Spelling error correction method and device based on Chinese character pronunciation and shape similarity and electronic equipment

Abstract

The embodiment of the invention provides a spelling error correction method and device based on Chinese character pronunciation and shape similarity and electronic equipment. The spelling error correction method comprises the steps: constructing a sample Chinese character set containing Chinese character pronunciation and shape information according to a standard Chinese character database; based on the Chinese character conversion cost in the sample Chinese character set, calculating the similarity of the corresponding Chinese character pronunciation and shape information between any two Chinese characters, and constructing a similar Chinese character set corresponding to each Chinese character in the sample Chinese character set according to the obtained similarity result; and acquiring candidate words associated with the target Chinese character, and screening by combining a numerical relationship between the similarity of the target Chinese character and the candidate words and a threshold value to obtain a replacement Chinese character after error correction of the target Chinese character. The Chinese character conversion cost calculation is only carried out in the initial process of pronunciation and shape editing, and the calculation among levels is not involved in the specific process, so that the Chinese character conversion cost is only taken out from a mapping dictionary of pre-loaded Chinese characters and dictionaries; the method can effectively reduce the huge calculation amount caused by continuous comparison from the top layer of the tree to the bottom in the BK tree Chinese error correction algorithm, and improves the error correction efficiency.

Description

technical field [0001] The present application relates to the field of text error correction, in particular to a spelling error correction method, device and electronic equipment based on the similarity of phonetic and shape of Chinese characters. Background technique [0002] In scenarios such as Chinese Optical Character Recognition (OCR) and Automatic Speech Recognition (ASR), recognition errors may occur due to the similarity of Chinese characters in sound and shape. Generally, a large number of errors can be resolved by adding post-processing modules (Chinese spelling error correction) output by models such as ASR and OCR. [0003] In order to reduce the number of search traversals, a BK (Burkhard-Keller) tree structure is introduced. The BK tree constructs a tree structure based on the conversion cost of Chinese character strings between the correct lexicons, and then quickly searches for similar (Chinese character conversion cost) Chinese character strings based on t...

AI Technical Summary

Problems solved by technology

[0004] (1) The BK tree structure mainly supports natural word segmentation scenarios (word segmentation is easy to obtain in general search scenarios, and it is almost impossible to obtain correct word segmentation results in other scenarios), and the scope of use is limited;

[0005] (2) BK tree error correction requires real-time calculation of the Chinese character conversion cost between two Chinese character strings, and the performance is poor when the tree depth is deep;

[0006] (3) As the domain dictionary becomes larger and the BK tree becomes deeper, the performance will drop sharply;

[0007] (4) The retrieval range of BK tree increases sharply with the increase of the threshold of the number of wrong Chinese characters, and the performance will also drop sharply

Although BK tree similarity retrieval is a reasonable intervention method for Chinese misspellings, it has problems of insufficient performance and limited scope of use.

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