Voice interaction data processing method and device supporting type-c interface

Abstract

The invention provides a voice interaction data processing method and device supporting a type-c interface, and belongs to the technical field of data processing.The device specifically comprises a main control board module, a sound card module and the type-c interface, the main control board module provides at least two interfaces for a host, one interface is a headset audio interface, and the other interface is a serial port data transmission interface; the serial port data transmission interface at least supports one serial port and performs data interaction with the mobile equipment by using the type-c interface, and the main control board realizes high-speed transmission among audio data, serial port data and sound card data between the main control board and the sound card module by setting the DMA module, so that the voice interaction data processing reliability is improved.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and in particular relates to a voice interaction data processing method and device supporting a Type-C interface. Background Art

[0002] In order to implement quality inspection of mobile phones, the invention patent application CN202311103890.4 "A sensitive word quality inspection method and device based on a large model" imports the input text into a customized large language model for quality inspection to obtain a third quality inspection result, thereby ensuring compliance, improving efficiency, reducing costs, and reducing disputes. However, there are the following technical problems: When conducting quality inspection on mobile devices, specific modifications are often made to the mobile devices, making the quality inspection more difficult. Therefore, how to use the type-c interface to obtain the voice data of the mobile device's operation data and generate targeted quality inspection strategies has become a technical problem that needs to be solved urgently.

[0003] In response to the above technical problems, the present invention provides a voice interaction data processing method and device supporting a type-c interface. Summary of the invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: According to one aspect of the present invention, a voice interaction data processing device supporting a type-c interface is provided, specifically comprising: Main control board module, sound card module, type-c interface; The main control board module provides at least two interfaces for the host, one is a headset audio interface, and the other is a serial port data transmission interface. The serial port data transmission interface supports at least one serial port and uses the type-c interface to exchange data with the mobile device. The main control board realizes high-speed transmission of audio data, serial port data and sound card data between the sound card module by setting up the DMA module.

[0005] A further technical solution is that the hardware circuit of the main control board module realizes the rapid transmission of audio data between the sound card module and the main control board module through the I2S bus, and the main control board module realizes the configuration and control of the sound card module through the I2C bus.

[0006] A further technical solution is that when the type-c interface is used to connect to a mobile device, the voice interaction data processing device is identified as a hardware device, and the hardware device is identified as a headset device by the mobile device, and voice data can be collected through the hardware device and transmitted back to the application software of the mobile device; The voice data transmitted back to the mobile device is stored or connected to the cloud AI, which responds to the voice data and obtains response audio. The response audio is then transmitted back to the hardware device through the application software of the mobile device. The hardware device provides voice feedback of the mobile device for the call through the microphone.

[0007] A further technical solution is that the hardware device is provided with at least two serial ports, one for transmitting the voice data of the earphone to the mobile device, and the other for transmitting the voice data transmitted by the external microphone to the software on the mobile device.

[0008] The two serial ports in the present invention can work simultaneously, or one serial port can be started to work separately. The present invention is not limited to two serial ports, and one or more serial ports can be independently set as needed.

[0009] A further technical solution is that the hardware device at least includes a headset device and a custom serial port communication device, and the hardware device includes a headset device, a custom serial port communication device, a USB storage device, and a charging device.

[0010] A further technical solution is that the hardware device can work without obtaining software authentication, and can also be set to obtain application authentication of the mobile device before starting the normal working state.

[0011] A further technical solution is that a method for determining the application authentication of the mobile device is as follows: Insert the hardware device into the mobile device, and after the application of the mobile device detects the hardware device, obtain the device information of the hardware device; Encrypting the device information to obtain encrypted data, and sending the encrypted data to the hardware device; After the hardware device successfully decrypts the encrypted data, the hardware device is set to a normal working state. If the decryption is unsuccessful, the hardware device is set to a standby state.

