WO2023003183A1 - Electronic device and real-time message generation method - Google Patents

Abstract

An electronic device according to various embodiments comprises a display, a microphone, a camera, memory, and a processor operatively connected with the display, the microphone, the camera, and the memory. The processor is set to: launch a messaging application; acquire input data received by at least one of the microphone or the camera on the basis of a user input to a menu provided on a messaging application launch screen; analyze an individual's emotional state included in the input data; generate graphic data including at least one graphic object on the basis of the analyzed emotional state; and generate a live message on the basis of the input data and the graphic data. Various other embodiments are possible.

Description

Electronic devices and methods for generating real-time messages

This document relates to an electronic device, and describes a method for generating a message based on a video or photo taken in real time by the electronic device, for example.

With the development of mobile communication technology and hardware/software technology, a portable electronic device (hereinafter referred to as an electronic device) can implement various functions beyond a conventional call function. An electronic device may exchange data by establishing a communication connection with an external device due to the development of communication technology. Electronic devices enable real-time connection with external users using various message applications.

An electronic device may provide various message types usable in a message application. The user may input text or emoticon into the electronic device using the provided keyboard UI. Using an additional means of expression such as an emoticon, an emoji, or a memoji, the user can convey his or her emotions more intuitively.

Conventional electronic devices provide emoticons created by combining 2D and 3D technologies. The user could select and transmit an emoticon provided on the keyboard application. This has a problem in that the user's actual emotion or facial expression cannot be realistically implemented. In addition, even when an emoticon is generated based on a user's real face, it takes a lot of time to create it, making it difficult to communicate immediately.

Various embodiments of this document, as described above, when an electronic device wants to generate and transmit a real-time message in a message application, faithfully implements a real-life exchange method in on-device mobile to provide realistic communication. Its purpose is to realize communication).

An electronic device according to various embodiments includes a display, a microphone, a camera, a memory, and a processor operatively connected to the display, the microphone, the camera, and the memory, wherein the processor executes a message application and , Based on a user input for a menu provided on the message application execution screen, input data received by at least one of the microphone and the camera is acquired, an emotional state of a person included in the input data is analyzed, and the analysis An electronic device configured to generate graphic data including at least one graphic object based on one emotional state, and generate a live message based on the input data and the graphic data.

A real-time message generation method of an electronic device according to various embodiments includes an operation of executing a message application and obtaining input data received through at least one of a microphone and a camera based on a user input for a menu provided on a message application execution screen. operation of analyzing the emotional state of the person included in the input data, operation of generating graphic data including at least one graphic object based on the analyzed emotional state, operation of generating graphic data including the input data and the graphic data and generating a live message based on the

According to various embodiments, the electronic device may analyze the motion, voice, and facial expression of a photo or video and generate a graphic caption or emoticon accordingly. The electronic device may provide a function of intuitively conveying the user's emotion by adding the generated graphic data to the generated input message.

According to various embodiments, the electronic device may classify generated content into several data types and determine a data type to transmit according to the type of an external device transmitting a live message. Through this, it is possible to provide a personalized means of expression that can faithfully implement an emotional exchange method in reality in an electronic device.

In addition, effects that can be obtained or predicted due to various embodiments of the present electronic device will be directly or implicitly disclosed in the detailed description of the embodiment of the electronic device. For example, various effects predicted according to various embodiments of an electronic device will be disclosed within the detailed description to be described later.

1 is a block diagram of an electronic device in a network environment, according to various embodiments.

2A and 2B are diagrams illustrating generating and transmitting a live message in an electronic device according to various embodiments.

3 is a block diagram of an electronic device according to various embodiments.

4 illustrates that an electronic device generates a live message based on video and audio data according to various embodiments.

5 illustrates generating a live message based on image data by an electronic device according to various embodiments.

6 illustrates generating a live message based on photo data by an electronic device according to various embodiments of the present disclosure.

7A and 7B illustrate a graphic UI provided to generate a real-time message in an electronic device according to various embodiments.

8 illustrates data types according to types of external devices according to various embodiments.

9 illustrates generating a real-time message based on voice data in an electronic device according to various embodiments.

10 is a flowchart of a method of generating a message in real time by an electronic device according to various embodiments.

