based at least on meaning of the target word. 
     
     
         15 . The text-processing device of  claim 11 , wherein the length of the first sequence of words is pre-set. 
     
     
         16 . The text-processing device of  claim 11 , wherein the linguistic model includes criteria for grammar. 
     
     
         17 . The text-processing device of  claim 11 , wherein the linguistic model includes criteria for meaning of every candidate sentence. 
     
     
         18 . The text-processing device of  claim 11 , wherein at least one candidate word whose similarity to the target word is determined based on the pronunciation of the candidate word. 
     
     
         19 . The text-processing device of  claim 11 , wherein the sentence database is updated periodically by acquiring sentences from internet sources. 
     
     
         20 . A non-transitory computer readable storage medium, storing one or more programs for execution by one or more processors of a computer system, the one or more programs including instructions for:
 selecting a target word in a target sentence by first predefined criteria;   from the target sentence, acquiring a first sequence of words that precede the target word and a second sequence of words that succeed the target word;   from a sentence database, searching and acquiring a group of words, each of which separates the first sequence of words from the second sequence of words in a sentence;   from the group of words, selecting candidate words whose similarity to the target word is above a pre-set threshold according to second predefined criteria;   creating a candidate sentence for each of the candidate words by replacing the target word in the target sentence with each of the candidate words;   determining the fittest sentence among the candidate sentences according to a linguistic model; and   suggesting the candidate word within the fittest sentence as a correction.