Conference data processing method and device, electronic equipment and storage medium

Abstract

The application provides a conference data processing method and device, electronic equipment and storage medium, wherein the method comprises: obtaining a target object in a first meta-universe conference; wherein the target object refers to a participant object in the first meta-universe conference whose speaking time meets a set condition; obtaining historical participation data of the target object before the first meta-universe conference and participation behavior data of the target object in the first meta-universe conference; determining a potential interaction value of the target object based on the historical participation data and the participation behavior data; wherein the potential interaction value is used to indicate an interaction priority of the target object; sending the potential interaction value to a conference server of the first meta-universe conference; wherein the conference server is used to send the potential interaction value to at least one participant terminal associated with the first meta-universe conference, so as to display the potential interaction value in the at least one participant terminal.

Description

Technical Field

[0001] This application relates to the fields of artificial intelligence and virtual conferencing technology, and in particular to a conferencing data processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the rapid integration of metaverse technology and virtual meeting scenarios, metaverse meetings have broken through the time and space limitations of traditional meetings. They have the advantages of immersion, high participation, and cross-regional access, and have gradually become the mainstream form of meeting interaction, capable of accommodating a massive number of participants to participate in meeting exchanges simultaneously.

[0003] However, existing technical solutions related to metaverse meetings mostly focus on analyzing the status and managing the behavior of participants who actively speak and interact, neglecting the silent participants who remain silent for extended periods and do not actively speak. Currently, there is a lack of methods for value discovery and potential assessment of silent participants, with problems such as single assessment dimensions and one-sided data, making it difficult to comprehensively and accurately identify the value of silent participants, and consequently failing to provide reliable data support for intelligent meeting guidance and other aspects. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, the first objective of this application is to propose a method for processing conference data.

[0006] The second objective of this application is to provide a conference data processing device.

[0007] The third objective of this application is to propose an electronic device.

[0008] The fourth objective of this application is to provide a computer-readable storage medium.

[0009] The fifth objective of this application is to provide a computer program product.

[0010] To achieve the above objectives, a first aspect of this application provides a method for processing conference data, comprising:

[0011] Obtain the target object in the first metaverse conference; wherein, the target object refers to the participant in the first metaverse conference whose non-speaking time meets the set condition; Obtain the target object's historical participation data before the first metaverse conference and the target object's participation behavior data during the first metaverse conference; Based on the historical attendance data and the attendance behavior data, the potential interaction value of the target object is determined; wherein, the potential interaction value is used to indicate the interaction priority of the target object; The potential interactive value is sent to the conference server of the first metaverse conference; wherein the conference server is used to send the potential interactive value to at least one participating terminal associated with the first metaverse conference, so as to display the potential interactive value in the at least one participating terminal.

[0012] To achieve the above objectives, a second aspect of this application provides a conference data processing apparatus, comprising: The first acquisition module is used to acquire target objects in the first metaverse conference; wherein, the target object refers to the participant in the first metaverse conference whose non-speaking time meets the set condition; The second acquisition module is used to acquire the target object's historical participation data before the first metaverse conference and the target object's participation behavior data in the first metaverse conference; The determination module is used to determine the potential interaction value of the target object based on the historical participation data and the participation behavior data; wherein the potential interaction value is used to indicate the interaction priority of the target object; A sending module is used to send the potential interactive value to the conference server of the first metaverse conference; wherein the conference server is used to send the potential interactive value to at least one participating terminal associated with the first metaverse conference, so as to display the potential interactive value in the at least one participating terminal.

[0013] To achieve the above objectives, a third aspect of this application provides an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement a conference data processing method as described in the first aspect of this application.

[0014] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement a conference data processing method as described in the first aspect of this application.

[0015] To achieve the above objectives, a fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements a conference data processing method as described in the first aspect of this application.

