Method and electronic device for providing coaching on basis of context of user

Abstract

Various embodiments of the present invention may comprise: a display (160); a memory (130) for storing instructions; and a processor (120). The instructions, when executed by the processor, may cause the electronic device to: execute an application associated with coaching; acquire detected progress state information and / or coaching history information stored in the executed application; identify a context of a user on the basis of the coaching history information and / or the progress state information; generate, on the basis of the context of the user, a prompt for determining a coaching characteristic; and provide a coaching guide corresponding to the generated coaching characteristic through generative AI on the basis of the prompt. Various embodiments are possible.

Description

Method for providing coaching based on user context and the electronic device thereof

[0001] Various embodiments of the present disclosure disclose a method for providing coaching based on the user's context and an electronic device thereof.

[0002] With the development of digital technology, various types of electronic devices such as mobile communication terminals, PDAs (personal digital assistants), electronic notebooks, smartphones, tablet PCs (personal computers), or wearable devices are widely used. To support and enhance the functionality of these electronic devices, the hardware and / or software parts of the devices are continuously being improved.

[0003] For example, electronic devices can provide various services by connecting to external devices (or external input / output devices) such as laptops, earphones (or headphones), and AR (augmented reality) (or VR (virtual reality)) glasses through short-range wireless communication technologies such as Bluetooth. In addition, wearable devices that can be worn on a user's body can acquire the user's biometric information to provide health information, acquire various exercise information (e.g., walking, running) to help the user manage their health, or provide coaching services.

[0004] Coaching services can provide guidance messages tailored to a user's current situation based on a configured algorithm. For example, if a user's current situation is identical, the coaching service may provide the same guidance message according to the algorithm. However, considering the user's current circumstances, it may be necessary to take their tendencies into greater consideration and observe them sensitively to act as a personalized one-on-one coach tailored to their changing behavior.

[0005] In one embodiment, a method and apparatus may be disclosed for identifying a user's context (situation, tendency, state) based on coaching history information or / and progress status information, determining coaching characteristics based on the user's context, and providing a coaching guide unique to the user that matches the user's context and coaching characteristics through generative AI.

[0006] An electronic device (101) according to one embodiment of the present disclosure comprises a display (160), a memory (130) for storing instructions; and a processor (120). When the instructions are executed by the processor, the electronic device executes an application associated with coaching, obtains coaching history information or / and detected progress status information stored in the executed application, identifies a user's context based on the coaching history information or / and the progress status information, generates a prompt for determining a coaching characteristic based on the user's context, and provides a coaching guide corresponding to the coaching characteristic generated based on the prompt through a generative AI.

[0007] A method of operation of an electronic device (101) according to one embodiment of the present disclosure may include: executing an application associated with coaching; obtaining coaching history information stored in the executed application and / or detected progress status information; identifying a user's context based on the coaching history information and / or the progress status information; generating a prompt to determine coaching characteristics based on the user's context; and providing a coaching guide corresponding to the coaching characteristics generated based on the prompt through a generative AI.

[0008] According to one embodiment, coaching guidance can be provided to the user with a tone of voice and facial expression suitable for the user's current situation, taking into account the user's disposition, health condition, or exercise history (evaluation of performance level).

[0009] According to one embodiment, whenever progress status information is obtained, the user's context is identified, and by changing the parameters of the coaching characteristics according to the identified user's context, the coaching characteristics can be variably changed according to the user's current state to provide a coaching guide suitable for the user's current situation.

[0010] According to one embodiment, coaching characteristics that reflect the user's needs can be determined by recommending coaching characteristics based on coaching history information and providing a user interface for determining parameters of said coaching characteristics.

[0011] According to one embodiment, if a goal set by a user is achieved based on progress status information obtained in real time, a coaching guide can be provided to the user with coaching characteristics different from the previous coaching characteristics.

[0012] FIG. 1 is a block diagram of an electronic device in a network environment according to one embodiment.

[0013] FIG. 2 is a block diagram illustrating a framework of an electronic device according to one embodiment.

[0014] FIG. 3 is a block diagram of a generative AI system according to one embodiment.

[0015] FIG. 4 is a diagram illustrating an example of providing a coaching guide based on the user's context in an electronic device according to one embodiment.

[0016] FIG. 5 is a flowchart illustrating a method of operation between an electronic device and a server according to one embodiment.

[0017] FIG. 6 is a flowchart illustrating the operation method of an electronic device according to one embodiment.

[0018] FIG. 7a is a drawing illustrating an example of providing a user interface associated with coaching characteristics in an electronic device according to one embodiment.

[0019] FIG. 7b is a diagram illustrating an example of providing a coaching guide corresponding to coaching characteristics in an electronic device according to one embodiment.

[0020] FIG. 8 is a flowchart illustrating a method of providing a coaching guide by changing coaching characteristics in an electronic device according to one embodiment.

[0021] FIG. 9a is a diagram illustrating an example in which coaching characteristics are provided differently according to coaching history information in an electronic device according to one embodiment.

[0022] FIG. 9b is a drawing illustrating an example of changing the parameters of a coaching characteristic in an electronic device according to one embodiment.

[0023] FIG. 9c is a diagram illustrating an example of providing a coaching guide corresponding to coaching characteristics in an electronic device according to one embodiment.

[0024] FIG. 10 is a diagram illustrating an example of providing a coaching guide corresponding to the coaching characteristics of exercise in an electronic device according to one embodiment.

[0025] FIGS. 11a and FIGS. 11b are drawings illustrating an example of providing a coaching guide corresponding to the coaching characteristics of a study in an electronic device according to one embodiment.

[0026] FIG. 12 is a flowchart illustrating a method of changing and providing a coaching guide according to progress status information in an electronic device according to one embodiment.

[0027] FIG. 13 is a diagram illustrating an example of an electronic device according to one embodiment providing a coaching guide differently depending on the user's context.

[0028] FIG. 1 is a block diagram of an electronic device (101) in a network environment (100) according to various embodiments.

[0029] Referring to FIG. 1, in a network environment (100), an electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or with at least one of an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through a server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0030] The processor (120) can control at least one other component (e.g., hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., program (140)), and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., sensor module (176) or communication module (190)) in volatile memory (132), process the commands or data stored in volatile memory (132), and store the resulting data in non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., central processing unit or application processor) or an auxiliary processor (123) that can operate independently or together with it (e.g., graphics processing unit, neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, if the electronic device (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0031] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (108)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0032] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, software (e.g., program (140)) and input data or output data for related commands. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0033] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0034] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0035] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0036] The display module (160) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0037] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0038] The sensor module (176) can detect the operating state of the electronic device (101) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (176) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0039] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0040] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0041] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0042] The camera module (180) can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0043] The power management module (188) can manage the power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0044] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0045] The communication module (190) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0046] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) can support a Peak data rate (e.g., 20 Gbps or more) for realizing eMBB, loss coverage (e.g., 164 dB or less) for realizing mMTC, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for realizing URLLC.

[0047] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (197).

[0048] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0049] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0050] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0051] FIG. 2 is a block diagram (200) illustrating a framework of an electronic device according to one embodiment.

[0052] Referring to FIG. 2, the program (140) may include an operating system (142), middleware (144), or an application (146) executable on the operating system (142) for controlling one or more resources of the electronic device (101). The operating system (142) is, for example, Android TM , iOS TM , Windows TM , Symbian TM , Tizen TM , or Bada TM It may include. At least some of the programs (140) may be preloaded into the electronic device (101) at manufacturing time, for example, or downloaded or updated from an external electronic device (e.g., electronic device (102 or 104), or server (108)) when used by a user.

