Abstract
AbstractWith the rapid development of the field of artificial intelligence, the traditional way to check whether there is a typo in the text is very inefficient. People have been looking for a way to automatically detect and correct wrong words used in texts. The use of artificial intelligence technology for detection and correction of typography came into being. The defects and causes of the existing Chinese wrong words detection and correction technology is analyzed in this paper. The algorithm is designed to detect and correct the wrong words twice and judge the interval between the first result and the second result. The sentence perplexity is calculated by combining the deep neural network language model, forming a double filter to reduce the misjudgment in the process of wrong words detection. Experiments in various text styles indicate that the improved algorithm can reduce more than 90% of misjudgments in the process of detection and correction.KeywordsArtificial intelligenceChinese word segmentationWrong words detection and correctionLanguage modelSentence perplexity
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