[0016] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0017] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart illustrating a conference data processing method provided in an embodiment of this application; Figure 2 A flowchart illustrating a conference data processing method provided in another embodiment of this application; Figure 3 This is a schematic diagram of the structure of a conference data processing device provided in an embodiment of this application; Figure 4 This is a block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0019] The following description, with reference to the accompanying drawings, outlines a conference data processing method, apparatus, electronic device, and storage medium according to embodiments of this application.

[0020] Figure 1 This is a flowchart illustrating a conference data processing method provided in an embodiment of this application.

[0021] like Figure 1 As shown, the conference data processing method includes the following steps: Step 101: Obtain the target object in the First Universe Conference; where the target object refers to the participant in the First Universe Conference whose unspeaking time meets the set conditions.

[0022] The First Metaverse Conference can refer to any one of the ongoing Metaverse Conferences; the target object refers to one or more participants in the First Metaverse Conference whose silence duration meets the set conditions. In other words, the target object refers to one or more participants in the First Metaverse Conference whose silence duration meets the set conditions.

[0023] Among them, the unspeaking time meeting the set conditions can mean that the unspeaking time is greater than or equal to the set time threshold, or it can mean that the ratio of the unspeaking time to the duration of the First Universe Conference is greater than or equal to the set ratio threshold.

[0024] Step 102: Obtain the target object's historical participation data before the First Universe Conference and the target object's participation behavior data during the First Universe Conference.

[0025] The historical participation data can be obtained through statistical analysis and / or data collection of virtual meetings attended by the target object prior to the First Metaverse Conference; virtual meetings can include the Metaverse Conference and / or ordinary virtual meetings. For example, an ordinary virtual meeting can include a two-dimensional audio-visual conference.

[0026] The participant behavior data can be obtained through statistical analysis and / or data collection of nonverbal and interactive behaviors of the target participants during the First Universe Conference. For example, nonverbal behaviors may include eye movements, changes in gaze, facial expressions, and body movements, while interactive behaviors may include clicking conference links, drawing or typing on a virtual whiteboard, and participating in real-time voting.

[0027] Step 103: Based on historical attendance data and attendance behavior data, determine the potential interaction value of the target object; wherein, the potential interaction value is used to indicate the interaction priority of the target object.

[0028] Among them, potential interaction value is used to measure whether the target object has unexpressed potential views, opinions or willingness to interact when in a silent state.

[0029] In some alternative embodiments, a large model can be used to determine the potential interaction value. That is, historical attendance data and attendance behavior data are input into the large model to obtain the potential interaction value output by the large model.

[0030] Step 104: Send potential interactive value to the conference server of the First Metaverse Conference; wherein the conference server is used to send the potential interactive value to at least one participating terminal associated with the First Metaverse Conference, so as to display the potential interactive value in at least one participating terminal.

[0031] The meeting server provides underlying infrastructure capabilities such as computing power, data storage, signaling forwarding, user management, scene rendering scheduling, and interactive data synchronization for the Metaverse Meeting. The Metaverse Meeting relies on the server capabilities to realize business functions such as virtual meeting rooms, digital clones, audio and video, and whiteboard interaction.

[0032] Among them, at least one participating terminal associated with the First Universe Conference can refer to the participating terminal of one or more participants in the First Universe Conference, or it can refer to the participating terminal of the conference host of the First Universe Conference.

[0033] Among these features, displaying potential interactive value on at least one participating terminal can transform the potential interactive intentions of silent participants into visual signals that participants can perceive. This helps other participants accurately identify high-value silent participants and initiate targeted interactive guidance, thereby activating and converting potential interactive value and improving the efficiency of meeting discussions.

[0034] In this embodiment, the target object in the First Metaverse Conference is obtained; wherein, the target object refers to the participant in the First Metaverse Conference whose non-speaking time meets the set condition; the historical participation data of the target object before the First Metaverse Conference and the participation behavior data of the target object in the First Metaverse Conference are obtained; based on the historical participation data and the participation behavior data, the potential interaction value of the target object is determined; wherein, the potential interaction value is used to indicate the interaction priority of the target object; the potential interaction value is sent to the conference server of the First Metaverse Conference; wherein, the conference server is used to send the potential interaction value to at least one participating terminal associated with the First Metaverse Conference, so as to display the potential interaction value in at least one participating terminal; wherein, by determining the potential interaction value of the target object through two dimensions of historical participation data and real-time participation behavior data, the accuracy of the calculation of potential interaction value is greatly improved, avoiding problems such as single evaluation dimension and one-sided data basis, and providing accurate data support for the intelligent interaction scheduling of the Metaverse Conference.

