Customer side risk analysis method based on voice recognition

By constructing the classification of multi-dimensional feature vectors and support vector machine models, combining the acoustic characteristics and historical speech behavior of speech signals, the total risk score is calculated and dynamic threshold judgment is made, the shortcomings of combining speech recognition with risk analysis in the existing technology are solved, and a more accurate and safe customer-side speech risk analysis is achieved.

CN119724165AInactive Publication Date: 2025-03-28JIANGSU SHAREJOY HEALTH TECH CO LTD
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Patent Information

Application Number
CN202411952482.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-27
Publication Date
2025-03-28
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The prior art has shortcomings in the combination of speech recognition and risk analysis, and cannot effectively distinguish between normal speech behavior and potential risk behavior. It also seems to be very limited when processing multi-scene and multi-dimensional voice data, making it difficult to provide accurate and real-time risk judgments.

Method used

By obtaining the background information of the received data of the device-side sensor and the voice interaction, performing mixed sampling and splicing to construct a multi-dimensional feature vector. Then, based on the support vector machine model, the speech content and acoustic characteristics in the speech signal are extracted, and the speech risk factor is constructed based on historical speech behavior. Finally, the total risk score is calculated based on the scene category, confidence and speech risk factor, and the judgment is made through the dynamic threshold function.

Benefits of technology

It improves the accuracy of feature fusion, makes the classification results more in line with the actual scenario, can flexibly adjust the scene risks, accurately verify the identity in voice interaction, and effectively identify unauthorized behaviors, improving the security of voice interaction on the client side.

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Abstract

The invention discloses a client-side risk analysis method based on voice recognition, and the method comprises the steps: carrying out the mixed sampling through obtaining the receiving data, voice interaction background information and voice signals of an equipment-side sensor, and generating a multi-dimensional feature vector; based on a support vector machine model, classifying the multi-dimensional feature vectors by taking historical scene data as training data to obtain scene categories and scene confidence; meanwhile, acoustic characteristics and historical voice behaviors of the voice signals are extracted, voice risk factors are constructed, a total risk score is comprehensively calculated, and risk score judgment is carried out through a dynamic threshold function; according to a judgment result, selecting to check a voice risk factor or regenerate a multi-dimensional feature vector so as to realize accurate analysis of the customer side risk; through feature fusion and classification optimization, the accuracy and real-time performance of risk analysis are effectively improved, and the method is suitable for customer risk management in a complex voice interaction scene.
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