[0012] On the other hand, the present application provides a method for processing voice interaction data supporting a type-c interface, using the above-mentioned voice interaction data processing device supporting a type-c interface, specifically comprising: S1 determines the matching person of the mobile device based on the corresponding relationship of the mobile device, and uses the historical violation behavior of the matching person and the identification result of the violation behavior to determine the violation risk coefficients of different matching persons and the mobile devices that need to be installed with the voice interaction data processing device, and uses them as target mobile devices; S2: using the type-c interface to obtain the operation data of the target mobile device, and using the analysis results of the operation data within a preset period of time to determine that the voice interaction data processing device is suspected of abnormal use, proceed to the next step; S3 obtains historical operation data of the target mobile device at different time periods within a preset time period, and determines a matching coefficient between the operation data at different time periods and the historical operation data according to the analysis result of the historical operation data, and proceeds to the next step when it is determined by using the matching coefficient that there is no abnormal time period; S4 determines the violation behaviors in different time periods and the identification results of the violation behaviors based on the operation data in different time periods, and determines whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device in combination with the matching coefficients in different time periods and the violation risk coefficients of the matching personnel.

[0013] The beneficial effects of the present invention are: By utilizing the analysis results of the operation data within a preset time period, it is determined whether there is any suspected abnormal use of the voice interaction data processing device, thereby realizing the screening of mobile terminals that do not have the voice interaction data processing device installed or do not properly install the voice interaction data processing device from the perspective of the operation data within the preset time period, avoiding the inability to accurately monitor illegal behaviors due to abnormal use of the voice interaction data processing device, and ensuring the reliability of monitoring and processing of illegal behaviors.

[0014] Whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device is determined based on the violation behaviors in different time periods and the identification results of the violation behaviors, the matching coefficients in different time periods and the violation risk coefficients of the matching persons. This not only takes into account the violation situations in the preset time period, but also takes into account the abnormal situations of the behaviors caused by the differences in the matching coefficients in different time periods. At the same time, it is further combined with the violation risk coefficient to realize the determination of mobile devices that need to be detected for abnormal usage behavior from multiple angles.

[0015] A further technical solution is that the matching person of the mobile device is determined according to the corresponding relationship between the mobile device and the person.

[0016] A further technical solution is that the historical illegal behaviors include the number of illegal uses of the software and the number of illegal communications.

[0017] A further technical solution is that the illegal behavior includes the number of violations during which the illegal behavior occurs.

[0018] A further technical solution is that the method for determining the violation risk coefficient of the matching person is: Determine the number of occurrences of the historical violations of the matching person based on the identification results of the historical violations of the matching person, and use it as the number of violations; Determine the number of occurrences of the violation of the matching person according to the identification result of the violation of the matching person, and use it as the number of occurrences of the violation; The violation risk coefficient of the matching person is determined based on the preset risk coefficient corresponding to the number of violation occurrences and the preset risk coefficient corresponding to the number of violation occurrences.

[0019] A further technical solution is to determine whether it is necessary to perform abnormal use behavior detection on the voice interaction data processing device, specifically including: determining the existence of illegal behaviors and the time period of illegal behaviors based on the illegal behaviors in different time periods and the identification results of illegal behaviors, and using them as the illegal time period, and determining the violation coefficient based on the number ratio of the illegal time period; The detection requirement coefficient of abnormal behavior is determined based on the violation coefficient, the matching coefficient and the violation risk coefficient of the matching person, and it is determined whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device according to the detection requirement coefficient.

[0020] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0023] Figure 1 It is a framework diagram of a voice interaction data processing device supporting a type-c interface; Figure 2 It is a hardware framework diagram of a voice interaction data processing device supporting a type-c interface; Figure 3 It is a flow chart of a method for processing voice interaction data supporting a type-c interface; Figure 4 is a flow chart of a method for determining a violation risk factor of a matching person; Figure 5 is a flow chart of a method for determining suspected abnormal use of a voice interaction data processing device; Figure 6 is a flow chart of a method for determining an abnormality-free period. DETAILED DESCRIPTION

[0024] The present invention connects an external hardware device through a type-c interface, and the device is recognized by the mobile device as a headset device. The call sound of the mobile device can be collected through the device and transmitted back to the mobile device application software. The application software is connected to the cloud AI, and the cloud AI responds to the sound. The response audio is then transmitted back to the external device through the mobile device application software. The external device provides sound feedback of the mobile device for the call through the microphone of the headset device.

[0025] The recording data involved in the application has been obtained with full consent and authorization, and the collection, use and processing of relevant information must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0026] The device provides an external headset interface. When a headset is plugged into the external headset interface, the call audio of the mobile device is cut off from the path to the cloud AI and automatically switches to the external headset.

