Artificial intelligence-based task recommendation apparatus and method

Abstract

To provide an artificial intelligence-based to-do recommendation device and method for supporting effective fulfillment of a project and work.SOLUTION: An artificial intelligence-based to-do recommendation device includes a memory and a processor that is electrically connected to the memory. The processor is configured to: receive a user request for generation or retrieval of meeting records from a user terminal; generate the meeting records or a meeting record list including the meeting records according to the user request; generate to-do recommendations related to conference contents of the meeting records through an artificial intelligence model when a to-do recommendation request related to the meeting records is received from the user terminal; and provide a to-do recommendation list including selection options for each to-do recommendation to the user terminal.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a technology for recommending tasks (hereinafter referred to as "tasks"), and more specifically to a technology for automatically recommending tasks related to minutes in the process of generating or referencing minutes that record the contents of meetings between project participants during the progress of a project, and for supporting task generation to support the effective execution of projects and tasks. [Background technology]

[0002] Generally, an Internet messenger is an application that transmits messages, including text and graphics, between users and is implemented as a chat room in which multiple users participate. In one embodiment, the Internet messenger includes a mobile messenger executed in a mobile environment (e.g., a mobile phone), such as KakaoTalk (registered trademark), LINE (registered trademark), WeChat (registered trademark), Facebook Messenger, etc. There is a trend toward increasingly diverse uses of such Internet messengers in business management and progress.

[0003] In particular, as the scale of a project gradually increases and the structure of the project becomes more complex, the number of chat rooms in which business participants simultaneously participate within a single project also increases, and business participants may find it difficult to easily grasp the flow of related work in the process of communication that is distributed across multiple chat rooms.

[0004] For this reason, various tools have been developed to support communication between the various participants in a project. For example, meeting minutes, which record the contents of meetings between participants, can be stored and shared among users to easily share progress.

[0005] Furthermore, various tasks related to the contents of the meeting are generated and shared among the participants, and there is a demand for a technology that improves work efficiency in generating and managing tasks. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Korean Patent Registration No. 10-1182535 Summary of the Invention [Problem to be solved by the invention]

[0007] The present invention has been made in consideration of the above-mentioned prior art, and an object of the present invention is to provide an AI-based task recommendation device and method that automatically recommends tasks related to minutes in the process of generating or referencing minutes that record the contents of meetings between business participants during the progress of a project, and supports task generation to support the effective execution of projects and tasks. [Means for solving the problem]

[0008] In order to achieve the above object, one aspect of the present invention provides an artificial intelligence-based task recommendation device that includes a memory and a processor electrically connected to the memory. The processor receives a user request for generating or querying minutes from a user terminal, generates the minutes according to the user request, or generates a minutes list including the minutes, and, when a task recommendation request for the minutes is received from the user terminal, generates recommended tasks related to the meeting content of the minutes via an artificial intelligence model, and provides the user terminal with a recommended task list including selection options for each recommended task.

[0009] The processor receives from the user terminal a dialogue recording file that records the dialogue between business participants regarding the content of the meeting, along with a user request for generating minutes, converts the dialogue recording file into text to generate dialogue text regarding the content of the meeting, and generates minutes that include a summary of the dialogue text and the recommended task-specific selection options.

[0010] The processor can transmit the dialogue recording file to an external STT (Speech-To-Text) server and receive the dialogue text from the STT server.

[0011] The processor can generate the minutes list according to a request from any one of the business participants on a chat room in which the business participants are participating or on a conference map for managing minutes.

[0012] If the minutes correspond to general minutes, the processor can add the recommended duties list to the minutes and convert the minutes into duties minutes.

[0013] The processor may remove a particular recommended task from the recommended task list when a task is generated for the particular recommended task included in the task minutes.

[0014] The processor may convert the task minutes into the general task minutes if all the recommended tasks are removed from the recommended task list.

[0015] The processor may generate a task related to a recommendation task when a user selection is input via the recommendation task-specific selection option.

[0016] The processor may set the user who inputs the user selection as a task instructor for the task, and set the corresponding recommended role as task content for the task.

[0017] The processor may sequentially generate tasks for each of the corresponding recommendation duties if multiple selection options are selected by the user who input the user selection.

[0018] The processor can receive a user's audio file associated with the conference content from the user terminal, recognize the speech in the audio file to generate a script and a summary message converted into text, and display the summary message as a dialogue message in a chat room selected by the user.

[0019] The processor may receive the user's voice in real time, input in a streaming manner from the user terminal, and generate the voice file.

[0020] The processor may input the audio file into a previously constructed speech recognition model to generate the script and the summary message, respectively.

[0021] The processor may generate and associate a tag associated with the summary message with the summary message, and provide a query function for the summary message via the tag.

[0022] The processor may assign a favorite function to each of the conversation messages and store the favorite function, and may provide a list of the conversation messages to which the favorite function has been assigned via a favorite page.

[0023] In order to achieve the above object, one aspect of the present invention provides an artificial intelligence-based task recommendation method executed by a task recommendation device including a memory and a processor electrically connected to the memory. The method is executed by the processor and includes the steps of receiving a user request for generating or querying minutes from a user terminal, generating the minutes or generating a minutes list including the minutes in accordance with the user request, and, when a task recommendation request related to the minutes is received from the user terminal, generating recommended tasks related to the meeting content of the minutes via an artificial intelligence model and providing the user terminal with a recommended task list including selection options for each recommended task. [Effects of the Invention]

[0024] The present invention has the following advantages. However, this does not mean that a particular embodiment should include all of the following advantages or only the following advantages, and the technical scope of the present invention should not be understood as being limited thereby.

[0025] The AI-based task recommendation device and method according to the present invention can support the effective execution of projects and tasks by automatically recommending tasks related to minutes or supporting task generation in the process of generating or referencing minutes that record the contents of meetings between business participants during the progress of a project. [Brief explanation of the drawings]

[0026] [Figure 1] FIG. 1 is a diagram illustrating a task recommendation system according to the present invention. [Figure 2] FIG. 2 is a diagram illustrating the system configuration of the task recommendation device of FIG. [Figure 3] FIG. 3 is a diagram illustrating the functional configuration of the processor in FIG. 2. [Figure 4] 1 is a flowchart illustrating an artificial intelligence-based task recommendation method according to the present invention. [Figure 5] 1 is a diagram illustrating an embodiment of minutes according to the present invention. [Figure 6] 1 is a diagram illustrating an embodiment of a process for generating minutes according to the present invention. [Figure 7] 1 is a diagram illustrating an embodiment of a dialogue message generation process according to the present invention; [Figure 8] 1 is a diagram illustrating an embodiment of a process for providing related functions within a chat room according to the present invention; [Figure 9] FIG. 2 is a diagram illustrating an embodiment of a task generation process according to the present invention. [Figure 10] FIG. 10 is a diagram illustrating an embodiment of a task modification process according to the present invention. [Figure 11] 1 is a diagram illustrating general minutes and working minutes according to the present invention. FIG. [Figure 12] 1 is a diagram illustrating an embodiment of a recommended task list updating process according to the present invention; [Figure 13] 1 is a diagram illustrating a process of sharing a conversation message related to a user's voice in a chat room according to the present invention; [Figure 14] FIG. 10 illustrates one embodiment of a detailed view page for an interactive message according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0027] The description of the present invention is merely an embodiment for the purpose of structural or functional description, and therefore the technical scope of the present invention should not be construed as being limited by the embodiments described in the specification. In other words, since the embodiments can be modified in various ways and can have various forms, the technical scope of the present invention should be understood to include equivalents that can realize the technical idea. Furthermore, the objectives or effects presented in the present invention do not mean that a particular embodiment should include all of these or only such effects, and therefore the technical scope of the present invention should not be understood as being limited thereby.

