The invention is suitable for the technical field of call management, and provides a call management method and system based on voiceprint recognition, and a mobile terminal, the method comprising: when a call request sent by any incoming call user is received, acquiring incoming call voice of the incoming call user, and performing voiceprint recognition on the incoming call voice to obtain an incoming call voiceprint; obtaining a communication channel of the incoming call voice, and performing condition query according to the communication channel to obtain a target call condition; judging whether the incoming call voiceprint meets a target call condition or not; and when judging that the incoming call voiceprint meets the target call condition, disconnecting the call request, and sendinga call error prompt to the incoming call user. According to the invention, a communication channel based on incoming call voice is obtained; therefore, whether the incoming call voiceprint of the incoming call user meets the corresponding target call condition or not is judged, whether the call request is rejected or not is judged based on the judgment result of the target call condition, and then the phenomenon that call management accuracy is low due to the fact that a rejected strange number is adopted is prevented.

Call management method and system based on voiceprint recognition and mobile terminal

The invention discloses a call person abnormity detection method and device, and the method comprises the steps: enabling terminal equipment to obtain the real audio and video data of a call object which needs abnormity detection and a corresponding pre-trained multi-stage neural network detection model at the beginning of a call; in the process of communication, the terminal device collecting communication data according to a preset data collection strategy; for each conversation object, inputting the currently collected conversation data and the real audio and video data of the conversationobject into the model of the conversation object, and determining whether the conversation object is abnormal or not according to a detection result output by the model; wherein the call data comprises image data and/or voice data, and the recognition mode adopted by the model comprises face recognition, voiceprint recognition, limb action recognition and/or lip language recognition. According tothe invention, the abnormity of the conversation person can be accurately detected, and false audio and video simulated by AI in conversation can be accurately identified.

Call person abnormity detection method and device

A method and an apparatus for detecting an abnormality of a caller are provided The method includes at the beginning of a call, acquiring, by a terminal device, real voice/video data of a call object who needs abnormality detection and a corresponding pre-trained multi-stage neural network detection model, during the call, collecting, by the terminal device, call data according to a preset data collection policy, for each call object, inputting the currently collected call data and the real voice/video data of the call object into the model of the call object, and determining whether the call object is abnormal according to a detection result output by the model, in which the call data includes image data and/or voice data, and an identification manner adopted by the model includes face identification, voiceprint identification, limb movement identification, and/or lip language identification By adopting the disclosure, the abnormality of the caller may be accurately detected, and the voice forgery and the video forgery mimicked by AI during a call may be accurately identified

Method and apparatus for detecting abnormality of caller

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Call person abnormity detection method and device

Method and apparatus for detecting abnormality of caller