Telephone traffic simulation training method, system, device, equipment and medium

Abstract

The embodiment of the invention discloses a telephone traffic simulation training method, system, device and equipment and a medium, and the method comprises the steps: obtaining a training plan which comprises training content and a target user identifier corresponding to a target user; performing voice-to-character conversion or character recognition on the training content, and generating a training text according to a voice-to-character conversion or character recognition result; according to the target user identifier, a target voice library of the target user is determined from a pre-established voice library set, and the target voice library comprises data pairs of characters and voice features corresponding to the target user; and generating training voice of a target user according to the training text and the target voice library, and executing telephone traffic training according to the training voice. According to the technical scheme provided by the invention, the quality and efficiency of telephone traffic training are improved, and the accuracy of telephone traffic training is improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a traffic simulation training method, system, device, equipment and medium. Background Art

[0002] Operator training refers to the training of staff engaged in answering, transferring and providing customer service, with the purpose of improving their business skills and service quality. Therefore, before the operators take up their posts, in order to ensure their working ability, they need to undergo a lot of simulation training.

[0003] The current telephone operator simulation training method mainly relies on manual teaching, that is, the operator will complete telephone operations with his teacher and complete the training by learning and imitating the teacher's standard behavior.

[0004] However, the current method consumes a lot of manpower and material resources, and the quality of telephone operator training is low, and the trainees who have received the training lack the actual operation ability. Summary of the invention

[0005] The embodiments of the present invention provide a method, system, device, equipment and medium for traffic simulation training. Through the technical solution of the embodiments of the present invention, the quality of traffic training can be improved and the manpower and material resources of traffic training can be saved.

[0006] In a first aspect, an embodiment of the present invention provides a traffic simulation training method, comprising:

[0007] Acquire a training plan, wherein the training plan includes training content and a target user identifier corresponding to the target user;

[0008] Performing speech-to-text conversion or text recognition on the training content, and generating training text according to the results of the speech-to-text conversion or text recognition;

[0009] According to the target user identifier, determining a target voice library of the target user from a pre-established voice library set, wherein the target voice library includes data pairs of text and voice features corresponding to the target user;

[0010] A training voice of a target user is generated according to the training text and the target voice library, and traffic training is performed according to the training voice.

[0011] In a second aspect, an embodiment of the present invention provides a traffic simulation training system, comprising: a trainer station, a training station and a training server, wherein the training server is used to execute any traffic simulation training method described in the embodiment of the present invention;

[0012] The instructor station is used to generate a training plan according to training requirements and send the training plan to the training server;

[0013] The training station is used to receive the training speech generated by the training server for the training plan, and send a training answer to the training speech to the training server.

[0014] In a third aspect, an embodiment of the present invention provides a traffic training device, including:

[0015] An acquisition module, used to acquire a training plan, wherein the training plan includes training content and a target user identifier corresponding to the target user;

[0016] A text generation module, used to perform speech-to-text conversion or text recognition on the training content, and generate training text according to the results of the speech-to-text conversion or text recognition;

[0017] A matching module, configured to determine a target voice library of the target user from a pre-established voice library set according to the target user identifier, wherein the target voice library includes data pairs of text and voice features corresponding to the target user;

[0018] The training module is used to generate the training speech of the target user according to the training text and the target speech library data pair, and perform traffic training according to the training speech.

[0019] In a fourth aspect, an embodiment of the present invention provides an electronic device, the electronic device comprising:

[0020] at least one processor; and,

[0021] a memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the traffic simulation training method described in any one of the embodiments of the present invention.

[0023] In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement any one of the traffic simulation training methods described in the embodiments of the present invention when executed.