[0028] Meanwhile, the meanings of the terms used in this specification should be understood as follows.

[0029] Terms such as "first" and "second" are used to distinguish one component from another, and should not be used to limit the scope of the technology. For example, a first component may be named a second component, and similarly, a second component may be named a first component.

[0030] When a component is said to be "connected" to another component, it should be understood that it is directly connected to the other component, or that there may be other components in between. Conversely, when a component is said to be "directly connected" to another component, it should be understood that there are no other components in between. Meanwhile, other expressions describing the relationship between components, such as "between" and "immediately between," or "adjacent to" and "directly adjacent to," should be interpreted similarly.

[0031] Singular expressions shall be understood to include plural expressions unless the context clearly dictates otherwise, and terms such as "comprise" or "have" are intended to specify the presence of embodied features, numerals, steps, operations, components, parts, or combinations thereof, but do not preclude the presence or possible addition of one or more other features, numerals, steps, operations, components, parts, or combinations thereof.

[0032] The designations (e.g., a, b, c, etc.) used in each step are for convenience of description and do not describe the order of each step, and each step may occur in a different order than specified unless the context clearly dictates a particular order. That is, each step may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the opposite order.

[0033] The present invention is embodied as computer-readable code on a computer-readable recording medium, which includes any type of recording device that stores data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. Furthermore, the computer-readable recording media can be distributed across computer systems connected via a network, so that the computer-readable code can be stored and executed in a distributed manner.

[0034] Unless otherwise defined, all terms used herein have the same meaning as commonly understood by a person of ordinary skill in the art to which this invention pertains. Terms defined in commonly used dictionaries should be interpreted to be consistent with the meaning they have in the context of the relevant art, and should not be interpreted as having an ideal or overly formal meaning unless expressly defined herein.

[0035] FIG. 1 is a diagram illustrating a task recommendation system according to the present invention.

[0036] Referring to FIG. 1, a task recommendation system 100 includes a plurality of user terminals 110 , a task recommendation device 130 , and a database 150 .

[0037] The user terminal 110 corresponds to a computing device operated by a user. For example, the user terminal 110 may be realized as a desktop PC, a notebook PC, a tablet PC, or a smartphone, but is not necessarily limited to these, and may be realized as various devices.

[0038] There may be one or more user terminals 110, and in this case, the user terminal may be any one or more of a first user terminal 110a, a second user terminal 110b, and a third user terminal 110c. For convenience, the user terminal 110 used by the first user will be referred to as the first user terminal 110a, the user terminal 110 used by the second user will be referred to as the second user terminal 110b, the user terminal 110 used by the third user will be referred to as the third user terminal 110c, etc.

[0039] In an embodiment of the present invention, multiple users are included in one or more user groups, which are referred to as a first user group, a second user group, a third user group, etc. Meanwhile, one user may be included in one or more user groups at the same time.

[0040] Furthermore, the multiple users correspond to business participants who participate in a joint project or business. For example, business participants include a business director who instructs the business, a business executor who executes the business, and business associates related to the business.

[0041] In this case, there is one overall project, which can include multiple business projects that proceed independently. In addition, plans, cards, notes, tasks, etc. are created and stored in relation to the overall project or business projects.

[0042] Here, a plan corresponds to a business plan established to achieve a specific goal, a card corresponds to a management card for a series of tasks, a note corresponds to a business record that stores details related to the task, and a task corresponds to various unit tasks that are created and processed according to a plan, card, or note.

[0043] Furthermore, in the process of processing a plan, card, note, or task, users can share objects such as messages, files, and photos (or images), and a chat room can be provided for users to converse and share objects. In this case, messages shared through the chat room can include conversational messages about daily matters and business messages about business matters.

[0044] In one embodiment, at least one of the user terminals 110 is a mobile terminal and is connected to the task recommendation device 130 via cellular or Wi-Fi communication. In another embodiment, at least one of the user terminals 110 is a desktop PC and is connected to the task recommendation device 130 via the Internet.

[0045] The task recommendation device 130 corresponds to a computing device connected via a network to at least one user terminal 110. In one embodiment, the task recommendation device 130 can manage at least one user group in which other users associated with one user are included as members, i.e., task participants.

[0046] In one embodiment, the task recommendation device 130 is connected to the user terminal 110 via a dedicated agent installed in the user terminal 110. Here, the dedicated agent corresponds to an agent program, which is software that, when installed in the user terminal 110, can enable the user terminal 110 and the task recommendation device 130 to interact with each other under the approval of the user terminal 110.

[0047] Meanwhile, the connection and coupling between the task recommendation device 130 and the user terminal 110 described here corresponds to one embodiment and can be modified and applied in various forms within the normal range according to various operating and implementation environments.

[0048] The database 150 corresponds to a storage device that stores various information required in the operation process of the task recommendation device 130. For example, the database 150 may store, but is not limited to, a dialogue recording file that records the contents of a meeting, a voice file that records a user's voice, or text information converted through voice recognition. The task recommendation device 130 may store information collected or processed in various forms in the process of performing the AI-based task recommendation method according to the present invention.

[0049] Furthermore, although in FIG. 1 the database 150 is shown as a logical storage device included in the task recommendation device 130, it is not necessarily limited to this and may be implemented as a device independent of the task recommendation device 130.

[0050] FIG. 2 is a diagram illustrating the system configuration of the task recommendation device of FIG.

[0051] Referring to FIG. 2, the task recommendation device 130 includes a processor 210 , a memory 230 , a user input / output unit 250 , and a network input / output unit 270 .

[0052] The processor 210 executes the artificial intelligence-based task recommendation procedure of the present invention, manages the memory 230 that is read or written in such process, and schedules synchronization times between the volatile and non-volatile memories in the memory 230.