[0027] The sound flow path of the present invention to implement the above method in the device is mobile device <-> sound card <-> serial port <-> APP <-> cloud AI.

[0028] In the present invention, a path selection switch is set on the hardware device to realize the switch from cloud AI call to call recording storage function. The path selection switch can be switched to (1) cloud AI call, (2) recording to the hardware device, and (3) synchronizing the call recording to the cloud.

[0029] Through the path selection switch, the present invention provides a method and device for recording and storing calls while realizing calls on a mobile device through external hardware.

[0030] The method connects a hardware device via a type-c interface, and the device is recognized by the mobile device as a headset device. The call sound of the mobile device can be collected and stored on the hardware device through the device. The stored sound data can be transmitted to the mobile device application software through the serial port and synchronized to the cloud storage.

[0031] When this method detects an external headset, it will switch to the recording and storage functions that support the external hardware.

[0032] The sound stream of the present invention that realizes the above-mentioned recording storage function has a circulation route in the device of mobile device <-> sound card <-> local storage <-> serial port <-> APP <-> cloud storage.

[0033] The hardware device in the present invention is an external terminal of a host device (mobile device or other host terminal), which is recognized as a hardware device by the host device. The hardware device includes at least a sound card and a custom serial communication device. The hardware device may include a sound card, a custom serial communication device and a USB storage device. The hardware device may include a sound card, a custom serial communication device, a USB storage device and a charging device.

[0034] Embodiment 1 To solve the above problem, according to one aspect of the present invention, Figure 1 As shown, a voice interaction data processing device supporting a type-c interface is provided, specifically comprising: Main control board module, sound card module, type-c interface; The main control board module provides at least two interfaces for the host, one is a headset audio interface, and the other is a serial port data transmission interface. The serial port data transmission interface supports at least one serial port and uses the type-c interface to exchange data with the mobile device. The main control board realizes high-speed transmission of audio data, serial port data and sound card data between the sound card module by setting up the DMA module.

[0035] The device includes both circuit hardware and a firmware program running on a main control board, wherein the firmware program runs on the hardware circuit and realizes the functions of the present invention based on the hardware circuit.

[0036] The hardware device in the present invention comprises a main control board module, a sound card module and a power master-slave charging module, wherein the charging module is an optional module.

[0037] The present invention may include a master-slave charging module, which can realize the functions of charging the host and supplying power to the main control board and the sound card without affecting the functions of the main control board.

[0038] The present invention may not include a master-slave charging module. In this case, the working power supply of the main control board is provided by the host.

[0039] The main control board circuit in the present invention provides at least two interfaces for the host, one is a headset audio interface, the other is a serial data transmission interface, and in addition, it can also include a master-slave charging device interface. The serial data transmission interface supports at least one serial port.

[0040] The main control board of the present invention realizes high-speed transmission between audio, serial port data and sound card data by setting a DMA module. The hardware circuit realizes fast transmission of audio data between the sound card and the main control board through the I2S bus. The main control board realizes configuration and control of the sound card through the I2C bus.

[0041] The digital form of the voice data in the present invention can be but is not limited to the PCM audio digital format. The digital audio realizes the input and output of sound through the A / D and D / A digital-to-analog conversion circuits on the sound card and the external headphones and microphones.

[0042] Optionally, the hardware circuit of the main control board module realizes fast transmission of audio data between the sound card module and the main control board module through the I2S bus, and the main control board module realizes configuration and control of the sound card module through the I2C bus.

[0043] Further, such as Figure 2 As shown, when the type-c interface is used to connect to a mobile device, the voice interaction data processing device is identified as a hardware device, and the hardware device is identified as a headset device by the mobile device. Voice data can be collected through the hardware device and transmitted back to the application software of the mobile device; The voice data transmitted back to the mobile device is stored or connected to the cloud AI, which responds to the voice data and obtains response audio. The response audio is then transmitted back to the hardware device through the application software of the mobile device. The hardware device provides voice feedback of the mobile device for the call through the microphone.

[0044] The present invention provides a method and device for automatically recording and storing calls on a mobile device or applications on a mobile device that uses voice, and can automatically connect to cloud AI. The device system consists of external hardware independent of the mobile device and software on the mobile device. After the device hardware is connected to the mobile device, it can run independently and is independent of the mobile device model, and has strong compatibility.