[0024] The embodiment of the present invention provides a method, system, device, equipment and medium for traffic simulation training, the method comprising: obtaining a training plan, the training plan comprising training content and a target user identifier corresponding to a target user; performing speech-to-text conversion or text recognition on the training content, and generating a training text according to the result of the speech-to-text conversion or text recognition; determining a target voice library of the target user from a pre-established voice library set according to the target user identifier, wherein the target voice library comprises data pairs of text and voice features corresponding to the target user; generating a training voice of the target user according to the training text and the target voice library, and performing traffic training according to the training voice. Specifically, the training voice required for training can be generated according to the training content and the target voice library of the target user to improve the training quality. Furthermore, by generating the training voice of the target user, the training voice is used to perform traffic training on the trainee, so as to simulate the actual traffic work with the target user and improve the processing efficiency of the traffic work. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A flow chart of a traffic simulation training method provided in Embodiment 1 of the present invention;

[0027] Figure 2 A schematic diagram of the structure of a traffic simulation training system provided in Embodiment 2 of the present invention;

[0028] Figure 3 A schematic diagram of a traffic simulation training system provided in Embodiment 3 of the present invention;

[0029] Figure 4 A schematic diagram of a mutual assistance training process provided by an embodiment of the present invention;

[0030] Figure 5 A schematic diagram of a call transfer training process provided by an embodiment of the present invention;

[0031] Figure 6 A schematic diagram of the process of the consultation question-answering training provided by an embodiment of the present invention;

[0032] Figure 7 A schematic diagram of voice conversion provided by an embodiment of the present invention;

[0033] Figure 8A schematic diagram of the structure of a traffic training device provided in Embodiment 4 of the present invention;

[0034] Fig. 9 This is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of the present invention. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] It should be noted that the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in the technical solution of the present disclosure are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0038] Embodiment 1

[0039] Figure 1 A flowchart of a traffic simulation training method provided in Example 1 of the present invention is provided. The method can be applicable to scenarios in which operators conduct voice training, such as call transfer training, consultation question and answer training, voice mutual assistance training, etc. Furthermore, the method can be executed by a traffic training device, which can be implemented by software and / or hardware and configured in a computer or server.

[0040] like Figure 1 As shown, including:

[0041] Step 110: Obtain a training plan, where the training plan includes training content and a target user identifier corresponding to the target user.

[0042] Among them, the training plan is a plan for conducting telephone training, which can be used to conduct voice training or telephone operation training for operators. The essence of a telephone task is that two people communicate through voice, that is, the communication between the trainee and the target user, to complete the corresponding answer or operation. Furthermore, the main body of the scheme of the embodiment of the present invention is to simulate the actual working environment and automatically generate the training voice of the target user, so that the trainee can complete the training according to the training voice of the target user. Therefore, the target user identifier is used to identify the target user of this training. It can be understood that the target user of the telephone training can be any person. Furthermore, in actual business, the target user can refer to the call initiator or the call customer.

[0043] The training content includes training type, training topic, training steps and training process. The training topic can be a text topic or a voice topic. For example, the training type can be call transfer training, consultation question and answer training or voice mutual assistance training. The call transfer training can be to transfer calls according to the training topic, the consultation question and answer training can be to conduct corresponding telephone questions and answers according to the training topic, and the voice mutual assistance training can be to have multiple trainees play the role of target users to conduct telephone training.

[0044] Step 120: perform speech-to-text conversion or text recognition on the training content, and generate training text according to the results of the speech-to-text conversion or text recognition.

[0045] Specifically, the training content includes text questions and voice questions. If the training content is text questions, text recognition is performed on the text questions, and training text is generated according to the results of the text recognition; if the training content is voice questions, voice-to-text conversion is performed on the voice questions, and training text is generated according to the results of the voice-to-text conversion.

[0046] Specifically, in order to ensure the diversity of traffic training, the training content may include text questions and voice questions, and then corresponding processing is performed according to different training contents to obtain training text. Specifically, in the embodiment of the present invention, it is necessary to first convert the training content into training text, and then complete the conversion of the training text into the training voice of the target user.

[0047] Exemplarily, the text recognition may be OCR (Optical Character Recognition) recognition or NLP (Natural Language Processing), and the speech-to-text conversion may be ASR (Automatic Speech Recognition) conversion.

[0048] Step 130: Determine a target voice library of the target user from a pre-established voice library set according to the target user identifier, wherein the target voice library includes data pairs of text and voice features corresponding to the target user.

[0049] The method of establishing a voice database includes:

[0050] Obtain historical traffic voice of sample users;

[0051] Performing speech recognition on the historical traffic speech to determine the speech attribute of each traffic word in the historical traffic speech;

[0052] A data pair is formed according to the speech text and the voice attribute of the speech text, and a voice library of the sample user is established according to the data pair.

