Method, device, equipment and storage medium for generating dissuasive speech

Abstract

The present invention discloses a method, device, equipment and storage medium for generating dissuasive speech, the method comprising: obtaining a speech brain model; obtaining the target user's demand audio based on an intelligent device; the speech brain model searches based on the demand audio to obtain a target dissuasive speech that matches the target user; and outputs the target dissuasive speech to the target user based on the intelligent device. The technical solution of the present invention obtains a large amount of original dissuasive audio, which can reasonably and fully utilize the police's dissuasive speech; in addition, the embodiment of the present invention establishes a speech brain model, which can enable robots and other intelligent devices to output corresponding target dissuasive speech more flexibly and more targetedly based on the user's demand audio; at the same time, the target dissuasive speech is processed based on the sound synthesis method, so that robots and other intelligent devices output more humanized voices, thereby better achieving the purpose of anti-fraud.

Description

Technical Field

[0001] The present invention belongs to the field of anti-fraud technology, and in particular relates to a method, device, equipment and storage medium for generating dissuasive speech. Background Art

[0002] At present, people use communication technologies such as telephone systems, mobile phone text messages, instant messaging, etc. to achieve long-distance communication at any time. The frequency of people contacting each other is getting higher and higher, and the age groups covered are getting wider and wider.

[0003] However, in recent years, new types of telecom network crimes have been fierce and intensified. Criminals seize the weaknesses of human nature, carefully set up scams, and take advantage of regulatory loopholes in the communications industry and the convenience of bank funds flow. Through SMS, phone calls, the Internet and other channels, they fabricate false information, set up scams, and carry out remote and contactless fraud against victims. The police's publicity, prevention, early warning and dissuasion work has a wide coverage, and pure manual processing is insufficient in timeliness and coverage. Intelligent equipment such as dissuasion robots are relatively simple in public security business and flexible dialogue. In addition, the police have accumulated a large number of effective dissuasion words when handling fraud cases. However, the police's dissuasion words have not been used reasonably, and the utilization rate is low, resulting in a waste of effective dissuasion words resources. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the related art at least to a certain extent. To this end, one object of the present invention is to provide a method, device, equipment and storage medium for generating dissuasive speech.

[0005] In order to solve the above technical problems, the embodiments of the present invention provide the following technical solutions:

[0006] A method for generating dissuasive speech, comprising:

[0007] Get the speech brain model;

[0008] Obtain target users’ audio needs based on smart devices;

[0009] The speech brain model searches based on the required audio to obtain the target dissuasion speech that matches the target user;

[0010] The target dissuasion speech is output to the target user based on the smart device.

[0011] Optionally, the step of obtaining the speech brain model includes:

[0012] Get the original dissuasion audio;

[0013] Recognize the original dissuasion audio based on the channel and obtain a recognition result;

[0014] Establishing a speech library and an intention library based on the recognition results;

[0015] The speech brain model is established based on the speech library and the intention library.

[0016] Optionally, obtaining the original dissuasion audio includes:

[0017] Acquire multiple groups of audio data, wherein each group of the audio data includes the user's audio and the dissuasive audio matching the user's audio.

[0018] Optionally, the identifying the original dissuasion audio based on the channel to obtain the identification result includes:

[0019] Recognize the audio of the user of each group of the audio data based on the first channel to obtain a plurality of first data;

[0020] Identify the dissuasive audio of each group of the audio data based on the second channel to obtain a plurality of second data;

[0021] Wherein, the first data matches the second data.

[0022] Optionally, establishing a speech library and an intention library based on the recognition result includes:

[0023] Establishing an intention library based on the plurality of the first data;

[0024] A speech library is established based on multiple pieces of the second data.

[0025] Optionally, the speech brain model searches based on the required audio to obtain a target dissuasion speech that matches the target user, including:

[0026] The speech brain model searches the intent library based on the required audio to obtain the target intent;

[0027] Based on the target intention, the speech library is searched to obtain the target dissuasion speech.

