Call black list setting method and device

Abstract

Embodiments of the present application disclose a call black list setting method and device, and relate to the field of cloud computing. A specific embodiment of the method comprises: in response to a user accepting a current call request, identifying the user's aversion granularity based on the call content of the user; and based on the aversion granularity, storing the user information of the user to a corresponding black list. The embodiment adds the user information of the user to the black list based on the aversion granularity of the user, thereby avoiding repeated harassment, preventing invalid phone calls, and improving the dialing efficiency of a phone out-bound robot.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, and more particularly to a method and device for setting a call blacklist. Background Art

[0002] Outbound call robots can use task scheduling to dial designated customer numbers and engage in conversations with them to complete specific tasks (such as notifications, debt collection, and customer return visits). Outbound call robots can perform multiple tasks, and sometimes they may call the same customer multiple times, potentially harassing the user.

[0003] To avoid this, outbound call robots should identify customers' negative intentions and stop calling users who express negative intentions. However, in some scenarios (such as debt collection), even if a customer expresses negative intentions, they still need to call the customer.

[0004] Currently, outbound call robots don’t know how to respond when faced with situations like the one above. Summary of the Invention

[0005] The embodiments of the present application provide a method and device for setting a call blacklist.

[0006] In a first aspect, an embodiment of the present application provides a method for setting a call blacklist, wherein the method includes: in response to a user accepting a current call request, identifying the user's objection granularity based on the content of the call with the user, the objection granularity being a range of telephone services for which the user has objectionable intentions; based on the objection granularity, storing the user's user information in a corresponding blacklist, the user information including the user name and the user's contact number.

[0007] In some embodiments, the method further includes: based on the user's aversion granularity, detecting whether the aversion granularity is a preset aversion granularity, the preset aversion granularity being the range of telephone services for re-initiating a call request to a user with aversion intention; in response to the aversion granularity being the preset aversion granularity, adding request information for indicating re-initiating a call request to the user to the scheduling engine; in response to detecting that the current moment is the preset moment for re-initiating a call request to the user, initiating a call request to the user through the scheduling engine.

[0008] In some embodiments, the user information also includes information on the degree of disgust, and the method also includes: detecting the user's voiceprint information based on the content of the call with the user; determining the user's degree of disgust information in response to the voiceprint information matching the preset degree of disgust information; and storing the user information corresponding to the degree of disgust information in a corresponding blacklist.

[0009] In some embodiments, before storing the user information of the user in a corresponding blacklist based on the objection granularity, the method further includes: setting a corresponding blacklist based on the scope of telephone services.

[0010] In some embodiments, the method further includes: in response to detecting that the content of the call with the user includes preset sensitive information, storing the user information of the user in a preset sensitive information blacklist.

[0011] In the second aspect, an embodiment of the present application provides a call blacklist setting device, wherein the device includes: an objection granularity identification unit, configured to identify the user's objection granularity based on the content of the call with the user in response to the user accepting the current call request, the objection granularity being the range of telephone services for which the user has objectionable intentions; a blacklist setting unit, configured to store the user's user information in a corresponding blacklist based on the objection granularity, the user information including the user name and the user's contact number.

[0012] In some embodiments, the device also includes: a call request unit, configured to detect whether the antipathy granularity is a preset antipathy granularity based on the user's antipathy granularity, the preset antipathy granularity being the range of telephone services for re-initiating a call request to a user with antipathy intentions; in response to the antipathy granularity being the preset antipathy granularity, adding request information for indicating re-initiating a call request to the user to the scheduling engine; in response to detecting that the current moment is the preset moment for re-initiating a call request to the user, initiating a call request to the user through the scheduling engine.

[0013] In some embodiments, the user information also includes information on the degree of disgust, and the device also includes: a disgust level identification unit, configured to detect the user's voiceprint information based on the content of the call with the user; determine the user's disgust level information in response to the voiceprint information matching the preset disgust level information; and store the user information corresponding to the disgust level information in a corresponding blacklist.

