Abstract: A system and method for authentication code generation based on adversarial machine learning are provided in this disclosure. The method includes a defensive authentication code generation system, an authentication code formation module, an authentication code scheduling module, an authentication-code adversarial processing center, an attack sample generation module, a verification and error reporting system, a division module, a grouping and distribution system, a category checking module, a data recording unit, a detection module and an integration terminal. In the system and method for authentication code generation based on adversarial machine learning according to the disclosure, attack scenes are simulated for continuous training for the authentication code, error-reporting data are recorded and optimized into the defensive authentication code generation system, so as to improve defense performance of the authentication code.

Abstract: This disclosure provides a method, apparatus, device, and storage medium for voice interaction, where the method is applied to an AI device to determine whether a current scenario of the AI device is a preset scenario and waken a voice interaction function of the AI device to facilitate voice interaction with a user in response to the current scenario of the AI device being the preset scenario. A scenario directly triggers the voice interaction process, thereby avoiding the process of wakening by physical wakening or a wakening word, simplifying the process of using voice interaction, reducing the costs of learning voice interaction, and improving user experience.

Abstract: This disclosure provides a method, apparatus, device, and storage medium for voice interaction, where the method is applied to an AI device to determine whether a current scenario of the AI device is a preset scenario and waken a voice interaction function of the AI device to facilitate voice interaction with a user in response to the current scenario of the AI device being the preset scenario. A scenario directly triggers the voice interaction process, thereby avoiding the process of wakening by physical wakening or a wakening word, simplifying the process of using voice interaction, reducing the costs of learning voice interaction, and improving user experience.