[0028] Optionally, the speech brain model searches the intent library based on the required audio to obtain the target intent, including:

[0029] When a similar intention is found, the similar intention is compared with the information contained in the required audio to obtain the similarity;

[0030] comparing the similarity with a preset similarity threshold;

[0031] If the similarity is greater than the preset similarity threshold, the similar intention is determined as the target intention.

[0032] Optionally, the outputting the target dissuasion speech to the target user based on a smart device includes:

[0033] Processing the target dissuasion speech based on a speech synthesis method to obtain target audio;

[0034] The target audio is output to the target user.

[0035] An embodiment of the present invention further provides a device for generating dissuasion speech, including:

[0036] Training module, used to obtain the speech brain model;

[0037] An acquisition module is used to acquire the audio required by the target user based on a smart device;

[0038] A matching module, used for the speech brain model to search based on the required audio to obtain a target dissuasion speech that matches the target user;

[0039] An output module is used to output the target dissuasion speech to the target user based on the smart device.

[0040] An embodiment of the present invention further provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the method described above when executing the computer program.

[0041] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method described above.

[0042] The embodiments of the present invention have the following technical effects:

[0043] The above-mentioned technical scheme of the present invention obtains a large amount of original dissuasion audio, which can make reasonable and full use of the police's dissuasion words, and greatly enrich the data brain of intelligent devices such as anti-fraud dissuasion robots; in addition, the embodiment of the present invention establishes a words brain model, which can enable robots and other intelligent devices to output corresponding target dissuasion words based on user demand audio more flexibly and more targetedly; at the same time, the target dissuasion words are processed based on the sound synthesis method, so that robots and other intelligent devices can output more humane voice, thereby better achieving the purpose of anti-fraud.

[0044] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flowchart of a method for generating dissuasion speech provided by an embodiment of the present invention;

[0046] Figure 2 It is a structural schematic diagram of a device for generating dissuasive speech provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0048] In order to facilitate those skilled in the art to understand the embodiments of the present invention, some terms are explained:

[0049] (1) TTS: Text To Speech, which is part of human-computer dialogue and enables machines to speak.

[0050] (2) ASI: AllSenseInteractiveTechnique is an interactive technology system that integrates multi-source information. After analyzing data through diversified perception recognition (sound, brainwave, touch, body sensation, face, etc.), it uses multi-screen linkage, image fusion, and image overlay to achieve interactive effects. It covers multi-dimensional dynamic full vision, physical system simulation, full sensory recognition, etc.

[0051] like Figure 1 As shown, an embodiment of the present invention provides a method for generating dissuasion speech, including:

[0052] Step S1: Obtaining the speech brain model;

[0053] Specifically, the step of obtaining the speech brain model includes:

[0054] Acquire original dissuasive audio; recognize the original dissuasive audio based on the channel to obtain a recognition result; establish a speech library and an intention library based on the recognition result; establish the speech brain model based on the speech library and the intention library.

[0055] In actual application scenarios, a large amount of original dissuasion audio is obtained to train the dialogue brain model, and the data of the dialogue brain model is continuously trained and updated in real time based on the audio of the user's specific needs contained in the original dissuasion audio and the matching dissuasion dialogue, so as to provide users with more accurate and effective dissuasion dialogue.

[0056] The obtaining of the original dissuasion audio includes:

[0057] Acquire multiple groups of audio data, wherein each group of the audio data includes the user's audio and the dissuasive audio matching the user's audio.

[0058] When the police use words of dissuasion to the public, the public will respond according to the police's words. The police will conceive the next step of dissuasion words based on the public's response, thereby gradually dissuading the public and achieving the effect of preventing fraud.

[0059] The above-mentioned long or short conversation between the police and the public, including multiple sets of audio data, can be collected as the original dissuasion audio.

[0060] The embodiments of the present invention obtain a large amount of original dissuasion audio, which can make reasonable and full use of the police's dissuasion words, and greatly enrich the data brain of intelligent devices such as anti-fraud dissuasion robots.