[0045] This method uses a type-c interface to connect a hardware device, which is recognized by the mobile device as a headset device. The voice of the mobile device can be collected through the device and sent back to the mobile device application software. The voice data sent back to the mobile device can be stored or connected to the cloud AI, which responds to the voice and then sends the response audio back to the external device through the mobile device application software. The external device provides voice feedback on the mobile device for the call through the microphone of the headset device.

[0046] The device provides an external headset interface. When a headset is plugged into the external headset interface, the call audio of the mobile device is cut off from the cloud AI and automatically switches to the external headset.

[0047] When the external headset interface has a headset working, the voice data of the external headset and microphone are also transmitted back to the mobile device for storage. In the present invention, two serial ports are set, one for transmitting the voice data of the headset and the microphone data sent to the mobile device by the mobile device software, and the other for transmitting the voice data transmitted by the external microphone to the mobile device software. The two serial ports in the present invention can work at the same time, or one serial port can be started separately. The present invention is not limited to two serial ports, and one or more serial ports can be independently set as needed.

[0048] Furthermore, the hardware device is provided with at least two serial ports, one for transmitting the voice data of the headset to the mobile device, and the other for transmitting the voice data transmitted by the external microphone to the software on the mobile device. The two serial ports in the present invention can work simultaneously, or one serial port can be started to work separately. The present invention is not limited to two serial ports, and one or more serial ports can be independently set as needed.

[0049] It should be noted that the hardware device at least includes a headset device and a custom serial port communication device. The hardware device includes a headset device, a custom serial port communication device, a USB storage device, and a charging device.

[0050] The transmission route of the voice stream in the device implemented by the present invention is mobile device<->headset device<->serial port<->APP<->cloud AI.

[0051] In the present invention, a path selection switch is set on the hardware device to realize the switch from cloud AI call to call recording storage function. The path selection switch can be switched to (1) cloud AI call, (2) recording to the hardware device, (3) synchronizing the call recording to the cloud. The call selection switch can select one of the above, or multiple at the same time.

[0052] Through the path selection switch, the present invention provides a method and device for recording and storing the voice call of the mobile device through external hardware.

[0053] The method connects a hardware device via a type-c interface, and the device is recognized by the mobile device as a headset device. The voice of the mobile device can be collected through the device and stored on the hardware device. The stored sound data can be transmitted to the mobile device application software through the serial port and synchronized to the cloud storage.

[0054] When the method detects that an external headset is connected, the recording and storage functions of the external hardware can be supported simultaneously.

[0055] The transmission route of the voice stream in the device for realizing the above-mentioned recording storage function of the present invention is mobile device<->sound card<->local storage<->serial port<->APP<->cloud storage.

[0056] The hardware device in the present invention is an external terminal of a host device (mobile device or other host terminal), and the terminal is recognized as a hardware device by the host device. The hardware device includes at least a headset device and a custom serial port communication device. The hardware device may include a headset device, a custom serial port communication device and a USB storage device.

[0057] The hardware device may include a headset device, a custom serial port communication device, a USB storage device and a charging device.

[0058] The method and device provided by the present invention can provide the mobile device phone user with an AI automatic answering function, and can provide the mobile device phone user with a call and synchronous recording function.

[0059] The device of the present invention is connected to a mobile device or other host device via a type-c port.

[0060] Furthermore, the hardware device can work without obtaining software authentication, or can be configured to obtain application authentication of the mobile device before starting a normal working state.

[0061] Specifically, the method for determining the application authentication of the mobile device is: Insert the hardware device into the mobile device, and after the application of the mobile device detects the hardware device, obtain the device information of the hardware device; Encrypting the device information to obtain encrypted data, and sending the encrypted data to the hardware device; After the hardware device successfully decrypts the encrypted data, the hardware device is set to a normal working state. If the decryption is unsuccessful, the hardware device is set to a standby state.

[0062] In another embodiment, the method for authenticating the application of the mobile device is: Insert the hardware device into the mobile device, and after the application of the mobile device detects the hardware device, obtain the device information and random number encrypted digital string of the hardware device; The application program calculates the random number encrypted digital string to obtain a calculation result, and sends the calculation result to the hardware device; After the hardware device successfully authenticates the calculation result, the hardware device is set to a normal working state.