[0014] In some embodiments, the blacklist setting unit is further configured to set a corresponding blacklist based on the scope of telephone services before storing the user information of the user in the corresponding blacklist based on the objection granularity.

[0015] In some embodiments, the blacklist setting unit is further configured to store the user information of the user into a preset sensitive information blacklist in response to detecting that the call content with the user includes preset sensitive information.

[0016] In a third aspect, an embodiment of the present application provides a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0017] In a fourth aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation method in the first aspect.

[0018] The call blacklist setting method and apparatus provided in the embodiments of the present application first identify the user's level of objection based on the content of the call with the user in response to the user accepting the current call request; then, based on the level of objection, store the user's user information in a corresponding blacklist. The outbound call robot of the present application adds the user's information to the blacklist based on the user's level of objection, thereby preventing repeated harassment and preventing invalid calls, thereby improving the outbound call robot's dialing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0020] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present application may be applied;

[0021] Figure 2 This is a flowchart of an embodiment of a method for setting a call blacklist according to the present application;

[0022] Figure 3 is a schematic diagram of an application scenario of the call blacklist setting method according to this embodiment;

[0023] Figure 4 is a flowchart of another embodiment of a method for setting a call blacklist according to the present application;

[0024] Figure 5 This is a structural diagram of an embodiment of a call blacklist setting device according to the present application;

[0025] Figure 6 It is a structural diagram of a computer system suitable for implementing the computer device of the embodiment of the present application. DETAILED DESCRIPTION

[0026] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0027] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0028] In a typical configuration of the present application, both the call device and the outbound call device include one or more processors (CPUs), input / output interfaces, network interfaces, and memory. Memory may include non-permanent memory in a computer-readable medium, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

[0029] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media such as modulated data signals and carrier waves.

[0030] Figure 1 An exemplary architecture 100 is shown to which the call blacklist setting method and apparatus of the present application can be applied.

[0031] like Figure 1 As shown, system architecture 100 may include communication devices 101, 102, and 103, a network 104, and an outbound call device 105. Network 104 is a medium for providing a communication link between communication devices 101, 102, and 103 and outbound call device 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0032] In this embodiment, the outbound calling device 105 can communicate with the user's calling devices 101, 102, and 103 through the network 104, such as performing tasks such as activity notifications, debt collection, and customer return visits.

[0033] Call devices 101, 102, and 103 can be hardware devices or software that support network connectivity and provide telephone call services. When call devices 101, 102, and 103 are hardware, they can be various electronic devices with functions such as connecting and making calls, including but not limited to smartphones, landline phones, smartwatches, and car phones. When call devices 101, 102, and 103 are software, they can be installed in the electronic devices listed above. They can be implemented as multiple software programs or software modules, for example, to provide call connection and making functions, or as a single software program or software module. This is not specifically limited here.

[0034] Outbound calling device 105 can be a device that provides various services, such as an outbound calling robot or server that provides event notifications, debt collection, and customer follow-up services to calling devices 101, 102, and 103. Outbound calling devices such as an outbound calling robot or server can determine the granularity of user dissatisfaction based on the content of the conversation with the user.

[0035] It should be noted that the outbound calling device can be either hardware or software. If the outbound calling device is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. If the outbound calling device is software, it can be implemented as multiple software programs or software modules, for example, to provide distributed services, or as a single software program or software module. This is not specifically limited here.

[0036] It should be understood that Figure 1 The number of communication devices, networks and outbound call devices in the embodiment is only illustrative. Any number of communication devices, networks and outbound call devices may be provided according to implementation requirements.

[0037] Continue to refer Figure 2 , shows a process 200 of an embodiment of a method for setting a call blacklist according to the present application, the method for setting a call blacklist includes the following steps:

[0038] Step 201 : In response to the user accepting the current call request, the user's objection granularity is identified based on the content of the call with the user.