11 is a flowchart of a method of generating graphic data by an electronic device according to various embodiments.

Hereinafter, embodiments of the present invention will be described in detail based on the accompanying drawings.

In describing the embodiments, descriptions of technical contents that are well known in the art to which the present invention pertains and are not directly related to the present invention will be omitted. In addition, detailed descriptions of components having substantially the same configuration and function will be omitted.

For the same reason, some components in the accompanying drawings are exaggerated, omitted, or schematically illustrated, and the size of each component does not entirely reflect the actual size. Accordingly, the present invention is not limited by the relative size or spacing drawn in the accompanying drawings.

1 is a block diagram of an electronic device in a network environment, according to various embodiments.

Referring to FIG. 1 , in a network environment 100, an electronic device 101 communicates with an electronic device 102 through a first network 198 (eg, a short-range wireless communication network) or through a second network 199. It may communicate with at least one of the electronic device 104 or the server 108 through (eg, a long-distance wireless communication network). According to one embodiment, the electronic device 101 may communicate with the electronic device 104 through the server 108 . According to an embodiment, the electronic device 101 includes a processor 120, a memory 130, an input module 150, an audio output module 155, a display module 160, an audio module 170, a 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 the antenna module 197 may be included. In some embodiments, in the electronic device 101, at least one of these components (eg, the connection terminal 178) may be omitted or one or more other components may be added. In some embodiments, some of these components (eg, sensor module 176, camera module 180, or antenna module 197) are integrated into a single component (eg, display module 160). It can be.

The processor 120, for example, executes software (eg, the program 140) to cause at least one other component (eg, hardware or software component) of the electronic device 101 connected to the processor 120. It can control and perform various data processing or calculations. According to one embodiment, as at least part of data processing or operation, processor 120 transfers instructions or data received from other components (e.g., sensor module 176 or communication module 190) to volatile memory 132. , processing commands or data stored in the volatile memory 132 , and storing resultant data in the non-volatile memory 134 . According to one embodiment, the processor 120 includes a main processor 121 (eg, a central processing unit or an application processor) or a secondary processor 123 (eg, a graphic processing unit, a neural network processing unit ( NPU: neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, when the electronic device 101 includes the main processor 121 and the auxiliary processor 123, the auxiliary processor 123 may use less power than the main processor 121 or be set to be specialized for a designated function. can The secondary processor 123 may be implemented separately from or as part of the main processor 121 .

The secondary processor 123 may, for example, take the place of the main processor 121 while the main processor 121 is in an inactive (eg, sleep) state, or the main processor 121 is active (eg, running an application). ) state, together with the main processor 121, at least one of the components of the electronic device 101 (eg, the display module 160, the sensor module 176, or the communication module 190) It is possible to control at least some of the related functions or states. According to one embodiment, the auxiliary processor 123 (eg, image signal processor or communication processor) may be implemented as part of other functionally related components (eg, camera module 180 or communication module 190). there is. According to an embodiment, the auxiliary processor 123 (eg, a neural network processing device) may include a hardware structure specialized for processing an artificial intelligence model. AI models can be created through machine learning. Such learning may be performed, for example, in the electronic device 101 itself where the artificial intelligence model is performed, or may be performed through a separate server (eg, the server 108). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning or reinforcement learning, but in the above example Not limited. The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the foregoing, but is not limited to the foregoing examples. The artificial intelligence model may include, in addition or alternatively, software structures in addition to hardware structures.

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

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

The input module 150 may receive a command or data to be used by a component (eg, the processor 120) of the electronic device 101 from the outside of the electronic device 101 (eg, a user). The input module 150 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).

The sound output module 155 may output sound signals to the outside of the electronic device 101 . The sound output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as multimedia playback or recording playback. A receiver may be used to receive an incoming call. According to one embodiment, the receiver may be implemented separately from the speaker or as part of it.

The display module 160 may visually provide information to the outside of the electronic device 101 (eg, a user). The display module 160 may include, for example, a display, a hologram device, or a projector and a control circuit for controlling the device. According to one embodiment, the display module 160 may include a touch sensor set to detect a touch or a pressure sensor set to measure the intensity of force generated by the touch.

