Intelligent conference implementation method and equipment based on intelligent agent platform, and medium

Abstract

The invention discloses an intelligent conference implementation method and device based on an intelligent agent platform and a medium, and the method comprises the steps: constructing a voice library of participants to associate and store standard voice samples and corresponding identity information of the participants, and receiving conference information inputted by the participants through the intelligent agent platform, creating a corresponding conference application and generating a unique conference identifier; based on a pre-configured voice data transmission channel, transmitting the obtained speaker voice data to a voice recognition interface for voice feature extraction, matching the voice features with a standard voice sample in a voice library, and determining the speaker identity based on a matching result; based on the identity information of the speaker and pre-stored participant information, determining a speaking position of the speaker in the conference process; and generating a structured conference summary through a natural language processing technology according to the identity of the speaker and the speaking content, and sending the structured conference summary to the corresponding participants according to pre-stored contact information of the participants.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device and medium for implementing intelligent conferencing based on an intelligent agent platform. Background Art

[0002] With the growing demand for enterprise collaboration and information sharing, intelligent conferencing systems are becoming a key tool for improving meeting efficiency. Existing technologies, automatic meeting minutes generation systems use speech recognition and natural language processing to convert meeting content into text records. However, traditional solutions struggle to accurately distinguish speakers with similar voices when identifying them. This is particularly true in scenarios with multiple participants or with background noise, leading to a significant increase in misidentification rates. This can lead to misalignment between speech content and identity information in meeting minutes, severely reducing the reliability of the records.

[0003] Furthermore, existing systems lack meeting process integration and information relevance. Most solutions only implement one-way speech-to-text conversion, resulting in a lack of contextual information in the generated meeting minutes, making it difficult to fully reconstruct the meeting scene. Furthermore, after the meeting, the minutes must be manually proofread and notifications distributed, a cumbersome process prone to omissions and failing to meet the needs of efficient collaboration. Summary of the Invention

[0004] The embodiments of the present application provide a method, device and medium for implementing an intelligent conference based on an intelligent agent platform to solve the above-mentioned technical problems.

[0005] On the one hand, an embodiment of the present application provides a method for implementing an intelligent conference based on an agent platform, including:

[0006] Build a voice database for participants to associate and store standard voice samples of participants with corresponding identity information, receive meeting information input by participants through the intelligent agent platform, create corresponding meeting applications and generate unique meeting identifiers;

[0007] Based on a pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to a voice recognition interface for voice feature extraction, and the voice features are matched with standard voice samples in the voice library, and the speaker identity is determined based on the matching results;

[0008] Determine the speaker's speaking position in the conference process based on the speaker's identity information and pre-stored participant information; the participant information includes a conference seating distribution map;

[0009] According to the identity of the speaker and the content of the speech, a structured meeting minutes is generated through natural language processing technology, and the structured meeting minutes is sent to the corresponding participants according to the pre-stored contact information of the participants.

[0010] In one implementation of the present application, a voice library of conference participants is constructed to associate and store standard voice samples of conference participants with corresponding identity information, specifically including:

[0011] Identify the meeting participants to build a voice library of the meeting participants and obtain standard voice samples corresponding to the meeting participants; the standard voice samples represent fixed terms related to the meeting scene, including common greetings and work-related terms;

[0012] Digitally processing the standard voice sample to extract voice features from the standard voice sample; the voice features include voice frequency, timbre and intonation;

[0013] The processed standard voice sample is associated with the identity information of the corresponding conference participant, and the associated standard voice sample and identity information are stored in the voice library.

[0014] In one implementation of the present application, based on a pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to a voice recognition interface for voice feature extraction, specifically including:

[0015] Connecting the conference application to the voice recognition interface and configuring a voice data transmission channel;

[0016] When the meeting is in progress, the voice data of the speaker in the meeting is obtained in real time through the audio acquisition device preset in the conference application, and the voice data of the speaker is transmitted to the voice recognition interface through the voice data transmission channel;

[0017] The speaker's voice data is analyzed through the voice recognition interface to extract spectral features, fundamental frequency parameters and intonation patterns from the speaker's voice data.

[0018] In one implementation of the present application, matching the voice features with standard voice samples in the voice database and determining the speaker identity based on the matching results specifically includes:

[0019] For each standard speech sample in the speech library, a dynamic time warping algorithm is used to compare the spectral features in the speech features with the standard speech sample frame by frame;

[0020] Determining the degree of match between the spectral feature and the standard speech sample based on the comparison result, and judging whether the degree of match exceeds a preset matching threshold;

[0021] When the matching degree of the specified number of frames exceeds the preset matching threshold, it is determined that the speaker's identity is successfully matched, and the participant corresponding to the standard voice sample is determined to be the identity information corresponding to the speaker.