[0039] In this embodiment, the call request can be various call requests, including but not limited to call requests related to activity notifications, debt collection, and customer return visits. First, the execution entity (such as Figure 1The outbound call device in the dispatch engine initiates a call request to the user in the order in which the user information is stored. The dispatch engine dispatches the appropriate outbound call device based on the configuration information to initiate the call request. This includes three functions: routing decision-making (determining the next step); data organization (preparing the correct data for the outbound call device in preparation); and invoking the outbound call device (conducting the call with the outbound system). User information in the dispatch engine includes, but is not limited to, user name, phone account number, and user needs.

[0040] In this embodiment, the objection granularity is used to characterize the range of telephone services that a user has objectionable intent to. Objectionable intent refers to negative emotions, such as dislike or dissatisfaction, expressed by the user during a call regarding the telephone service offered by the call provider. For example, in the case of a sales call, if a user says, "Please stop calling me for marketing purposes," it indicates that the user has expressed objection to the call from the call provider.

[0041] In this embodiment, the scope of telephone services varies depending on the industry or scenario in which they are used, and the scope of telephone services can be specifically defined and divided according to actual circumstances. Taking a banking system as an example, the scope of its telephone services can be roughly divided into activity notifications, debt collection, and customer return visits. Furthermore, if actual circumstances require further subdivision of the above telephone service scopes, telephone services under the activity notification type can be further divided based on different activities, telephone services under the debt collection type can be further divided based on different debts, and telephone services under the customer return visit type can be further divided based on different return visit content.

[0042] In this embodiment, the objection granularity is used to characterize the scope of telephone services that the user has objection intentions. The scope of telephone services that the user expresses objection intentions during the call is the user's objection granularity. The user's objection granularity can be targeted at the scope of one or more telephone services, or it can be based on the scope of all telephone services of the executing entity. Continuing with the above-mentioned sales call as an example, the user's expression of "Please don't call me for marketing anymore" indicates that the user's objection granularity is marketing calls. For other telephone service scopes, the executing entity can still initiate a call request to the user. And when the user expresses "Please don't call me anymore", it indicates that the user's objection granularity is the scope of all telephone services of the executing entity that initiated the call to him.

[0043] The execution entity identifies the user's offensive intent based on the content of the conversation with the user to determine the user's offensive granularity. In some optional implementations of this embodiment, a database of offensive phrases can be established based on how people express their offensive intent regarding telephone services. During a conversation with the user, the user's conversation content can be compared with the database of offensive phrases to identify the user's offensive intent and determine the user's offensive granularity.

[0044] In some optional implementations of this embodiment, based on the content of the call with the user, the executing entity can detect the user's voiceprint information; in response to the voiceprint information matching the preset disgust level information, the user's disgust level information is determined, thereby assisting in determining the user's disgust intention.

[0045] Voiceprint information is a sound wave spectrum that carries speech information and is displayed by an electroacoustic instrument. The fluctuation of the sound wave spectrum can be used to detect emotional changes in the user who generated the voiceprint information. The emotional changes displayed by the user when expressing offensive intent can be reflected in the fluctuations of the sound wave spectrum. Based on the correspondence between emotional changes and fluctuations in the sound wave spectrum, corresponding preset offensive degree information is set. When the voiceprint information matches the preset offensive degree information, the user's offensive degree information can be determined. In this embodiment, multiple preset offensive degree information of varying degrees can be set, each corresponding to a different degree of offensive intent by the user. The execution entity determines whether to add the user to the blacklist based on the user's offensive degree.

[0046] Step 202: Based on the objection granularity, the user information of the user is stored in a corresponding blacklist.

[0047] In this embodiment, user information includes username and contact number. After the execution entity determines the level of objection to a user who has expressed objectionable intent, the user information is stored in a blacklist corresponding to that level of objection. The execution entity then retrieves the blacklisted user information during subsequent phone calls and uses it to determine whether to initiate a call request with the user.