[0063] Embodiment 2 In the second aspect, as Figure 3As shown, the present application provides a voice interaction data processing method supporting the type-c interface, specifically including: S1 determines the matching person of the mobile device based on the corresponding relationship of the mobile device, and uses the historical violation behavior of the matching person and the identification result of the violation behavior to determine the violation risk coefficients of different matching persons and the mobile devices that need to be installed with the voice interaction data processing device, and uses them as target mobile devices; S2: using the type-c interface to obtain the operation data of the target mobile device, and using the analysis results of the operation data within a preset period of time to determine that the voice interaction data processing device is suspected of abnormal use, proceed to the next step; S3 obtains historical operation data of the target mobile device at different time periods within a preset time period, and determines a matching coefficient between the operation data at different time periods and the historical operation data according to the analysis result of the historical operation data, and proceeds to the next step when it is determined by using the matching coefficient that there is no abnormal time period; S4 determines the violation behaviors in different time periods and the identification results of the violation behaviors based on the operation data in different time periods, and determines whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device in combination with the matching coefficients in different time periods and the violation risk coefficients of the matching personnel.

[0064] Furthermore, the matching person of the mobile device is determined according to the corresponding relationship between the mobile device and the person.

[0065] Specifically, the historical violations include the number of illegal uses of the software and the number of illegal communications.

[0066] It should be noted that the violation includes the number of violations during which the violation occurred.

[0067] It should be noted that if Figure 4 As shown, the method for determining the violation risk coefficient of the matching personnel is: Determine the number of occurrences of the historical violations of the matching person based on the identification results of the historical violations of the matching person, and use it as the number of violations; Determine the number of occurrences of the violation of the matching person according to the identification result of the violation of the matching person, and use it as the number of occurrences of the violation; The violation risk coefficient of the matching person is determined based on the preset risk coefficient corresponding to the number of violation occurrences and the preset risk coefficient corresponding to the number of violation occurrences.

[0068] Furthermore, the violation risk coefficient of the matching person is determined based on the sum of the preset risk coefficient corresponding to the number of violation occurrences and the preset risk coefficient corresponding to the number of violation occurrences.

[0069] Optionally, the preset risk coefficient corresponding to the number of violation occurrences is determined based on a preset corresponding relationship between the number of violation occurrences and the risk coefficient.

[0070] It should also be noted that the method for determining the violation risk coefficient of the matching personnel is: Determine the number of occurrences of the historical violations of the matching person based on the identification results of the historical violations of the matching person, and use it as the number of violations; Determine the number of occurrences of the violation of the matching person according to the identification result of the violation of the matching person, and use it as the number of occurrences of the violation; The total number of violations is determined based on the number of violation occurrences and the number of violation occurrences, and the violation risk coefficient of the matching person is determined using the total number of violations.

[0071] Furthermore, the violation risk coefficient of the matching person is determined based on the ratio of the total number of violations to a preset number of violations.

[0072] Optionally, the method for determining the violation risk coefficient of the matching personnel is: S11 determines the number of times the matching person has used different software in violation of the rules based on the identification results of the matching person's historical violation behaviors, and determines the violation coefficient of the matching person according to the number of times the different software has been used in violation of the rules and the number of times the violation communications have been made; S12 determines the number of times the matching person has violated the rules based on the identification results of the matching person's violation behaviors, and determines the violation coefficient of the matching person according to the number of times the violation has occurred in different preset time periods; S13 determines the violation risk coefficient of the matching person based on the violation coefficient and the violation behavior coefficient.

[0073] Specifically, the mobile device that needs to be installed with the voice interaction data processing device is a mobile device corresponding to a matching person whose violation risk coefficient does not meet the requirements.

[0074] Optional, such as Figure 5 As shown, determining that the voice interaction data processing device has suspected abnormal use specifically includes: Determine the operation data of different time periods within the preset time period based on the analysis result of the operation data within the preset time period, and determine the idle time period of the time period based on the operation data of different time periods; Determine whether the voice interaction data processing device has suspected abnormal use based on the number of the idle time periods.

[0075] Furthermore, when the number of the idle time periods is greater than the number of preset time periods, it is determined that there is suspected abnormal use of the voice interaction data processing device.