The audio module 170 may convert sound into an electrical signal or vice versa. According to one embodiment, the audio module 170 acquires sound through the input module 150, the sound output module 155, or an external electronic device connected directly or wirelessly to the electronic device 101 (eg: Sound may be output through the electronic device 102 (eg, a speaker or a headphone).

The sensor module 176 detects an operating state (eg, power or temperature) of the electronic device 101 or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the detected state. can do. According to one embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyro sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a bio sensor, It may include a temperature sensor, humidity sensor, or light sensor.

The interface 177 may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device 101 to an external electronic device (eg, the 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.

The connection terminal 178 may include a connector through which the electronic device 101 may be physically connected to an external electronic device (eg, the 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 (eg, a headphone connector).

The haptic module 179 may convert electrical signals into mechanical stimuli (eg, vibration or motion) or electrical stimuli that a user may 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 electrical stimulation device.

The camera module 180 may capture still images and moving images. According to one embodiment, the camera module 180 may include one or more lenses, image sensors, image signal processors, or flashes.

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

The battery 189 may 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 cell, a rechargeable secondary cell, or a fuel cell.

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

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

The antenna module 197 may transmit or receive signals or power to the outside (eg, an external electronic device). According to one embodiment, the antenna module 197 may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (eg, PCB). According to one embodiment, the antenna module 197 may include a plurality of antennas (eg, an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network such as the first network 198 or the second network 199 is selected from the plurality of antennas by the communication module 190, for example. can be chosen 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, other components (eg, a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module 197 in addition to the radiator.

According to various embodiments, the antenna module 197 may form a mmWave antenna module. According to one embodiment, the mmWave antenna module includes a printed circuit board, an RFIC disposed on or adjacent to a first surface (eg, a lower surface) of the printed circuit board and capable of supporting a designated high frequency band (eg, mmWave band); and a plurality of antennas (eg, array antennas) disposed on or adjacent to a second surface (eg, a top surface or a side surface) of the printed circuit board and capable of transmitting or receiving signals of the designated high frequency band. can do.

At least some of the components are connected to each other through a communication method between peripheral devices (eg, a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)) and signal ( e.g. commands or data) can be exchanged with each other.

According to an embodiment, commands or data may be transmitted or received between the electronic device 101 and the external electronic device 104 through the server 108 connected to the second network 199 . Each of the external electronic devices 102 or 104 may be the same as or different from the electronic device 101 . According to an embodiment, all or part of operations executed in the electronic device 101 may be executed in one or more external electronic devices among the external electronic devices 102 , 104 , or 108 . For example, when the electronic device 101 needs to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device 101 instead of executing the function or service by itself. Alternatively or additionally, one or more external electronic devices may be requested to perform the function or at least part of the service. One or more external electronic devices receiving the request may execute at least a part of the requested function or service or an additional function or service related to the request, and deliver the execution result to the electronic device 101 . The electronic device 101 may provide the result as at least part of a response to the request as it is or additionally processed. To this end, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device 101 may provide an ultra-low latency service 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. Server 108 may be an intelligent server using machine learning and/or neural networks. According to one embodiment, the external electronic device 104 or server 108 may be included in the second network 199 . The electronic device 101 may be applied to intelligent services (eg, smart home, smart city, smart car, or health care) based on 5G communication technology and IoT-related technology.

Electronic devices according to various embodiments disclosed in this document may be devices of various types. The electronic device may include, for example, a portable communication device (eg, a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a home appliance. An electronic device according to an embodiment of the present document is not limited to the aforementioned devices.

Various embodiments of this document and terms used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, like reference numbers may be used for like or related elements. The singular form of a noun corresponding to an item may include one item or a plurality of items, unless the relevant context clearly dictates otherwise. In this document, "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 "A Each of the phrases such as "at least one of , B, or C" may include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", or "first" or "secondary" may simply be used to distinguish a given component from other corresponding components, and may be used to refer to a given component in another aspect (eg, importance or order) is not limited. A (e.g., first) component is said to be "coupled" or "connected" to another (e.g., second) component, with or without the terms "functionally" or "communicatively." When mentioned, it means that the certain component may be connected to the other component directly (eg by wire), wirelessly, or through a third component.

