Abstract: A text error correction method and a text error correction apparatus based on a recurrent neural network of artificial intelligence are provided. The method includes: acquiring text data to be error-corrected; performing error correction on the text data to be error-corrected by using a trained recurrent neural network model so as to generate error-corrected text data.

Abstract: A method, a device, and a storage medium for correcting an error in a speech recognition result are provided. The method includes: performing phonetic notation on a speech recognition result to be corrected, to obtain a pinyin corresponding to the speech recognition result; obtaining one or more candidate texts according to the pinyin, and determining an optimum candidate text from the one or more candidate texts; judging whether the optimum candidate text satisfies a preset condition; and determining the optimum candidate text as a corrected result of the speech recognition result to be corrected in response to satisfying the preset condition.

Abstract: A method, a device, and a storage medium for correcting an error in a speech recognition result are provided. The method includes: performing phonetic notation on a speech recognition result to be corrected, to obtain a pinyin corresponding to the speech recognition result; obtaining one or more candidate texts according to the pinyin, and determining an optimum candidate text from the one or more candidate texts; judging whether the optimum candidate text satisfies a preset condition; and determining the optimum candidate text as a corrected result of the speech recognition result to be corrected in response to satisfying the preset condition.

Abstract: An amendment source-positioning method and apparatus, a computer device and a readable medium. The method includes: obtaining a first target word identifying an amendment source and defining parameters of the amendment source, from semantic parsing information of a user-input speech error correction instruction; positioning the amendment source from a to-be-corrected text according to the first target word and the defining parameters. As compared with the template matching and positioning scheme employed in the prior art, the technical solution of the present disclosure can support a speech error correction instruction in any form, and exhibits a more flexible amendment source-positioning manner, thereby effectively improving the amendment source-positioning efficiency.

Abstract: A method and a device for processing a speech instruction are provided. With the method, a speech instruction is recognized so as to generate text information corresponding to the speech instruction. Semantic analysis is performed on the text information so as to obtain a semantic analysis result of the text information. Whether a corresponding operation is executable based on the semantic analysis result of the text information is determined. If it is determined that the corresponding operation is not executable based on the semantic analysis result of the text information, whether the text information belongs to instruction text data is determined. If yes, the text information is corrected so as to obtain corrected text information. Semantic analysis is performed on the corrected text information, and the corresponding operation is executed according to a semantic analysis result of the corrected text information.

Abstract: A method and an apparatus for processing a semantic analysis result based on AI are provided. With the method, the weight of the analysis text in the corresponding analysis result is determined according to the preset weight configuration information; the semantic confidence of the analysis result is detected via the pattern matching algorithm; the analysis type of the analysis texts is determined by the first classification model, and the field matching confidence of the analysis texts over the analysis result is determined by the second classification model; and then the analysis quality data of the analysis result is obtained according to the weights, the semantic confidence, the analysis type and the field matching confidence.

Abstract: A text error correction method and a text error correction apparatus based on a recurrent neural network of artificial intelligence are provided. The method includes: acquiring text data to be error-corrected; performing error correction on the text data to be error-corrected by using a trained recurrent neural network model so as to generate error-corrected text data.

Abstract: An amendment source-positioning method and apparatus, a computer device and a readable medium. The method includes: obtaining a first target word identifying an amendment source and defining parameters of the amendment source, from semantic parsing information of a user-input speech error correction instruction; positioning the amendment source from a to-be-corrected text according to the first target word and the defining parameters. As compared with the template matching and positioning scheme employed in the prior art, the technical solution of the present disclosure can support a speech error correction instruction in any form, and exhibits a more flexible amendment source-positioning manner, thereby effectively improving the amendment source-positioning efficiency.

Abstract: A method and a device for processing a speech instruction are provided. With the method, a speech instruction is recognized so as to generate text information corresponding to the speech instruction. Semantic analysis is performed on the text information so as to obtain a semantic analysis result of the text information. Whether a corresponding operation is executable based on the semantic analysis result of the text information is determined. If it is determined that the corresponding operation is not executable based on the semantic analysis result of the text information, whether the text information belongs to instruction text data is determined. If yes, the text information is corrected so as to obtain corrected text information. Semantic analysis is performed on the corrected text information, and the corresponding operation is executed according to a semantic analysis result of the corrected text information.

Abstract: A method and an apparatus for processing a semantic analysis result based on AI are provided. With the method, the weight of the analysis text in the corresponding analysis result is determined according to the preset weight configuration information; the semantic confidence of the analysis result is detected via the pattern matching algorithm; the analysis type of the analysis texts is determined by the first classification model, and the field matching confidence of the analysis texts over the analysis result is determined by the second classification model; and then the analysis quality data of the analysis result is obtained according to the weights, the semantic confidence, the analysis type and the field matching confidence.