[0076] It should also be noted that determining that the voice interaction data processing device is suspected of abnormal use specifically includes: Determine the operation data of different time periods within the preset period based on the analysis result of the operation data within the preset period, and determine the number of operations within the preset period using the operation data of different time periods; Determine whether the voice interaction data processing device has suspected abnormal use based on the number of operations within the preset time period.

[0077] Optionally, determining that the voice interaction data processing device is in suspected abnormal use specifically includes: S21 determines the operation data of different time periods within the preset period based on the analysis result of the operation data within the preset period; Optionally, the above step S21 includes the following contents: S211 determines the operation data of different time periods within the preset period based on the analysis result of the operation data within the preset period. When there is no operation data within the preset period, it is determined that there is suspected abnormal use of the voice interaction data processing device. When there is operation data within the preset period, the process proceeds to step S212. S212 determines the operation times of different softwares based on the analysis result of the operation data. When the total operation times of different softwares are less than the preset operation times threshold, the process proceeds to step S213. When the total operation times of different softwares are not less than the preset operation times threshold, the process proceeds to step S22. S213 obtains the operation times of different software. When there is no software whose operation times are greater than the preset limit value, it is determined that there is suspected abnormal use of the voice interaction data processing device. When there is software whose operation times are greater than the preset limit value, it goes to step S22.

[0078] S22 determines the usage idle coefficients of different time periods according to the number of operations of different software in different time periods, and determines the idle time period in the time period by using the usage idle coefficients; Optionally, the above step S22 includes steps S221-S223, specifically: S221 determines the idle coefficients of different time periods according to the number of operations of different software in different time periods, and when it is determined by using the idle coefficients that there is no idle period in the time period, it is determined that there is no suspected abnormal use of the voice interaction data processing device, and when it is determined by using the idle coefficients that there is an idle period in the time period, it proceeds to step S222; S222: determining an idle period in the period by using the idle coefficient; when the number of idle periods does not meet the requirement, determining that the voice interaction data processing device has suspected abnormal use; when the number of idle periods meets the requirement, proceeding to step S223; S223 determines the average value of the idle coefficients for different time periods based on the idle coefficients for different time periods. When the average value of the idle coefficients for different time periods is greater than the preset idle coefficient threshold, it is determined that there is suspected abnormal use of the voice interaction data processing device. When the average value of the idle coefficients for different time periods is not greater than the preset idle coefficient threshold, proceed to step S23.

[0079] S23 determines the idle coefficient evaluation value of the voice interaction data processing device according to the time corresponding to different idle time periods and the idle coefficient used in the idle time periods, and uses the idle coefficient evaluation value to determine whether there is suspected abnormal use of the voice interaction data processing device.

[0080] Optionally, the above step S23 includes the following contents: S21 determines the weight coefficients of different idle time periods according to the time corresponding to different idle time periods. When the sum of the weight coefficients of the idle time periods does not meet the requirement, it is determined that the voice interaction data processing device is suspected of abnormal use. When the sum of the weight coefficients of the idle time periods meets the requirement, the process proceeds to step S22. S22 determines the modified idle coefficients of different idle periods by using the weight coefficients of different idle periods and the idle coefficients used. When the sum of the modified idle coefficients of the idle periods does not meet the requirements, it is determined that the voice interaction data processing device is suspected of abnormal use. When the sum of the modified idle coefficients of the idle periods meets the requirements, it proceeds to step S23. S23 determines the idle coefficient evaluation amount of the voice interaction data processing device according to the time corresponding to different idle periods and the idle coefficient used in the idle periods, and uses the idle coefficient evaluation amount to determine whether the voice interaction data processing device has suspected abnormal use. Figure 6 As shown, it is determined that there is no abnormal period, including: Determine the number of times the software was used in the period on different dates using historical operation data in the period; Determine the number of times the software is used and the times during the period according to the operation data of the period, and determine the coefficient of deviation from different dates in combination with the times and the times the software is used on different dates; The deviation coefficient is used to determine the matching date in the date, and the matching coefficient is determined according to the proportion of the matching date in the date, and whether the time period is an abnormal time period is determined based on the matching coefficient.

[0081] Specifically, the deviation coefficient is determined according to an average value of the deviation amount of the number of times on different dates and the deviation amount of the number of times the software is used.

[0082] Furthermore, the matching date is a date whose deviation coefficient is less than a preset deviation coefficient.