[0022] In one implementation of the present application, a structured meeting summary is generated based on the speaker's identity and speech content using natural language processing technology, specifically including:

[0023] Collect the speaker's speech content in real time, convert the speech content into text in real time, and mark the corresponding timestamp and speaker identity in the text information;

[0024] Through a keyword extraction algorithm, core topics and decision items are identified from the text information, and a structured meeting minutes is generated based on the relevance between the speaker identity and the topic; the structured meeting minutes includes a summary of the topic, decision results, and division of responsibilities.

[0025] In one implementation of the present application, based on the speaker's identity information and pre-stored participant information, determining the speaker's speaking position in the conference process specifically includes:

[0026] The real-time location coordinates of the speaker are obtained through the positioning equipment pre-deployed in the venue, and the real-time location coordinates are mapped with the pre-stored conference seating distribution map to generate the speaker's location identifier;

[0027] The location identifier is associated with the speech content and the identity information of the speaker, and the associated speaker information is stored in a structured database.

[0028] In one implementation of the present application, the structured meeting minutes are sent to the corresponding participants according to the pre-stored contact information of the participants, specifically including:

[0029] Retrieving pre-stored participant contact information and an email feedback template from a structured database based on the unique conference identifier corresponding to the conference application;

[0030] Segmenting the structured meeting minutes according to different speaker identities, and inserting position identifiers of corresponding speakers into the segmented minutes paragraphs;

[0031] According to the email feedback template and the structured meeting minutes, the email subject, body and attachments are automatically filled in, and a complete email data packet to be sent is generated, so that the complete email data packet can be sent to the corresponding participant according to the email account in the participant's contact information.

[0032] In one implementation of the present application, the conference application is connected to the voice recognition interface, and a voice data transmission channel is configured, specifically including:

[0033] When a conference application is created, automatically detect a third-party speech recognition service and bind the conference application to the speech recognition interface of the third-party speech recognition service;

[0034] Configure the encryption protocol and real-time streaming processing parameters for voice data transmission, and perform error checking on the recognition results returned by the voice recognition interface. If the check fails, trigger a re-recognition process.

[0035] On the other hand, an embodiment of the present application further provides an intelligent conference implementation device based on an agent platform, the device comprising:

[0036] at least one processor;

[0037] and, a memory communicatively coupled to the at least one processor;

[0038] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned method for implementing an intelligent conference based on an intelligent agent platform.

[0039] On the other hand, an embodiment of the present application further provides a non-volatile computer storage medium storing computer executable instructions. When the computer executable instructions are executed, an intelligent conference implementation method based on an intelligent agent platform as described above is implemented.

[0040] The embodiments of the present application provide a method, device, and medium for implementing an intelligent conference based on an agent platform, which have at least the following beneficial effects:

[0041] By collecting and matching the voice features of the speaker, the identities of different participants can be accurately distinguished, effectively overcoming the misidentification problem caused by similar voices or environmental noise in traditional solutions, and ensuring that the speech content in the meeting minutes corresponds to the identity information. At the same time, natural language processing technology is used to generate structured meeting minutes containing topic summaries, decision results and division of responsibilities, and the speech location identifier is associated with the participant information for storage, so that the meeting records have complete contextual information, which is convenient for subsequent review and scene restoration. In addition, notification emails are automatically generated and sent based on the preset contact information of the participants, realizing the automation of the entire process from meeting content recording to information distribution, greatly reducing manual intervention and improving collaborative efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0043] Figure 1 A flowchart of a method for implementing an intelligent conference based on an agent platform provided in an embodiment of the present application;

[0044] Figure 2 A schematic diagram of the internal structure of an intelligent conference implementation device based on an intelligent agent platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0046] The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.

[0047] Figure 1 A flowchart of a method for implementing an intelligent conference based on an agent platform provided in an embodiment of the present application.

[0048] The analysis method involved in the embodiments of the present application can be implemented by a terminal device or a server, and the present application does not impose any special restrictions on this. For ease of understanding and description, the following embodiments are described in detail using a server as an example.

[0049] It should be noted that the server can be a single device or a system composed of multiple devices, that is, a distributed server, and this application does not make any specific restrictions on this.