[0053] The processor 210 controls the overall operation of the task recommendation device 130, and is electrically connected to the memory 230, the user input / output unit 250, and the network input / output unit 270, and controls the data flow among them. The processor 210 is realized by a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) of the task recommendation device 130.

[0054] The memory 230 includes a secondary storage device implemented as a nonvolatile memory such as a solid state disk (SSD) or a hard disk drive (HDD) and used to store all data required for the task recommendation device 130, and a primary storage device implemented as a volatile memory such as a random access memory (RAM). Thus, the memory 230 may be implemented as both a volatile and nonvolatile memory, and if implemented as a nonvolatile memory, it may be implemented so as to be connected via a hyperlink.

[0055] The user input / output unit 250 includes an environment for receiving user input and an environment for outputting specific information to a user, and includes input devices including or connected to an adapter such as a mouse, trackball, touchpad, graphic tablet, scanner, touchscreen, keyboard, or pointing device, and output devices including an adapter such as a monitor or touchscreen. In one embodiment, the user input / output unit 250 corresponds to a computing device connected via a remote connection, in which case the task recommendation device 130 acts as a server.

[0056] The network input / output unit 270 provides a communication environment for connecting with the user terminal 110 via a network, and includes, for example, adapters for communication with a LAN (Local Area Network), a MAN (Metropolitan Area Network), a WAN (Wide Area Network), a VAN (Value Added Network), etc. The network input / output unit 270 is also implemented to provide a short-range communication function such as WiFi (registered trademark) or Bluetooth (registered trademark) or a wireless communication function of 4G or higher for wireless data transmission.

[0057] FIG. 3 is a diagram illustrating the functional configuration of the processor in FIG.

[0058] 3, the task recommendation device 130 executes the AI-based task recommendation method according to the present invention through a processor 210. To this end, the processor 210 includes a user request receiving unit 310, a user request processing unit 330, a task recommendation unit 350, a task management unit 370, and a control unit (not shown in FIG. 3).

[0059] In this regard, the embodiments of the present invention do not necessarily include all of the above functional components at the same time, but may omit some of the above components or selectively include some or all of the above components according to each embodiment. Furthermore, one embodiment of the present invention may be realized as independent modules selectively including some of the above components, and the AI-based job recommendation method according to the present invention may be performed through the interworking of each module. The operation of each component will now be described in detail.

[0060] The user request receiving unit 310 receives a user request for creating or viewing minutes from the user terminal 110. Here, minutes are business records that record the contents of discussions held during a meeting between business participants, and are a type of note created in relation to an entire project or a business project. A user request is a command or information that a user requests the system to execute regarding minutes, and is generated by a user (e.g., a business participant) on the user terminal 110. That is, user requests include a request to create minutes, a request to view minutes, a request to delete minutes, a request to modify minutes, etc. The user request receiving unit 310 receives and interprets a user request input from the user terminal 110, and then supports the execution of a series of operations related to the request. The user request receiving unit 310 analyzes the user request to determine the type of user request, the target minutes, the requested task, etc.

[0061] In addition, the user request receiving unit 310 may operate in conjunction with an independent module to process a user request. For example, in the case of a request to create minutes, the user request receiving unit 310 calls a minutes generation module to start a minutes generation operation. In the case of a request to query minutes, the user request receiving unit 310 calls a minutes query module to start a minutes query operation. The user request receiving unit 310 provides the user terminal 110 with an interface through which a request for creating or querying minutes can be input, and the interface is implemented via an application running on the user terminal 110.

[0062] In one embodiment, the user request receiving unit 310 may receive a dialogue recording file that records a dialogue between business participants regarding the content of the conference along with a user request for generating minutes from the user terminal 110. In particular, the user request receiving unit 310 may receive a dialogue recording file that records a dialogue between business participants regarding the content of the conference from the user terminal 110 in conjunction with the user terminal 110. In this case, the dialogue recording file corresponds to a file that records the dialogue between business participants who participated in the conference, and is recorded using a recording function included in the user terminal 110. The user request receiving unit 310 may directly receive the dialogue recording file from the user terminal 110, or may record the dialogue content transmitted in real time from the user terminal 110 to generate the dialogue recording file.

[0063] In one embodiment, the user request receiving unit 310 can receive a user's voice file related to the content of the conference from the user terminal 110. Here, the voice file corresponds to a file in which the user's voice is recorded, and is recorded using a recording function included in the user terminal 110. The user can directly record voice through the user terminal 110 to generate a voice file, and can select and transmit one of various voice files stored in the user terminal 110.

[0064] In addition, the user request receiving unit 310 can directly generate a voice file by receiving in real time the user's voice input in a streaming manner from the user terminal 110. That is, the user directly records his / her voice on the user terminal 110 equipped with a voice recording function, such as a smartphone, tablet, or PC, and the user request receiving unit 310 receives the user's voice recorded in real time in a streaming manner in conjunction with the user terminal 110 and generates a file in a voice data format such as WAV or MP3. In this case, the user request receiving unit 310 compresses the voice data received in real time to save storage space for the voice file and determines the compression method taking into account the network status, etc.

[0065] The user request processor 330 generates minutes in response to a user request or generates a minutes list including the minutes. Specifically, the user request processor 330 can generate minutes that record the contents of a meeting in response to a request for minutes generation. In this case, the minutes can be manually generated by business participants who attended the meeting or automatically generated by artificial intelligence based on a file recording the contents of the meeting, and the generated minutes can be stored and managed in the database 150. In addition, the user request processor 330 can query the minutes in response to a request for querying the minutes and generate a list of one or more minutes as a query result. In other words, the minutes list corresponds to a list of minutes generated as a query result.

[0066] More specifically, when a dialogue recording file is received in response to a request to generate minutes, the user request processor 330 converts the dialogue recording file into text to generate dialogue text about the meeting content, and then generates minutes including a summary of the dialogue text and recommended task-specific selection options. The user request processor 330 can recognize the voices of business participants from the dialogue recording file using a Speech-To-Text (STT) algorithm or a voice recognition model, identify the dialogue of each business participant from the voice, and generate dialogue text as dialogue text. In this case, the dialogue text corresponds to a text file generated by converting the dialogue content recorded during the meeting between business participants into text, and is generated via an external Speech-To-Text (STT) server as needed.

[0067] Furthermore, the dialogue text can be used as input data for the text summarization model, which can generate a summary that summarizes the dialogue text as an output. Here, the text summarization model corresponds to a language model that receives text or a text file as input and generates a summary that summarizes the text or text file. Furthermore, the text summarization model can be designed to generate a summary of the meeting content while also generating recommendations related to the meeting content.

[0068] For example, a text summarization model is realized as ChatGPT. ChatGPT is a massive language model that corresponds to a conversational AI chatbot. In particular, GPT stands for "Generative Pre-trained Transformer," and corresponds to generative AI that pre-trains a huge amount of data through machine learning and generates sentences. In this case, the text summarization model can selectively generate at least one of a summary and a recommendation by setting the input and output data format and structure.