[0083] It should also be noted that when the matching coefficient of the time period is less than a preset matching coefficient, the time period is determined to be an abnormal time period.

[0084] Further, when it is determined that there is an abnormal period, it is determined that the voice interaction data processing device needs to be subjected to abnormal usage behavior detection.

[0085] Optionally, determining that there is no abnormal period includes: Determine the number of times and times of software usage in the period according to the operation data of the period, and when the number of times and times of software usage in the period are both within a preset number range, determine that the period is an abnormal period; When the number of times the software is used during the period and any of the times is not within the preset range: Determine the number of times and the number of times the software is used in the period on different dates based on the historical operation data in the period, determine the number of times and the number of times the software is used in the period based on the operation data in the period, and determine the deviation coefficient from different dates based on the number of times and the number of times the software is used on different dates; When the deviation date is determined according to the deviation coefficient: When the number of deviation dates does not meet the requirement, the period is determined to be an abnormal period; When the number of deviation dates meets the requirement: Based on the deviation coefficients of different dates, an average value of the deviation coefficients of different dates is determined. When the average value of the deviation coefficients of different dates does not meet the requirements, the period is determined to be an abnormal period. When the average value of the coefficient of variation on different dates meets the requirements: Based on the deviation coefficients of different deviation dates, a comprehensive deviation coefficient is determined, and when the comprehensive deviation coefficient does not meet the requirements, the period is determined to be an abnormal period; When it is determined based on the deviation coefficient that there is no deviation date or the comprehensive deviation coefficient does not meet the requirements: The deviation coefficient is used to determine the matching date in the date, and the matching coefficient is determined according to the proportion of the matching date in the date, and whether the time period is an abnormal time period is determined based on the matching coefficient.

[0086] Specifically, determining whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device specifically includes: The violations and the identification results of the violations in different time periods are used to determine the violations and the time periods in which the violations exist, and these are used as the violation time periods. The violation coefficient is determined using the percentage of the number of violation time periods. The detection requirement coefficient of abnormal behavior is determined based on the violation coefficient, the matching coefficient and the violation risk coefficient of the matching person, and it is determined whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device according to the detection requirement coefficient.

[0087] Optionally, before entering step S11, the following contents are also included: Determine the number of occurrences of the matching person's historical violations based on the identification results of the matching person's historical violations, and use it as the number of violations; determine the number of occurrences of the matching person's historical violations based on the identification results of the matching person's violations, and use it as the number of violations; When the number of illegal uses and the number of violations are both less than the preset threshold, it is determined that the mobile device does not belong to the mobile device that requires the installation of a voice interaction data processing device. When the number of illegal uses and the number of violations are both not less than the preset threshold, proceed to step S11.

[0088] Optionally, the above step S11 includes the following contents: S111 determines the number of times the matching person has used different software illegally based on the identification result of the matching person's historical illegal behavior. When the number of illegal uses is within a preset number interval and the number of violations is within the preset number interval, the process proceeds to step S112. When the number of violations and the number of violations are not within the preset number interval, the process proceeds to step S113. S112: When there is no software with a number of illegal uses greater than the preset number of illegal uses threshold, it is determined that the mobile device does not belong to the mobile device that needs to be installed with the voice interaction data processing device. When there is software with a number of illegal uses greater than the preset number of illegal uses threshold, the process proceeds to step S113; S113 determines the violation coefficient of the matching person according to the number of illegal uses of different software and the number of illegal communications, and proceeds to step S12.

[0089] Optionally, the above step S12 includes the following contents: S121: When the violation coefficient of the matching person meets the requirement, the process proceeds to step S122; when the violation coefficient of the matching person does not meet the requirement, the process proceeds to step S123; S122: determining the number of violations of the matching person according to the identification result of the violation of the matching person; when the number of violations is less than the preset number threshold, determining that the mobile device does not belong to the mobile device that needs to be installed with the voice interaction data processing device; when the number of violations is not less than the preset number threshold, proceeding to step S123; S123 determines the violation coefficient of the matching person according to the number of violations in different preset time periods. When the violation coefficient of the matching person meets the requirement, it is determined that the mobile device does not belong to the mobile device that needs to be installed with the voice interaction data processing device. When the violation coefficient of the matching person does not meet the requirement, it goes to step S123; S124 directly goes to step S13.