[0053] The operating system (142) can control the management (e.g., allocation or reclamation) of one or more system resources (e.g., processes, memory, or power) of the electronic device (101). The operating system (142) may additionally or substantially include one or more driver programs for driving other hardware devices of the electronic device (101), e.g., an input module (150), an audio output module (155), a display module (160), an audio module (170), a sensor module (176), an interface (177), a haptic module (179), a camera module (180), a power management module (188), a battery (189), a communication module (190), a subscriber identification module (196), or an antenna module (197).

[0054] Middleware (144) may provide various functions to an application (146) so that functions or information provided from one or more resources of an electronic device (101) can be used by the application (146). Middleware (144) may include, for example, an application manager (201), a window manager (203), a multimedia manager (205), a resource manager (207), a power manager (209), a database manager (211), a package manager (213), a connectivity manager (215), a notification manager (217), a location manager (219), a graphics manager (221), a security manager (223), a call manager (225), a voice recognition manager (227), or an AI client (299).

[0055] The application manager (201) can, for example, manage the life cycle of the application (146). The window manager (203) can, for example, manage one or more GUI resources used on the screen. The multimedia manager (205) can, for example, identify one or more formats required for the playback of media files and perform encoding or decoding of the corresponding media files among the media files using a codec that matches the selected corresponding format. The resource manager (207) can, for example, manage the source code of the application (146) or the memory space of the memory (130). The power manager (209) can, for example, manage the capacity, temperature, or power of the battery (189) and, using the relevant information, determine or provide relevant information required for the operation of the electronic device (101). According to one embodiment, the power manager (209) can interact with the BIOS (basic input / output system) (not shown) of the electronic device (101).

[0056] The database manager (211) can, for example, create, search, or modify a database to be used by the application (146). The package manager (213) can, for example, manage the installation or update of the application distributed in the form of a package file. The connectivity manager (215) can, for example, manage a wireless or direct connection between the electronic device (101) and an external electronic device. The notification manager (217) can, for example, provide a function to notify the user of the occurrence of a specified event (e.g., an incoming call, a message, or an alarm). The location manager (219) can, for example, manage location information of the electronic device (101). The graphics manager (221) can, for example, manage one or more graphic effects or related user interfaces to be provided to the user.

[0057] The security manager (223) may, for example, provide system security or user authentication. The telephony manager (225) may, for example, manage voice call functions or video call functions provided by the electronic device (101). The voice recognition manager (227) may, for example, transmit user voice data to the server (108) and receive from the server (108) a command corresponding to a function to be performed on the electronic device (101) based on at least part of the voice data, or text data converted based on at least part of the voice data. According to one embodiment, the middleware (244) may dynamically delete some existing components or add new components. According to one embodiment, at least part of the middleware (144) may be included as part of the operating system (142) or implemented as separate software different from the operating system (142).

[0058] The AI ​​client (299) can identify the user's context based on coaching history information stored in a coaching-related application (e.g., a health application (279)) and / or detected progress status information, generate a prompt to determine coaching characteristics based on the user's context, and provide a coaching guide corresponding to the coaching characteristics generated based on the prompt through a generative AI. The AI ​​client (299) can provide the coaching guide to the user with a tone of voice and facial expression suitable for the user's current situation, taking into account the user's disposition, health status, or exercise history (performance evaluation). The AI ​​client (299) can change the parameters of the coaching characteristics according to the progress status information. If the goal set by the user in the application is achieved, the AI ​​client (299) can request the generative AI to provide the coaching guide to the user with coaching characteristics different from the previous coaching characteristics.

[0059] The application (146) may include, for example, a home (251), a dialer (253), an SMS / MMS (255), an IM (instant message) (257), a browser (259), a camera (261), an alarm (263), a contact (265), a voice recognition (267), an email (269), a calendar (271), a media player (273), an album (275), a watch (277), a health (279) (e.g., measuring biometric information such as exercise volume or blood sugar), or an environmental information (281) (e.g., measuring atmospheric pressure, humidity, or temperature information). According to one embodiment, the application (146) may further include an information exchange application (not shown) capable of supporting information exchange between the electronic device (101) and an external electronic device. The information exchange application may include, for example, a notification relay application configured to transmit information (e.g., a call, a message, or an alarm) designated to an external electronic device, or a device management application configured to manage the external electronic device. The notification relay application may transmit notification information corresponding to a designated event (e.g., receiving mail) generated in another application of the electronic device (101) (e.g., an email application (269)) to the external electronic device. Additionally or alternatively, the notification relay application may receive notification information from the external electronic device and provide it to the user of the electronic device (101).

[0060] A device management application can control the power (e.g., turn-on or turn-off) or function (e.g., brightness, resolution, or focus) of an external electronic device or a part of its components (e.g., a display module or camera module 1 of the external electronic device) that communicates with the electronic device (101). The device management application can additionally or substantially support the installation, deletion, or updating of applications running on the external electronic device.

[0061] FIG. 3 is a block diagram of a generative AI system according to one embodiment.

[0062] Referring to FIG. 3, a generative AI (artificial intelligence) system (301) according to one embodiment may include a user interface (310), a database (320), an application / service component (330), an AI (artificial intelligence) framework (350), and a generative AI model (370). According to one embodiment, the generative AI system may be included in an electronic device (e.g., the electronic device (101) of FIG. 1) (e.g., an AI engine) or in an intelligent server (e.g., an external server (e.g., the server (108) of FIG. 1).

[0063] The user interface (310) can receive user queries. User queries can be in the form of natural language, images, and videos. Additionally, context information may be transmitted along with the user query. As another example, user queries can be non-natural language inputs that do not generate natural language, such as design requests or modifications. Additionally, a mixed form of the natural language, images, sounds, and context information described above is also possible. Furthermore, the user interface (310) can output results from a generative artificial intelligence system to the user. The output can be in the form of natural language or specific content, and it can also be provided in the form of actions requested by the user.

[0064] The AI ​​framework (350) can receive a user query and coordinate and control each component necessary to perform the user's intent. The AI ​​framework (350) may include a prompt design component (351), an APIs / Plugins Management component (353), and an output modification component (355).

[0065] User queries or actions entered in the user interface (310) can be transmitted to a prompt design component (351). The prompt design component (351) can be used to generate prompts suitable for input into a large language model (LLM) or large multimodal models. The prompt design component (351) may be an AI component that uses machine learning algorithms or neural networks to develop better prompts over time. The prompt design component (351) can generate prompts by accessing a knowledge component containing user preference data, a prompt library, and prompt examples, and transmit them to a large language model (LLM) or large multimodal model (LMM).

[0066] The application / plugin management component (353) can perform the role of communicating with external information when there is a request for additional information when transmitting user input as input to a generative model. The application / plugin management component (353) establishes a channel to communicate with the outside of the AI ​​Interface through an application programming interface (API), thereby enabling access to various data sources. Additionally, the application / plugin management component (353) can request an action through the API if the application or service needs to perform an action that ultimately executes a user query rather than an intermediate result. Information obtained from the outside can be transmitted as input to the generative model along with the user input.

[0067] The output modification component (355) can fine-tune the output of the generative model. For example, the output modification component (355) can verify whether the content generated through the language model (LLM) or large-scale multimodal model (LMM) is irrelevant, contains biased content, or contains harmful content. Additionally, the output modification component (355) can determine the extent to which the output matches what the user wants and, if additional processing is required, proceed with that process. Furthermore, the output modification component (355) can configure and provide hints to the user to avoid unwanted output.