[0048] In this embodiment, the blacklist is set in correspondence with the scope of telephone services. Since the scope of telephone services is specifically set and subdivided according to actual conditions, the blacklist also needs to be specifically set according to actual conditions.

[0049] In some optional implementations of this embodiment, a preset sensitive information blacklist may also be provided. This preset sensitive information blacklist is used to store user information of users who have used sensitive terms during a call. Sensitive terms may be specifically defined based on the scope of the telephone service and are not further described here. In response to detecting that a call with a user includes preset sensitive information, the execution entity stores the user information in the preset sensitive information blacklist.

[0050] The execution subject of the embodiment adds the user information of the user into the blacklist based on the user's anti-feeling granularity, avoids repeated harassment, improves the humanization of the service, prevents invalid phone calls, and improves the calling efficiency of the phone calling robot.

[0051] With reference to Figure 3 continuously, an application scenario of the call blacklist setting method according to the embodiment is schematically shown. The phone calling device of the bank 301 performs an activity notification task to the user 302 of the bank 301 according to the preferential activity held by the bank 301. In response to the user 302 accepting the current call request, the phone calling device of the bank 301 introduces the preferential activity to the user 302. The user 302 expresses the anti-feeling intention of "don't call me again" during the call; the phone calling device recognizes the anti-feeling intention of the user 302 based on the call content with the user 302, and determines the anti-feeling granularity of the user 302 as the range of all telephone services of the bank 301, and stores the user information of the user 302 into all blacklists.

[0052] With reference to Figure 4 continuously, an application scenario of the call blacklist setting method according to the embodiment is schematically shown. The phone calling device of the bank 301 performs an activity notification task to the user 302 of the bank 301 according to the preferential activity held by the bank 301. In response to the user 302 accepting the current call request, the phone calling device of the bank 301 introduces the preferential activity to the user 302. The user 302 expresses the anti-feeling intention of "don't call me again" during the call; the phone calling device recognizes the anti-feeling intention of the user 302 based on the call content with the user 302, and determines the anti-feeling granularity of the user 302 as the range of all telephone services of the bank 301, and stores the user information of the user 302 into all blacklists.

[0053] Step 401, in response to the user accepting the current call request, recognizing the anti-feeling granularity of the user based on the call content with the user.

[0054] In the embodiment, step 401 is performed in a similar manner to step 201, and will not be described herein again.

[0055] Step 402, storing the user information of the user into the corresponding blacklist based on the anti-feeling granularity.

[0056] In the embodiment, step 402 is performed in a similar manner to step 202, and will not be described herein again.

[0057] Step 403, detecting whether the anti-feeling granularity is a preset anti-feeling granularity based on the anti-feeling granularity of the user.

[0058] In the embodiment, the preset anti-feeling granularity is the range of telephone services that should still initiate a call request to the user even if the user expresses the anti-feeling intention. Taking the debt collection telephone service as an example, the user generally expresses the anti-feeling intention when receiving the debt collection telephone call, but in this case, the user should still initiate a call request to the user for debt collection even if the user expresses the anti-feeling intention.

[0059] In view of the complexity of the actual situation, a preset objection granularity is set to flexibly respond to various complex situations and prevent the user information from being added to the blacklist based solely on the user's objection intention, which may cause certain telephone services to be unable to proceed.

[0060] Step 404: In response to the objection granularity being the preset objection granularity, request information for instructing to re-initiate a call request to the user is added to the scheduling engine.

[0061] In this embodiment, the request information is used to indicate that a call request is to be initiated to the user again, including but not limited to the preset time information for initiating the call request again, the user name, and the user's phone account information.

[0062] In this embodiment, in response to determining that the objection granularity is the preset objection granularity, the execution entity should ignore the user's objection intention to the telephone service and add request information for instructing to initiate a call request to the user again to the scheduling engine.