[0053] The sample users are users required for training, and may include various operators required for call training. The historical call voice is the voice recorded by the sample users in historical call tasks, and the historical call voice may include original data such as call recordings, call slips, and operation records.

[0054] Specifically, the speech text and speech attributes of the historical speech can be determined by performing speech recognition on the historical speech. Since different people have unique speech attributes when speaking text, such as speech speed, timbre and pitch, the speech text and the speech attributes of the speech text can be used as a data pair to complete the recording of the target user's voice characteristics, that is, to establish the speech library of the sample user.

[0055] Specifically, different training plans require different target user voices, and the voice library containing the target user voice features, ie, the target voice library, can be uniquely determined through the target user identifier, thereby completing the conversion of the training voice.

[0056] Step 140: Generate a training voice of the target user according to the training text and the target voice library, and perform traffic training according to the training voice.

[0057] Specifically, the traffic text can be determined through the training text, and then the speech characteristics of the target user for the traffic text can be determined by matching the speech attributes of the traffic text in the target speech library, and then the training speech of the target user corresponding to the training text can be generated.

[0058] Optionally, each traffic word of the training text is determined based on the training text; based on each traffic word of the training text, the data pairs of the target speech library are queried to obtain the voice features of each traffic word of the training text; and based on the traffic words of the training text and the voice features of each traffic word, the training speech of the target user is generated.

[0059] Specifically, the data pairs of the traffic words in the database can be determined by one-by-one matching, and then the voice features of the traffic words in the data pairs can be determined, and then the training voice of the target user can be generated by each traffic word and the corresponding voice feature.

[0060] Optionally, performing traffic training according to the training voice includes: obtaining training answers corresponding to the training content, receiving training responses to the training voice; and performing traffic training according to the training answers and the training responses.

[0061] Specifically, the training result can be determined by calculating the answer deviation between the call answer and the training answer. If the answer deviation is greater than a preset threshold, it means that the current call training result is not ideal and it is necessary to re-execute the call training according to the training voice. Otherwise, the training can be terminated.

[0062] The embodiment of the present invention provides a method for traffic simulation training, which includes: obtaining a training plan, the training plan including training content and a target user identifier corresponding to a target user; performing speech-to-text conversion or text recognition on the training content, and generating a training text according to the result of the speech-to-text conversion or text recognition; determining a target voice library of the target user from a pre-established voice library set according to the target user identifier, wherein the target voice library includes data pairs of text and voice features corresponding to the target user; generating a training voice of the target user according to the training text and the target voice library, and performing traffic training according to the training voice. Specifically, the training content can be converted into the training voice required for training according to the training content and the target voice library of the target user, thereby realizing the automatic output of traffic voice and saving training manpower. At the same time, the training voice can be automatically converted into the training voice of the target user according to the target user identifier to realize directional training and improve the training accuracy.

[0063] Embodiment 2

[0064] Figure 2 A structural diagram of a traffic simulation training system provided in Embodiment 2 of the present invention includes:

[0065] The instructor station 210 , the training station 220 and the training server 230 .

[0066] The training server 230 is used to execute any of the traffic simulation training methods described in the embodiments of the present invention.

[0067] Optionally, used to execute acquisition of a training plan, wherein the training plan includes training content and a target user identifier corresponding to the target user;

[0068] Performing speech-to-text conversion or text recognition on the training content, and generating training text according to the results of the speech-to-text conversion or text recognition;

[0069] According to the target user identifier, determining a target voice library of the target user from a pre-established voice library set, wherein the target voice library includes data pairs of text and voice features corresponding to the target user;

[0070] A training voice of a target user is generated according to the training text and the target voice library, and traffic training is performed according to the training voice.

[0071] Optionally, the training server 230 is further used to: obtain historical traffic speech of sample users;

[0072] Performing speech recognition on the historical traffic speech to determine the speech attribute of each traffic word in the historical traffic speech;

[0073] A data pair is formed according to the speech text and the voice attribute of the speech text, and a voice library of the sample user is established according to the data pair.

[0074] Optionally, the training content includes text questions and voice questions; the voice-to-text conversion or text recognition of the training content, and generating training text according to the result of the voice-to-text conversion or text recognition, includes:

[0075] If the training content is a text test question, performing text recognition on the text test question, and generating a training text according to the result of the text recognition;

[0076] If the training content is a phonetic test question, the phonetic test question is converted from phonetic to text, and a training text is generated according to the result of the phonetic to text conversion.