[0035] This embodiment provides another method for processing conference data. Figure 2 This is a flowchart illustrating a conference data processing method provided in an embodiment of this application.

[0036] like Figure 2 As shown, the conference data processing method may include the following steps: Step 201: Obtain the target object in the First Universe Conference; where the target object refers to the participant in the First Universe Conference whose unspeaking time meets the set conditions.

[0037] Step 202: Obtain the target object's historical participation data before the First Universe Conference and the target object's participation behavior data during the First Universe Conference.

[0038] In one possible embodiment of this application, obtaining the target object's historical participation data prior to the first metaverse conference includes: obtaining the target object's participation data in at least one second metaverse conference; wherein, the second metaverse conference is a metaverse conference that the target object participated in prior to the first metaverse conference; the participation data includes the target object's index value under at least one statistical indicator; and obtaining historical participation data based on the target object's participation data in at least one second metaverse conference.

[0039] The Second Metaverse Meeting refers to any metaverse meeting that the target object participated in before the First Metaverse Meeting; that is, the Second Metaverse Meeting was held earlier than the First Metaverse Meeting.

[0040] The statistical indicators are used to indicate the target object's participation status, behavioral characteristics, and level of engagement in the Second Universe Conference. For example, the statistical indicators may include the number of participants within the statistical time interval of the Second Universe Conference, the duration of participation, the number of times any interactive action was performed, and the contribution of the interactive action to the conference. Interactive actions may refer to downloading materials, participating in voting, or interacting in virtual scenarios; the contribution of interactive actions to the conference can be obtained through post-conference satisfaction surveys, assessments of the correlation between conference outcomes and the target object's interactive actions, etc.

[0041] The historical participation data includes the target object's participation data in at least one second-dimensional universe conference.

[0042] By combining statistical indicators to obtain the target object's indicator values ​​in the Second Universe Conference, we can comprehensively and multidimensionally characterize the target object's past participation characteristics, providing sufficient basic data support for generating the first evaluation result, thereby improving the accuracy and credibility of subsequent potential interaction value judgments.

[0043] In one possible embodiment of this application, obtaining the target object's participation behavior data in the First Universe Conference includes: obtaining the target object's eye movement trajectory data, facial expression data, and interaction behavior data during the participation of the target object in the First Universe Conference; and obtaining the participation behavior data based on at least one of the eye movement trajectory data, facial expression data, and interaction behavior data.

[0044] Specifically, eye movement trajectory data can be collected through eye-tracking devices, facial expression data can be captured through facial expression recognition cameras, and the operation and interaction behavior of the target object in the First Universe Conference can be recorded through a behavior log recording module, thereby obtaining interaction behavior data.

[0045] The data on participant behavior can include any one of the following: eye movement trajectory data, facial expression data, and interactive behavior data; or it can include any combination of these three data types.

[0046] For example, the participant behavior data may include eye movement trajectory data, facial expression data, and interaction behavior data.

[0047] Interactive behavior data refers to data related to the target object's operational and interactive behaviors during the First Universe Conference. For example, interactive behavior data includes the number of times conference materials are clicked, the number of times drawings or text inputs are made on the virtual whiteboard, and the speed at which real-time voting is conducted.

[0048] By collecting three types of underlying behavioral data of the target object in the first-dimensional universe meeting, namely eye movement trajectory, facial expression and interactive behavior, covering multiple dimensions of silent behavior such as expression, visual gaze and operation interaction, it is possible to comprehensively capture the non-verbal and implicit participation state of silent participants, and provide multi-source and three-dimensional data support for the subsequent generation of second evaluation results.