[0069] In one embodiment, the user request processor 330 may transmit a dialogue recording file to an external Speech-To-Text (STT) server and receive dialogue text from the STT server. For example, the external STT server may include a CLOVA Speech server or a Whisper server that supports multilingual speech recognition. That is, the user request processor 330 may generate dialogue text regarding the contents of a meeting between business participants via an external STT server that provides an Automatic Speech Recognition (ASR) service.

[0070] In one embodiment, the user request processor 330 may insert minutes into a chat room in which a business participant is participating or into a conference map for managing minutes, depending on the location of the minutes creation request. Here, the conference map corresponds to a dedicated management tool for managing minutes. Furthermore, when minutes are created and inserted into a chat room in response to a minutes creation request, a message regarding the minutes creation is shared through the chat room, and business participants can directly select the message to access the minutes or download the minutes file. Furthermore, when minutes are created and inserted into the conference map in response to a minutes creation request, various functions related to the minutes, such as querying, modifying, and deleting, are performed through a dedicated interface. Meanwhile, the minutes inserted into the conference map or chat room are stored and managed through an independent memory area associated with the conference map or chat room.

[0071] In one embodiment, the user request processor 330 may generate a minutes list according to a request from a business participant in a chat room in which the business participant is participating or in a conference map for managing minutes. The user request processor 330 provides an interface through which a request for minutes inquiry can be input for each location where minutes can be inquired, and the interface is implemented through an application running on the user terminal 110. For example, a business participant can activate a minutes inquiry function through a menu in a chat room, or can activate the minutes inquiry function through a dedicated interface provided on the conference map.

[0072] In addition, when minutes are viewed in a chat room in response to a minutes view request, the minutes list generated as a result of the view is shared through the chat room, and business participants can directly select specific minutes from the minutes list to access the minutes or download the minutes file. In this case, the minutes list is displayed in the form of a message in the chat room and independently displayed through separate interfaces on the conference map. The minutes list provided in list form is sorted and displayed according to the time the minutes were created and can be sorted according to various criteria other than viewpoint.

[0073] In addition, when minutes are viewed on the conference map in response to a minutes view request, various functions such as confirmation, modification, and deletion of each minutes can be performed along with the minutes list through a dedicated interface. Meanwhile, the minutes list viewed within the conference map or chat room is temporarily created, shared, and then deleted, and is selectively stored and managed in an independent memory area associated with the conference map or chat room as needed.

[0074] In one embodiment, the user request processor 330 may generate independent query results for each type of minutes. For example, the user request processor 330 may generate query results by classifying general minutes and task minutes in response to a minutes query request. In this case, a minutes list for general minutes and task minutes is generated independently. Here, general minutes correspond to minutes that record the contents of a regular meeting, and task minutes correspond to minutes that include one or more recommended tasks along with the contents of a regular meeting.

[0075] In one embodiment, when the user request processor 330 receives a user's voice file related to the content of a meeting from the user terminal 110, it recognizes the voice of the voice file, converts it into text, generates a script and a summary message, and displays the summary message as a conversation message in a chat room selected by the user. That is, the user request processor 330 can share the summary message generated by summarizing the script recognized from the user's voice as a conversation message in the chat room in which the user is participating. Here, a conversation message is defined as a voice memo, which is a message shared within a chat room.

[0076] At this time, other users participating in the chat room can recognize the conversation message as a message entered by the user. This allows the user to easily convey the voice-recorded content to other users in the chat room through a conversation message (or voice memo) without having to enter a separate message in the chat room. The user request processing unit 330 can basically convert the text of the summary message into a conversation message format and share it in the chat room, and, if necessary, display an image or video related to the content of the summary message together with the conversation message.

[0077] More specifically, the user request processor 330 analyzes the voice data stored in the voice file using various voice recognition algorithms and then converts it into text. For example, the voice recognition process includes a voice analysis process that breaks down the voice signal into elements such as frequency and intensity, a voice analysis process that analyzes the voice signal using a trained model, and a voice conversion process that converts the voice extracted through the model into text. Here, the script corresponds to the result of converting the user's voice content stored in the voice file into text, and the summary message corresponds to the result of concisely summarizing the main content of the script.

[0078] Therefore, the script and summary message are expressed as text data and stored and managed in association with the corresponding user or voice file. For example, a voice file associated with a specific user can be selectively referenced, or a script or summary message associated with a specific voice file can be selectively referenced.

[0079] In one embodiment, the user request processor 330 may input an audio file into a pre-built voice recognition model to generate a script and a summary message, respectively. The user request processor 330 may generate both the script and the summary message from the audio file using only the voice recognition model. To this end, the voice recognition model is trained and built to receive the audio file as input data and generate output data including the script and the summary message. In this case, the voice recognition model may be implemented as a single model, or may include multiple sub-models as needed. For example, the voice recognition model may include a first model that generates a script from the audio file and a second model that generates a summary message from the script, with the output of the first model connected to the input of the second model.

[0080] In one embodiment, when the user request processor 330 receives a conversation message selection from a chat room participant in the chat room, it displays an interface related to the conversation message. That is, each user participating in the chat room can directly select a shared conversation message, and when the user request processor 330 detects each user's selection for each conversation message, it can provide functions related to the conversation message through separate interfaces. The interfaces basically include basic functions such as copying, deleting, and sharing messages.

[0081] In one embodiment, the user request processor 330 stores and manages summary messages or conversation messages in the database 150. The user request processor 330 assigns a unique identifier to each message and stores the date and time each message was created, audio file and script information associated with each message, and the message content (i.e., text) in the database 150. The user request processor 330 also stores and manages additional information, such as tags and categories, created in association with each message. The user request processor 330 provides management functions for managing each message, such as search, deletion, modification, sorting, and filtering.

[0082] In one embodiment, the user request processor 330 generates tags related to the summary message, associates them with the summary message, and provides a search function for the summary message through the tags. To generate tags, the user request processor 330 analyzes the content of each message to extract key keywords, etc., generates related tags based on the extracted information, and associates them with the message. Tag types include subject tags that indicate the subject of each message, entity tags that indicate people, places, and things that appear in each message, and description tags that briefly describe the content of each message. The user request processor 330 can also search for tagged messages by tag, filter search results using specific tags, and recommend messages based on tags that interest the user.

[0083] In one embodiment, the user request processing unit 330 provides at least one of an audio file, a script, and a summary message associated with a conversation message via a detail view page of the conversation message, and blocks other users from viewing the audio file, script, or summary message according to a privacy setting set by the user. The user request processing unit 330 provides a detail view function for each conversation message generated in association with an audio file and shared within a chat room, and provides a detail view page for displaying detailed content of the conversation message within the chat room.