[0090] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0091] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A voice interaction data processing device supporting type-c interface, characterized in that: Specifically include: Main control board module, sound card module, type-c interface; The main control board module provides at least two interfaces for the host, one is a headset audio interface, and the other is a serial port data transmission interface. The serial port data transmission interface supports at least one serial port and uses the type-c interface to exchange data with the mobile device. The main control board realizes high-speed transmission of audio data, serial port data and sound card data between the sound card module by setting up the DMA module.

2. The voice interaction data processing device supporting the type-c interface according to claim 1, characterized in that: The hardware circuit of the main control board module realizes the rapid transmission of audio data between the sound card module and the main control board module through the I2S bus, and the main control board module realizes the configuration and control of the sound card module through the I2C bus.

3. The voice interaction data processing device supporting the type-c interface according to claim 1, characterized in that: When the type-c interface is used to connect to a mobile device, the voice interaction data processing device is identified as a hardware device, and the hardware device is identified as a headset device by the mobile device. Voice data can be collected through the hardware device and transmitted back to the application software of the mobile device. The voice data transmitted back to the mobile device is stored or connected to the cloud AI, which responds to the voice data and obtains response audio. The response audio is then transmitted back to the hardware device through the application software of the mobile device. The hardware device provides voice feedback of the mobile device for the call through the microphone.

4. The voice interaction data processing device supporting the type-c interface as claimed in claim 3, characterized in that: The hardware device is provided with at least two serial ports, one for transmitting the voice data of the earphone to the mobile device, and the other for transmitting the voice data transmitted by the external microphone to the software on the mobile device.

5. The voice interaction data processing device supporting type-c interface as claimed in claim 3, characterized in that: The hardware device at least includes a headset device and a custom serial port communication device.

6. The voice interaction data processing device supporting type-c interface as claimed in claim 3, characterized in that: The hardware device can work without obtaining software authentication, or can be set to obtain application authentication of the mobile device before starting the normal working state.

7. The voice interaction data processing device supporting the type-c interface according to claim 6, characterized in that: The method for determining the application authentication of the mobile device is: Insert the hardware device into the mobile device, and after the application of the mobile device detects the hardware device, obtain the device information of the hardware device; Encrypting the device information to obtain encrypted data, and sending the encrypted data to the hardware device; After the hardware device successfully decrypts the encrypted data, the hardware device is set to a normal working state. If the decryption is unsuccessful, the hardware device is set to a standby state.

8. The voice interaction data processing device supporting type-c interface according to claim 6, characterized in that: The method for authenticating the application of the mobile device is: Insert the hardware device into the mobile device, and after the application of the mobile device detects the hardware device, obtain the device information and random number encrypted digital string of the hardware device; The application program calculates the random number encrypted digital string to obtain a calculation result, and sends the calculation result to the hardware device; After the hardware device successfully authenticates the calculation result, the hardware device is set to a normal working state.

9. A method for processing voice interaction data supporting a type-c interface, using a voice interaction data processing device supporting a type-c interface as described in any one of claims 1 to 8, specifically comprising: Determine the matching person of the mobile device based on the corresponding relationship of the mobile device, and use the historical violation behavior of the matching person and the identification result of the violation behavior to determine the violation risk coefficient of different matching persons and the mobile device that needs to be installed with the voice interaction data processing device, and use it as the target mobile device; The operation data of the target mobile device is acquired by using the type-c interface, and when it is determined that there is suspected abnormal use of the voice interaction data processing device by using the analysis result of the operation data within a preset period, the next step is entered; Acquire historical operation data of the target mobile device at different time periods within a preset time period, and determine a matching coefficient between the operation data at different time periods and the historical operation data according to the analysis result of the historical operation data, and proceed to the next step when it is determined by using the matching coefficient that there is no abnormal time period; The operation data of different time periods are used to determine the violations in different time periods and the identification results of the violations, and combined with the matching coefficients of different time periods and the violation risk coefficients of the matching personnel, it is determined whether it is necessary to perform abnormal usage behavior detection on the voice interaction data processing device.

10. The voice interaction data processing method supporting type-c interface according to claim 9, characterized in that: The matching person of the mobile device is determined according to the corresponding relationship between the mobile device and the person.

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