[0049] Step 203: Based on historical attendance data, determine the first assessment result of the target object; wherein the first assessment result is used to indicate the degree of disorder in the target object's historical attendance behavior.

[0050] In one possible embodiment of this application, for any statistical indicator, the indicator values ​​corresponding to the target object in at least one second-dimensional universe meeting are sorted according to time order to obtain a corresponding indicator value sequence; based on the indicator value sequence, the probability distribution corresponding to any statistical indicator is determined; wherein, the probability distribution is used to indicate the probability of any indicator value or any set indicator value interval in the indicator value sequence appearing in the indicator value sequence; based on the probability distribution, the entropy value corresponding to any statistical indicator is determined; and a first evaluation result is obtained according to the entropy value corresponding to at least one statistical indicator.

[0051] Among them, the indicator value sequence can refer to sequences such as the meeting duration sequence, the number of document downloads sequence, and the voting participation degree sequence.

[0052] Taking the probability distribution as an example to indicate the probability of any index value appearing in the index value sequence, the formula for calculating the entropy value of the corresponding statistical index for any index value sequence is as follows:

[0053] Where h represents the entropy value, This represents the probability of the i-th index value appearing in the index value sequence.

[0054] By measuring the historical value of a target object by entropy values ​​as uncertainty decays over time, it is possible to dynamically adjust value judgments based on the historical performance of the target object. This makes the initial assessment results more dynamic and scientific, providing a reliable historical dimension for determining potential interactive value.

[0055] It should be noted that, in order to facilitate unified calculation, the sequence of each index value can be standardized before calculating the entropy value. For example, the index values ​​in the sequence can be converted into values ​​in the range of [0, 1].

[0056] Among them, the entropy values ​​corresponding to each statistical indicator can be summed to obtain the first evaluation result H.

[0057] Step 204: Based on the participation behavior data, determine the second evaluation result of the target object; wherein the second evaluation result is used to indicate the participation level of the target object.

[0058] In one possible embodiment of this application, based on eye movement trajectory data, the first gaze duration of the target object to the main conference screen, the second gaze duration to the designated data display area, and the target object's screen switching frequency are obtained, and the cognitive focus level of the target object is determined based on at least one of the first gaze duration, the second gaze duration, and the screen switching frequency; based on facial expression data, the emotional state of the target object towards the conference content is identified, and the emotional participation level of the target object is determined based on the emotional score corresponding to the emotional state; based on interactive behavior data, the behavior score and occurrence frequency corresponding to any interactive behavior are obtained, and the behavioral activity level of the target object is determined based on the behavior score and occurrence frequency; and a second evaluation result is determined based on at least one of the cognitive focus level, emotional participation level, and behavioral activity level.

[0059] The cognitive focus level of the target object can be determined based on one or more of the first fixation duration, the second fixation duration, and the screen switching frequency.

[0060] In some alternative embodiments, the cognitive attention level of the target object can be determined based on the first gaze duration, the second gaze duration, and the screen switching frequency. For example, the formula for calculating the cognitive attention level is as follows:

[0061] Where C represents cognitive focus level; the higher the C value, the higher the target audience's focus on the meeting content; F t F represents the duration of the first fixation. d S represents the second fixation duration. fThe screen switching frequency refers to the number of screen switches per unit time; α, β, and γ are weighting coefficients, which can be set according to the meeting type of the First Universe Conference.

[0062] This involves calculating (e.g., summing) the emotional score corresponding to the target audience's emotional state to determine their level of emotional engagement. The positive or negative value and magnitude of the emotional engagement score reflect the target audience's emotional inclination and intensity towards the meeting content. It should be noted that the emotional scores corresponding to different emotional states can be pre-set, for example, +3 points for interested, -2 points for confused, etc.

[0063] The score for any interactive action can be pre-set, such as clicking on the document once: +1 point, operating the virtual whiteboard once: +2 points, voting once: +2 points.