The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and is interchangeable with terms such as, for example, logic, logical blocks, parts, or circuits. can be used as A module may be an integrally constructed component or a minimal unit of components or a portion thereof that performs one or more functions. For example, according to one embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of this document provide one or more instructions stored in a storage medium (eg, internal memory 136 or external memory 138) readable by a machine (eg, electronic device 101). It may be implemented as software (eg, the program 140) including them. For example, a processor (eg, the processor 120 ) of a device (eg, the electronic device 101 ) may call at least one command among one or more instructions stored from a storage medium and execute it. This enables the device to be operated to perform at least one function according to the at least one command invoked. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' only means that the storage medium is a tangible device and does not contain a signal (e.g. electromagnetic wave), and this term refers to the case where data is stored semi-permanently in the storage medium. It does not discriminate when it is temporarily stored.

According to one embodiment, the method according to various embodiments disclosed in this document may be included and provided in a computer program product. Computer program products may be traded between sellers and buyers as commodities. A computer program product is distributed in the form of a device-readable storage medium (e.g. compact disc read only memory (CD-ROM)), or through an application store (e.g. Play Store ^TM ) or on two user devices (e.g. It can be distributed (eg downloaded or uploaded) online, directly between smart phones. In the case of online distribution, at least part of the computer program product may be temporarily stored or temporarily created in a storage medium readable by a device such as a manufacturer's server, an application store server, or a relay server's memory.

According to various embodiments, each component (eg, module or program) of the above-described components may include a single object or a plurality of entities, and some of the plurality of entities may be separately disposed in other components. there is. According to various embodiments, one or more components or operations among the aforementioned corresponding components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg modules or programs) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by a corresponding component of the plurality of components prior to the integration. . According to various embodiments, the actions performed by a module, program, or other component are executed sequentially, in parallel, iteratively, or heuristically, or one or more of the actions are executed in a different order, or omitted. or one or more other actions may be added.

2A and 2B are diagrams illustrating generating and transmitting a live message in an electronic device according to various embodiments.

Referring to FIG. 2A , the electronic device may obtain input data 210 received through a microphone or camera. The input data 210 may include at least one of voice, picture, and video. For example, the electronic device may recognize an object using a camera located on the front or rear of the housing and display a preview as shown in FIG. 2a(a) on one side of the display.

According to various embodiments, the electronic device may generate graphic data 220 based on input data 210 . For example, the electronic device may analyze the input data 210 and generate graphic data 220 corresponding to the emotion of a person included in the input data 210 . The electronic device may generate graphic data 220 composed of “Really”, “good”, and a laughing emoticon by analyzing the smiley expression of the person of the input data 210 and the motion of raising the thumb of the right hand. The electronic device may use an emotion deep learning module or a motion deep learning module to analyze the input data 210 . For example, the electronic device may determine emotion information of a character in the input data 210 by using an emotion deep learning module and generate graphic data 220 including an emoticon corresponding thereto. The electronic device may generate a live message by synthesizing the input data 210 and the graphic data 220 . FIG. 2A(B) illustrates a live message synthesized with graphic data 220 by analyzing the input data 210 of FIG. 2A(A) by the electronic device.

Referring to FIG. 2B , the electronic device may transmit a live message created through a message application. The electronic device may execute the message application (230) and provide a preview screen for generating a live message on the message application. The electronic device may operate a camera and a microphone based on a user input to receive input data 210 and generate graphic data 220 to generate a live message (240). The electronic device may store the generated live message in a memory and transmit the live message to an external device through a message application based on a user input. An operation of generating a live message by an electronic device will be described in detail with reference to FIGS. 3 to 10 below.

3 is a block diagram of an electronic device according to various embodiments.

Referring to FIG. 3 , an electronic device 300 may include a display 320, a camera 340, a microphone 330, a communication module 350, a processor 310, and a memory 360, and in various implementations In examples, some of the illustrated components may be omitted or substituted. The electronic device 300 may further include at least some of the configurations and/or functions of the electronic device 101 of FIG. 1 . At least some of the components of the illustrated (or not illustrated) electronic device 300 may be operatively, functionally, and/or electrically connected to each other.

