Voice interaction method and system for employee visit training

Abstract

The embodiment of the application discloses a kind of staff visit training voice interaction method and system, method includes: the voice data and voiceprint feature information of staff are collected by voice interaction terminal;The real-time position of staff is obtained by positioning base station;According to voice data, voiceprint feature information and real-time position, staff identity association information is generated, and is given training interactive equipment simultaneously, staff identity association information includes the terminal number, staff state information, staff position information and staff question information associated with staff identity mark one-to-one, staff identity mark is associated with voiceprint feature information;According to staff identity association information, execute position boundary-crossing warning operation and multi-concurrent audio processing operation.The application can solve the problem that new staff position boundary-crossing risk is difficult to early warning and multi-person concurrent question when guiding response is chaotic in the scene of staff pre-service visit training, improve the intelligence and safety of staff pre-service visit training.

Description

Technical Field

[0001] This application relates to the technical field of signaling devices or calling devices, or the technical field of data processing systems or methods specifically applicable to management and supervision, or the technical field of digital information transmission, and in particular to a voice interaction method and system for employee visit training. Background Technology

[0002] Pre-employment visits and practical training for new employees need to balance safety management and teaching efficiency. Traditional models rely on manual guidance and one-on-one instruction, which makes it difficult to manage multiple people simultaneously, monitor location compliance in real time, and share interactive teaching resources efficiently. There is an urgent need for an intelligent system that integrates positioning, audio interaction, and identity recognition technologies.

[0003] The existing intelligent voice interaction system for pre-job training of employees has problems such as difficulty in timely warning of new employees crossing the boundary, chaotic guidance response when multiple people ask questions at the same time, and lack of accurate correlation between employee identity and operation behavior, resulting in prominent safety hazards and low training efficiency. Summary of the Invention

[0004] In view of this, this application provides a voice interaction method and system for employee visits and training. By integrating voice data, voiceprint feature information, and real-time location to generate employee identity association information, it achieves fine binding of multiple employee identities and operational behavior data. Furthermore, by configuring electronic fence boundaries in visit and practical operation scenarios, it automatically detects behaviors such as approaching high-risk areas and leaving dedicated training workstations, and constructs a dual location boundary crossing warning mechanism by combining system voice alarms and trainer manual voice warnings. Moreover, by extracting keywords, determining types, ranking and sorting, and clustering and merging spatial and content dimensions of multiple employees' concurrent questions, and combining individual and batch voice response methods, it achieves a closed-loop processing of multiple concurrent questions from parsing and optimization to response playback, effectively improving training guidance efficiency and safety management level.

[0005] In a first aspect, embodiments of this application provide a voice interaction method for employee training visits, applied to a server of a voice interaction system. The system further includes a voice interaction terminal worn by employees, a training interaction device worn by trainers, and a positioning base station located within the factory area. The positioning base station is communicatively connected to the voice interaction terminal, and the server is communicatively connected to the voice interaction terminal, the training interaction device, and the positioning base station, respectively. The method includes:

[0006] The voice data and voiceprint feature information of the employees are collected through the voice interaction terminal;

[0007] The real-time location of the employee is obtained through the positioning base station;

[0008] Employee identity association information is generated based on the voice data, the voiceprint feature information, and the real-time location, and synchronized to the training interaction device. The employee identity association information includes a terminal number that is one-to-one associated with the employee identity identifier, employee status information, employee location information, and employee question information. The employee identity identifier is associated with the voiceprint feature information.

[0009] Based on the employee's identity association information, a location boundary warning operation and a multi-concurrent audio processing operation are performed. The location boundary warning operation is used to detect the employee's location boundary violation behavior in different training scenarios and trigger the voice interaction terminal to play a location boundary violation voice alarm. The multi-concurrent audio processing operation is used to sort the multiple concurrent employee questions and trigger the voice interaction terminal to play voice training content.

[0010] Secondly, this application also provides a voice interaction system, which includes a server, a voice interaction terminal worn by employees, a training interaction device worn by trainers, and a positioning base station located in the factory area. The positioning base station is communicatively connected to the voice interaction terminal, and the server is communicatively connected to the voice interaction terminal, the training interaction device, and the positioning base station, respectively. The server is used to execute the steps in the first aspect of the embodiments of this application.

[0011] Thirdly, embodiments of this application provide an electronic device, including a processing module, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processing module, and the programs include instructions for performing the steps in the first aspect of embodiments of this application.

[0012] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of embodiments of this application.

[0013] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of embodiments of this application. The computer program product may be a software installation package.

[0014] As can be seen, the voice interaction method and system for employee training provided in this application involves the server collecting employees' voice data and voiceprint feature information through a voice interaction terminal; obtaining employees' real-time location through a positioning base station; generating employee identity association information based on voice data, voiceprint feature information, and real-time location, and simultaneously transmitting this information to the training interaction equipment. The employee identity association information includes a terminal number one-to-one associated with the employee's identity identifier, employee status information, employee location information, and employee question information; the employee identity identifier is associated with the voiceprint feature information; and location boundary warning operations and multi-concurrent audio processing operations are executed based on the employee identity association information. Thus, compared to traditional manual training solutions and existing intelligent employee training solutions, this application, by integrating voice data, voiceprint feature information, and real-time location to generate employee identity association information, achieves the association and binding of multiple employee identities with operational behavior data. Combined with location boundary warnings and multi-concurrent audio processing operations, it not only solves the problem of orderly response and accurate guidance for multiple employees asking questions concurrently, but also achieves timely early warning of scenario-based location risks, significantly improving training efficiency and safety management levels. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the architecture of a voice interaction system provided in an embodiment of this application;

[0017] Figure 2 This is a flowchart illustrating a voice interaction method for employee visit and training provided in an embodiment of this application;

[0018] Figure 3 This is a flowchart illustrating an example of performing a location out-of-bounds warning operation according to an embodiment of this application;

[0019] Figure 4 This is a flowchart illustrating the execution of multiple concurrent audio processing operations provided in an embodiment of this application;

[0020] Figure 5 This is a schematic diagram illustrating a scenario where a location boundary violation warning operation is executed during a visitor activity, as provided in an embodiment of this application.

[0021] Figure 6 This is a schematic diagram illustrating a scenario for performing a location boundary crossing warning operation in a practical training setting, as provided in an embodiment of this application.

[0022] Figure 7This is a schematic diagram illustrating a scenario of performing multiple concurrent audio processing operations in a practical training setting, as provided in an embodiment of this application.

[0023] Figure 8 This is a block diagram of the functional units of a voice interaction system provided in an embodiment of this application;

[0024] Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0026] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0027] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article indicates that the preceding and following related objects have an "or" relationship.

[0028] In this application's embodiments, "multiple" refers to two or more. In this application's embodiments, "connection" refers to various connection methods, such as direct or indirect connections, to achieve communication between devices; this application's embodiments do not impose any limitations on this.

[0029] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0030] The following describes the relevant content, concepts, meanings, technical issues, technical solutions, and beneficial effects involved in the embodiments of this application.

[0031] The existing intelligent voice interaction system for pre-job training of employees has problems such as difficulty in timely warning of new employees crossing the boundary, chaotic guidance response when multiple people ask questions at the same time, and lack of accurate correlation between employee identity and operation behavior, resulting in prominent safety hazards and low training efficiency.