[0064] In some alternative embodiments, the formula for calculating behavioral activity is as follows:

[0065] Where B represents the level of behavioral activity, B j M represents the behavior score corresponding to the j-th operation interaction of the target object in the first-dimensional universe meeting. j This indicates the number of times the j-th interaction occurs.

[0066] In some alternative embodiments, different behavioral scores can be set according to voting speed. For example, if the real-time voting speed ranks in the top 1 / 3: +3 points, if the real-time voting speed ranks in the middle 1 / 3: +2 points, and if the real-time voting speed ranks in the bottom 1 / 3: +1 point.

[0067] Among them, the level of cognitive focus, the level of emotional participation, and the level of behavioral activity can be summed / weighted summed to obtain the second evaluation result S.

[0068] By using eye gaze characteristics, facial emotion recognition, frequency of interactive behaviors, and scores for quantitative evaluation, the system achieves in-depth analysis of the target object's real-time participation status from multiple dimensions, including cognitive focus, emotional engagement, and behavioral activity. The results are then integrated to obtain a second evaluation, which can reveal the target object's true level of engagement in visual focus, emotional identification, and operational interaction, thus improving the accuracy and comprehensiveness of the evaluation.

[0069] Step 205: Determine the potential interaction value based on the results of the first and second assessments.

[0070] Among these methods, the first evaluation result and the second evaluation result can be summed to obtain the potential interaction value.

[0071] In some alternative embodiments, the Analytic Hierarchy Process (AHP) can be used to fuse the first and second evaluation results to obtain the potential interaction value. Specifically, a hierarchical model can be constructed first, with the target layer set as the potential interaction value evaluation, the criterion layer as the historical value entropy value (first evaluation result) and the real-time scenario value (second evaluation result), and the indicator layer as the specific evaluation indicators (such as meeting duration, number of document downloads, number of votes, cognitive focus level, emotional participation level, and behavioral activity level). The weight of the criterion layer on the target layer is determined through expert scoring or data statistics. (Weight of the first evaluation result) and (Second evaluation result weight), then the first evaluation result H and the second evaluation result S are standardized to obtain and The potential interaction value is calculated using the following formula:

[0072] in, For potential interactive value, The value obtained by standardizing the first evaluation result H is... The value is obtained by standardizing the second evaluation result S.

[0073] The weights of the first and second evaluation results can be dynamically adjusted based on the type of the First Universe Conference. For example, if the First Universe Conference is a decision-making meeting, then... =0.6, =0.4; If the First Universe Conference is a creative workshop, then =0.3, =0.7.

[0074] Step 206: Send potential interactive value to the conference server of the First Metaverse Conference.

[0075] After obtaining the potential interactive value, corresponding interactive prompts can be generated based on the potential interactive value, and the potential interactive value and interactive prompts can be sent to the conference server of the First Universe Conference, so that the conference server can send the potential interactive value and interactive prompts to at least one participating terminal associated with the First Universe Conference, so that the potential interactive value and interactive prompts can be displayed on at least one participating terminal.

[0076] In some optional embodiments, if the potential interaction value is greater than or equal to a first value threshold, detailed interaction prompts can be generated. These detailed prompts may include the target object's potential viewpoint and relevant historical behavior references. For example, potential viewpoints may include "potentially supporting a certain issue, with previous active participation on similar topics," and relevant historical behavior references may include "operation records of similar topics in past meetings." If the potential interaction value is greater than or equal to a second value threshold but less than the first value threshold, brief interaction prompts can be generated. These brief prompts may include a focus prompt for the target object, such as "This participant may have potential ideas; it is recommended to invite them to participate in the discussion." If the potential interaction value is less than the second value threshold, no interaction prompts may be generated, and only routine recording is performed. The first value threshold is greater than the second value threshold; for example, the first value threshold can be 80, and the second value threshold can be 50.

[0077] Upon receiving potential interactive value, the meeting server can adjust the meeting flow accordingly. For example, it can add discussion sessions for potential opinions from high-value silent participants or send customized questions to these participants to invite them to interact. It should be noted that if the meeting server sends potential interactive value and interaction prompts to the meeting host's participating terminals, the meeting host can also adjust the meeting flow based on these information.