[0084] For example, user A can share a text-format conversation message via a chat room through an audio file containing his / her own voice. Furthermore, users can set whether to make public the audio file, script, or summary message associated with the conversation message as the setting information for the conversation message. For example, if user A sets the audio file associated with conversation message M to private, user A can view all of the audio file, script, and summary message, while other user B can view only the script and summary message, excluding the private audio file.

[0085] In one embodiment, the user request processor 330 selectively provides a message translation function while providing detailed message content through a conversation message detail view page. The user request processor 330 provides a separate, independent interface for the detail view page. That is, the user request processor 330 provides the message translation function as one of various functions within the interface for the detail view page. To this end, the interface is implemented to operate in conjunction with a translation engine. A user can receive translations of conversation messages by selecting the message translation function. The user request processor 330 can provide each conversation message together with its translation through the interface and replace a specific conversation message with its translation before displaying it. Meanwhile, the user request processor 330 can also provide a similar function for summary messages.

[0086] In one embodiment, the user request processor 330 may assign a favorite function to each conversation message, store the favorite function, and provide a list of the conversation messages to which the favorite function has been assigned via a favorite page. Here, the favorite page corresponds to a dedicated interface that provides detailed operations and functions related to the favorite function. The favorite page may be provided within a chat room or provided via an independent interface from outside the chat room. For example, the favorite page may provide a list of conversation messages to which the favorite function has been assigned for each chat room or for all chat rooms.

[0087] Meanwhile, the favorite function corresponds to a function that helps a user to easily view and manage important or frequently used conversation messages by adding them to a separate list. That is, a user can add the favorite function to conversation messages created by the user as well as conversation messages created by other users shared through a chat room.

[0088] For example, the user request processor 330 may provide a favorites menu from a detail view page for each conversation message, and the user may select a favorites menu item to add the conversation message to a favorites list. The user request processor 330 stores the favorites list in association with the user account. The user request processor 330 may provide the favorites list to the user terminal 110 through various interfaces.

[0089] In addition, the user request processor 330 can sort the favorites list according to various criteria, such as most recently added, by title, or by date, and selectively remove conversation messages desired by the user from the favorites list. The user request processor 330 manages important conversation messages through separate favorites lists for each chat room or for all chat rooms. The user request processor 330 provides a function for sharing the favorites list with other users, a tag function for the favorites list, and notifies the user when a conversation message added to the favorites list is updated.

[0090] When the task recommendation unit 350 receives a task recommendation request related to the minutes from the user terminal 110, it generates recommended tasks related to the meeting content of the minutes through an artificial intelligence model and can provide a recommended task list including selection options for each recommended task to the user terminal 110. The task recommendation unit 350 receives a signal related to the task recommendation request from the user terminal 110 and starts a response operation in response to the reception of the task recommendation request.

[0091] In this case, the AI ​​model for recommending tasks may be implemented as a deep learning model that receives text related to the meeting content as input and generates recommended tasks as output, but is not limited to this. The AI ​​model is also constructed in conjunction with a task table that stores recommended tasks. In this case, the AI ​​model generates index information of the table as recommended task information. That is, the task recommendation unit 350 queries the task table based on the index information output by the AI ​​model to generate recommended tasks.

[0092] The task recommendation unit 350 may also generate a recommended task list including selection options for each recommended task and provide it to the user terminal 110. Here, the selection options correspond to functions that are activated according to a user's selection for each of one or more recommended tasks. For example, the selection options may be implemented as checkboxes. In other words, the recommended task list corresponds to a recommended task list and is represented as a set of pairs between recommended tasks and selection options. The user can individually select a recommended task through each selection option on the recommended task list. The task recommendation unit 350 generates the recommended task list in response to the task recommendation request and provides it to the user terminal 110, and the recommended task list is displayed through a dedicated interface implemented on the user terminal 110.

[0093] In one embodiment, if the minutes correspond to general minutes, the task recommendation unit 350 may convert the minutes to task minutes by adding a recommended task list to the minutes. Here, general minutes correspond to minutes that do not include recommended tasks, and task minutes correspond to minutes that include recommended tasks. That is, minutes are basically generated as general minutes, and if recommended tasks are generated in response to a task recommendation request from a user (e.g., a business participant), the recommended tasks are generated and managed as objects separate from the minutes. In this case, the task recommendation unit 350 adds the generated recommended task list to the minutes as needed, and as a result of adding the recommended task list to the minutes, the general minutes are converted to task minutes. The task recommendation unit 350 performs an operation of converting general minutes to task minutes upon receiving a user request or when a preset condition is met.

[0094] In one embodiment, the task recommendation unit 350 removes a specific recommended task from the recommended task list when a task is generated for a specific recommended task included in the task minutes. For example, if recommended tasks a and b are included in the task minutes A, and a task for recommended task b is generated by a user (e.g., a business participant), recommended task b is removed from the task minutes A. Thereafter, when the task minutes A is referenced, only recommended task a is referenced along with the task minutes A. Meanwhile, the task recommendation unit 350 can maintain the recommended task as it is even when a task related to the task minutes is generated. That is, in the above example, even when a task for recommended task b is generated, recommended tasks a and b are still included in the task minutes A, and recommended tasks a and b are also referenced when the task minutes A is referenced.

[0095] In one embodiment, the task recommendation unit 350 converts task minutes into general minutes when all recommended tasks are removed from the recommended task list. For example, if recommended tasks a and b are included in the minutes A, when a task for recommended task b is created by a user (e.g., a business participant), recommended task b is removed from the minutes A. Thereafter, when a task for recommended task a is created by the user, recommended task a is removed from the minutes A. As a result, if there are no recommended tasks included in the minutes A, the minutes A is automatically converted into general minutes.

[0096] In one embodiment, when a specific meeting minutes is a meeting minutes and a new recommended task list is generated in response to a task recommendation request, the task recommendation unit 350 updates the existing recommended task list included in the specific meeting minutes to the new recommended task list. The recommended tasks associated with the specific meeting minutes may change at the time of the task recommendation request due to changes in conditions, such as changes to the content of the meeting or the passage of time. When a new recommended task list is generated, the task recommendation unit 350 updates the existing recommended task list included in the meeting minutes to the new list. In other words, a user (e.g., a business participant) can request additional task recommendations even when recommended tasks already exist for a specific meeting minutes, and the task recommendation unit 350 generates new recommended tasks for the meeting minutes in response to the additional request.

[0097] When a user selection is input through a selection option for each recommendation task, the task management unit 370 generates a task related to the recommendation task. The user selects an activated selection option on a recommendation task list provided through an interface to request the generation of a task related to the recommendation task. The task management unit 370 starts a task generation operation related to the recommendation task for which the user selection is input through the selection option.