[0068] A generative AI model (370) generally refers to an artificial intelligence neural network that generates new forms of data based on user input information. Representative models that generate images include GANs (generative adversarial networks) and VAEs (variational autoencoders), and recently, Diffusion-based generative models using VAEs and Transformer structures are referred to as generative models. Additionally, language models are models trained to output the statistically most appropriate output value based on input values, and representative examples include models such as CHAT-GPT 3 and CHAT-GPT 4. Furthermore, a generative AI model (370) can recognize various forms of data input, such as text, images, and voice, and generate new data corresponding to them.

[0069] FIG. 4 is a diagram illustrating an example of providing a coaching guide based on the user's context in an electronic device according to one embodiment.

[0070] Referring to FIG. 4, an electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can identify the user's context based on coaching history information stored in the executed application and / or detected progress status information when a coaching-related application is executed, generate a prompt to determine a coaching characteristic based on the user's context, and provide a coaching guide (e.g., natural language) corresponding to the coaching characteristic generated based on the prompt through a generative AI (e.g., AI client (229)). The electronic device (101) can execute a coaching-related application (e.g., health application, study application) based on user input and obtain coaching history information and / or detected progress status information stored in the executed application. The generative AI may be the generative AI system (301) of FIG. 3 and may be included in an electronic device (101) (e.g., AI engine) or in an intelligent server (e.g., an external server (e.g., the server (108) of FIG. 1). The electronic device (101) initially generates and receives coaching characteristics through the server (108), and can continuously maintain and manage the coaching characteristics by a character management module inside the electronic device (101).

[0071] For example, if the application associated with the coaching is a health application, the coaching history information may be a coaching history related to the user's health or exercise. The progress information measured in the health application may include heart rate, body temperature, type of exercise, exercise distance, or exercise time. The progress information may be obtained based on at least one of acceleration, angular velocity, and rotation information detected (or measured) through a sensor module of the electronic device (101) (e.g., sensor module (176) of FIG. 1). Alternatively, the progress information may be obtained based on at least one of acceleration, angular velocity, and rotation information detected (or measured) by an external device connected to the electronic device (101).

[0072] If the application associated with the above coaching is a study application, the above coaching history information may be the coaching history related to the user's study. The progress status information measured in the above study application may be the date of the most recent study, the study time, or the amount of study. The above coaching characteristic may represent the personality (or individuality) of the coach (e.g., virtual assistant, AI assistant) providing the above coaching guide. For example, the above coaching characteristic may include at least one of the coach's character, tone of voice, style, frequency, speed, or facial expression. The coach's character generated according to the above coaching characteristic may be one or more. The electronic device (101) may provide the coaching guide to the user with a tone of voice and facial expression suitable for the user's current situation, taking into account the user's disposition, health condition, or exercise history (performance evaluation).

[0073] The electronic device (101) can identify the user's context (e.g., situation, disposition, state) based on the coaching history information or / and the progress status information, and determine a first coaching characteristic (401) or a second coaching characteristic (403) based on the user's context. The first coaching characteristic (401) or the second coaching characteristic (403) can be determined by a generative AI based on the user's context. To this end, the electronic device (101) can generate a prompt for determining the coaching characteristic based on the user's context. The prompt may include the coaching history information or / and the progress status information. Alternatively, if the coaching history information includes a previous coaching characteristic, the previous coaching characteristic may also be included in the prompt.

[0074] The first coaching characteristic (401) is authoritative and analytical, and the coach's character image may be male, with an authoritative tone and style, frequent coaching, a medium speed, and a stern expression. The electronic device (101) can determine the first coaching characteristic (401) through generative AI. Referring to the first user interface (410), the electronic device (101) can generate a first prompt (411) based on the first coaching characteristic (401) and provide a first coaching guide (413) based on the first prompt (411) through generative AI. That is, the coaching characteristic may change depending on the user's context. The first coaching guide (413) may be provided frequently with a stern expression and a male character with an authoritative tone and style, in accordance with the first coaching characteristic (401).

[0075] The second coaching characteristic (403) is warm and persuasive, and the character image of the coach is female, with a warm tone and style, coaching frequency infrequently, coaching speed slow, and a soft facial expression. The electronic device (101) can determine the second coaching characteristic (403) through generative AI. Referring to the second user interface (430), the electronic device (101) can generate a second prompt (431) based on the second coaching characteristic (403) and provide a second coaching guide (433) based on the second prompt (431) through generative AI. The second coaching guide (433) can be provided occasionally with a female character with a warm tone and style and a soft facial expression, in accordance with the second coaching characteristic (403).

[0076] According to one embodiment, the electronic device (101) can display a prompt transmitted to the generative AI on a display (e.g., the display module (160) of FIG. 1) so that the user can verify it. The prompt is transmitted to a server (108), and the electronic device (101) generates and receives coaching characteristics through the server (108), and can continuously maintain and manage the coaching characteristics by a character management module inside the electronic device (101).

[0077] The electronic device (101) may receive coaching characteristics generated by a generative AI (e.g., a server) and generate a coaching guide (e.g., natural language) that matches the coaching characteristics and provide it to the user. Alternatively, the electronic device (101) may receive parameters of coaching characteristics from a generative AI and generate a coaching guide based on the parameters of coaching characteristics and provide it to the user. The parameters of coaching characteristics may include information on at least one of character image, tone of voice, style, frequency, speed, or facial expression. The electronic device (101) may display the coaching guide on a display module (160) or output it as audio through the speaker of the electronic device (101) (e.g., the sound output module (155) of FIG. 1). The electronic device (101) may change the parameters of coaching characteristics according to progress status information. For example, if the user has achieved a goal set by the user, the electronic device (101) may request the generative AI to provide a coaching guide to the user with coaching characteristics different from the previous coaching characteristics.

[0078] According to one embodiment, an electronic device (101) can obtain progress status information from an external device (102, 104) (e.g., a wearable device) connected (e.g., paired) to the electronic device (101). The external device can measure heart rate, body temperature, activity time, and distance and transmit them to the electronic device (101). The electronic device (101) can identify the user's context based on the progress status information received from the external device. The electronic device (101) can provide a coaching guide that matches the coaching characteristics whenever the progress status information changes. That is, the electronic device (101) can provide a coaching guide that matches the progress status information periodically, optionally, and in real time according to a value set in the application. For example, if a user is receiving running coaching, the electronic device (101) can provide a coaching guide that matches the progress status information in real time according to a value set in the application (e.g., every 1 km, or every 10 minutes).

[0079] According to one embodiment, the electronic device (101) can determine parameters of coaching characteristics based on additional input from the user. The electronic device (101) provides a user interface for determining parameters of coaching characteristics and can transmit parameters selected by the user through the user interface to the generative AI. Alternatively, the electronic device (101) can recommend coaching characteristics based on the coaching history information, receive a selection of parameters of coaching characteristics from the user among the recommended coaching characteristics, and transmit the parameters selected by the user to the generative AI.

[0080] An electronic device (101) according to one embodiment of the present disclosure comprises a display (160), a memory (130) for storing instructions; and a processor (120). When the instructions are executed by the processor, the electronic device executes an application associated with coaching, obtains coaching history information or / and detected progress status information stored in the executed application, identifies a user's context based on the coaching history information or / and the progress status information, generates a prompt for determining a coaching characteristic based on the user's context, and provides a coaching guide corresponding to the coaching characteristic generated based on the prompt through a generative AI.

[0081] If the application associated with the above coaching is a health application, the progress status information measured by the health application may include at least one of heart rate, body temperature, type of exercise, exercise distance, or exercise time.

