Man-machine interaction intention analysis method and device, computer equipment and storage medium

Abstract

The embodiment of the invention discloses a man-machine interaction intention analysis method and device, computer equipment and a storage medium. The method comprises: picking up semantic interaction voice and converting the semantic interaction voice into a semantic text; performing syntactic dependency analysis to obtain an analysis result; judging whether punctuation marks exist in the analysis result or not; if the first punctuation mark exists, cutting off the analysis result according to the position of the first punctuation mark to obtain two clauses; determining a core relationship and a relationship between the advertent of the clause where the core relationship is located and the head word; determining whether the semantic text contains effective information or not; if not, judging whether the end of the semantic text is a virtual word or not; if yes, deleting the virtual words at the end of the semantic text; if not, retrieving a core relationship; and judging whether the semantic text contains effective information or not by combining the subscript length of the core relationship. By implementing the method provided by the embodiment of the invention, the problem that the current semantic service cannot accurately judge the real intention of the user is solved, so that the semantic service understanding is more accurate.

Description

technical field [0001] The present invention relates to a robot, and more specifically refers to a human-computer interaction intention analysis method, device, computer equipment and storage medium. Background technique [0002] In the current human-computer voice interaction in a specific scenario, when the user says "I don't want to go to Shenzhen Bay Park, I want to go to Peking University Hospital" or similar sentences, the semantic service will most likely determine that the starting point is Shenzhen Bay Park and the end point is Peking University Hospital, that is, the current specific The semantic service of the scene cannot accurately judge the real intention of the user, which is not conducive to the triggering of related services by the semantic service; in the existing semantic interaction intention analysis algorithm, when the user's voice is directly converted into text, regardless of the length of the voice text, the converted text All without punctuation mar...

AI Technical Summary

Problems solved by technology

[0002] In the current human-computer voice interaction in a specific scenario, when the user says "I don't want to go to Shenzhen Bay Park, I want to go to Peking University Hospital" or similar sentences, the semantic service will most likely determine that the starting point is Shenzhen Bay Park and the end point is Peking University Hospital, that is, the current specific The semantic service of the scene cannot accurately judge the real intention of the user, which is not conducive to the triggering of related services by the semantic service; in the existing semantic interaction intention analysis algorithm, when the user's voice is directly converted into text, regardless of the length of the voice text, the converted text All without punctuation punctuation, that is, without sentence breaks

For this kind of sound pickup results, the efficiency of semantic service analysis is low, and it is impossible to accurately judge the real intention of the user

[0003] Therefore, it is necessary to design a new method to solve the problem that the current semantic service cannot accurately judge the user's true intention, so as to make the understanding of semantic service more accurate

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