[0098] In one embodiment, the task management unit 370 sets the user who inputs a user selection for a recommended task selection option as the task assignor of the corresponding task, and sets the recommended task as the task content of the task. A task can be generated including various work-related items. For example, a task is generated including the task assignor who generated the task, task content, etc. The task management unit 370 automatically sets the user who requested the creation of the task as the task assignor, and automatically sets the recommended task as the task content.

[0099] In one embodiment, when a task is created, the task management unit 370 grants the user who requested the task creation the right to modify the task content. In other words, the task can be updated by the task creator by adding other items after the task is created. For example, the task creator can enter a task performer who will handle the task-related work after the task is created, or a deadline by which the task should be performed.

[0100] In one embodiment, when multiple selection options are selected by the user, the task management unit 370 sequentially generates tasks related to each of the corresponding recommendation tasks. When multiple recommendation tasks exist in one minutes, the task generator selects a selection option for each recommendation task and generates a task for each recommendation task. In this case, the corresponding tasks are sequentially generated according to the order in which the task generator selected the selection options. Furthermore, the task management unit 370 generates tasks by receiving task content input directly from the task generator in addition to the recommendation tasks, thereby sequentially generating multiple tasks related to one minutes.

[0101] In one embodiment, when a task related to a recommended task is generated, the task management unit 370 adds the remaining recommended tasks in the recommended task list to the specific minutes, converting the specific minutes into task minutes. Basically, when a recommended task list is provided in response to a task recommendation request, a business participant selects the recommended tasks and generates a task, and the remaining tasks for which no tasks are generated are deleted without being stored. Alternatively, when a task related to a recommended task is generated in conjunction with the task recommendation unit 350, the task management unit 370 may add the remaining recommended tasks in the recommended task list to the specific minutes, converting the specific minutes into task minutes. That is, when the task management unit 370 completes task generation, it transmits a task generation completion signal to the task recommendation unit 350, and the task recommendation unit 350 adds the recommended tasks in the recommended task list to the minutes and converts the general minutes into task minutes.

[0102] The control unit (not shown in FIG. 3) controls the overall operation of the task recommendation device 130 and manages the control flow or data flow between the user request receiving unit 310, the user request processing unit 330, the task recommendation unit 350, and the task management unit 370.

[0103] FIG. 4 is a flowchart illustrating the artificial intelligence-based task recommendation method according to the present invention.

[0104] 4, the task recommendation device 130 receives a user request for generating or querying minutes from the user terminal 110 via the processor 210 (step S410). The task recommendation device 130 generates minutes or generates a minutes list including the minutes in response to the user request via the processor 210 (step S430).

[0105] In addition, when the task recommendation device 130 receives a task recommendation request related to minutes from the user terminal 110 via the processor 210, it generates recommended tasks related to the meeting content of the minutes via an artificial intelligence model and provides the user terminal 110 with a recommended task list including selection options for each recommended task (steps S450 and S470).

[0106] In one embodiment, when a user selects a recommended task through a selection option for each recommended task, the task recommendation device 130 generates a task related to the recommended task. In this case, the task generation operation is performed via the task management unit 370 of the processor 210.

[0107] FIG. 5 is a diagram illustrating an embodiment of the minutes according to the present invention.

[0108] 5, the task recommendation device 130 queries and provides minutes 510 that record meeting content 550 between business participants in response to a minutes query request. In this case, the minutes 510 are manually generated by business participants or automatically generated by an artificial intelligence model.

[0109] 5, the minutes 510 may include various items, such as a meeting content 550 automatically summarized by the AI ​​model and a recommended task 560 recommended by the AI ​​model. For example, the minutes 510 may include a creator 520, a meeting date and time 530, a storage location 540, the meeting content 550, and the recommended task 560.

[0110] The creator 520 corresponds to the user who created the minutes, and corresponds to one of the business participants who attended the meeting. The creator information is automatically determined in response to a request to create minutes. The meeting date and time 530 includes the date, day of the week, time, etc., when the meeting took place, and is automatically determined based on the time when the request to create minutes was made.

[0111] The storage location 540 corresponds to a location where the minutes 510 are generated and stored. For example, the storage location 540 corresponds to information about the space (e.g., folder name) where the minutes are actually stored in the user terminal 110 or the task recommendation device 130, and in some cases, is represented by link information that allows access to the minutes 510.

[0112] In addition, the meeting content 550 corresponds to a summary of the meeting content automatically summarized by an AI model, and corresponds to text information generated through voice recognition from a dialogue recording file that records the meeting content. The recommended task 560 corresponds to task information automatically recommended by an AI model, and includes business information related to the meeting content. The recommended task 560 is generated including one or more detailed tasks 570 and selection options 580. The detailed task 570 expresses the task title, purpose, etc. in simple text. The selection options 580 are generated independently for each detailed task 570, and are implemented in various ways, such as checkboxes and radio buttons.

[0113] The minutes 510 may include the name of the meeting, information about the meeting participants, etc., and may also include various minutes menus. For example, the minutes menu may include a task creation reservation menu, a shared link creation menu, and a file, image, and image upload menu. In this case, the minutes menu is provided together with the minutes when the minutes are viewed after they are created.

[0114] The task creation reservation menu corresponds to a function that allows a business participant with access rights to reserve task creation based on a specific point in time after the minutes have been created. In other words, when task creation is reserved for time A, a notification or reminder for task creation is provided to the business participant who made the reservation at time A. The sharing link creation menu corresponds to a function that generates a sharing link that allows direct access to the minutes from outside as a link for sharing the minutes. The upload menu corresponds to a function that allows files and images related to the meeting content to be added to the minutes after they have been created.

[0115] FIG. 6 is a diagram illustrating an embodiment of a process for generating minutes according to the present invention.

[0116] 6, the task recommendation device 130 generates a summary and a recommended task for the meeting content through an artificial intelligence model 630. The task recommendation device 130 receives a dialogue recording file of the meeting content between business participants along with a user request for generating minutes, and converts the dialogue recording file into text to generate a dialogue text 610 for the meeting content.

[0117] The task recommendation device 130 provides the dialogue text 610 as input to the artificial intelligence model 630 and generates a summary sentence and a recommended task from the output of the artificial intelligence model 630. At this time, the artificial intelligence model is pre-built based on a language model that receives input related to the text and generates output related to the text. The output of the artificial intelligence model is generated in the form of an output vector 650 having a dimension of a specific size, and the task recommendation device 130 generates a summary sentence and one or more tasks using each component data of the output vector 650. Furthermore, the input of the artificial intelligence model can also be converted into vector-form data extracted from the dialogue text 610.

[0118] FIG. 7 is a diagram illustrating an embodiment of a process for generating a dialogue message according to the present invention.

