Auxiliary control method and system based on post verification

Abstract

The invention provides an auxiliary control method and system based on post verification. The method comprises the steps that through the pre-processing of original command signals, obtaining auxiliary control information, conducting grammatical template matching of the auxiliary control information based on fields to obtain command operator parts and operation parameter parts, using the post verification method corresponding to the fields to analyze the operation parameter parts, treating the result which is obtained from the analysis and with the highest matching level as the operation parameters of the command operator parts, generating auxiliary control commands and sending the control commands to a central processing unit for operation, thus achieving the auxiliary control. The invention hugely enhances the precision of semantic identification based on current grammatical retrieval. By simulating the manner of human understanding of language, all the semantic meanings which can be extracted from the colloquial expression content inputted by the user are identified, and the identification rate and the user's experience are enhanced.

Description

Technical field [0001] The present invention relates to a technology in the field of semantic recognition, in particular to an auxiliary control method and system based on post-verification. Background technique [0002] Semantic recognition enables artificial intelligence to better understand humans, and finally adjust the hardware working state is the main problem facing the field of industrial automation control. The existing semantic recognition is mainly based on natural language understanding, and usually uses a regular expression retrieval method of grammar + keyword list. For example: The syntax is: I want to eat <slot1> ; And the keyword, namely <slot1> For specific food names, restaurant names, etc. The general recognition method matches all the characters after the keyword "eat" with the keyword list one by one when it conforms to the grammar, and the follow-up operation is performed only when there is a matching result. [0003] Although the existing voice...

AI Technical Summary

Problems solved by technology

[0004] 1. It is difficult to balance between recognition synchronization and resource occupation: as things are updated and developed, the keyword list will become very large

Maintaining corresponding keyword lists of different grammars will lead to huge workload and system resources, thereby reducing recognition performance; if the maintenance of keyword lists is not synchronized, new keywords will not be recognized; if fuzzy retrieval is added, it will further Leading to resource occupation and user experience degradation

[0005] 2. The standardization of grammatical expression: users must strictly follow the system's preset method for grammatical expression, and it is difficult to clearly identify the correct semantics of colloquial input, inversion, postposition or emphasis sentence patterns

Makes the level of knowledge expression to the user higher in the actual recognition process, which limits the popularization of speech technology

[0006] 3. There is no follow-up intelligent processing when there is ambiguity or no matching result: When the same grammar is used in multiple different fields, it is easy to conflict due to ambiguity in the understanding of keywords

[0007] To sum up, although the existing recognition technology can identify the general intention of the user through grammar to a certain extent, it is difficult to accurately identify the precise parameters based on the intention. The result of the recognition is to directly judge the content containing the meaning of the parameter as ordinary characters, so that the semantics of user input are lost

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