[0063] Step 405 : In response to detecting that the current time is the preset time for initiating a call request to the user again, initiating a call request to the user through the scheduling engine.

[0064] In this embodiment, the execution entity detects whether the current time has reached the preset time for re-initiating a call request to the user. This detection method can be real-time detection or detection at a predetermined time interval. In response to detecting that the current time has reached the preset time for re-initiating a call request to the user, the scheduling engine initiates a call request to the user.

[0065] from Figure 4 It can be seen that Figure 2 Compared with the corresponding embodiment, the process 400 of the call blacklist setting method in this embodiment specifically illustrates that when the objection granularity is the preset objection granularity, although the user has expressed his objection intention, a call request should still be initiated to the user again; in order to cope with complex actual situations, such as debt collection business, etc., the intelligence level of the outbound call equipment is improved and the flexibility of the outbound call equipment is improved.

[0066] Continue to refer Figure 5 , shows a call blacklist setting device according to the present application

[0067] In embodiment 500 , the device for setting a call blacklist includes: an objection granularity identification unit 501 , an objection degree identification unit 502 , a blacklist setting unit 503 and a call request unit 504 .

[0068] The objection granularity identification unit 501 is configured to identify the user's objection granularity based on the content of the call with the user in response to the user accepting the current call request. The objection granularity is used to characterize the range of telephone services that the user has objection intentions.

[0069] The disgust level identification unit 502 is configured to detect the user's voiceprint information based on the content of the call with the user; determine the user's disgust level information in response to the voiceprint information matching the preset disgust level information; and store the user information corresponding to the disgust level information in the corresponding blacklist.

[0070] The blacklist setting unit 503 is configured to store the user's user information in a corresponding blacklist based on the objection granularity, where the user information includes the user name and the user's contact number. In some embodiments, the blacklist setting unit 503 is further configured to store the user's user information in a preset sensitive information blacklist in response to detecting that the content of a call with the user includes preset sensitive information. In some embodiments, the blacklist setting unit 503 is further configured to set a corresponding blacklist based on the scope of the telephone service before storing the user's user information in the corresponding blacklist based on the objection granularity.

[0071] The call request unit 504 is configured to detect whether the antipathy granularity is a preset antipathy granularity based on the user's antipathy granularity, where the preset antipathy granularity is the range of telephone services for re-initiating a call request to a user with antipathy intentions; in response to the antipathy granularity being the preset antipathy granularity, adding request information for indicating re-initiating a call request to the user to the scheduling engine; in response to detecting that the current moment is the preset moment for re-initiating a call request to the user, initiating a call request to the user through the scheduling engine.

[0072] Reference below Figure 6 , which shows a device suitable for implementing the embodiments of the present application (eg Figure 1 Schematic diagram of the structure of the computer system 600 of the devices 101, 102, 103, 105 shown. Figure 6 The device shown is only an example and should not limit the functions and scope of use of the embodiments of the present application.

[0073] like Figure 6 As shown, the computer system 600 includes a processor (e.g., CPU, central processing unit) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the system 600 are also stored in the RAM 603. The processor 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0074] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, and the like; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read therefrom can be installed into the storage section 608 as needed.

[0075] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from a removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the method of the present application are performed.

[0076] It should be noted that the computer-readable medium of the present application may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0077] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0078] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the devices, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0079] The units involved in the embodiments described in the present application can be implemented by software or by hardware. The described units can also be set in a processor. For example, they can be described as: a processor including an objection granularity identification unit, an objection degree identification unit, a blacklist setting unit, and a call request unit. Among them, the names of these units do not constitute a limitation of the units themselves under certain circumstances. For example, the objection granularity identification unit can also be described as a unit that "identifies the user's objection granularity based on the content of the call with the user in response to the user accepting the current call request."