[0078] After obtaining the potential interaction value, for target objects whose potential interaction value is greater than or equal to the first value threshold, the focus of data collection can be optimized, such as improving their eye-tracking accuracy.

[0079] In this embodiment, target objects in the First Metaverse Conference are acquired; where target objects refer to participants in the First Metaverse Conference whose non-speaking time meets the set conditions; historical participation data of target objects before the First Metaverse Conference and participation behavior data of target objects in the First Metaverse Conference are acquired; based on the historical participation data, a first evaluation result of the target objects is determined; where the first evaluation result is used to indicate the degree of disorder in the target objects' historical participation behavior; based on the participation behavior data, a second evaluation result of the target objects is determined; where the second evaluation result is used to indicate the degree of participation engagement of target objects; based on the first evaluation result and the second evaluation result, potential interaction value is determined; the potential interaction value is sent to the conference server of the First Metaverse Conference; where the first evaluation result reflects the degree of disorder in the target objects' historical participation behavior, can reflect the stability of the target objects' long-term participation habits, and can provide historical reference for judging their interaction potential; the second evaluation result reflects the target objects' current participation engagement, can reflect their attention to and willingness to participate in the content of this conference, and can provide realistic evidence for judging their immediate interaction potential. By combining the two to determine the potential interaction value, the one-sidedness of single data evaluation is avoided, making the potential interaction value evaluation result more comprehensive and accurate.

[0080] To implement the above embodiments, this application also proposes a conference data processing device.

[0081] Figure 3 This is a schematic diagram of a conference data processing device provided in an embodiment of this application.

[0082] like Figure 3 As shown, the conference data processing device 300 includes: The first acquisition module 310 is used to acquire target objects in the first metaverse conference; whereby the target objects refer to the participants in the first metaverse conference whose non-speaking time meets the set conditions. The second acquisition module 320 is used to acquire the target object’s historical participation data before the First Metaverse Conference and the target object’s participation behavior data in the First Metaverse Conference. The determination module 330 is used to determine the potential interaction value of the target object based on historical attendance data and attendance behavior data; wherein, the potential interaction value is used to indicate the interaction priority of the target object; The sending module 340 is used to send potential interactive value to the conference server of the First Universe Conference; wherein the conference server is used to send the potential interactive value to at least one participating terminal associated with the First Universe Conference, so as to display the potential interactive value in at least one participating terminal.

[0083] Optionally, the determining module 330 is specifically used to: determine a first evaluation result of the target object based on historical participation data; wherein the first evaluation result is used to indicate the degree of disorder in the target object's historical participation behavior; determine a second evaluation result of the target object based on participation behavior data; wherein the second evaluation result is used to indicate the target object's level of participation engagement; and determine the potential interaction value based on the first evaluation result and the second evaluation result.

[0084] Optionally, the second acquisition module 320 is specifically used to: acquire the target object's participation data in at least one second metaverse conference; wherein, the second metaverse conference is a metaverse conference that the target object participated in before the first metaverse conference; the participation data includes the target object's index value under at least one statistical indicator; and obtain historical participation data based on the target object's participation data in at least one second metaverse conference.

[0085] Optionally, the determining module 330 is specifically used for: for any statistical indicator, sorting the indicator values ​​of the target object in at least one second-dimensional universe meeting according to the time sequence to obtain the corresponding indicator value sequence; determining the probability distribution corresponding to any statistical indicator based on the indicator value sequence; wherein, the probability distribution is used to indicate the probability of any indicator value or any set indicator value interval in the indicator value sequence appearing in the indicator value sequence; determining the entropy value corresponding to any statistical indicator based on the probability distribution; and obtaining a first evaluation result based on the entropy value corresponding to at least one statistical indicator.

[0086] Optionally, the second acquisition module 320 is specifically used to: acquire eye movement trajectory data, facial expression data, and interaction behavior data of the target object during its participation in the First Universe Conference; and obtain the conference participation behavior data based on at least one of the eye movement trajectory data, facial expression data, and interaction behavior data.

