Correcting optical character recognition result via a novel approach

Abstract

Optical character recognition (OCR) is a recognition system used to recognize the substance of a checked picture. This system gives erroneous results, which necessitates a post-treatment, for the sentence correction. In this paper, we proposed a new method for syntactic and semantic correction of sentences it is based on the frequency of two correct words in the sentence and a recursive technique. This approach starts with the frequency calculation of each two words successive in the corpora, the words that have the greatest frequency build a correction center. We found 98% using our approach when we used the noisy channel. Further, we obtained 96% using the same corpus in the same conditions.

Realization of an intelligent evaluation system

“…The note reserved for this question is 3 points. The correction of this type of question starts with the verification of the spelling errors, the spelling errors, in this example we found two errors "defined" and "th", after the syntax correction of this answer [28] we consider the new answer is "a class is a model to generate and define the objects for the same attributes and method". Figure 4 demonstrate an example to calculate the similarity between response of teacher and student.…”

“…The syntax correction of the sentence is a technique that allows to correct the syntax errors based on a corpus and a dictionary to correct a sentence syntactically, we need to determine the correction center of the sentence (the position of the word in the sentence that has a maximum frequency in the corpus) using ( 7) [28]:…”

“…with 𝑚𝑎𝑥𝑓𝑟𝑒𝑞𝑤 is the maximum frequency of the phrase words. The second step is the detection of the erroneous words of the sentence by doing a search and a comparison of the words of the sentence with the words of the dictionary, then the calculation of the distance between the erroneous words and the words of the dictionary, in order to recover all the words close to the erroneous word, by ( 8) and ( 9) [28]:…”

“…Afterwards, the correction of the wrong word is based on the correct words of the sentence, the correction center and the list of words close to the wrong word. This processing applies a recursive technique [12] and the n-gram correction to the left and right to choose the correct word among the words of the list by calculating the frequency of each word in the list followed or preceded by a n correct word of the phrase [29]. Then the correct word is that has a non-zero frequency with a maximum n.…”