[0032] To address the aforementioned issues, this application provides a voice interaction method and system for employee training visits. By integrating voice data, voiceprint feature information, and real-time location to generate employee identity association information, it aims to associate and bind multiple employee identities with operational behavior data. Combined with location boundary warnings and concurrent audio processing operations, it not only solves the problem of orderly response and accurate guidance for multiple employees asking questions concurrently, but also achieves timely early warning of scenario-based location risks, significantly improving training efficiency and safety management level.

[0033] First, combined Figure 1 The voice interaction system in the embodiments of this application will be described. Figure 1 This is a schematic diagram of the architecture of a voice interaction system provided in an embodiment of this application, such as... Figure 1 As shown, the system includes a factory area, which is equipped with a production workshop, a central server 130, a voice interactive terminal 140, and training interactive equipment 150. The production workshop is equipped with a positioning base station 110 and an edge server 120. The edge server 120 is communicatively connected to the positioning base station 110 and the central server 130, respectively. The central server 130 is communicatively connected to the voice interactive terminal 140 and the training interactive equipment 150, respectively.

[0034] Specifically, the positioning base station 110 is a location sensing device in the production workshop, used to collect the location data of the voice interaction terminal 140 in real time and transmit the data to the edge server 120; the edge server 120 is a local processing and communication node in the production workshop, responsible for receiving the location data of the positioning base station 110, performing industrial environment anti-interference verification and data correction, and synchronizing the corrected location information to the central server 130, while supporting low-latency communication with the voice interaction terminal 140.

[0035] Among them, the voice interaction terminal 140 is the core interactive terminal that new employees can wear. It is used to collect the voice data and voiceprint feature information of new employees and upload the data to the central server 130. At the same time, it receives control commands issued by the central server 130, performs operations such as playing location boundary crossing voice alarms and playing voice training content, and also supports displaying training scene information, safe return routes and other content.

[0036] Among them, the training interaction device 150 is an interactive terminal used by trainers to receive employee identity association information, location boundary warning information and question queue synchronized by the central server 130, send voice response data or pre-recorded guidance audio and video to the central server 130, and support viewing employee training process data; the central server 130 is the core management and processing hub of the voice interaction system, responsible for generating employee identity association information, performing location boundary warning operations, multi-concurrent audio processing operations, and core functions such as summarizing training data and generating training archives.

[0037] As can be seen, in this embodiment, the voice interaction system supports a voice interaction mode for pre-job training of new employees. In this mode, the voice interaction terminal 140 collects the voice and voiceprint information of new employees, the positioning base station 110 collects their location data, and the central server 130 integrates multi-dimensional data to generate employee identity association information. After being synchronized to the training interaction device 150, it performs scenario-based location boundary warnings and customized multi-concurrent audio processing, thereby realizing accurate identity binding, real-time security control, and orderly response to questions during the new employee training process, effectively improving the efficiency and safety level of pre-job training.

[0038] The following is combined with Figure 2 The following provides a further explanation of the voice interaction method for employee visit training provided in the embodiments of this application. Please refer to... Figure 2 , Figure 2 This is a flowchart illustrating a voice interaction method for employee visit training provided in an embodiment of this application, applied to... Figure 1 The central server 130, such as Figure 2 As shown, the method includes the following steps:

[0039] Step S210: Collect the employee's voice data and voiceprint feature information through the voice interaction terminal.

[0040] Among them, voice data refers to the audio stream corresponding to the voice content sent by employees through voice interaction terminals; voiceprint feature information is the voice features extracted from voice data that can uniquely identify the employee's identity (such as fundamental frequency, formant frequency, spectral envelope, voice rhythm, pause interval, pitch variation amplitude, etc.).

[0041] Specifically, the voice interaction terminal, as a portable device that new employees can wear, has a built-in microphone array to collect the voice content spoken by new employees during visits or hands-on operations. The collected raw audio is then uploaded to the central server in real time through a dedicated communication link within the factory area. After receiving the audio stream, the central server first performs preprocessing such as noise reduction and segment purification to obtain structured voice data. Then, it extracts voiceprint feature information from the voice data through a built-in voiceprint recognition algorithm.

[0042] In this embodiment, before collecting the employee's voice data and voiceprint feature information through the voice interaction terminal, system initialization and device activation operations need to be performed. Specifically, this includes: the central server sending initialization instructions to the edge server clusters in each workshop; the edge servers starting the positioning algorithm and establishing communication with the positioning base station to generate a positioning coverage area map (factory map) marking high-risk areas (such as the "pressing workshop press area") and safe visiting areas (such as the "assembly line sightseeing corridor"); after a new employee receives the voice interaction terminal, the terminal automatically connects to the factory's WiFi and sends the device number to the central server to complete network registration; the trainer logs into the central server through the training interaction device, activates the "visit / training mode," and loads a list of new employees containing preset voiceprint templates, ensuring that the positioning network, voice interaction terminal, and training interaction device are all in a normal communication and ready state.

[0043] Furthermore, the process involves verifying the identity of new employees and activating the visit mode. Specifically, the new employee speaks a wake-up phrase (e.g., "Factory Training System") through a voice interaction terminal. The terminal sends the real-time voice message to the central server. The central server then uses a voiceprint recognition algorithm to compare the collected voice message with a preset voiceprint template (a match of ≥95% is considered successful), completing the identity binding. After successful verification, the central server sends a "visit mode" activation command to the terminal, activating its location function and displaying the visit route map. Simultaneously, it synchronizes the new employee's identity and status association information with the training interaction equipment, providing a foundation for the collection and association of voice data and voiceprint feature information during subsequent visit and training.

[0044] Step S220: Obtain the real-time location of the employee through the positioning base station.

[0045] Specifically, the positioning base stations deployed in various production workshops of the factory can support the UWB positioning algorithm, collect the location signals of the voice interactive terminals that have activated the visitor mode in real time, and after anti-interference verification and data correction by the edge server cluster, synchronize the accurate real-time location coordinates of employees to the central server.

[0046] Step S230: Generate employee identity association information based on the voice data, the voiceprint feature information, and the real-time location, and synchronize it to the training interaction device.

[0047] The employee identity association information includes a terminal number, employee status information, employee location information, and employee question information that are associated one-to-one with the employee identity identifier, and the employee identity identifier is associated with the voiceprint feature information.

[0048] Specifically, employee identification is determined by comparing voiceprint feature information with the new employee voiceprint template pre-stored on the central server; terminal number is obtained by reporting to the central server when the voice interaction terminal is registered; employee status information is determined according to the "visit / practical training" mode activated by the system and the employee's operation instructions; employee location information is collected in real time by the positioning base station and synchronized to the central server after being corrected by the edge server; and employee question information is obtained by extracting key content from the voice data through voice recognition.

[0049] Furthermore, employee identity-related information may include, but is not limited to, the timestamp of the question initiation, the training batch to which it belongs, the training workstation to which it is bound (such as "A3 practical workstation", only practical scenarios), and the number of historical question records (such as "3 records").

[0050] Step S240: Perform location boundary warning operation and multi-concurrent audio processing operation according to the employee identity association information. The location boundary warning operation is used to detect the employee's location boundary behavior in different training scenarios and trigger the voice interaction terminal to play a location boundary voice alarm. The multi-concurrent audio processing operation is used to sort the multiple concurrent employee questions and trigger the voice interaction terminal to play voice training content.

[0051] The voice training content includes the trainer's voice responses and / or pre-recorded guidance audio and video recordings input by the training interaction device in response to multiple employee questions.