[0119] 7, the task recommendation device 130 receives a voice file 710 of user A recorded on the user terminal 110. The task recommendation device 130 recognizes the voice of the voice file 710 and generates a script converted into text and a summary message. The summary message is generated based on the script and is generated through a pre-built voice recognition model 730. That is, the voice recognition model 730 is designed to receive the script as input and output a summary message that summarizes the content of the corresponding text. The task recommendation device 130 displays the summary message as a conversation message in a chat room 750 related to the user's selection.

[0120] In addition, the task recommendation device 130 stores and manages the script, summary message, and conversation message associated with the voice file 710 of user A in the database 150. When a conversation message is selected in the chat room 750, the task recommendation device 130 queries the database 150 and provides the voice file, script, summary message, etc. associated with the corresponding conversation message.

[0121] FIG. 8 is a diagram illustrating an embodiment of a process for providing related functions in a chat room according to the present invention.

[0122] 8, when the task recommendation device 130 receives a selection of a conversation message from a chat room participant in a chat room, it displays an interface related to the conversation message. In this case, the interface includes functions related to the conversation message. For example, functions such as (1) listening to an audio file, (2) script view, (3) message view, and (4) task creation are provided through the interface, and the user can select a specific function to access the corresponding content. The task recommendation device 130 accesses the database 150 to query data related to the user's selection and then provides the data via the user terminal 110.

[0123] In addition, the task recommendation device 130 restricts the provision of an interface to a user who does not have access rights to the conversation message even if the user is participating in the chat room. That is, when a conversation message is selected by a user who does not have access rights, the task recommendation device 130 does not perform an interface providing operation according to the message selection. To this end, when the task recommendation device 130 displays a conversation message related to a summary message through a chat room, it sets access rights to the conversation message.

[0124] That is, when the task recommendation device 130 displays a summary message extracted from a user's voice file as a conversation message in a chat room, the task recommendation device 130 grants access rights preset by the user. For example, when a user records his or her own voice and shares it as a conversation message in a chat room, the device 130 can set the device 130 to restrict access to other users in the chat room, and the task recommendation device 130 can revoke the access rights of other users while displaying the conversation message in the chat room.

[0125] FIG. 9 is a diagram illustrating one embodiment of a task creation process according to the present invention.

[0126] 9, the task recommendation device 130 classifies and queries general minutes or task minutes 910 depending on whether the minutes contain recommended tasks, and generates a query result. Unlike general minutes, task minutes 910 include a list of recommended tasks 970 related to the content of meetings in the minutes. That is, a business participant can select a specific minute from the minutes list provided as a result of querying the minutes to check detailed items, and can select some of the recommended tasks included in the minutes to generate related tasks. Here, a task corresponds to the smallest unit of work related to a project.

[0127] Specifically, the detailed items of the minutes provided to the business participant include a summary of the meeting content and recommended tasks related to the meeting content, and the recommended tasks include individually selectable selection options 930. In this case, the task recommendation device 130 changes the activation state of each recommended task depending on the business participant and provides it. For example, if the business participant has normal authority or the recommended task has high priority, the task recommendation device 130 activates and provides the selection option 930. In other words, the activation state of the selection option 930 corresponds to a state selectable by the business participant.

[0128] In Fig. 9, when task #1 and task #2 are selected by the business participant (USER1), the corresponding selection option 930 is converted to the "selected" state, and the task recommendation device 130 generates tasks (Task 1 and Task 2) matched to the corresponding tasks. In this case, task 2 (Task 2) corresponds to task 950 generated corresponding to task #2 among the recommended tasks. The corresponding task 950 corresponds to a temporary task with some fields left blank.

[0129] In this case, when the corresponding task 950 is created, the task instructor is automatically set to "USER1" who requested the creation of the task, and the task content is automatically set to the content of "Job #2" selected by USER1. In addition, the corresponding task 950 is created and saved with information about the remaining items other than the task instructor and task content left blank, and then the corresponding items are entered by the business participant (USER1).

[0130] Meanwhile, the corresponding task 950 is generated and stored with all items entered through additional input by the business participant, and of course, it is generated and stored with some items left blank depending on the selective input by the business participant.

[0131] FIG. 10 is a diagram illustrating an embodiment of a task modification process according to the present invention.

[0132] 10, the task recommendation device 130 may generate a task 950 according to a selection by a business participant for each recommended task included in the minutes. In this case, the task recommendation device 130 grants task modification authority to the business participant who generated the task 950.

[0133] In the case of Fig. 10, task 950 is generated with the task instructor set to the task participant "USER1" who requested task generation for the recommended "Task #2" in Fig. 9, and the content of the selected "Task #2" set to the task content. After that, the task recommendation device 130 receives input for blank fields from the task participant "USER1" who has the authority to modify via the input interfaces 1010 and 1030, and updates the corresponding task 950.

[0134] For example, the task performer is set to another task participant "USER4" selected by the task participant "USER1" on the first input interface 1010, and the task deadline is set to "00.05.05" input by the task participant "USER1" on the second input interface 1030. That is, the task recommendation device 130 updates the corresponding task 950 when the remaining information is input by the task participant.

[0135] FIG. 11 is a diagram illustrating the general minutes and the working minutes according to the present invention.

[0136] 11, the task recommendation device 130 can convert a general minutes 1110 into a task minutes 1150 by adding a recommended task list 1130 to the general minutes 1110. The general minutes 1110 correspond to minutes that do not include recommended tasks, while the task minutes 1150 correspond to minutes that include recommended tasks. That is, the task recommendation device 130 basically generates and stores the general minutes 1110 that do not include recommended tasks. If a business participant requests or if a specific condition is met, the task recommendation device 130 converts the general minutes 1110 into a task minutes 1150 by adding a recommended task list 1130 to the general minutes 1110. In this case, the business participant can also check recommended tasks related to the minutes through the query results for the minutes, and can easily create tasks related to the recommended tasks by selecting the recommended tasks as needed.

[0137] FIG. 12 is a diagram illustrating an embodiment of a recommended task list updating process according to the present invention.

[0138] 12, when a task is generated in response to a business participant's selection for a specific recommended task on the recommended task list 1210 included in the task minutes, the recommended task device 130 removes the specific recommended task from the recommended task list 1210. For example, in FIG. 12, when the recommended task list 1210 includes task #1, task #2, task #3, etc., the business participant "USER1" selects the selection option for task #1 to generate the first task 1231 for task #1. When the generation of the first task 1231 for task #1 is completed, the recommended task device 130 removes task #1 from the recommended task list 1210.

[0139] Furthermore, the business participant "USER1" selects the selection option for task #2 to generate a second task 1233 for task #2. When the generation of the second task 1233 for task #2 is completed, the recommended task device 130 removes task #2 from the recommended task list 1210. If all recommended tasks are removed from the recommended task list 1210 by sequential task generation for the remaining recommended tasks, including task #3, the recommended task device 130 converts the task minutes into general minutes.