[0061] Specifically, the identifying the original dissuasion audio based on the channel to obtain the identification result includes:

[0062] Recognize the audio of the user of each group of the audio data based on the first channel to obtain a plurality of first data;

[0063] Identify the dissuasive audio of each group of the audio data based on the second channel to obtain a plurality of second data;

[0064] Wherein, the first data matches the second data.

[0065] In actual application scenarios, recognition technology (for example, ASI) is used to identify and classify the original dissuasion audio based on the police's dissuasion words and the specific needs of the public or users, and divide it into dissuasion words and user demand audio that matches the dissuasion words.

[0066] For example: the user's audio is: need; the matching dissuasion words are: this is a scam.

[0067] Specifically, establishing a speech library and an intention library based on the recognition result includes:

[0068] Establishing an intention library based on the plurality of the first data;

[0069] A speech library is established based on multiple pieces of the second data.

[0070] In actual application scenarios, each speech in the speech library can find a corresponding intent in the intent library; or

[0071] Each intent in the intent library can find a corresponding speech in the speech library.

[0072] For example: by parsing the original dissuasion audio based on the existing audio data parsing method, the parsing result is obtained;

[0073] The parsing result is extracted based on the existing audio data extraction method to obtain the extraction result.

[0074] Using recognition technology (e.g. ASI) to classify the extraction results and obtain classification results;

[0075] The classification results are filtered based on the existing data of the speech brain model to avoid data duplication and obtain the filtering results.

[0076] The specific steps of the above-mentioned existing audio data analysis method and audio data extraction method are not within the scope of protection of the present invention, so they will not be described in detail.

[0077] The screening result may specifically include n pairs of matching data (An, Bn), where n is an integer greater than 0.

[0078] Then, A1, A2, A3, A4, A5...An are stored to form an intention library;

[0079] B1, B2, B3, B4, B5...Bn are stored to form a speech library.

[0080] For duplicate matching data, the speech brain model can delete them to reduce storage space, while shortening the response time of the speech brain model and improving the success rate of preventing fraud.

[0081] Step S2: obtaining the target user's required audio based on the smart device;

[0082] In actual application scenarios, intelligent devices such as robots can obtain the target user's required audio in real time based on microphones, smart terminals and other devices.

[0083] Step S3: the speech brain model searches based on the required audio to obtain a target dissuasion speech that matches the target user;

[0084] Specifically, the speech brain model searches based on the required audio to obtain the target dissuasion speech that matches the target user, including:

[0085] The speech brain model searches the intent library based on the required audio to obtain the target intent;

[0086] Based on the target intention, the speech library is searched to obtain the target dissuasion speech.

[0087] The speech brain model searches the intent library based on the required audio to obtain the target intent, including:

[0088] When a similar intention is found, the similar intention is compared with the information contained in the required audio to obtain the similarity;

[0089] comparing the similarity with a preset similarity threshold;

[0090] If the similarity is greater than the preset similarity threshold, the similar intention is determined as the target intention.

[0091] The preset similarity threshold can be set according to actual needs, for example, 85% or 90%.

[0092] In actual application scenarios, due to the noise of the surrounding environment and the user's own accent and other issues, the dialogue brain model will cause certain interference in recognizing the user's desired audio.

[0093] Therefore, when the speech brain model obtains the user's demand audio, it searches all the intents in the intent library based on the specific information contained in the user's demand audio to obtain preliminary search results;

[0094] When similar intents are found, the specific information contained in the required audio is compared with the similar intents to obtain the similarity;

[0095] For example, when the preset similarity is 85% and the obtained similarity is 80%, the similarity is less than the preset similarity threshold; the similar intent is not used as the target intent, and the speech brain model does not search the speech library based on the similar intent; until the speech brain model obtains the user's required audio again, and then repeats the above steps.

[0096] When the preset similarity is 85% and the obtained similarity is 90%, the similarity is greater than the preset similarity threshold; the similar intention is used as the target intention, and the speech brain model searches the speech library based on the target intention, and the speech found is the target dissuasion speech.