[0052] In one possible embodiment, the step of performing the location boundary warning operation and the multi-concurrent audio processing operation based on the employee identity association information includes: determining the current training scenario based on the employee status information, wherein the training scenario includes a factory visit scenario and a practical training scenario, and the employee status information includes the employee's real-time status, which includes a visit status and a practical training status; performing the location boundary warning operation based on the current training scenario, a preset factory map, and the employee location information, wherein the employee location information includes the employee's location coordinates and a preset employee-specific training workstation; and performing the multi-concurrent audio processing operation based on the current training scenario, multiple employee question information, multiple employee location information, a preset question sorting priority, and a preset question sorting constraint rule.

[0053] The training scenarios are divided into factory tour scenarios and practical training scenarios. Factory tour scenarios are areas where new employees learn about the factory under the guidance of a designated person, covering the factory tour corridors and various workshop display areas. Access to high-risk areas requires strict control. Practical training scenarios are dedicated areas for new employees to practice specific operations. These are independent practice spaces within the factory area, and operational boundaries must be strictly limited to prevent accidental entry into production areas. Employee real-time status includes tour status and practical training status, corresponding one-to-one with the training scenario, serving as a status indicator for the new employee's current training behavior.

[0054] Among them, the factory area map is a digital map of the factory area pre-installed in the system. It accurately marks the boundaries and location information of the factory visitor passage, high-risk areas, special training areas, and production areas. It also incorporates spatial parameters of high-precision positioning, which is the core spatial basis for the system to determine whether the location of new employees is compliant and to implement location control.

[0055] Specifically, the location violation warning operation relies on high-precision positioning technology and spatial boundary information from the factory map. Based on the employee's real-time status, a corresponding training scenario is matched, and the dedicated location control boundary marked on the factory map for that scenario is retrieved. Employee location information obtained in real-time through positioning base stations continuously verifies whether new employees have deviated from the designated area. For tour scenarios, the focus is on monitoring whether they are approaching / entering high-risk areas; for practical training scenarios, the focus is on monitoring whether they have exceeded the designated training area. Once a non-compliant location is determined, the warning mechanism of the voice interaction terminal is immediately triggered, providing real-time location alerts to new employees. Simultaneously, trainers can monitor the location risks of new employees, ensuring location compliance throughout the entire tour and practical training process.

[0056] Specifically, the multi-concurrent audio processing operation is built on multi-concurrent full-duplex audio technology. Addressing the real-time questioning needs of new employees during visits and hands-on practice, it supports multiple new employees initiating voice calls simultaneously. Combining the training scenario with employee location information, it uniformly schedules and processes concurrent questions from multiple employees according to preset rules. Simultaneously, it establishes a full-duplex audio link between trainers and new employees, allowing trainers to provide remote voice guidance for questions and share pre-recorded instructional audio and video resources with multiple new employees. This solves the problem of disordered response when multiple employees ask questions simultaneously, while ensuring that new employees receive targeted guidance in real time during visits, explanations, and hands-on exercises. It also allows remote guidance from trainers to efficiently cover the training needs of multiple new employees.

[0057] As can be seen, in this embodiment, by integrating voice data, voiceprint feature information and real-time location to generate employee identity association information, the association and binding of multiple employee identities and operational behavior data are realized. Combined with location boundary warning and multi-concurrent audio processing operations, it not only solves the problem of orderly response and accurate guidance for multiple employees asking questions at the same time, but also realizes timely warning of scenario-based location risks, significantly improving training efficiency and safety management level.

[0058] Please refer to details. Figure 3 , Figure 3 This is a flowchart illustrating an example of executing a location out-of-bounds warning operation according to an embodiment of this application. Figure 3 As shown, the step of executing the location boundary violation warning operation based on the current training scenario, the preset factory map, and the employee's location information includes the following steps:

[0059] S301, determine the electronic fence parameters based on the factory area map. The electronic fence parameters include a first boundary of the high-risk area corresponding to the factory visit scenario, and multiple second boundaries of multiple training workstation areas corresponding to the practical training scenario.

[0060] High-risk areas are those areas within the factory that pose safety hazards related to equipment operation, machinery handling, and material processing, and where new employees are prohibited from entering or approaching them without permission. The spatial scope of these areas is precisely defined on the factory map using the first boundary, and they are the core focus of location control during visits. Common high-risk areas in the factory include the press operation area in the stamping workshop, the welding operation area in the welding workshop, the machine tool operation area in the machining workshop, the heavy material storage area in the storage area, and the equipment linkage area of ​​the production line.

[0061] Among them, the training workstation area is a dedicated operating area within the factory for practical training of new employees. It is physically isolated from the actual production area. Each area corresponds to specific practical training content and is equipped with dedicated training equipment. Its spatial range is precisely defined on the factory map by a second boundary, which is the core basis for determining the compliance of the location in practical scenarios. Common factory training workstation areas include parts assembly training workstation area, basic equipment operation training workstation area, product testing process training workstation area, tool usage standard training workstation area, and production line basic process simulation training workstation area, etc.

[0062] S302, it is detected that the distance between the employee's location coordinates and the first boundary is less than a first preset threshold in the factory visit scenario, or it is detected that the employee's location coordinates exceed the second boundary corresponding to the training workstation area where the employee's dedicated training workstation is located in the practical training scenario.

[0063] Among them, the dedicated training workstations for new employees are pre-set workstations before pre-job training. They are uniformly planned and allocated by training management personnel according to the practical training subjects, skills learning needs and resource allocation of training workstations in the factory area for the current period of new employees. After allocation, the workstation information is bound to the new employee's identity and entered into the central server, and synchronized to the second boundary parameter of the corresponding training workstation area on the factory map. The system can directly match the corresponding dedicated training workstation through the employee's identity.

[0064] S303, a first control command is sent to the voice interaction terminal. The first control command is used to instruct the voice interaction terminal to perform a first warning operation, which includes playing the location boundary crossing voice alarm.

[0065] In addition to playing a voice alarm for out-of-bounds location, the first warning operation can also include multimodal on-site reminder actions to adapt to the noisy industrial environment of the factory area and improve the reach of warning information. Specifically, it can include triggering the vibration reminder of the voice interactive terminal to strengthen the physical perception reminder through continuous vibration; lighting up the red warning indicator light of the terminal to provide visual assistance; and suspending other non-core training functions of the terminal to allow new employees to focus on the location warning information.

[0066] Among them, the location boundary crossing voice alarm is a standardized voice reminder played by the voice interactive terminal. It needs to be concise, clear, and highly targeted. The corresponding scripts are customized according to the boundary crossing situation in different training scenarios. The voice alarm in the visit scenario may include "You have approached a high-risk area, please return to the visitor channel immediately" and "Do not enter the press operation area, pay attention to safety". The voice alarm in the practical operation scenario may include "You have exceeded your designated training station, please return to the operation area immediately" and "Do not leave the practical training area to avoid accidentally entering the production area". It accurately informs new employees of the boundary crossing type and rectification requirements, so that new employees can quickly understand the adjustment direction and improve the efficiency of on-site location management.

[0067] S304, send a second control command to the training interactive device. The second control command carries location boundary warning information, which includes the employee's identity identifier, the employee's location coordinates, and location boundary prompt information.