[0082] The above coaching characteristics include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expression, and the coach's character generated according to the above coaching characteristics may be one or multiple.

[0083] When the above instructions are executed by the processor, the electronic device may display the generated prompt on the display, display a coaching guide corresponding to the prompt on the display, or output it as audio through the sound output module of the electronic device.

[0084] When the above instructions are executed by the processor, the electronic device can change the parameters of the coaching characteristics according to the progress status information.

[0085] When the above instructions are executed by the processor, if the electronic device achieves a goal set by the user in the executed application, it can provide a coaching guide to the user with coaching characteristics different from the previous coaching characteristics through the generative AI.

[0086] When the above instructions are executed by the processor, the electronic device can obtain progress status information from an external device connected to the electronic device and provide a coaching guide with coaching characteristics that are changed according to the progress status information and the user's context.

[0087] When the above instructions are executed by the processor, the electronic device provides a user interface for determining parameters of the coaching characteristics and can transmit parameters selected by the user through the user interface to the generative AI.

[0088] When the above instructions are executed by the processor, the electronic device may recommend coaching characteristics based on the coaching history information according to the execution of the application, and receive a parameter of the coaching characteristic from the user among the recommended coaching characteristics.

[0089] When the above instructions are executed by the processor, the electronic device receives feedback from the user while providing the coaching guide, and reflects the received feedback in the coaching characteristics, thereby providing a coaching guide corresponding to the coaching characteristics in which the feedback is reflected.

[0090] FIG. 5 is a flowchart illustrating a method of operation between an electronic device and a server according to one embodiment.

[0091] Referring to FIG. 5, in operation 501, an electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can execute an application related to coaching. The electronic device (101) can execute an application related to coaching, for example, a health application (e.g., the health application (279) of FIG. 2), an exercise application, a study application, based on user input among the applications installed on the electronic device (101).

[0092] In operation 503, the application (146) can extract coaching history information as the application related to the coaching is executed. The coaching history information is information about what the user has coached through the application related to the coaching, and may include, for example, at least one of the coaching date and time (e.g., date, time), coaching type, coaching characteristics, coaching guide, or progress status information according to the coaching guide.

[0093] In operation 502, an external device (510) may detect (or measure) progress status information. The progress status information may be obtained based on at least one of acceleration, angular velocity, and rotation information detected (or measured) through a sensor module of the electronic device (101) (e.g., sensor module (176) of FIG. 1). Alternatively, the progress status information may be obtained based on at least one of detected (or measured) acceleration, angular velocity, and rotation information measured by an external device (510) connected (e.g., paired) to the electronic device (101). The external device (510) refers to a wearable device that can be worn (or attached) to the user's body, such as a watch or a ring.

[0094] If the application associated with the coaching is a health application, the progress status information measured in the health application may include at least one of heart rate, body temperature, type of exercise, distance of exercise, or time of exercise. The heart rate or body temperature may be obtained from a wearable device, and the heart rate, body temperature, type of exercise, distance of exercise, and time of exercise may all be obtained from a device. Alternatively, the type of exercise, distance of exercise, or time of exercise among the progress status information may be obtained from an electronic device (101). If the application associated with the coaching is a study application (e.g., worksheet), the progress status information in the study application may include at least one of the date of the most recent study, the time of study, or the amount of study.

[0095] In operation 504, the external device (510) can transmit the progress status information to the application (146) of the electronic device (101). According to one embodiment, when the electronic device (101) obtains progress status information using the external device (510), it can obtain progress status information from the external device (510) in real time, periodically, or optionally.

[0096] In operation 505, the application (146) can obtain progress status information. If the application (146) can detect and obtain the progress status information, operation 502 or operation 504 may be omitted.

[0097] In operation 507, the application (146) can transmit progress status information and coaching history information to the AI ​​client (229) of the electronic device (101). The coaching history information can be transmitted to the AI ​​client (229) when the application related to the coaching is executed. The progress status information can be transmitted to the AI ​​client (229) when it is detected (or measured) through the application (146) or an external device (510).

[0098] In operation 509, the AI ​​client (229) of the electronic device (101) can identify (or analyze, determine) the user's context. The AI ​​client (229) can identify the user's context based on the coaching history information and the progress status information. The user's context represents the user's current state, and the user's current state may vary depending on the coaching history information or the progress status information.

[0099] In operation 511, the AI ​​client (229) may generate a prompt based on the user's context. The prompt is delivered to the generative AI and may be a request for a coaching guide to be provided according to the coaching characteristics desired by the user based on the user's context. The prompt may include the coaching history information or / and the progress status information. Alternatively, if the coaching history information includes previous coaching characteristics, the previous coaching characteristics may also be included in the prompt. The AI ​​client (229) may display the generated prompt on the display of the electronic device (101) (e.g., the display module (160) of FIG. 1).

[0100] In operation 513, the AI ​​client (229) can transmit the generated prompt to the server (108). The server (108) may be the generative AI system (301) of FIG. 3. Although the server (108) and the AI ​​client (229) are shown separately in the drawing, depending on the implementation of the electronic device (101), the operation of the server (108) may also be performed by the AI ​​client (229).

[0101] In operation 515, the server (108) may generate coaching characteristics based on the prompt. The coaching characteristics represent the personality (or individuality) of the coach providing the coaching guide (e.g., virtual assistant, AI assistant). For example, the coaching characteristics may include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expression. One or more coach characters may be generated according to the coaching characteristics. The server (108) may generate the coaching characteristics and transmit them to the electronic device (101). Alternatively, the server (108) may generate a coaching guide corresponding to the coaching characteristics and transmit it to the electronic device (101). This is merely an implementation issue and the invention is not limited by description.

[0102] In operation 517, the AI ​​client (229) can generate a coaching guide corresponding to the coaching characteristics. For example, if the coaching characteristics are those of a strict and thorough tiger running coach, the AI ​​client (229) can generate a coaching guide that matches the coaching characteristics. The AI ​​client (229) can provide the coaching guide to the user with a tone of voice and facial expression suitable for the user's current situation, taking into account the user's disposition, health condition, or exercise history (performance evaluation). Although the drawing describes the AI ​​client (229) generating the coaching guide, the server (108) can generate the coaching guide and transmit it to the AI ​​client (229).

[0103] In action 519, the AI ​​client (229) can deliver a coaching guide to the application (146). The coaching guide may encourage the user or provide instructions for the user's behavior.

[0104] In operation 521, the application (146) may provide a coaching guide (e.g., natural language). The coaching guide may be displayed on a display module (160) or output as audio through a speaker of the electronic device (101) (e.g., the sound output module (155) of FIG. 1). The coaching guide may include at least one of text, images, video, or audio. For example, if the user is receiving running coaching, audio (e.g., voice) corresponding to the coaching guide may be output. Alternatively, if there is an external device connected to the electronic device (101), the coaching guide may be delivered to the external device. If the external device is an earphone, audio corresponding to the coaching guide may be output. If the external device is a watch, a user interface corresponding to the coaching guide may be displayed and audio corresponding to the coaching guide may be output.

[0105] According to one embodiment, the application (146) may acquire progress status information in real time, periodically, or selectively using an external device (510) or an electronic device (101), and transmit the acquired progress status information to an AI client (229). Whenever the AI ​​client (229) acquires progress status information from the application (146), it may identify the user's context and generate a prompt based on the user's context and transmit it to the server (108). The server (108) may generate a coaching guide corresponding to the coaching characteristics according to the prompt and transmit it to the AI ​​client (229). The AI ​​client (229) transmits the coaching guide acquired from the server (108) to the application (146), and the application (146) may provide the coaching guide to the user.