[0050] like Figure 1 As shown, an embodiment of the present application provides a method for implementing an intelligent conference based on an agent platform, including:

[0051] Step 101: Build a voice library for the participants to associate and store the standard voice samples of the participants with the corresponding identity information, receive the meeting information input by the participants through the intelligent platform, create a corresponding meeting application and generate a unique meeting identifier.

[0052] In this embodiment, a voice database of meeting participants needs to be constructed as a reference data source for identity recognition. The process of constructing the voice database first requires determining the scope of meeting participants and collecting standard voice samples within the corresponding scope. It is understandable that standard voice samples are fixed phrases commonly used by meeting participants in meeting scenarios, such as "I will report on this topic" or "The project progress needs to be adjusted." For example, a department director needs to record voice samples containing sentences related to his position, such as "80% of the goals for this quarter have been completed." It should be noted that these voice samples need to cover a variety of tones and speaking speeds to improve the robustness of subsequent matching.

[0053] Specifically, after the standard voice samples are collected, they undergo digital processing, including noise reduction, normalization, and feature extraction. For example, the Mel-Frequency Cepstral Coefficient (MFCC) algorithm is used to extract characteristic parameters such as voice frequency and timbre, generating a standardized voice feature template. This template is then bound to the participant's identity information, such as name, position, and department, and stored in the database of the voice library storage module.

[0054] Participants then initiate a meeting creation request through the agent platform interface, entering information such as the meeting topic, attendee list, time, and location. For example, if a participant enters the topic "Annual Strategic Meeting," the agent platform automatically invokes a pre-configured workflow template, generates a dedicated meeting application instance, and assigns a unique identifier to the meeting, such as MEET_2023STRAT. It should be noted that this unique meeting identifier is used for subsequent data association and process tracking, ensuring the independence of meeting records.

[0055] Step 102: Based on the pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to the voice recognition interface for voice feature extraction, and the voice features are matched with standard voice samples in the voice library, and the speaker identity is determined based on the matching results.

[0056] In this embodiment, after the conference application is created, the agent platform automatically detects and binds to the API interface of the third-party speech recognition service. For example, when using the iFlytek speech recognition interface, a real-time streaming protocol and data encryption mechanism must be configured to ensure the security and real-time performance of the voice data. A real-time streaming protocol such as WebSocket and a data encryption mechanism such as TLS are required.

[0057] In this embodiment, while a meeting is in progress, a directional microphone array deployed at the venue collects the speaker's voice signal in real time and sends the collected raw voice data to the voice recognition interface via a transmission channel. It should be noted that the audio acquisition equipment must have a noise suppression function to filter out background noise. For example, when a participant begins to speak, their voice signal is transmitted to the interface via a channel and is first framed, with each frame being 20 milliseconds long. Subsequently, voiceprint features such as spectral features, fundamental frequency parameters, and intonation patterns are extracted.

[0058] Furthermore, the speech recognition interface uses a dynamic time warping (DTW) algorithm to compare the current speaker's spectral features with the standard samples in the speech library frame by frame. It is understandable that the DTW algorithm can align speech sequences of different lengths and eliminate the impact of differences in speaking speed. For example, when the speaker's spectral energy distribution matches the sample of the technical director in the speech library in multiple consecutive frames and the degree of match exceeds a preset threshold, the system determines that the identity match is successful, confirms its identity and records the corresponding position information.

[0059] Step 103: Determine the speaker's speaking position in the conference process based on the speaker's identity information and pre-stored participant information.

[0060] It should be noted that the participant information in the embodiment of the present application includes a conference seat distribution map.

[0061] In this embodiment, after identity recognition is complete, the system further determines the speaker's real-time location. Pre-installed positioning devices in the venue, such as UWB sensors or cameras, acquire the speaker's coordinate data in real time. For example, when a speaker is located on the left side of the front row of a conference room, the UWB base station calculates their coordinates (x1, y1) through triangulation and transmits them to the agent platform.

[0062] It's important to note that the pre-stored conference seating map is a digitized version of the conference room floor plan, with each seat marked with a zone identifier, such as Section A, Row 2. The agent platform maps the speaker's real-time coordinates to the seating map to generate a location identifier. For example, if the coordinates (x1, y1) fall within the area of ​​Section B, Row 1, the speaker's location is marked as B1.