[0097] Step S4: outputting the target dissuasion speech to the target user based on the smart device.

[0098] Specifically, the outputting the target dissuasion speech to the target user based on the smart device includes:

[0099] Processing the target dissuasion speech based on a speech synthesis method to obtain target audio;

[0100] The target audio is output to the target user.

[0101] In actual application scenarios, processing can be performed based on TTS target dissuasion scripts, so that when the voice output by a robot or an intelligent device with voice output function recognizes that the user's inquiries are similar to those of manual dissuasion during the actual dissuasion process, the actual manual dissuasion scripts in the script brain can be called to respond flexibly, allowing the intelligent dissuasion to have the voice and chat reaction thinking of a real person, and to be able to "listen and speak, interact naturally, and answer questions" like a human being.

[0102] The embodiments of the present invention obtain a large amount of original dissuasion audio, which can make reasonable and full use of the police's dissuasion words, and greatly enrich the data brain of intelligent devices such as anti-fraud dissuasion robots; in addition, the embodiments of the present invention establish a words brain model, which can enable robots and other intelligent devices to output corresponding target dissuasion words more flexibly and more targetedly based on user demand audio; at the same time, the target dissuasion words are processed based on the sound synthesis method, so that robots and other intelligent devices can output more humanized voices, thereby better achieving the purpose of anti-fraud.

[0103] The above embodiment can be implemented based on the following implementation methods:

[0104] (1) A robot or other intelligent device obtains the user's demand audio, analyzes the user's demand audio, and obtains specific demand information contained in the user's demand audio;

[0105] (2) The robot sends the demand information obtained through analysis to the speech brain model;

[0106] (3) The speech brain model searches the intent library based on the demand information and finds similar intents;

[0107] (4) The speech brain model compares similar intentions and demand information to obtain similarities;

[0108] (5) comparing the similarity with a preset similarity threshold, and when the similarity is greater than the preset similarity threshold, confirming the similar intention as the target intention;

[0109] (6) The speech brain model searches the speech library based on the target intention and obtains the target dissuasion speech;

[0110] (7) The robot processes the target dissuasive speech based on the sound synthesis method, and then outputs humanized dissuasive speech to the user.

[0111] like Figure 2 As shown, an embodiment of the present invention further provides a device 200 for generating dissuasion speech, comprising:

[0112] A training module 201 is used to obtain a speech brain model;

[0113] An acquisition module 202 is used to acquire the audio required by the target user based on the smart device;

[0114] Matching module 203, used for the speech brain model to search based on the required audio, and obtain the target dissuasion speech that matches the target user;

[0115] The output module 204 is used to output the target dissuasion speech to the target user based on the smart device.

[0116] Optionally, the step of obtaining the speech brain model includes:

[0117] Get the original dissuasion audio;

[0118] Recognize the original dissuasion audio based on the channel and obtain a recognition result;

[0119] Establishing a speech library and an intention library based on the recognition results;

[0120] The speech brain model is established based on the speech library and the intention library.

[0121] Optionally, obtaining the original dissuasion audio includes:

[0122] Acquire multiple groups of audio data, wherein each group of the audio data includes the user's audio and the dissuasive audio matching the user's audio.

[0123] Optionally, the identifying the original dissuasion audio based on the channel to obtain the identification result includes:

[0124] Recognize the audio of the user of each group of the audio data based on the first channel to obtain a plurality of first data;

[0125] Identify the dissuasive audio of each group of the audio data based on the second channel to obtain a plurality of second data;

[0126] Wherein, the first data matches the second data.

[0127] Optionally, establishing a speech library and an intention library based on the recognition result includes:

[0128] Establishing an intention library based on the plurality of the first data;

[0129] A speech library is established based on multiple pieces of the second data.

[0130] Optionally, the speech brain model searches based on the required audio to obtain a target dissuasion speech that matches the target user, including:

[0131] The speech brain model searches the intent library based on the required audio to obtain the target intent;

[0132] Based on the target intention, the speech library is searched to obtain the target dissuasion speech.