[0068] Understandably, while the central server sends the first control command to the voice interaction terminal, it simultaneously sends a second control command carrying location boundary violation warning information to the training interaction device used by the trainer. This pushes the location violation information of new employees to the trainer's end in real time, allowing the trainer to know immediately which new employee has violated the boundary and what kind of boundary violation has occurred in which location. This breaks the single management model that relies solely on the new employee's self-adjustment on-site and supports the trainer to make timely remote voice reminders or on-site interventions based on the warning information.

[0069] The location boundary crossing warning information is a concise description of the boundary crossing situation. The content will be customized according to different training scenarios. For example, in the visit scenario, it is "approaching the high-risk boundary of the press area in the stamping workshop", and in the practical operation scenario, it is "exceeding the boundary of the A3 assembly training station area". It clearly informs trainers of key information such as the type of boundary crossing and the area involved for new employees.

[0070] In one possible embodiment, after sending the second control command to the training interactive device, the method further includes: receiving voice call data sent by the training interactive device, the voice call data including a warning voice issued by the trainer in response to the location boundary warning information recorded by the training interactive device; sending a third control command to the voice interactive terminal, the third control command carrying the voice call data, the third control command being used to instruct the voice interactive terminal to perform a second warning operation, the second warning operation including playing the warning voice.

[0071] Among them, the warning voice is a personalized voice reminder issued by the trainer based on the location boundary warning information, targeting specific new employees who have crossed the boundary and the specific circumstances of the boundary crossing. It is different from the standardized location boundary crossing voice alarm of the system. Its content is more targeted and the tone is more reminder-like. It can be flexibly adjusted according to the actual boundary crossing situation, which can effectively attract the attention of new employees, guide them to quickly correct the location violation behavior, and realize the trainer's remote real-time voice reminder to new employees who have crossed the boundary.

[0072] As can be seen, in this embodiment, the location boundary violation warning operation relies on the electronic fence parameters of the factory area map and high-precision positioning technology to achieve accurate detection of location violations in both training scenarios of visits and practical operations. By triggering multimodal warnings to the new employee's voice interaction terminal, it provides real-time on-site reminders. At the same time, it pushes structured location boundary violation warning information to the trainer's terminal. It also supports trainers to issue personalized warning voices to complete a second layer of manual intervention, thus constructing a dual location control system that combines automatic system warnings with manual control by trainers. This accurately enables the timely detection, rapid reminders, and effective correction of new employees' location violations, comprehensively ensuring location compliance and on-site safety during new employees' factory area visits and practical training.

[0073] Please refer to details. Figure 4 , Figure 4 This is a flowchart illustrating the execution of multiple concurrent audio processing operations provided in an embodiment of this application, such as... Figure 4 As shown, the step of performing the multi-concurrent audio processing operation based on the current training scenario, the multiple employee question information, the multiple employee location information, the preset question sorting priority, and the preset question sorting constraint rules includes the following steps:

[0074] S401, extract the question keywords from the multiple employee question information to obtain multiple keyword sets that correspond one-to-one with the multiple employee question information.

[0075] Specifically, the central server uses keyword extraction algorithms from natural language processing to break down each question from multiple employees, removing redundant content such as interjections and conjunctions, and accurately extracting words that reflect the core message of the question, forming a keyword set that corresponds one-to-one with each employee's question. For example, if an employee asks "What is the hourly capacity of this assembly line?", the extracted keyword set would be {assembly line, hourly capacity}; if the employee asks "What are the correct installation steps for this part?", the extracted keyword set would be {part, installation steps}.

[0076] S402, determine multiple question types corresponding to the multiple employee question information based on the multiple keyword sets, the current training scenario, and multiple employee location information.

[0077] The various question types include questions about safety in high-risk areas, questions about visiting and understanding the area, and questions about practical skills.

[0078] Specifically, safety-related questions in high-risk areas mainly refer to questions raised by new employees when they are visiting areas near high-risk areas, concerning safety regulations, hazard prevention, and other related matters. Even when new employees are visiting safe areas, questions raised by them regarding safety regulations, hazard prevention, access requirements, and emergency procedures in high-risk areas also fall into this category.

[0079] Specifically, the "visiting and understanding questions" are questions raised by new employees during a factory tour, focusing on their basic understanding of the factory's production line layout, basic equipment functions, overall production process, and workshop functional divisions. These questions highlight their need to understand the basic information related to the factory's production and operations.

[0080] Specifically, practical skills questions are questions raised by new employees during practical training sessions, focusing on practical skills such as equipment operation methods, parts assembly processes, process execution standards, and tool usage techniques. These questions revolve around the skill mastery and operational execution needs during practical training and are tailored to the specific learning scenarios of practical training.

[0081] In one possible embodiment, determining the multiple question types corresponding to the multiple employee question information based on the multiple keyword sets, the current training scenario, and multiple employee location information includes: performing the following operations for each employee question information's corresponding keyword set and employee location information to obtain the multiple question types corresponding to the multiple employee question information: determining a first type of the keyword set, the first type including safety, cognition, and equipment operation; if it is detected that the employee's location coordinates are located in the high-risk area in the factory visit scenario, and / or the first type is the safety type, then the employee question information is determined to be a high-risk area safety question; and if it is detected that the employee's location coordinates are located in a non-high-risk area in the factory visit scenario, and the first type is the cognition type, then the employee question information is determined to be a visit cognition question; and if it is detected that the employee's location coordinates are located in the training workstation area where the employee's dedicated training workstation is located in the practical training scenario, and the first type is the equipment operation type, then the employee question information is determined to be a practical skills question.

[0082] The first type is a basic qualitative classification based on the keyword set of employee questions, from the perspective of content attributes. Specifically, the safety category includes key terms related to safety such as high-risk area safety regulations, hazard prevention, emergency response, and access requirements, reflecting a desire to answer questions about safety-related content. The cognition category includes key terms related to basic factory information such as production line layout, equipment functions, production processes, and workshop functions, reflecting a desire to answer questions about basic factory knowledge. The equipment operation category includes key terms related to practical operations such as equipment operation, parts assembly, process execution, and tool use, reflecting a desire to answer questions about practical skills and equipment operation. This classification focuses solely on the content of the question itself, without considering the context or location; it is a purely attribute-based judgment of the question content.

[0083] Specifically, safety-related questions in high-risk areas are based on the premise of a factory visit. The location is in a high-risk area (regardless of the first type), or the first type of the keyword set is safety-related (even if it is in a non-high-risk area). Meeting either one is sufficient to determine safety. This logic comprehensively covers all kinds of questions related to safety in high-risk areas in the visit scenario.

[0084] Specifically, the questions for understanding the factory area are based on the premise of a factory visit. They must meet two conditions simultaneously: the location must be in a non-high-risk area and the first type of the keyword set must be cognitive. Through double screening, the basic cognitive questions for non-safety factory areas under the visit scenario are accurately defined, forming a clear distinction from the safety questions for high-risk areas.

[0085] Specifically, practical skills questions are based on practical training scenarios and must simultaneously meet two conditions: the location must be in a dedicated training workstation area and the first type of the keyword set must be equipment operation. This achieves a triple match between training scenario, compliant location, and practical content, accurately identifying compliant practical questions in the practical scenario.

[0086] For example, in a factory tour scenario, if an employee is in the high-risk area of ​​the stamping workshop's press area, their question's keyword set is {assembly line, capacity}, and the first type is cognitive; therefore, this question is classified as a high-risk area safety question. In the same scenario, if an employee is in the assembly line viewing corridor, a non-high-risk area, their question's keyword set is {press area, safety regulations}, and the first type is safety; therefore, this question is also classified as a high-risk area safety question. Again, in a factory tour scenario, if an employee is in the assembly line viewing corridor, their question's keyword set is {assembly line, production process}, and the first type is cognitive; therefore, this question is classified as a tour-related cognitive question. In a practical training scenario, if an employee is in the A3 assembly training workstation area, their question's keyword set is {parts, assembly steps}, and the first type is equipment operation; therefore, this question is classified as a practical skills question.