[0063] Furthermore, the location identifier is associated with the speaker's identity and speech content and stored in a structured database. It is understandable that this association allows the subsequent generated meeting minutes to restore the actual location of the speaker, for example, marking the R&D manager (B1) for requesting a change.

[0064] Step 104: Generate structured meeting minutes based on the speaker's identity and speech content through natural language processing technology, and send the structured meeting minutes to the corresponding participants based on the pre-stored contact information of the participants.

[0065] In this embodiment, after the speech recognition interface converts the speech content into text, the system uses natural language processing technology to structure the text. For example, the BERT model extracts entities, actions, and relationships in the text to generate a topic summary, with entities such as Project A and Budget and actions such as Extension and Approval.

[0066] It's important to note that the generation of structured meeting minutes also incorporates speaker identity information. For example, if the CTO's speech includes a topic about technical architecture optimization, the system automatically identifies the CTO as the person responsible for that topic and generates a decision item, indicating that the technical department will take the lead. Furthermore, the speaker's location information, such as the speaker's seat, is included in the minutes, creating a complete record with timestamps, identity, location, and content.

[0067] Furthermore, after the meeting, the system retrieves the pre-stored contact information (such as email addresses) and email templates of the participants based on the meeting identifier, and segments the meeting minutes by department or role. The body of the email is segmented by speaker identity, with the corresponding minutes content and location identifiers inserted, and a structured meeting minutes document is attached. For example, the emails from R&D department members only contain paragraphs on relevant topics and task assignments. Finally, the email server sends the customized emails to the corresponding participants, completing the automation of the entire process from meeting records to information distribution.

[0068] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, this application embodiment also provides an intelligent conference implementation device based on an intelligent agent platform, the structure of which is as follows: Figure 2 shown.

[0069] Figure 2 This is a schematic diagram of the internal structure of an intelligent conference implementation device based on an intelligent agent platform provided in an embodiment of the present application. Figure 2 As shown, the equipment includes:

[0070] at least one processor;

[0071] and, a memory communicatively coupled to the at least one processor;

[0072] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0073] Build a voice database for participants to associate and store standard voice samples of participants with corresponding identity information, receive meeting information input by participants through the intelligent agent platform, create corresponding meeting applications and generate unique meeting identifiers;

[0074] Based on the pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to the voice recognition interface for voice feature extraction, and the voice features are matched with standard voice samples in the voice library, and the speaker identity is determined based on the matching results;

[0075] Determine the speaker's speaking position in the meeting process based on the speaker's identity information and pre-stored participant information; participant information includes a conference seating distribution map;

[0076] Based on the speaker's identity and speech content, structured meeting minutes are generated through natural language processing technology, and the structured meeting minutes are sent to the corresponding participants based on the pre-stored contact information of the participants.

[0077] The present application also provides a non-volatile computer storage medium storing computer-executable instructions. When the computer-executable instructions are executed, they can:

[0078] Build a voice database for participants to associate and store standard voice samples of participants with corresponding identity information, receive meeting information input by participants through the intelligent agent platform, create corresponding meeting applications and generate unique meeting identifiers;

[0079] Based on the pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to the voice recognition interface for voice feature extraction, and the voice features are matched with standard voice samples in the voice library, and the speaker identity is determined based on the matching results;

[0080] Determine the speaker's speaking position in the meeting process based on the speaker's identity information and pre-stored participant information; participant information includes a conference seating distribution map;

[0081] Based on the speaker's identity and speech content, structured meeting minutes are generated through natural language processing technology, and the structured meeting minutes are sent to the corresponding participants based on the pre-stored contact information of the participants.

[0082] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device and medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant portions, refer to the descriptions of the method embodiments.

[0083] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0084] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0085] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0086] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0087] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0088] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0089] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0090] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0091] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0092] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for implementing intelligent conference based on an agent platform, characterized in that: The method comprises: Build a voice database for participants to associate and store standard voice samples of participants with corresponding identity information, receive meeting information input by participants through the intelligent agent platform, create corresponding meeting applications and generate unique meeting identifiers; Based on a pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to a voice recognition interface for voice feature extraction, and the voice features are matched with standard voice samples in the voice library, and the speaker identity is determined based on the matching results; Determine the speaker's speaking position in the conference process based on the speaker's identity information and pre-stored participant information; the participant information includes a conference seating distribution map; According to the identity of the speaker and the content of the speech, a structured meeting minutes is generated through natural language processing technology, and the structured meeting minutes is sent to the corresponding participants according to the pre-stored contact information of the participants.