[0106] FIG. 6 is a flowchart (600) illustrating the operation method of an electronic device according to one embodiment.

[0107] Referring to FIG. 6, in operation 601, a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment may execute a coaching-related application. A user may execute a coaching-related application by selecting an icon of the coaching-related application or by selecting a coaching-related application from a recent execution list. The coaching-related application may include an application capable of coaching the user through generative AI. For example, the coaching-related application may be an application related to health, exercise, or study.

[0108] In operation 603, the processor (120) may obtain coaching history information or / and progress status information. The coaching history information may be obtained if the user has previously received coaching. For example, the coaching history information may include at least one of the following: coaching date, time, type of coaching, coaching characteristics, coaching guide, or progress status information according to the coaching guide. The type of coaching may be related to exercise, study, or health. The coaching characteristics represent the personality or character of the coach providing the coaching guide, and may be, for example, "strict and thorough," "warm and persuasive," or "motivating and descriptive." There may be one or more coach characters generated according to the coaching characteristics. The above description is an example to aid in understanding the invention and is not intended to limit the invention.

[0109] The progress status information may vary depending on the application executed. For example, if the application executed is exercise, the progress status information may include biometric information measured in relation to exercise (e.g., heart rate, blood pressure, body temperature) and exercise information (e.g., type of exercise, time of exercise, distance of exercise). If the application executed is study, the progress status information may include study progress information measured in relation to study (e.g., type of study, time of study, amount of study). The progress status information may be obtained based on at least one of acceleration, angular velocity, and rotation information detected (or measured) through a sensor module of the electronic device (101) (e.g., sensor module (176) of FIG. 1). Alternatively, the progress status information may be obtained based on at least one of the detected (or measured) acceleration, angular velocity, and rotation information measured by an external device (e.g., external device (510) of FIG. 5) (wearable device) connected to the electronic device (101). The processor (120) may obtain the progress status information in real time, periodically, or optionally.

[0110] In operation 605, the processor (120) can identify the user's context. The processor (120) can identify (or determine) the user's context (e.g., situation, disposition, state) based on the coaching history information or / and the progress status information. The user's context represents the user's situation, disposition, or state and may vary depending on the coaching history information or / and the progress status information. Even if the coaching history information is the same, the user's context may vary if the progress status information is different. Or, conversely, even if the progress status information is the same, the user's context may vary if the coaching history information is different.

[0111] In operation 607, the processor (120) may generate and display a prompt based on the context of the user. The prompt may include the coaching history information or / and the progress status information. Alternatively, if the coaching history information includes previous coaching characteristics, the previous coaching characteristics may also be included in the prompt. The processor (120) may display the generated prompt on a display (e.g., the display module (160) of FIG. 1) so that the user can view it.

[0112] According to one embodiment, the processor (120) may recommend coaching characteristics based on the user's context and determine parameters of the coaching characteristics based on additional input from the user. The processor (120) may provide a user interface for determining parameters of the coaching characteristics and transmit parameters selected by the user through the user interface to the generative AI. Alternatively, the processor (120) may recommend coaching characteristics based on the coaching history information, receive a selection of parameters of the coaching characteristics from the user among the recommended coaching characteristics, and transmit the parameters selected by the user to the generative AI.

[0113] In operation 609, the processor (120) may provide a coaching guide corresponding to a coaching characteristic generated through a generative AI. The coaching characteristic may represent the personality (or personality) of the coach (e.g., virtual assistant, AI assistant) providing the coaching guide. For example, the coaching characteristic may include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expression. There may be one or more coach characters generated according to the coaching characteristic. The processor (120) may transmit the prompt to the generative AI and receive the coaching characteristic generated from the generative AI. If the generative AI is a server (e.g., the generative AI system (301) of FIG. 3), the processor (120) may transmit the prompt to the generative AI system (301), receive the coaching characteristic from the generative AI system (301), and continuously maintain and manage the coaching characteristic by a character management module inside the electronic device (101). The processor (120) can generate a coaching guide that matches the coaching characteristics transmitted from the generative AI and provide it to the user. Alternatively, the processor (120) can receive parameters of the coaching characteristics from the generative AI and generate a coaching guide based on the parameters of the coaching characteristics and provide it to the user. The processor (120) can display the coaching guide on a display module (160) or output it as audio through a speaker of the electronic device (101) (e.g., the sound output module (155) of FIG. 1).

[0114] According to one embodiment, the processor (120) may acquire progress status information in real time, periodically, or optionally, and change parameters of coaching characteristics according to the progress status information. For example, if a goal set by the user has been achieved, the processor (120) may request the generative AI to provide coaching guidance to the user with coaching characteristics different from the previous coaching characteristics. The user may set a goal in the application before starting coaching.

[0115] According to one embodiment, the processor (120) can obtain progress status information from an external device (102, 104) (e.g., a wearable device) connected to the electronic device (101). The external device can measure heart rate, body temperature, activity time, and distance and transmit them to the electronic device (101). The processor (120) can identify the user's context based on the progress status information received from the external device. The processor (120) can provide a coaching guide that matches the coaching characteristics whenever the progress status information changes. For example, if the user is receiving running coaching, the processor (120) can provide a coaching guide that matches the progress status information in real time according to a value set in the application (e.g., every 1 km, or every 10 minutes).

[0116] FIG. 7a is a drawing illustrating an example of providing a user interface associated with coaching characteristics in an electronic device according to one embodiment.

[0117] Referring to FIG. 7a, when a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment receives a request from a user to execute a coaching-related application, the processor may display a first user interface (710) on a display (e.g., display module (160) of FIG. 1). The first user interface (710) may be an execution screen of a coaching-related application. Although the drawing describes an example where the coaching-related application is a health application, the invention is not limited by this description.

[0118] When the start button (711) is selected in the first user interface (710), the processor (120) may extract coaching history information stored in the health application and generate a prompt for creating coaching characteristics based on the coaching history information. The coaching history information is information about what the user has coached through the application related to coaching, and may include, for example, at least one of the following: coaching date and time (e.g., date, time), coaching type, coaching characteristics, coaching guide, or progress status information according to the coaching guide. The prompt may include the coaching history information, and if the coaching history information includes previous coaching characteristics, the previous coaching characteristics may also be included in the prompt. Alternatively, if there is progress status information, the processor (120) may also include the progress status information in the prompt.

[0119] The processor (120) can identify coaching characteristics based on the generated prompt through generative AI. The coaching characteristics may represent the personality (or individuality) of the coach providing the coaching guide (e.g., virtual assistant, AI assistant). For example, the coaching characteristics may include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expression. There may be one or more coach characters generated according to the coaching characteristics.

[0120] The processor (120) may provide a second user interface (730) when coaching characteristics are determined through generative AI. Alternatively, the processor (120) may provide a second user interface (730) when recommending coaching characteristics based on coaching history information. The second user interface (730) may include a first coaching characteristic (731) and a second coaching characteristic (733). The first coaching characteristic (731) is authoritative and analytic, and the coach's character image may be male, with an authoritative tone and style, frequent coaching, fast coaching speed, and a strict facial expression. The second coaching characteristic (733) is warm and persuasive, and the coach's character image may be female, with a warm tone and style, infrequent coaching, slow coaching speed, and a soft facial expression. That is, the coaching characteristics may differ depending on the user's context.

[0121] The processor (120) may provide a third user interface (750) when a first coaching characteristic (731) is selected in the second user interface (730). The third user interface (750) is for selecting parameters of the coaching characteristic and may include at least one of tone of voice (751), style (753), coaching speed (755), or coaching frequency (757). The user can determine the coach profile they want by selecting parameters of the coaching characteristic.