[0080] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the device, the computer device: in response to the user accepting the current call request, identifies the user's objection granularity based on the content of the call with the user, where the objection granularity is used to characterize the range of telephone services that the user has objectionable intentions; based on the objection granularity, stores the user's user information in a corresponding blacklist, where the user information includes the user name and the user's contact number.

[0081] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for setting a call blacklist, wherein: The method comprises: In response to the user accepting the current call request, during the call with the user, the user's call content is compared with the offensive phrase database to identify the user's offensive granularity, where the offensive granularity is used to characterize the range of multiple telephone services that the user has offensive intent to use. The range of telephone services is divided according to application industries or application scenarios. The offensive phrase database is established based on the way people express their offensive intent regarding telephone services; Based on the objection granularity, the user information of the user is stored in a blacklist corresponding to the scope of the telephone service, the blacklist being independently set for the scope of the telephone service, the user information including the user name and the user contact number; Based on the user's objection granularity, detecting whether the objection granularity is a preset objection granularity, the preset objection granularity being a range of telephone services for initiating a call request again to the user with objection intention; In response to the objection granularity being a preset objection granularity, adding request information for instructing to re-initiate a call request to the user to a scheduling engine, the scheduling engine being configured to schedule an appropriate outbound calling device according to the configuration information and initiate a call request to the user; In response to detecting that the current time is a preset time for initiating a call request to the user again, initiating a call request to the user through a scheduling engine.

2. The method according to claim 1, wherein The user information also includes information on the degree of disgust, and The method further comprises: Detecting the user's voiceprint information based on the content of the conversation with the user; In response to the voiceprint information matching the preset objection level information, determining the objection level information of the user; The user information corresponding to the objection level information is stored in a corresponding blacklist.

3. The method according to claim 1, wherein Before storing the user information of the user in the corresponding blacklist based on the objection granularity, the method further includes: Set up corresponding blacklists based on the scope of telephone services.

4. The method according to claim 1, wherein The method further comprises: In response to detecting that the content of the call with the user includes preset sensitive information, the user information of the user is stored in a preset sensitive information blacklist.

5. A device for setting a call blacklist, wherein: The device comprises: an objection granularity identification unit configured to, in response to a user accepting a current call request, compare the user's call content with the objection phrase database during a call with the user to identify the user's objection granularity, wherein the objection granularity is a range of multiple telephone services that characterize the user's objection intentions, the range of the telephone services being divided according to application industries or application scenarios, and the objection phrase database being established based on how people express their objection intentions regarding telephone services; a blacklist setting unit configured to store the user information of the user in a blacklist corresponding to a range of telephone services based on the objection granularity, wherein the blacklist is independently set for the range of telephone services, and the user information includes a user name and a user contact number; A call request unit is configured to detect, based on the user's objection granularity, whether the objection granularity is a preset objection granularity, where the preset objection granularity is the range of telephone services for re-initiating a call request to a user with objection intentions; in response to the objection granularity being the preset objection granularity, adding request information for indicating that a call request should be re-initiated to the user to initiate a call request is added to a scheduling engine, where the scheduling engine is configured to schedule a suitable outbound call device according to the configuration information to initiate a call request to the user; in response to detecting that the current moment is the preset moment for re-initiating a call request to the user, a call request is initiated to the user through the scheduling engine.

6. The device according to claim 5, wherein The user information also includes information on the degree of disgust, and The device further comprises: The disgust level identification unit is configured to detect the user's voiceprint information based on the content of the call with the user; determine the user's disgust level information in response to the voiceprint information matching the preset disgust level information; and store the user information corresponding to the disgust level information in a corresponding blacklist.

7. The device according to claim 5, wherein The blacklist setting unit is further configured to set a corresponding blacklist based on the scope of telephone services before storing the user information of the user in the corresponding blacklist based on the objection granularity.

8. The device according to claim 5, wherein The blacklist setting unit is further configured to store the user information of the user into a preset sensitive information blacklist in response to detecting that the call content with the user includes preset sensitive information.

9. A computer-readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

10. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

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