2. The method for realizing intelligent conference based on agent platform according to claim 1, characterized in that: Build a voice database for conference participants to associate and store standard voice samples of conference participants with their corresponding identity information, including: Identify the meeting participants to build a voice library of the meeting participants and obtain standard voice samples corresponding to the meeting participants; the standard voice samples represent fixed terms related to the meeting scene, including common greetings and work-related terms; Digitally processing the standard voice sample to extract voice features from the standard voice sample; the voice features include voice frequency, timbre and intonation; The processed standard voice sample is associated with the identity information of the corresponding conference participant, and the associated standard voice sample and identity information are stored in the voice library.

3. The method for realizing intelligent conference based on agent platform according to claim 1, characterized in that: Based on the pre-configured voice data transmission channel, the acquired speaker voice data is transmitted to the voice recognition interface for voice feature extraction, specifically including: Connecting the conference application to the voice recognition interface and configuring a voice data transmission channel; When the meeting is in progress, the voice data of the speaker in the meeting is obtained in real time through the audio acquisition device preset in the conference application, and the voice data of the speaker is transmitted to the voice recognition interface through the voice data transmission channel; The speaker's voice data is analyzed through the voice recognition interface to extract spectral features, fundamental frequency parameters and intonation patterns from the speaker's voice data.

4. The method for realizing intelligent conference based on an agent platform according to claim 1, characterized in that: Matching the voice features with standard voice samples in the voice database, and determining the speaker identity based on the matching results, specifically comprising: For each standard speech sample in the speech library, a dynamic time warping algorithm is used to compare the spectral features in the speech features with the standard speech sample frame by frame; Determining the degree of match between the spectral feature and the standard speech sample based on the comparison result, and judging whether the degree of match exceeds a preset matching threshold; When the matching degree of the specified number of frames exceeds the preset matching threshold, it is determined that the speaker's identity is successfully matched, and the participant corresponding to the standard voice sample is determined to be the identity information corresponding to the speaker.

5. The method for realizing intelligent conference based on agent platform according to claim 1, characterized in that: Based on the speaker's identity and speech content, a structured meeting summary is generated using natural language processing technology, specifically including: Collect the speaker's speech content in real time, convert the speech content into text in real time, and mark the corresponding timestamp and speaker identity in the text information; Through a keyword extraction algorithm, core topics and decision items are identified from the text information, and a structured meeting minutes is generated based on the relevance between the speaker identity and the topic; the structured meeting minutes includes a summary of the topic, decision results, and division of responsibilities.

6. The method for realizing intelligent conference based on agent platform according to claim 1, characterized in that: Determine the speaker's speaking position in the conference process based on the speaker's identity information and pre-stored participant information, specifically including: The real-time location coordinates of the speaker are obtained through the positioning equipment pre-deployed in the venue, and the real-time location coordinates are mapped with the pre-stored conference seating distribution map to generate the speaker's location identifier; The location identifier is associated with the speech content and the identity information of the speaker, and the associated speaker information is stored in a structured database.

7. The method for realizing intelligent conference based on agent platform according to claim 1, characterized in that: Send the structured meeting minutes to the corresponding participants based on the pre-stored contact information of the participants, including: Retrieving pre-stored participant contact information and an email feedback template from a structured database based on the unique conference identifier corresponding to the conference application; Segmenting the structured meeting minutes according to different speaker identities, and inserting position identifiers of corresponding speakers into the segmented minutes paragraphs; According to the email feedback template and the structured meeting minutes, the email subject, body and attachments are automatically filled in, and a complete email data packet to be sent is generated, so that the complete email data packet can be sent to the corresponding participant according to the email account in the participant's contact information.

8. The method for realizing intelligent conference based on agent platform according to claim 3, characterized in that: Connect the conference application to the voice recognition interface and configure the voice data transmission channel, specifically including: When a conference application is created, automatically detect a third-party speech recognition service and bind the conference application to the speech recognition interface of the third-party speech recognition service; Configure the encryption protocol and real-time streaming processing parameters for voice data transmission, and perform error checking on the recognition results returned by the voice recognition interface. If the check fails, trigger a re-recognition process.

9. An intelligent conference implementation device based on an intelligent agent platform, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent conference implementation method based on the intelligent agent platform as described in any one of claims 1-8.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: When the computer executable instructions are executed, an intelligent conference implementation method based on an intelligent agent platform as described in any one of claims 1 to 8 is implemented.

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