[0077] Optionally, generating a training voice of a target user according to the training text and the target voice library includes:

[0078] Determine each traffic word of the training text according to the training text;

[0079] According to each speech character of the training text, query the data pair of the target speech library to obtain the speech features of each speech character of the training text;

[0080] The training speech of the target user is generated according to the speech characters of the training text and the speech features of each speech character.

[0081] Optionally, performing traffic training according to the training voice includes:

[0082] Obtaining a training answer corresponding to the training content, and receiving a training answer to the training speech;

[0083] Carry out traffic training according to the training answers and training responses.

[0084] Optionally, performing traffic training according to the training answer and the training response includes:

[0085] determining an answer deviation based on the training answer and the training response;

[0086] If the answer deviation is greater than a preset threshold, traffic training is performed according to the training voice.

[0087] The instructor station 210 is used to generate a training plan according to training requirements and send the training plan to the training server.

[0088] Specifically, the instructor station has the functions of student management, test question management and training management. The instructor can use the instructor station to prepare training plans, set training scenarios, organize call center trainees to conduct simulation training, and score the training results of call center trainees.

[0089] Optionally, the training station 220 is used to provide functions such as a learning center, simulation training assessment, etc. for the operator trainees. The training station replicates all the functions of the operator station of the manual operator system and can normally handle services such as call transfer, consultation and question answering. Operator trainees can conduct simulation training on the training station in full simulation of the on-duty system according to the training plan.

[0090] An embodiment of the present invention provides a traffic simulation training system. Through the cooperation of the various modules of the traffic simulation training system, corresponding traffic training can be completed according to the training plan. Specifically, the training server can convert the training content into the training voice required for training according to the training content and the target voice library of the target user, thereby realizing automatic output of the training voice and saving training manpower. At the same time, it can automatically convert the training voice into the target user's training voice according to the target user identifier to realize targeted training and improve training accuracy.

[0091] Embodiment 3

[0092] In order to help those skilled in the art to more clearly understand the technical details of the embodiments of the present invention, Figure 3 A schematic diagram of a traffic simulation training system provided by an embodiment of the present invention, wherein the training service server and the intelligent service server together constitute the training server in the above embodiment, and the instructor station can be the instructor station in the above embodiment.

[0093] Specifically, the training service server mainly provides training plan management, training question bank management and simulation training services. The training service server can receive raw data such as recordings, call records, and operation records of real manual call systems and generate test questions. The training service server can simulate the target user's voice and conduct intelligent dialogue with trainees according to the actual business process.

[0094] The intelligent business server includes an ASR speech recognition engine, an NLP natural language processing engine, and a TTS (Text-to-Speec) text-to-speech engine, providing voiceprint recognition, semantic understanding, speech synthesis, and speech conversion services.

[0095] The instructor station has the functions of student management, test question management and training management. The instructor can use the instructor station to prepare training plans, set training scenarios, organize call center trainees to conduct simulation training, and score the training results of call center trainees.

[0096] The training station provides functions such as a learning center and simulation training assessment for call center trainees. The training station replicates all the functions of the manual call center system, and can normally handle call transfers, consultation and question-and-answer services. Call center trainees can conduct simulation training on the training station in a completely simulated on-duty system according to the training plan. Among them, the monitor station of the manual call center system is the monitoring end during call center work, which is used to monitor the actual work of each call center. Furthermore, the call data collected by the call center and the monitor station can be transmitted through the network switch, and the simulation training system can use the transmitted call data for test question generation, training plan generation and voice library generation.

[0097] Furthermore, the telephone traffic simulation training system provided by the embodiment of the present invention can complete different types of telephone traffic training, such as mutual assistance training, telephone transfer training and consultation question and answer training.

[0098] For example, Figure 4 A flowchart of mutual assistance training provided by an embodiment of the present invention. Specifically, the coach formulates a training plan, sets the binding relationship between the trainee and the real user, and the trainees conduct mutual assistance training. The trainee initiates a call on the training station, and the two training stations establish a call. The training service server forwards the voice stream of the calling trainee, and the intelligent service server converts the trainee's voice into the training voice of the real user (target user) in real time, and the trainees conduct interactive questions and answers for simulation training.