[0122] FIG. 7b is a diagram illustrating an example of providing a coaching guide corresponding to coaching characteristics in an electronic device according to one embodiment.

[0123] Referring to FIG. 7b, the fourth user interface (770) illustrates an example of providing a coaching guide based on progress status information. Referring to the fourth user interface (770), the processor (120) may generate and display a first prompt (771) based on coaching history information and / or first progress status information, and may provide a first coaching guide (773) based on the first prompt (771). The first prompt (771) may include previous coaching history (e.g., strict, thorough). The processor (120) may obtain second progress status information related to running, generate and display a second prompt (775) containing (or updating) the second progress status information, and provide a second coaching guide (777) based on the second prompt (775). Since the progress status information included in the second prompt (775) has been updated, the processor (120) can provide a second coaching guide (777) that is different from the first coaching guide (733).

[0124] Continuing, the processor (120) may provide a fifth user interface (790) as progress status information is updated. The processor (120) may generate and display a third prompt (791) based on the third progress status information and provide a third coaching guide (793) based on the third prompt (791). If the processor (120) checks the third progress status information and determines that the user has achieved the running goal set by the user, it may provide a coaching guide to the user with coaching characteristics different from the previous coaching characteristics. The user may set a goal in the application before starting coaching.

[0125] FIG. 8 is a flowchart (800) illustrating a method of providing a coaching guide by changing coaching characteristics in an electronic device according to one embodiment. FIG. 8 can be performed after operation 601 of FIG. 6.

[0126] Referring to FIG. 8, in operation 801, a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment may recommend coaching characteristics based on coaching history information. The processor (120) may receive a request from a user to execute a coaching-related application and, upon executing the coaching-related application, extract coaching history information stored in the coaching-related application. The processor (120) may provide a user interface (e.g., second user interface (730) of FIG. 7a) that recommends coaching characteristics based on the extracted coaching history information.

[0127] In operation 803, the processor (120) can select a coaching characteristic based on user input. The processor (120) can select at least one coaching characteristic from the recommended coaching characteristics based on the user input.

[0128] In operation 805, the processor (120) can determine whether a parameter is changed. The processor (120) can receive user input that changes the parameter of the selected coaching characteristic. If the parameter of the coaching characteristic is changed, the processor (120) can perform operation 807, and if the parameter of the coaching characteristic is not changed, it can perform operation 809.

[0129] In the case of changing the parameters of a coaching characteristic, in operation 807, the processor (120) can change the parameters of the coaching characteristic. The parameters of the coaching characteristic may correspond to values ​​that set the coaching characteristic. The parameters of the coaching characteristic may be included in the setting values ​​for at least one of character image, tone of voice, style, frequency, speed, or facial expression. The processor (120) can transmit the changed parameters of the coaching characteristic to the generative AI.

[0130] In operation 809, the processor (120) may provide a coaching guide corresponding to a coaching characteristic. The processor (120) may generate a prompt including at least one of the coaching characteristic selected in operation 803, coaching history information or / and progress status information, and transmit the generated prompt to a generative AI. The processor (120) may generate a prompt including at least one of the parameters of the coaching characteristic selected in operation 807, coaching history information or / and progress status information, and transmit the generated prompt to a generative AI. The processor (120) may provide the coaching guide obtained from the generative AI to the user. The coaching guide may include at least one of text, image, video, or audio. The processor (120) may display the coaching guide on a display (e.g., the display module (160) of FIG. 1) or output it as audio through a speaker of the electronic device (101) (e.g., the sound output module (155) of FIG. 1).

[0131] In operation 811, the processor (120) can obtain progress status information. The progress status information obtained may vary depending on the application executed. For example, if the application executed is exercise, the progress status information may include biometric information measured in relation to exercise (e.g., heart rate, blood pressure, body temperature) and exercise information (e.g., type of exercise, time of exercise, distance of exercise). If the application executed is study, the progress status information may include study progress information measured in relation to study (e.g., type of study, time of study, amount of study). The progress status information may be measured in the application of the electronic device (101) or in an external device connected to the electronic device (101) (e.g., the external device (510) of FIG. 5) (wearable device). The processor (120) may obtain the progress status information in real time, periodically, or optionally.

[0132] In operation 813, the processor (120) can determine whether the goal has been achieved. The user can set a goal after launching the coaching application and before starting coaching. For example, if the user sets a goal of running 5 km before running coaching, the processor (120) can determine whether the user has achieved the goal based on the progress status information. If the user has achieved the goal, the processor (120) can perform operation 815, and if the user has not achieved the goal, it can return to operation 809. If the user has not achieved the goal, the processor (120) can return to operation 809 and repeat operations 809 through 813.

[0133] When the user achieves a goal, in action 815, the processor (120) may provide a coaching guide with different coaching characteristics. When the user achieves a goal, the processor (120) may provide a coaching guide by changing the parameters of the coaching characteristics. The processor (120) may change the parameters of the coaching characteristics, transmit the changed parameters of the coaching characteristics to the generative AI, receive the coaching guide from the generative AI, and provide it to the user. The processor (120) may transmit to the generative AI that since the user has achieved a goal, the parameters of the coaching characteristics should be changed to provide a coaching guide, receive the coaching guide from the generative AI, and provide it to the user. For example, if the coaching characteristics were strict and thorough before achieving the goal, they may be changed to motivating and persuasive after achieving the goal.

[0134] FIG. 9a is a diagram illustrating an example in which coaching characteristics are provided differently according to coaching history information in an electronic device according to one embodiment.

[0135] Referring to FIG. 9a, when a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment receives a request from a user to execute a coaching-related application, the processor may display a first user interface (910) on a display (e.g., display module (160) of FIG. 1) based on first coaching history information stored in said coaching-related application. The first user interface (910) may include a first coaching characteristic (911) or a second coaching characteristic (913). For example, the first coaching characteristic (911) may include a character image of the coaching characteristic, a coaching guide example (e.g., let's break together! You are doing good job), or / and parameters of the coaching characteristic (e.g., warm, persuasive). If the processor (120) has stored second coaching history information (e.g., exercise time is 10 times or more in the last 10 days) that is different from the first coaching history information (e.g., exercise time is 1 day or less in the last 10 days) in the application related to the coaching, it may recommend a third coaching characteristic that is different from the first coaching characteristic (911) or the second coaching characteristic (913). Alternatively, the processor (120) may display a selection history of coaching characteristics based on the coaching history information. Alternatively, if the user is unable to select a coaching characteristic, the processor (120) may provide a second user interface (920). The second user interface (920) may include a third coaching characteristic (921) or a fourth coaching characteristic (923).

[0136] FIG. 9b is a drawing illustrating an example of changing the parameters of a coaching characteristic in an electronic device according to one embodiment.

[0137] Referring to FIG. 9B, the processor (120) can provide an example of a coaching guide for a coaching characteristic as the parameters of the coaching characteristic change. For example, referring to the third user interface (930), the processor (120) can provide an example of a first coaching guide (935) corresponding to the set parameters of the coaching characteristic when the parameters of the coaching characteristic are set to a first tone (931) (e.g., warm), a first style (933) (e.g., analytic), a first speed (937), and a first frequency (939). The processor (120) can provide audio corresponding to the first coaching guide (935), and when the first speed (937) of the first parameter changes, it can change the audio speed corresponding to the first coaching guide (935). The user can select a coaching characteristic or a parameter of the coaching characteristic by checking the first coaching guide (935).