[0133] Optionally, the speech brain model searches the intent library based on the required audio to obtain the target intent, including:

[0134] The speech brain model searches the intent library based on the required audio to obtain the target intent;

[0135] Based on the target intention, the speech library is searched to obtain the target dissuasion speech.

[0136] Optionally, the speech brain model searches the intent library based on the required audio to obtain the target intent, including:

[0137] When a similar intention is found, the similar intention is compared with the information contained in the required audio to obtain the similarity;

[0138] comparing the similarity with a preset similarity threshold;

[0139] If the similarity is greater than the preset similarity threshold, the similar intention is determined as the target intention.

[0140] Optionally, the outputting the target dissuasion speech to the target user based on the smart device includes:

[0141] Processing the target dissuasion speech based on a speech synthesis method to obtain target audio;

[0142] The target audio is output to the target user.

[0143] An embodiment of the present invention further provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the method described above when executing the computer program.

[0144] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method described above.

[0145] In addition, other structures and functions of the device in the embodiment of the present invention are known to those skilled in the art and will not be described herein in detail to reduce redundancy.

[0146] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0147] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0148] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0149] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “clockwise”, “counterclockwise”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0150] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0151] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0152] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0153] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for generating dissuasive speech, characterized in that: include: Get the speech brain model; Obtain target users’ audio needs based on smart devices; The speech brain model searches based on the required audio to obtain the target dissuasion speech that matches the target user; Outputting the target dissuasion speech to the target user based on the smart device; The step of obtaining the speech brain model comprises: Get the original dissuasion audio; Recognize the original dissuasion audio based on the channel and obtain a recognition result; Establishing a speech library and an intention library based on the recognition results; Establishing the speech brain model based on the speech library and the intention library; The obtaining of the original dissuasion audio includes: Acquire multiple groups of audio data; wherein each group of the audio data includes the user's audio and the dissuasion audio matching the user's audio, and when the police use words to dissuade the public, the public will respond according to the police's words, and the police will conceive the next dissuasion words according to the public's response. A long or short conversation between the police and the public, including multiple groups of audio data, can be collected as the original dissuasion audio; The identifying the original dissuasion audio based on the channel to obtain the identification result includes: Recognize the audio of the user of each group of the audio data based on the first channel to obtain a plurality of first data; Identify the dissuasive audio of each group of the audio data based on the second channel to obtain a plurality of second data; Wherein, the first data matches the second data.

2. The method according to claim 1, characterized in that The establishing of a speech library and an intention library based on the recognition result includes: Establishing an intention library based on the plurality of the first data; A speech library is established based on multiple pieces of the second data.

3. The method according to claim 1, characterized in that The speech brain model searches based on the required audio to obtain a target dissuasion speech that matches the target user, including: The speech brain model searches the intent library based on the required audio to obtain the target intent; Based on the target intention, the speech library is searched to obtain the target dissuasion speech.

4. The method according to claim 3, characterized in that The speech brain model searches the intent library based on the required audio to obtain the target intent, including: When a similar intention is found, the similar intention is compared with the information contained in the required audio to obtain the similarity; comparing the similarity with a preset similarity threshold; If the similarity is greater than the preset similarity threshold, the similar intention is determined as the target intention.

5. The method according to claim 1, characterized in that The step of outputting the target dissuasion speech to the target user based on the smart device includes: Processing the target dissuasion speech based on a speech synthesis method to obtain target audio; The target audio is output to the target user.

6. A device for generating dissuasive speech, characterized in that: The device is used to perform the method described in any one of claims 1 to 5, and the device comprises: Training module, used to obtain the speech brain model; An acquisition module is used to acquire the audio required by the target user based on a smart device; A matching module, used for the speech brain model to search based on the required audio to obtain a target dissuasion speech that matches the target user; An output module is used to output the target dissuasion speech to the target user based on the smart device.

7. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 5.

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