[0087] As can be seen, in this embodiment, the first type of basic qualitative classification is completed based on the keyword set and the content attributes. Then, combined with the training scenario and employee location information, the combination judgment logic of the classification achieves accurate classification of questions related to safety in high-risk areas, visit and cognition, and practical skills. This ensures that the question type judgment result is highly compatible with the training scenario, employee location, and core content of the question, providing a reliable basis for category judgment for question sorting and targeted response in subsequent multi-concurrent audio processing.

[0088] S403, sort the multiple employee identity association information containing the multiple employee question information according to the multiple question types and the preset question sorting priority to obtain a first question queue arranged in a first order.

[0089] The core purpose of sorting the employee identity association information containing the multiple employee questions is to solve the problems of disordered question responses and unclear processing priorities in multi-concurrency scenarios where multiple employees simultaneously initiate questions.

[0090] In one possible embodiment, sorting multiple employee identity association information containing multiple employee question information according to the multiple question types and the preset question sorting priority to obtain a first question queue arranged in a first order includes: performing a first-level sorting operation on the multiple employee identity association information containing multiple employee question information according to the preset question sorting priority to obtain a third question queue arranged in a third order, wherein the first-level sorting operation is used to sort the multiple employee identity association information according to the high-to-low priority order corresponding to high-risk area safety questions, practical skills questions, and visit and cognition questions; and performing a second-level sorting operation on the third question queue according to the preset question sorting priority to obtain a first question queue arranged in the first order, wherein the second-level sorting operation is used to sort the multiple employee identity association information according to the question initiation time order when the question types are the same.

[0091] The first level of sorting is based on the priority of question type. Following a pre-defined priority order of "high-risk area safety questions > practical skills questions > visit and knowledge questions," employee identity information containing questions is sorted as a whole, achieving hierarchical categorization of different question types and placing questions with high urgency and importance at the top of the sorting results. The second level of sorting is a supplementary and refined sorting based on the first level. For employee identity information with the same question type in the third question queue, it sorts the questions according to the actual time they were initiated, ensuring timeliness and fairness in processing questions of the same priority.

[0092] S404, the first question queue is adjusted according to the multiple keyword sets, the multiple employee location information and the preset question sorting constraint rules to obtain the second question queue.

[0093] In one possible embodiment, adjusting the first question queue according to the multiple keyword sets, the multiple employee location information, and the preset question sorting constraint rules to obtain a second question queue includes: determining multiple first employee identity association information in the first question queue whose question type is the high-risk area safety question and whose employee location coordinates are located in the high-risk area; multiple second employee identity association information whose question type is the practical skills question; and multiple third employee identity association information whose question type is the visit and cognition question; when the maximum distance difference between the multiple first employee location coordinates corresponding to the multiple first employee identity association information is less than a first preset difference, and the similarity of the corresponding multiple keyword sets is greater than a first preset threshold, clustering and merging the multiple first employee identity association information to obtain a first question package, wherein a single question package includes the number of employees, multiple employee identity identifiers, and clustering... The system uses class tags, core question information, and the earliest question timestamp. When the maximum distance difference between multiple employee-specific training workstations corresponding to multiple second employee identity association information is less than a second preset difference, and the similarity of the corresponding multiple keyword sets is greater than a second preset threshold, the multiple second employee identity association information is clustered and merged to obtain a second question package. When the maximum distance difference between multiple third employee location coordinates corresponding to multiple third employee identity association information is less than a second preset difference, and the similarity of the corresponding multiple keyword sets is greater than a third preset threshold, the multiple third employee identity association information is clustered and merged to obtain a third question package. The first question package, the second question package, and the third question package respectively replace the multiple first employee identity association information, the multiple second employee identity association information, and the multiple third employee identity association information in the first question queue to obtain the second question queue.

[0094] Among them, clustering and merging is a targeted optimization of the sorted first question queue. The core is to solve the problem of repetitive questions with similar spatial proximity and highly similar content in multi-concurrency scenarios. This avoids trainers repeating explanations of similar questions, reduces ineffective audio processing work, and significantly improves the overall response efficiency of multi-concurrency questions. At the same time, multiple related and similar questions are merged into standardized question packages, making the processing queue more concise. This makes it easier for the system and trainers to process similar questions in batches, saving training guidance resource costs. It also enables unified responses to similar questions from multiple employees with similar spatial proximity, ensuring the consistency of training guidance content and further optimizing the practical effect of multi-concurrency audio processing.

[0095] Specifically, for sorted questions of the same type, employee identity association information of the same type with spatial distance difference less than the corresponding preset difference and content similarity greater than the corresponding preset threshold is aggregated. Multiple concurrent questions with spatial association and content similarity are merged into a standardized question package containing the number of employees, employee identity identifier, cluster label, core question information, and earliest question timestamp. Then, the corresponding single employee identity association information in the original first question queue is replaced with each type of question package, thereby optimizing and adjusting the question queue.

[0096] S405, the second question queue is sent to the training interaction device.

[0097] Furthermore, trainers can process questions sequentially according to the predetermined order of the second question queue, ensuring that high-priority questions receive priority responses and providing unified explanations for the clustered question packages, effectively improving the efficiency and relevance of manual responses.

[0098] In one possible embodiment, after sending the second question queue to the training interaction device, the method further includes: receiving a first voice signal sent by the training interaction device, the first voice signal carrying voice response type information and the voice training content, the voice training content including voice responses from the trainer to multiple employee questions and / or pre-recorded guidance audio and video, the voice response type information including a voice response type and its corresponding one or more terminal numbers, the voice response type including individual responses and batch responses, the batch responses including synchronous responses to multiple voice interaction terminals associated with the clustering label; sending a fourth control instruction to one or more voice interaction terminals corresponding to the one or more terminal numbers, the fourth control instruction carrying the voice training content, the fourth control instruction being used to instruct the one or more voice interaction terminals to play the voice training content.

[0099] In this process, the batch reply function precisely corresponds to the aforementioned clustering and merging operation, enabling unified guidance for similar questions. Furthermore, the individual reply function and the precise matching of terminal numbers enable targeted responses to individual questions, ultimately achieving accurate playback from the trainer's human voice reply to the employee's voice interaction terminal.

[0100] As can be seen, in this embodiment, the multi-concurrent audio processing operation is optimized by extracting keywords, accurately determining the question type based on the scenario and location, hierarchical sorting, and clustering and merging in both spatial and content dimensions to form an orderly question queue that is pushed to the trainer's end. It also supports both individual and batch voice response methods to achieve accurate delivery of training content to employee terminals. This constructs a closed-loop processing system for multi-concurrent questions, from system analysis and optimization to human response and terminal playback, effectively solving the problems of disordered response and repetitive processing of multi-concurrent questions, and significantly improving the efficiency of audio interaction processing.