[0140] FIG. 13 is a diagram illustrating a process of sharing a conversation message related to a user's voice in a chat room according to the present invention.

[0141] 13 , the task recommendation device 130 shares a dialogue message 1310 generated from a user's voice file via a chat room 1300. In one embodiment, the dialogue message 1310 generated as a result of recognizing the user's voice is displayed as a "voice memo" in the chat room 1300. That is, the voice memo includes the result of converting the user's voice into text and summarizing it, and is displayed in the chat room 1300 in the form of a dialogue message 1310.

[0142] Furthermore, the task recommendation device 130 may provide a detailed view page of the interactive message 1310 while displaying the interactive message 1310 via the chat room 1300. To this end, the task recommendation device 130 provides a detailed view menu 1330 together with the interactive message 1310.

[0143] That is, by selecting (e.g., clicking) the detail view menu 1330 of the conversation message 1310, the user can access a detail view page that provides details of the conversation message 1310. For example, the detail view page of the conversation message 1310 provides at least one of an audio file, a script, and a summary message related to the conversation message 1310. In this case, the audio file, script, or summary message provided via the detail view page may be restricted from other users' access depending on the privacy setting set by the user who created the conversation message 1310.

[0144] FIG. 14 is a diagram illustrating one embodiment of a detailed view page of an interactive message according to the present invention.

[0145] 14, the task recommendation device 130 may provide a detailed view page 1400 of an interaction message. In one embodiment, the interaction message generated based on the user's voice is defined as a voice memo, and the following description will focus on the voice memo.

[0146] More specifically, the voice memo detail view page 1400 is accessed by a user selecting a conversation message in a chat room. The detail view page 1400 provides details related to the voice memo. For example, the detail view page 1400 displays the title of the voice memo (e.g., Voice Memo #1), the creation date and time, the creator, etc. Additionally, the detail view page 1400 displays the user's audio file 1410, summary message 1430, and script 1450 associated with the voice memo.

[0147] A user can select an audio file 1410 displayed on the details view page 1400, download the file itself, and check the entire contents of the summary message 1430 and script 1450. If the total length of the script 1450 is long, the script 1450 is converted into a file format such as "Voice Memo Recording.txt" and attached to the details view page 1400. Furthermore, if the voice memo has been set to private by the creator, other users without access rights are restricted from downloading the audio file 1410 that has been set to private, from viewing the summary message 1430 that has been set to private, and from downloading attachments related to the script 1450 that has been set to private.

[0148] Although the present invention has been described above with reference to preferred embodiments, it will be understood that those skilled in the art can make various modifications to the present invention without departing from the spirit and scope of the present invention. [Explanation of symbols]

[0149] 100: Job recommendation system 110: User terminal 130: Duty recommendation device 150: Database 210: Processor 510: Minutes 610: Dialogue text 630: Artificial Intelligence Model 650: Output vector 730: Speech recognition model 750, 1300: Chat room 910: Minutes of Service 930:Selection options 950: Task 970: Recommended task list 1010: First input interface 1030: Second input interface 1110: General minutes 1130, 1210: Recommended Work List 1150:Minutes of Service 1231: First Task 1233: Second Task

Claims

1. Memory and a processor electrically connected to the memory; The processor receiving a user request for generating or querying minutes from a user terminal; generating the minutes in response to the user request or generating a minutes list including the minutes; When a task recommendation request for the minutes is received from the user terminal, the system is configured to generate recommended tasks related to the meeting content of the minutes through an artificial intelligence model, and provide the user terminal with a recommended task list including selection options for each recommended task; The processor: When a user selects a task via the recommended task selection options, the AI-based task recommendation device generates a task related to the recommended task.

2. The processor: receiving, from the user terminal, a dialogue recording file recording the dialogue between business participants regarding the contents of the meeting, together with a user request for generating the minutes; converting the dialogue recording file into text to generate dialogue text relating to the content of the conference; The AI-based task recommendation device according to claim 1 , wherein a meeting minutes including a summary of the dialogue text and selection options for each of the recommended tasks is generated.

3. The processor: The AI-based task recommendation device of claim 2, wherein the dialogue recording file is transmitted to an external STT (Speech-To-Text) server, and the dialogue text is received from the STT server.

4. The processor: The AI-based task recommendation device of claim 1, wherein the minutes list is generated in accordance with a query request from any one of the business participants on a chat room in which the business participants are participating or a conference map for managing minutes.

5. The processor: The artificial intelligence-based task recommendation device according to claim 1, characterized in that if the minutes correspond to general minutes, the recommended task list is added to the minutes, and the minutes are converted into task minutes.

6. The processor: The artificial intelligence-based task recommendation device of claim 5, wherein when a task is generated for a specific recommended task included in the task minutes, the specific recommended task is removed from the recommended task list.

7. The processor: The AI-based task recommendation device according to claim 6, wherein when all the recommended tasks are removed from the recommended task list, the task minutes are converted into the general minutes.

8. The processor: The AI-based task recommendation device according to claim 1, characterized in that the user who inputs the user selection is set as the task instructor of the task, and the recommended task is set as the task content of the task.

9. The processor: The AI-based task recommendation device of claim 1, wherein if a plurality of selection options are selected by the user who inputs the user selection, tasks relating to each of the recommended tasks are generated sequentially.

10. The processor: receiving a user voice file associated with the conference content from the user terminal; Recognizing the speech in the audio file to generate a transcribed script and summary message; The AI-based task recommendation device according to claim 1, wherein the summary message is displayed as a conversation message in a chat room selected by the user.

11. The processor: The AI-based task recommendation device according to claim 10, wherein the voice file is generated by receiving the user's voice in real time, the voice being input from the user terminal in a streaming manner.

12. The processor: The AI-based task recommendation device of claim 10, wherein the audio file is input into a pre-built speech recognition model to generate the script and the summary message, respectively.

13. The processor: generating and binding a tag associated with the summary message to the summary message; The artificial intelligence-based task recommendation device according to claim 10, wherein the device provides a query function for the summary message through the tag.

14. The processor: A favorite function is assigned to each of the conversation messages and stored. The AI-based task recommendation device according to claim 10, further comprising: providing a list of dialogue messages to which the favorite function has been assigned via a favorites page.

15. Memory and A method performed on a task recommendation device including a processor electrically connected to the memory, The method is executed by the processor, receiving a user request for generating or viewing minutes from a user terminal; generating the minutes in response to the user request or generating a minutes list including the minutes; When receiving a task recommendation request for the minutes from the user terminal, generating recommended tasks related to the meeting content of the minutes through an artificial intelligence model, and providing a recommended task list including selection options for each recommended task to the user terminal; The method is an artificial intelligence-based task recommendation method, including the step of generating, by the processor, a task related to the recommended task when a user selection is input via the recommended task-specific selection options.

Images