[0099] For example, Figure 5A flowchart of telephone transfer training provided in an embodiment of the present invention, specifically, the trainer formulates a training plan, compiles training questions, and issues training tasks. Trainees conduct telephone transfer simulation training on the training station. The trainee initiates telephone transfer training, the training service server initiates a call, and the call is established after the trainee answers. The training service server sends the test questions to the intelligent service server, and the intelligent service server randomly generates a real user A telephone transfer voice based on the test question content. The training service server forwards the voice stream of user A, and the trainee calls user B according to the request of user A. The training service server automatically connects to the training station and sends the answer voice of user B to the trainee to perform the telephone transfer operation. The training service server saves the answer record and scores the call training.

[0100] For example, Figure 6 A flow chart of the consultation question and answer training provided in an embodiment of the present invention. Specifically, the coach formulates a training plan, compiles training questions, and issues training tasks. The trainee performs consultation question and answer simulation training on the training table. The trainee initiates the consultation question and answer training, the training service server initiates a call, and the call is established after the trainee answers. The training service server sends the test questions to the intelligent service server, and the intelligent service server generates real user voice according to the content of the test questions. The training service server forwards the question voice stream, and the trainee answers according to the question. The intelligent service server recognizes the trainee's voice and the training service server saves the answer record and performs scoring.

[0101] Specifically, each type of voice training mentioned above includes the process of converting the training content into the target user's voice. Figure 7 The voice conversion diagram provided by the embodiment of the present invention is as follows: specifically, the training service server will forward the original material to the intelligent service server, and the intelligent service server will perform voiceprint recognition on the original material and generate the user's voice feature library. Furthermore, when the voice of the teacher / student is input into the intelligent service server, the voice of the teacher / student will be processed by ASR, NLP and TTS to generate the voice of the real user (target user).

[0102] The traffic simulation training system provided by the embodiment of the present invention can convert the training content into the training voice required for training according to the training content and the target voice library of the target user, thereby realizing the automatic output of the traffic voice, saving training manpower, and can automatically convert the training voice into the target user's training voice according to the target user identifier to realize targeted training and improve the training accuracy. Furthermore, the system can complete various types of traffic training and improve the training efficiency.

[0103] Embodiment 4

[0104] Figure 8This is a structural schematic diagram of a traffic training device provided in Embodiment 4 of the present invention. The device is used to execute any traffic simulation training method described in the embodiments of the present invention.

[0105] Specifically, the traffic training device includes: an acquisition module 410, which is used to acquire a training plan, wherein the training plan includes training content and a target user identifier corresponding to a target user;

[0106] A text generation module 420 is used to perform speech-to-text conversion or text recognition on the training content, and generate training text according to the results of the speech-to-text conversion or text recognition;

[0107] A matching module 430 is used to determine a target voice library of the target user from a pre-established voice library set according to the target user identifier, wherein the target voice library includes data pairs of text and voice features corresponding to the target user;

[0108] The training module 440 is used to generate a training voice of a target user according to the training text and the target voice library data pair, and perform traffic training according to the training voice.

[0109] The device provided by the embodiment of the present invention can convert the training content into the training voice required for training according to the training content and the target voice library of the target user, thereby realizing the automatic output of the traffic voice, saving training manpower, and can automatically convert the training voice of the target user according to the target user identifier to realize targeted training and improve the training accuracy. Furthermore, the system can complete various types of traffic training and improve the training efficiency.

[0110] Optionally, the traffic training device also includes: a voice library generation module, used to obtain the historical traffic speech of the sample user; perform voice recognition on the historical traffic speech to determine the voice attributes of each traffic text in the historical traffic speech; form data pairs based on the traffic text and the voice attributes of the traffic text, and establish the voice library of the sample user based on the data pairs.

[0111] Optionally, the text generation module 420 is specifically configured to, if the training content is a text test question, perform text recognition on the text test question, and generate a training text according to the result of the text recognition;

[0112] If the training content is a phonetic test question, the phonetic test question is converted from phonetic to text, and a training text is generated according to the result of the phonetic to text conversion.

[0113] Optionally, the training module 440 includes: a speech generation unit and a training unit.