[0138] Additionally, referring to the fourth user interface (940), the processor (120) may provide a second coaching guide (945) as an example corresponding to the set coaching characteristic parameter when the coaching characteristic parameter is set to a second tone (941) (e.g., warm) or a second style (943) (e.g., descriptive). The processor (120) provides audio corresponding to the second coaching guide (945) so that the user can check the second coaching guide (945) and select the coaching characteristic or the coaching characteristic parameter.

[0139] Referring to the fifth user interface (950), the processor (120) may provide a third coaching guide (955) as an example corresponding to the set coaching characteristic parameter when the coaching characteristic parameter is set to a third tone (951) (e.g., motivational) or a third style (953) (e.g., persuasive). The processor (120) provides audio corresponding to the third coaching guide (955) so that the user can check the third coaching guide (955) and select the coaching characteristic or the coaching characteristic parameter.

[0140] FIG. 9c is a diagram illustrating an example of providing a coaching guide corresponding to coaching characteristics in an electronic device according to one embodiment.

[0141] Referring to FIG. 9c, the processor (120) can display a sixth user interface (960) containing progress status information and a coaching guide on the display module (160). Referring to the sixth user interface (960), the processor (120) can provide progress status information (961) including exercise time, exercise distance, and pace, and a coaching guide (963) based on the progress status information (961). Referring to the seventh user interface (970), the processor (120) can generate and display a first prompt (971) based on the first progress status information and provide a first coaching guide (973) corresponding to the first prompt (971) through a generative AI. When the progress status information changes, the processor (120) can generate and display a second prompt (975) based on the second progress status information and provide a second coaching guide (977) corresponding to the second prompt (975) through a generative AI.

[0142] The first coaching guide (973) or the second coaching guide (977) may consist of at least one of text, image, video, or audio. For example, the processor (120) may display the first coaching guide (973) or the second coaching guide (977) on the display module (160) or output it as audio through the speaker of the electronic device (101) (e.g., the sound output module (155) of FIG. 1).

[0143] FIG. 10 is a diagram illustrating an example of providing a coaching guide corresponding to the coaching characteristics of exercise in an electronic device according to one embodiment.

[0144] Referring to FIG. 10, when a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment executes an exercise application, a first user interface (1010) can be displayed on a display (e.g., display module (160) of FIG. 1). The first user interface (1010) is an execution screen of the exercise application, and when a start button (1011) is selected, a second user interface (1030) can be provided.

[0145] When the start button (1011) is selected, the processor (120) can measure exercise time, exercise distance, or pace using a sensor module (e.g., sensor module (176) of FIG. 1). Alternatively, when the start button (1011) is selected, the processor (120) can obtain exercise time, exercise distance, or pace measured from an external device (e.g., external device (510) of FIG. 5) (e.g., ring) connected (e.g., paired) to the electronic device (101). The second user interface (1030) may include progress status information (1031) and a coaching guide (1035). The processor (120) can identify the user's context based on coaching history information and progress status information (1031) stored in the exercise application, generate a prompt based on the context, and provide a coaching guide (1035) based on the prompt through generative AI.

[0146] FIGS. 11a and FIGS. 11b are drawings illustrating an example of providing a coaching guide corresponding to the coaching characteristics of a study in an electronic device according to one embodiment.

[0147] Referring to FIG. 11a, when a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment receives a request from a user to execute a study coaching application, the processor (120) may display a first user interface (1110) on a display (e.g., display module (160) of FIG. 1). The first user interface (1110) may be an execution screen of the study coaching application. When a start button (1101) is selected in the first user interface (1110), the processor (120) may extract coaching history information stored in the study coaching application and recommend coaching characteristics based on the coaching history information. The second user interface (1130) may include a first coaching characteristic (1131) and a second coaching characteristic (1133). The first coaching characteristic (1131) may be authoritative, the coach's character image may be male, and coaching may be provided every 30 minutes. The processor (120) may provide an example of a coaching guide for the first coaching characteristic (1131). The second coaching characteristic (1133) may be warm, the character image of the coach may be female, and coaching may take place every 2 minutes. The processor (120) may provide an example of a coaching guide for the second coaching characteristic (1133).

[0148] The third user interface (1150) may include an example of a first coaching guide (1153) when the first coaching history information (e.g., studied more than 10 times in the last 10 days) and the parameter of the coaching characteristic has a first tone of voice (1151).

[0149] Referring to FIG. 11b, the fourth user interface (1170) may include an example of a second coaching guide (1173) when the second coaching history information (e.g., studying more than twice in the last 10 days) and the coaching characteristic parameter has a second tone (1171). The fifth user interface (1190) may include an example of a third coaching guide (1193) when the third coaching history information (e.g., studying for the first time in the last 10 days) and the coaching characteristic parameter has a third tone (1191). That is, if the coaching history information or the coaching characteristic parameter is different, the coaching characteristic may be different.

[0150] FIG. 12 is a flowchart (1200) illustrating a method of changing and providing a coaching guide according to progress status information in an electronic device according to one embodiment. FIG. 12 may be an embodiment of the operation 609 of FIG. 6.

[0151] Referring to FIG. 12, in operation 1201, a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1) according to one embodiment may provide a first coaching guide based on a first prompt. The first prompt may include coaching history information and / or first progress status information stored in an application related to coaching. The first coaching guide may be provided according to coaching characteristics generated based on the first prompt through generative AI.

[0152] In operation 1203, the processor (120) may acquire (or update) progress state information. The progress state information acquired after the first progress state information used in operation 1201 may mean second progress state information. The second progress state information may be acquired based on at least one of acceleration, angular velocity, and rotation information detected (or measured) through a sensor module of the electronic device (101) (e.g., sensor module (176) of FIG. 1). Alternatively, the second progress state information may be acquired based on at least one of acceleration, angular velocity, and rotation information detected (or measured) by an external device connected to the electronic device (101) (e.g., external device (510) of FIG. 5). The processor (120) may acquire the second progress state information in real time, periodically, or optionally.

[0153] In operation 1205, the processor (120) may generate and display a second prompt. The processor (120) may generate the second prompt based on the second progress status information. Alternatively, the second prompt may include coaching history information stored in an application related to coaching and / or the second progress status information.

[0154] In operation 1207, the processor (120) may provide a second coaching guide based on the second prompt. The second coaching guide may be provided according to coaching characteristics generated based on the second prompt through generative AI.

[0155] In operation 1209, the processor (120) can determine whether feedback is received. For example, the processor (120) may receive feedback on the coaching guide from the user while providing the coaching guide or before and after the coaching ends. If feedback is received, the processor (120) may perform operation 1211, and if feedback is not received, perform operation 1231.

[0156] When feedback is received, in operation 1211, the processor (120) can reflect the feedback in the coaching characteristics. The processor (120) can transmit the feedback to a generative AI to reflect it in the coaching characteristics. The processor (120) can generate a new prompt containing the feedback and transmit the generated new prompt to a generative AI to reflect it in the coaching characteristics.

[0157] If no feedback is received, or after the feedback has been reflected in the coaching characteristics, in action 1213, the processor (120) can determine whether the coaching has ended. The user may request to end the coaching by selecting the end button within the user interface. If the coaching has ended, the processor (120) performs action 1215, and if the coaching has not ended, it can return to action 1203.

[0158] When coaching is terminated, in operation 1215, the processor (120) may store coaching history information. The coaching history information may include at least one of the following: coaching date and time (e.g., date, time), coaching type, coaching characteristics, coaching guide, or progress status information according to the coaching guide. The processor (120) may store the information obtained by performing operations 1201 to 1213 as coaching history information in memory (e.g., memory (130) of FIG. 1).