[0101] Please see Figure 5 , Figure 6 , Figure 5 This is a schematic diagram illustrating a scenario where a location boundary violation warning is executed during a visitor activity, as provided in an embodiment of this application. Figure 6 This is a schematic diagram illustrating a scenario of performing a location out-of-bounds warning operation in a practical training setting, as provided in an embodiment of this application. Figure 5 In the factory tour scenario, the positioning base station 110 collects real-time location data of the voice interaction terminal 140 worn by employees approaching high-risk areas, transmits it to the edge server 120, and then synchronizes it to the central server 130. The central server 130, combined with the electronic fence parameters (the first boundary of the high-risk area) determined by the factory map, detects that when the distance between the employee's location coordinates and the first boundary is less than a first preset threshold, it sends a first control command to the voice interaction terminal 140, triggering a first warning operation and playing a system voice alarm saying "You have approached a high-risk area, please return to the tour route immediately." At the same time, it sends a second control command carrying the employee's identification and location coordinates to the training interaction device 150. The trainer records a warning voice message saying "Hello, employee, I am the trainer. You are currently approaching a high-risk area. Please return to the tour group" through the training interaction device 150 and sends the voice call data. After receiving the data, the central server 130 sends a third control command to the voice interaction terminal 140, triggering a second warning operation and playing the manual warning voice message. Through the dual mechanism of automatic system warning and manual warning, the location boundary control of high-risk areas in the tour scenario is realized.

[0102] exist Figure 6 In the practical training scenario, the positioning base station 110 collects the location data of the voice interaction terminal 140 worn by the employee who has left the employee's dedicated training workstation A4 in real time. After verification and correction by the edge server 120, the data is synchronized to the central server 130. When the central server 130 detects that the employee's location coordinates have exceeded the second boundary (based on the electronic fence parameters determined by the factory map, corresponding to the second boundary of the A4 workstation), it sends a first control command to the voice interaction terminal 140, triggering a first warning operation and playing a system voice alarm that says "You have exceeded your dedicated training workstation, please return to the operating area immediately." At the same time, it sends a second control command carrying the employee's identification and location coordinates to the training interaction device 150. The trainer enters a warning voice message through the training interaction device 150 that says "Employee at workstation A4, I am the trainer. Please return to your workstation, otherwise the training cannot continue" and sends the voice call data. After receiving the data, the central server 130 sends a third control command to the voice interaction terminal 140, triggering a second warning operation and playing the manual warning voice message. Through the coordination of automatic system intervention and manual reminders from the trainer, the system ensures that the employee returns to the workstation, guaranteeing the orderly conduct of the practical training.

[0103] As can be seen, in this embodiment, relying on the collaborative architecture of positioning base stations, edge servers and central servers, and combined with electronic fence parameters, accurate detection of employees crossing the boundary in both visit and practical training scenarios is achieved. Through a dual location boundary warning mechanism of automatic voice warning from the system and manual voice warning from the trainer, timely warning of scenario-based location risks is realized, significantly improving training efficiency and safety management level.

[0104] Please see Figure 7 , Figure 7 This is a schematic diagram illustrating a scenario of performing multiple concurrent audio processing operations in a practical training setting provided by an embodiment of this application. Figure 7 As shown, in the practical training scenario, employees at workstations A1, A2, and A4 initiate multiple concurrent questions via voice interaction terminal 140, including "assembly steps for part A," "how to assemble part A," and "how to assemble part B." These questions are transmitted to the central server 130. The central server 130 first extracts the keyword set corresponding to each question through keyword extraction. Combining this with the current practical training scenario and the employees' location information at their respective workstations, it determines that all questions are practical skills-related. Then, it performs a first-level sorting based on preset priorities, and performs a second-level sorting based on the initiation time of similar questions to obtain the first question queue. Finally, it clusters and merges the questions from employees at workstations A1 and A2 (II). Trainers whose dedicated training workstations are close together and whose keyword sets are highly similar form a second question package containing core question information. This second question package, together with the single question from workstation A4, forms a second question queue and is pushed to the training interaction device 150. Trainers input voice training content through the training interaction device 150, select batch responses for the clustered question packages of A1 and A2, and select individual responses for the single question from A4. After receiving the first voice signal, the central server 130 sends a fourth control command to the voice interaction terminal 140 with the corresponding terminal number to achieve accurate playback of the voice training content. The entire process, through multi-stage processing and optimization, efficiently solves the problem of orderly response and batch processing of multiple concurrent questions in practical training scenarios.

[0105] As can be seen, in this embodiment, in the practical training scenario, the orderly processing of questions is achieved by extracting keywords, determining types, and sorting hierarchically from multiple concurrent questions. The clustering and merging based on workstation distance and content similarity reduces duplicate responses. Furthermore, the precise reach through batch and individual replies not only significantly improves the processing efficiency of multiple concurrent audio interactions but also ensures the pertinence of training guidance and the consistency of explanations for similar questions, effectively optimizing the overall experience and management efficiency of practical training.

[0106] This application embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0107] Please see Figure 8 , Figure 8 This is a functional block diagram of a voice interaction system provided in this application embodiment. The system includes: an acquisition unit 801 and a processing unit 802; wherein, the acquisition unit 801 is used to collect the employee's voice data and voiceprint feature information through the voice interaction terminal; and to obtain the employee's real-time location through the positioning base station; the processing unit 802 is used to generate employee identity association information based on the voice data, the voiceprint feature information and the real-time location, and synchronize it to the training interaction device, wherein the employee identity association information includes a terminal number one-to-one associated with the employee's identity identifier, employee status information, employee location information and employee question information, and the employee identity identifier is associated with the voiceprint feature information; and to perform a location boundary warning operation and a multi-concurrent audio processing operation based on the employee identity association information, wherein the location boundary warning operation is used to detect the employee's location boundary behavior in different training scenarios and trigger the voice interaction terminal to play a location boundary voice alarm, and the multi-concurrent audio processing operation is used to sort the multi-concurrent employee question information and trigger the voice interaction terminal to play voice training content.

[0108] In one possible embodiment, the processing unit 802 performs a location boundary warning operation and a multi-concurrent audio processing operation based on the employee identity association information. Specifically, it is used to: determine the current training scenario based on the employee status information, where the training scenario includes a factory visit scenario and a practical training scenario; the employee status information includes the employee's real-time status, which includes both visit status and practical training status; perform the location boundary warning operation based on the current training scenario, a preset factory map, and the employee location information, where the employee location information includes the employee's location coordinates and a preset employee-specific training workstation; and perform the multi-concurrent audio processing operation based on the current training scenario, multiple employee question information, multiple employee location information, a preset question sorting priority, and preset question sorting constraint rules.

[0109] In one possible embodiment, the location boundary violation warning operation is executed based on the current training scenario, a preset factory map, and the employee's location information. Specifically, the processing unit 802 is configured to: determine electronic fence parameters based on the factory map, the electronic fence parameters including a first boundary of a high-risk area corresponding to the factory visit scenario, and multiple second boundaries of multiple training workstation areas corresponding to the practical training scenario; detect that the distance between the employee's location coordinates and the first boundary is less than a first preset threshold in the factory visit scenario, or detect that the employee's location coordinates exceed the second boundary corresponding to the training workstation area where the employee's dedicated training workstation is located in the practical training scenario; send a first control command to the voice interaction terminal, the first control command instructing the voice interaction terminal to execute a first warning operation, the first warning operation including playing the location boundary violation voice alarm; and send a second control command to the training interaction device, the second control command carrying location boundary violation warning information, the location boundary violation warning information including the employee's identity identifier, the employee's location coordinates, and location boundary violation prompt information.