[0114] The speech generation unit includes:

[0115] A decomposition subunit, used for determining each traffic word of the training text according to the training text;

[0116] A matching subunit, configured to query the data pairs of the target speech library according to each speech word of the training text, and obtain the speech features of each speech word of the training text;

[0117] The generating subunit is used to generate the training speech of the target user according to the speech characters of the training text and the speech features of each speech character.

[0118] Training modules include:

[0119] An acquisition subunit, used to acquire a training answer corresponding to the training content, and receive a training answer to the training speech;

[0120] The training subunit is used to perform traffic training according to the training answers and training responses.

[0121] The training subunit is specifically used to determine the answer deviation according to the training answer and the training answer;

[0122] If the answer deviation is greater than a preset threshold, traffic training is performed according to the training voice.

[0123] The traffic training device provided in the embodiment of the present invention can execute the traffic simulation training method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0124] Embodiment 5

[0125] Fig. 9 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0126] like Fig. 9As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0127] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0128] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the traffic simulation training method.

[0129] In some embodiments, the traffic simulation training method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the traffic simulation training method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the traffic simulation training method in any other appropriate manner (e.g., by means of firmware).

[0130] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0131] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0132] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0133] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0134] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0135] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0136] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0137] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A traffic simulation training method, characterized in that: include: Acquire a training plan, wherein the training plan includes training content and a target user identifier corresponding to the target user; Performing speech-to-text conversion or text recognition on the training content, and generating training text according to the results of the speech-to-text conversion or text recognition; According to the target user identifier, determining a target voice library of the target user from a pre-established voice library set, wherein the target voice library includes data pairs of text and voice features corresponding to the target user; A training voice of a target user is generated according to the training text and the target voice library, and traffic training is performed according to the training voice.

2. The method according to claim 1, characterized in that Also includes: Obtain historical traffic voice of sample users; Performing speech recognition on the historical traffic speech to determine the speech attribute of each traffic word in the historical traffic speech; A data pair is formed according to the speech text and the voice attribute of the speech text, and a voice library of the sample user is established according to the data pair.

3. The method according to claim 1, characterized in that The training content includes text questions and voice questions; the voice-to-text conversion or text recognition of the training content, and generating training text according to the result of the voice-to-text conversion or text recognition, includes: If the training content is a text test question, performing text recognition on the text test question, and generating a training text according to the result of the text recognition; If the training content is a phonetic test question, the phonetic test question is converted from phonetic to text, and a training text is generated according to the result of the phonetic to text conversion.

4. The method according to claim 1, characterized in that: The step of generating a training speech of a target user according to the training text and the target speech library includes: Determine each traffic word of the training text according to the training text; According to each speech word of the training text, query the data pair of the target speech database to obtain the speech feature of each speech word of the training text; The training speech of the target user is generated according to the speech characters of the training text and the speech features of each speech character.

5. The method according to claim 1, characterized in that The performing traffic training according to the training voice comprises: Obtaining a training answer corresponding to the training content, and receiving a training answer to the training speech; Carry out traffic training according to the training answers and training responses.

6. The method according to claim 5, characterized in that The performing of traffic training according to the training answers and the training responses includes: determining an answer deviation based on the training answer and the training response; If the answer deviation is greater than a preset threshold, traffic training is performed according to the training voice.

7. A traffic simulation training system, characterized in that: include: A trainer station, a training station and a training server, wherein the training server is used to execute any traffic simulation training method described in claims 1-6; The instructor station is used to generate a training plan according to training requirements and send the training plan to the training server; The training station is used to receive the training speech generated by the training server for the training plan, and send a training answer to the training speech to the training server.

8. A traffic training device, characterized in that: include: An acquisition module, used to acquire a training plan, wherein the training plan includes training content and a target user identifier corresponding to the target user; A text generation module, used to perform speech-to-text conversion or text recognition on the training content, and generate training text according to the results of the speech-to-text conversion or text recognition; A matching module, configured to determine a target voice library of the target user from a pre-established voice library set according to the target user identifier, wherein the target voice library includes data pairs of text and voice features corresponding to the target user; The training module is used to generate the training speech of the target user according to the training text and the target speech library data pair, and perform traffic training according to the training speech.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the traffic simulation training method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the traffic simulation training method according to any one of claims 1 to 6 when executed.

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