[0159] FIG. 13 is a diagram illustrating an example of an electronic device according to one embodiment providing a coaching guide differently depending on the user's context.

[0160] Referring to FIG. 13, an electronic device according to one embodiment (e.g., the processor of the electronic device (101) of FIG. 1 (e.g., the processor (120) of FIG. 1)) may provide a coaching guide differently depending on the user's context. When the user is in a first context (e.g., watching TV or driving), the processor (120) may provide a first coaching guide (1313) according to a first coaching characteristic (1311). A first user interface (1310) may illustrate an example of providing a first coaching guide (1313) corresponding to the first coaching characteristic (1311). When the user is in a second context (e.g., a general situation), the processor (120) may provide a second coaching guide (1333) according to a second coaching characteristic (1331). A second user interface (1330) may illustrate an example of providing a second coaching guide (1333) corresponding to the second coaching characteristic (1331). The processor (120) may provide a third coaching guide (1353) according to a third coaching characteristic (1351) when the user is in a third context (e.g., waking up). The third user interface (1350) may illustrate an example of providing a third coaching guide (1353) corresponding to a fifth coaching characteristic (1351).

[0161] A method of operation of an electronic device (101) according to one embodiment of the present disclosure may include: executing an application associated with coaching; obtaining coaching history information stored in the executed application and / or detected progress status information; identifying a user's context based on the coaching history information and / or the progress status information; generating a prompt to determine coaching characteristics based on the user's context; and providing a coaching guide corresponding to the coaching characteristics generated based on the prompt through a generative AI.

[0162] If the application associated with the above coaching is a health application, the progress status information measured by the health application may include at least one of heart rate, body temperature, type of exercise, exercise distance, or exercise time.

[0163] The above coaching characteristics include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expression, and the coach's character generated according to the above coaching characteristics may be one or multiple.

[0164] The above method may further include the operation of displaying the generated prompt on the display, and the operation of displaying a coaching guide corresponding to the prompt on the display or outputting it as audio through the sound output module of the electronic device.

[0165] The above method may further include an operation to change the parameters of the coaching characteristics according to the progress status information.

[0166] The above method may further include an action of providing a coaching guide to the user with coaching characteristics different from the previous coaching characteristics through the generative AI when the user achieves a goal set by the user in the executed application.

[0167] The above method may further include the operation of obtaining progress status information from an external device connected to the electronic device, and the operation of providing a coaching guide of coaching characteristics that are changed according to the progress status information and are suitable for the user's context.

[0168] The above method may further include an operation of providing a user interface for determining parameters of the coaching characteristics, and an operation of transmitting parameters selected by the user through the user interface to the generative AI.

[0169] The above method may further include an action of recommending coaching characteristics based on coaching history information according to the execution of the above application, and an action of receiving a parameter of a coaching characteristic from the user among the recommended coaching characteristics.

[0170] The above method may further include the action of receiving feedback from a user while providing the coaching guide, and the action of reflecting the received feedback in the coaching characteristics and providing a coaching guide corresponding to the coaching characteristics in which the feedback is reflected.

[0171] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0172] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., first) component is referred to as “coupled” or “connected” to another (e.g., second) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., by wire), wirelessly, or through a third component.

[0173] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0174] Various embodiments of the present document may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0175] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or an application store (e.g., Play Store). TM It can be distributed online (e.g., downloaded or uploaded) through ) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0176] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0177] The various embodiments of the present invention disclosed in this specification and drawings are provided merely as specific examples to facilitate the explanation of the technical content of the invention and to aid in understanding the invention, and are not intended to limit the scope of the invention. Accordingly, the scope of the present invention should be interpreted to include all modifications or variations derived based on the technical concept of the invention, in addition to the embodiments disclosed herein.

Claims

1. In an electronic device (101), Display (160), Memory (130) for storing instructions; and The electronic device includes a processor (120), and when the instructions are executed by the processor, the electronic device Launch an application related to coaching, Acquire coaching history information stored in the above-mentioned executed application or / and detected progress status information, and Identify the user's context based on the above coaching history information or / and the above progress status information, and Generate a prompt to determine coaching characteristics based on the context of the above user, and An electronic device that provides a coaching guide corresponding to coaching characteristics generated based on the above prompt through generative AI.

2. In Paragraph 1, An electronic device in which, when the application associated with the above coaching is a health application, the progress status information measured in the health application includes at least one of heart rate, body temperature, type of exercise, distance of exercise, or time of exercise.

3. In Paragraph 1, The above coaching characteristics include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expressions, and An electronic device in which the coach character generated according to the above coaching characteristics is one or more.

4. In paragraph 1, when the instructions are executed by the processor, the electronic device, Display the generated prompt above on the display, An electronic device that displays a coaching guide corresponding to the above prompt on the above display or outputs it as audio through the sound output module of the electronic device.

5. In paragraph 1, when the instructions are executed by the processor, the electronic device, An electronic device that changes the parameters of the coaching characteristics according to the progress status information.

6. In paragraph 5, when the above instructions are executed by the processor, the electronic device, An electronic device that, when a goal set by the user in the above-executed application is achieved, provides a coaching guide to the user with coaching characteristics different from the previous coaching characteristics through the generative AI.

7. In paragraph 1, when the instructions are executed by the processor, the electronic device, Obtaining the progress status information from an external device connected to the electronic device, and An electronic device that provides a coaching guide of coaching characteristics tailored to the user's context, which changes according to the above progress status information.

8. In paragraph 1, when the instructions are executed by the processor, the electronic device, A user interface for determining parameters of the above coaching characteristics is provided, and An electronic device that transmits parameters selected by a user to the generative AI through the above user interface.

9. In paragraph 1, when the instructions are executed by the processor, the electronic device, Recommend coaching characteristics based on the above coaching history information according to the execution of the above application, and An electronic device that allows the user to select parameters of coaching characteristics from the above recommended coaching characteristics.

10. In paragraph 1, when the instructions are executed by the processor, the electronic device, While providing the above coaching guide, receive feedback from the user, and An electronic device that reflects the received feedback into the coaching characteristics and provides a coaching guide corresponding to the coaching characteristics in which the feedback is reflected.

11. In the method of operating the electronic device (101), The action of running an application related to coaching; An action of obtaining coaching history information stored in the above-executed application or / and detected progress status information; An action of identifying the user's context based on the above coaching history information or / and the above progress status information; An action of generating a prompt to determine coaching characteristics based on the context of the above-mentioned user; and A method comprising the action of providing a coaching guide corresponding to a coaching characteristic generated based on the above prompt through a generative AI.

12. In Paragraph 11, A method in which, when the application associated with the above coaching is a health application, the progress status information measured in the health application includes at least one of heart rate, body temperature, type of exercise, distance of exercise, or time of exercise.

13. In Paragraph 11, The above coaching characteristics include at least one of the coach's character image, tone of voice, style, frequency, speed, or facial expressions, and A method in which the coach character generated according to the above coaching characteristics is one or multiple.

14. In Paragraph 11, The operation of displaying the generated prompt on the display; and A method further comprising the operation of displaying a coaching guide corresponding to the above prompt on the above display or outputting it as audio through the sound output module of the electronic device.

15. In Paragraph 11, An action of changing the parameters of the coaching characteristics according to the progress status information above; and A method further comprising, when the user achieves a goal set by the user in the application executed above, providing a coaching guide to the user with coaching characteristics different from the previous coaching characteristics through the generative AI.

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