[0110] In one possible embodiment, after sending the second control command to the training interactive device, the processing unit 802 is specifically configured to: receive voice call data sent by the training interactive device, the voice call data including a warning voice issued by the trainer in response to the location boundary warning information recorded by the training interactive device; and send a third control command to the voice interactive terminal, the third control command carrying the voice call data, the third control command being used to instruct the voice interactive terminal to perform a second warning operation, the second warning operation including playing the warning voice.

[0111] In one possible embodiment, the multi-concurrent audio processing operation is performed based on the current training scenario, the multiple employee question information, the multiple employee location information, a preset question sorting priority, and a preset question sorting constraint rule. Specifically, the processing unit 802 is used to: extract question keywords from each of the multiple employee question information to obtain multiple keyword sets corresponding one-to-one with each of the multiple employee question information; determine multiple question types corresponding to the multiple employee question information based on the multiple keyword sets, the current training scenario, and the multiple employee location information, the multiple question types including high-risk area safety questions, visit and knowledge questions, and practical skills questions; sort multiple employee identity association information containing the multiple employee question information according to the multiple question types and the preset question sorting priority to obtain a first question queue arranged in a first order; adjust the first question queue according to the multiple keyword sets, the multiple employee location information, and the preset question sorting constraint rule to obtain a second question queue; and send the second question queue to the training interaction device.

[0112] In one possible embodiment, multiple question types corresponding to the multiple employee question information are determined based on the multiple keyword sets, the current training scenario, and multiple employee location information. The processing unit 802 is specifically configured to perform the following operations for each employee question information's corresponding keyword set and employee location information to obtain the multiple question types corresponding to the multiple employee question information: determining a first type of the keyword set, the first type including safety, cognition, and equipment operation; if it is detected that the employee's location coordinates are located in the high-risk area during the factory visit scenario, and / or the first type is the safety category, then the employee question information is determined to be a high-risk area safety question; and if it is detected that the employee's location coordinates are located in a non-high-risk area during the factory visit scenario, and the first type is the cognition category, then the employee question information is determined to be a visit cognition question; and if it is detected that the employee's location coordinates are located in the training workstation area where the employee's dedicated training workstation is located during the practical training scenario, and the first type is the equipment operation category, then the employee question information is determined to be a practical skills question.

[0113] In one possible embodiment, multiple employee identity association information containing multiple employee question information is sorted according to the multiple question types and the preset question sorting priority to obtain a first question queue arranged in a first order. The processing unit 802 is specifically used to: perform a first-level sorting operation on the multiple employee identity association information containing multiple employee question information according to the preset question sorting priority to obtain a third question queue arranged in a third order. The first-level sorting operation is used to sort the multiple employee identity association information according to the high-to-low priority order corresponding to high-risk area safety questions, practical skills questions, and visit and cognition questions; and perform a second-level sorting operation on the third question queue according to the preset question sorting priority to obtain a first question queue arranged in the first order. The second-level sorting operation is used to sort the multiple employee identity association information according to the question initiation time order when the question types are the same.

[0114] In one possible embodiment, the first question queue is adjusted according to the multiple keyword sets, the multiple employee location information, and the preset question sorting constraint rules to obtain a second question queue. The processing unit 802 is specifically used to: determine multiple first employee identity association information in the first question queue whose question type is the high-risk area safety question and whose employee location coordinates are located within the high-risk area; multiple second employee identity association information whose question type is the practical skills question; and multiple third employee identity association information whose question type is the visit and understanding question. When the maximum distance difference between the multiple first employee location coordinates corresponding to the multiple first employee identity association information is less than a first preset difference, and the similarity of the corresponding multiple keyword sets is greater than a first preset threshold, the multiple first employee identity association information is clustered and merged to obtain a first question package. A single question package includes the number of employees, multiple employee identity labels, and other relevant information. The system identifies, clusters, identifies ...

[0115] In one possible embodiment, after sending the second question queue to the training interaction device, the processing unit 802 is specifically configured to: receive a first voice signal sent by the training interaction device, the first voice signal carrying voice response type information and the voice training content, the voice training content including the trainer's voice responses to multiple employee questions and / or pre-recorded guidance audio and video, the voice response type information including the voice response type and its corresponding one or more terminal numbers, the voice response type including individual responses and batch responses, the batch responses including synchronous responses to multiple voice interaction terminals associated with the clustering label; and send a fourth control instruction to one or more voice interaction terminals corresponding to the one or more terminal numbers, the fourth control instruction carrying the voice training content, the fourth control instruction being used to instruct the one or more voice interaction terminals to play the voice training content.

[0116] As can be seen, in this embodiment, by integrating voice data, voiceprint feature information and real-time location to generate employee identity association information, the association and binding of multiple employee identities and operational behavior data are realized. Combined with location boundary warning and multi-concurrent audio processing operations, it not only solves the problem of orderly response and accurate guidance for multiple employees asking questions at the same time, but also realizes timely warning of scenario-based location risks, significantly improving training efficiency and safety management level.

[0117] It is understood that since the method embodiments and the device embodiments are different presentations of the same technical concept, the content of the method embodiment section in this application should be adapted to the device embodiment section in a synchronous manner, and will not be repeated here.

[0118] Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of this application. For example... Figure 9 As shown, the electronic device 900 may include one or more of the following components: a processing module 901 and a memory 902 coupled to the processing module 901, wherein the memory 902 may store one or more computer programs, which may be configured to implement the methods described in the examples above when executed by one or more processing modules 901. The electronic device 900 may be as follows: Figure 1 The central server 130 is shown.

[0119] The processing module 901 may include one or more processing cores. The processing module 901 connects to various parts within the electronic device 900 using various interfaces and lines. It executes various functions and processes data of the electronic device 900 by running or executing instructions, programs, code sets, or instruction sets stored in the memory 902, and by calling data stored in the memory 902. Optionally, the processing module 901 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processing module 901 may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. It is understood that the aforementioned modem may also not be integrated into the processing module 901 and may be implemented separately through a communication chip.

[0120] The memory 902 may include random access memory (RAM) or read-only memory (ROM). The memory 902 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 902 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), and instructions for implementing the above-described method examples. The data storage area may also store data created during the use of the electronic device 900.

[0121] It is understood that the electronic device 900 may include more or fewer structural elements than those shown in the above block diagram, such as a power module, physical buttons, WiFi (Wireless Fidelity) module, speaker, Bluetooth module, sensor, etc., without limitation.

[0122] This application also provides a computer storage medium storing a computer program / instructions thereon, which, when executed by a processor, implements some or all of the steps of any of the methods described in the above method embodiments.

[0123] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0124] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0125] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for example, the division of units is merely a logical functional division, and there may be other division methods in actual implementation; for example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0126] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can be physically comprised separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware or in the form of hardware plus software functional units.

[0128] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute partial steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes: a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, volatile memory, or non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM), etc., which are various media capable of storing program code.

[0129] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can easily conceive of variations or substitutions without departing from the spirit and scope of the present invention, and various modifications and alterations can be made, including combinations of the different functions and implementation steps described above, as well as software and hardware implementation methods, all of which are within the protection scope of the present invention.