[0087] Optionally, the determining module 330 is specifically used to: based on eye movement trajectory data, acquire the target object's first gaze duration on the main conference screen, the second gaze duration on the designated document display area, and the target object's screen switching frequency; and determine the target object's cognitive focus level based on at least one of the first gaze duration, the second gaze duration, and the screen switching frequency; based on facial expression data, identify the target object's emotional state towards the conference content; and determine the target object's emotional participation level based on the emotional score corresponding to the emotional state; based on interactive behavior data, acquire the behavior score and frequency of any interactive behavior; and determine the target object's behavioral activity level based on the behavior score and frequency of occurrence; and determine a second evaluation result based on at least one of the cognitive focus level, emotional participation level, and behavioral activity level.

[0088] It should be noted that the foregoing explanation of the embodiments of the conference data processing method also applies to the conference data processing device of this embodiment, and will not be repeated here.

[0089] In this embodiment, the target object in the First Metaverse Conference is obtained; wherein, the target object refers to the participant in the First Metaverse Conference whose non-speaking time meets the set condition; the historical participation data of the target object before the First Metaverse Conference and the participation behavior data of the target object in the First Metaverse Conference are obtained; based on the historical participation data and the participation behavior data, the potential interaction value of the target object is determined; wherein, the potential interaction value is used to indicate the interaction priority of the target object; the potential interaction value is sent to the conference server of the First Metaverse Conference; wherein, the conference server is used to send the potential interaction value to at least one participating terminal associated with the First Metaverse Conference, so as to display the potential interaction value in at least one participating terminal; wherein, by determining the potential interaction value of the target object through two dimensions of historical participation data and real-time participation behavior data, the accuracy of the calculation of potential interaction value is greatly improved, avoiding problems such as single evaluation dimension and one-sided data basis, and providing accurate data support for the intelligent interaction scheduling of the Metaverse Conference.

[0090] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 400 in this embodiment is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0091] like Figure 4 As shown, the above-mentioned electronic device 400 includes: The memory 401 and the processor 402 are connected by a bus 403, which connects the different components (including the memory 401 and the processor 402). The memory 401 stores a computer program, and when the processor 402 executes the program, it implements the conference data processing method of the present application embodiment.

[0092] Bus 403 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0093] Electronic device 400 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by electronic device 400, including volatile and non-volatile media, removable and non-removable media.

[0094] Memory 401 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 404 and / or cache memory 405. Electronic device 400 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 406 may be used to read and write non-removable, non-volatile magnetic media (… Figure 4 Not shown; usually referred to as a "hard drive"). Although Figure 4 As not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 403 via one or more data media interfaces. Memory 401 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of this application.

[0095] A program / utility 408 having a set (at least one) of program modules 407 may be stored, for example, in memory 401. Such program modules 407 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 407 typically perform the functions and / or methods described in the embodiments of this application.

[0096] Electronic device 400 can also communicate with one or more external devices 409 (e.g., keyboard, pointing device, display 411, etc.), and with one or more devices that enable a user to interact with the electronic device 400, and / or with any device that enables the electronic device 400 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 412. Furthermore, electronic device 400 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 413. Figure 4 As shown, network adapter 413 communicates with other modules of electronic device 400 via bus 403. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0097] The processor 402 performs various functional applications and data processing by running programs stored in the memory 401.

[0098] It should be noted that the implementation process and technical principles of the electronic device in this embodiment are explained in the foregoing description of the meeting data processing method in the embodiments of this application, and will not be repeated here.

[0099] To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0100] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0101] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application comply with relevant laws and regulations and do not violate public order and good morals.

[0102] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0103] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this application is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0104] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0105] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0106] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0107] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0108] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0109] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0110] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0111] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for processing conference data, characterized in that, Includes the following steps: Obtain the target object in the first metaverse conference; wherein, the target object refers to the participant in the first metaverse conference whose non-speaking time meets the set condition; Obtain the target object's historical participation data before the first metaverse conference and the target object's participation behavior data during the first metaverse conference; Based on the historical attendance data and the attendance behavior data, the potential interaction value of the target object is determined; wherein, the potential interaction value is used to indicate the interaction priority of the target object; The potential interactive value is sent to the conference server of the first metaverse conference; wherein the conference server is used to send the potential interactive value to at least one participating terminal associated with the first metaverse conference, so as to display the potential interactive value in the at least one participating terminal.

2. The method according to claim 1, characterized in that, The determination of the potential interactive value of the target object based on the historical attendance data and the attendance behavior data includes: Based on the historical attendance data, a first evaluation result for the target object is determined; wherein, the first evaluation result is used to indicate the degree of disorder in the target object's historical attendance behavior; Based on the meeting participation behavior data, a second evaluation result for the target object is determined; wherein, the second evaluation result is used to indicate the level of participation engagement of the target object; The potential interaction value is determined based on the first evaluation result and the second evaluation result.

3. The method according to claim 2, characterized in that, The step of obtaining the target object's historical attendance data prior to the first metaverse conference includes: Obtain the participation data of the target object in at least one second metaverse conference; wherein, the second metaverse conference is a metaverse conference that the target object participated in before the first metaverse conference; the participation data includes the indicator values ​​of the target object under at least one statistical indicator; The historical participation data is obtained based on the target object's participation data in at least one second-dimensional universe conference.

4. The method according to claim 3, characterized in that, The determination of the first evaluation result of the target object based on the historical attendance data includes: For any statistical indicator, the indicator values ​​of the target object in at least one second-dimensional universe conference are sorted according to time order to obtain the corresponding indicator value sequence. Based on the index value sequence, determine the probability distribution corresponding to any statistical index; wherein, the probability distribution is used to indicate the probability of any index value or any set index value interval in the index value sequence appearing in the index value sequence. Based on the probability distribution, determine the entropy value corresponding to any statistical indicator; The first evaluation result is obtained based on the entropy value corresponding to at least one statistical indicator.

5. The method according to claim 2, characterized in that, Acquiring the target object's participation behavior data in the first metaverse conference, including: Acquire the target object's eye movement trajectory data, facial expression data, and interaction behavior data during its participation in the first metaverse meeting; The meeting participation behavior data is obtained based on at least one of the eye movement trajectory data, facial expression data, and interaction behavior data.

6. The method according to claim 5, characterized in that, The determination of the second evaluation result of the target object based on the participation behavior data includes: Based on the eye movement trajectory data, the first gaze duration of the target object to the main conference screen, the second gaze duration to the set material display area, and the screen switching frequency of the target object are obtained. Based on at least one of the first gaze duration, the second gaze duration, and the screen switching frequency, the cognitive focus level of the target object is determined. Based on the facial expression data, the target object's emotional state towards the meeting content is identified, and the target object's degree of emotional participation is determined based on the emotional score corresponding to the emotional state. Based on the interaction behavior data, obtain the behavior score and occurrence frequency corresponding to any interaction behavior, and determine the behavioral activity level of the target object based on the behavior score and occurrence frequency; The second assessment result is determined based on at least one of the cognitive focus level, the emotional engagement level, and the behavioral activity level.

7. A conference data processing device, characterized in that, include: The first acquisition module is used to acquire target objects in the first metaverse conference; wherein, the target object refers to the participant in the first metaverse conference whose non-speaking time meets the set condition; The second acquisition module is used to acquire the target object's historical participation data before the first metaverse conference and the target object's participation behavior data in the first metaverse conference; The determination module is used to determine the potential interaction value of the target object based on the historical participation data and the participation behavior data; wherein the potential interaction value is used to indicate the interaction priority of the target object; A sending module is used to send the potential interactive value to the conference server of the first metaverse conference; wherein the conference server is used to send the potential interactive value to at least one participating terminal associated with the first metaverse conference, so as to display the potential interactive value in the at least one participating terminal.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-6.

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