Claims

1. A voice interaction method for employee training visits, characterized in that, A server is used in a voice interaction system. The system further includes a voice interaction terminal worn by employees, a training interaction device worn by trainers, and a positioning base station located within the factory area. The positioning base station is communicatively connected to the voice interaction terminal. The server is communicatively connected to the voice interaction terminal, the training interaction device, and the positioning base station, respectively. The method includes: The voice data and voiceprint feature information of the employees are collected through the voice interaction terminal; The real-time location of the employee is obtained through the positioning base station; Employee identity association information is generated based on the voice data, the voiceprint feature information, and the real-time location, and synchronized to the training interaction device. The employee identity association information includes a terminal number that is one-to-one associated with the employee identity identifier, employee status information, employee location information, and employee question information. The employee identity identifier is associated with the voiceprint feature information. The current training scenario is determined based on the employee status information. The training scenario includes a factory visit scenario and a practical training scenario. The employee status information includes the employee's real-time status, which includes the visit status and the practical training status. The location boundary warning operation is executed based on the current training scenario, the preset factory map and the employee location information. The employee location information includes the employee's location coordinates and the preset employee-specific training workstation. The location boundary warning operation is used to detect the employee's location boundary behavior in different training scenarios and trigger the voice interaction terminal to play a location boundary voice alarm. The concurrent audio processing operation is executed based on the current training scenario, multiple employee questions, multiple employee location information, preset question sorting priority, and preset question sorting constraint rules. The concurrent audio processing operation is used to sort the multiple concurrent employee questions and trigger the voice interaction terminal to play the voice training content. The execution of the location boundary warning operation includes: The electronic fence parameters are determined based on the factory area map. The electronic fence parameters include a first boundary of a high-risk area corresponding to the factory area visit scenario, and multiple second boundaries of multiple training workstation areas corresponding to the practical training scenario. The system detects that the distance between the employee's location coordinates and the first boundary is less than a first preset threshold in the factory tour scenario, or detects that the employee's location coordinates exceed the second boundary corresponding to the training workstation area where the employee's dedicated training workstation is located in the practical training scenario. Send a first control command to the voice interaction terminal, the first control command instructing the voice interaction terminal to perform a first warning operation, the first warning operation including playing a location boundary crossing voice alarm; and... Send a second control command to the training interactive device. The second control command carries location boundary warning information, which includes the employee's identity identifier, the employee's location coordinates, and location boundary prompt information. The system receives voice call data sent by the training interaction device, the voice call data including a warning voice message issued by the trainer in response to the location boundary warning information, which is recorded by the training interaction device. Send a third control command to the voice interaction terminal. The third control command carries the voice call data and is used to instruct the voice interaction terminal to perform a second warning operation, which includes playing the warning voice. The execution of the multi-concurrent audio processing operation includes: Extract keywords from the multiple employee questions to obtain multiple keyword sets that correspond one-to-one with the multiple employee questions. Based on the multiple keyword sets, the current training scenario, and multiple employee location information, multiple question types corresponding to the multiple employee question information are determined. The multiple question types include safety questions related to high-risk areas, questions related to visits and understanding, and questions related to practical skills. Based on the multiple question types and the preset question sorting priority, multiple employee identity association information containing the multiple employee question information is sorted to obtain a first question queue arranged in a first order; The first question queue is adjusted according to the multiple keyword sets, the multiple employee location information, and the preset question sorting constraint rules to obtain the second question queue; The second question queue is sent to the training interaction device.

2. The method according to claim 1, characterized in that, The step of determining multiple question types corresponding to the multiple employee question information based on the multiple keyword sets, the current training scenario, and multiple employee location information includes: Perform the following operations for each employee's question information, based on the keyword set and employee location information, to obtain multiple question types corresponding to the multiple employee question information: Determine a first type for the keyword set, the first type including security, cognition, and operating device categories; If it is detected that the employee's location coordinates are located within a high-risk area during the factory visit scenario, and / or if the first type is detected as the safety category, then the employee's question is determined to be a high-risk area safety category question; and, If it is detected that the employee's location coordinates are within a non-high-risk area during the factory visit scenario, and the first type is the cognitive type, then the employee's question is determined to be a visit cognitive type question; and, If it is detected that the employee's location coordinates are located in the training workstation area where the employee's dedicated training workstation is located in the practical training scenario, and the first type is the operating equipment type, then the employee's question information is determined to be a practical skills type question.

3. The method according to claim 2, characterized in that, The step of sorting multiple employee identity association information containing multiple employee question information according to the multiple question types and the preset question sorting priority to obtain a first question queue arranged in a first order includes: According to the preset question sorting priority, a first-level sorting operation is performed on multiple employee identity association information containing multiple employee question information to obtain a third question queue arranged in a third order. The first-level sorting operation is used to sort the multiple employee identity association information according to the high-to-low priority order corresponding to high-risk area safety questions, practical skills questions, and visit and cognition questions. The second-level sorting operation is performed on the third question queue according to the preset question sorting priority to obtain the first question queue arranged in the first order. The second-level sorting operation is used to sort the multiple employee identity association information according to the question initiation time when the question types are the same.

4. The method according to claim 1, characterized in that, The step of adjusting the first question queue according to the multiple keyword sets, the multiple employee location information, and the preset question sorting constraint rules to obtain the second question queue includes: The system identifies multiple first employee identity information in the first question queue that are questions of the type of high-risk area safety and whose employee location coordinates are located in the high-risk area, multiple second employee identity information that are questions of the type of practical skills, and multiple third employee identity information that are questions of the type of visit and knowledge. When the maximum distance difference between the location coordinates of the multiple first employees corresponding to the multiple first employee identity association information is less than a first preset difference, and the similarity of the corresponding multiple keyword sets is greater than a first preset threshold, the multiple first employee identity association information is clustered and merged to obtain a first question package. A single question package includes the number of employees, multiple employee identity identifiers, clustering labels, core question information, and the earliest question timestamp. When the maximum distance difference between multiple employee-specific training workstations corresponding to the multiple second employee identity association information is less than a second preset difference, and the similarity of the corresponding multiple keyword sets is greater than a second preset threshold, the multiple second employee identity association information is clustered and merged to obtain a second question package; When the maximum distance difference between the location coordinates of the multiple third employees corresponding to the multiple third employee identity association information is less than the second preset difference, and the similarity of the corresponding multiple keyword sets is greater than the third preset threshold, the multiple third employee identity association information is clustered and merged to obtain the third question package; The first question packet, the second question packet, and the third question packet are used to replace the plurality of first employee identity association information, the plurality of second employee identity association information, and the plurality of third employee identity association information in the first question queue, respectively, to obtain the second question queue.

5. The method according to claim 4, characterized in that, After sending the second question queue to the training interaction device, the method further includes: The system receives a first voice signal sent by the training interaction device. The first voice signal carries voice response type information and the voice training content. The voice training content includes the trainer's voice responses to multiple employee questions and / or pre-recorded guidance audio and video. The voice response type information includes the voice response type and its corresponding one or more terminal numbers. The voice response type includes individual responses and batch responses. The batch responses include synchronous responses to multiple voice interaction terminals associated with the clustering label. A fourth control instruction is sent to one or more voice interactive terminals corresponding to the one or more terminal numbers. The fourth control instruction carries the voice training content and is used to instruct the one or more voice interactive terminals to play the voice training content.

6. A voice interaction system, characterized in that, The system includes a server, a voice interaction terminal worn by employees, a training interaction device worn by trainers, and a positioning base station located in the factory area. The positioning base station is communicatively connected to the voice interaction terminal, and the server is communicatively connected to the voice interaction terminal, the training interaction device, and the positioning base station, respectively. The server is used to perform the steps of the method as described in any one of claims 1-5.

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