According to various embodiments, the display 320 may display various images under the control of the processor 310 . The display 320 may be a liquid crystal display (LCD), a light-emitting diode (LED) display, a micro LED display, a quantum dot (QD) display, or an organic light emitting diode (QD) display. -Emitting diode (OLED)) may be implemented as any one of displays, but is not limited thereto. The display 320 may be formed as a touch screen that senses a touch and/or proximity touch (or hovering) input using a user's body part (eg, a finger) or an input device (eg, a stylus pen). The display 320 may include at least some of the components and/or functions of the display module 160 of FIG. 1 .

According to various embodiments, at least a portion of the display 320 may be flexible, and may be implemented as a foldable display or a rollable display.

According to various embodiments, the microphone 330 may collect an external sound such as a user's voice and convert it into a voice signal that is digital data. According to various embodiments, the electronic device 300 may include a microphone 330 in a part of a housing (not shown) or may receive a voice signal collected from an external microphone connected wired/wireless.

According to various embodiments, the camera 340 may acquire external image data. The camera 340 may acquire image data using various types of image sensors such as a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS). The camera 340 may include at least some of the components and/or functions of the camera module 180 of FIG. 1 . The electronic device 300 may place one or more cameras 340 on the front and/or rear of the housing, and unless otherwise specified, image data including an external device is acquired using the rear camera 340. may have been

According to various embodiments, the memory 360 includes a volatile memory (eg, the volatile memory 132 of FIG. 1 ) and a non-volatile memory (eg, the non-volatile memory 134 of FIG. 1 ) to temporarily store various data. or stored permanently. The memory 360 includes at least some of the configuration and/or functions of the memory 130 of FIG. 1 and may store the program 140 of FIG. 1 .

According to various embodiments, the memory 360 may store various instructions that may be executed by the processor 310 . These instructions may include control commands such as arithmetic and logical operations, data movement, input/output, and the like that may be recognized by the processor 310 .

According to various embodiments, the processor 310 may include components of the electronic device 300 (eg, the display 320, the camera 340, the microphone 330, the communication module 350, and the memory 360) and It may be a configuration that is operatively, functionally, and/or electrically connected to perform calculations or data processing related to control and/or communication of each component. The processor 310 may include at least some of the components and/or functions of the processor 120 of FIG. 1 .

According to various embodiments, arithmetic and data processing functions that the processor 310 can implement on the electronic device 300 will not be limited, but hereinafter, a message based on an image or photo taken in real time by the electronic device 300 will be sent. Various embodiments for generating will be described. Operations of the processor 310 to be described later may be performed by loading instructions stored in the memory 360.

According to various embodiments, the processor 310 may obtain input data (eg, input data 210 of FIG. 2 ) from the camera 340 or the microphone 330 . The input data may include at least one of audio, video and pictures. The processor 310 may obtain input data received through a user device connected to the electronic device 300 through short-range communication. For example, the processor 310 may establish a communication connection with a user device equipped with the microphone 330 and obtain voice data from the user device.

According to various embodiments, the processor 310 may analyze input data using an emotion deep learning module and a motion deep learning module. The emotion deep learning module can determine the character's emotion information by analyzing the voice, facial expression, and voice data of the character appearing in the input data. The processor 310 may determine at least one emotion information (eg, joy, sadness, excitement, anger, fear, tenderness) by controlling the emotion deep learning module. The motion deep learning module can determine emotion information by analyzing motions of characters appearing in input data.

According to an embodiment, the processor 310 may map and store at least one word and at least one graphic element corresponding to the corresponding word in the memory 360 . If a word defined in advance is included in the input data, the processor 310 may generate a graphic element corresponding thereto. For example, the processor 310 may map the word 'sea' to a wave emoticon, a seagull emoticon, and a palm tree emoticon and store them in the memory 360 . When the word 'sea' is included in the obtained input data, the processor 310 may generate graphic data including at least one of a wave emoticon, a seagull emoticon, and a palm tree emoticon defined in advance.

According to various embodiments, processor 310 may identify facial features to determine emotional information of a character. According to an embodiment, the deep emotion learning module may learn data by adopting various face recognition technologies. For example, face recognition algorithms include principal component analysis, which may include unique faces, linear discriminate analysis, and elastic bunch graph matching, which may additionally use Fisher's face algorithm. matching), hidden Markov models, multilinear subspace learning that can use tensor representations, and neuronal motivated dynamic link matching. . These facial recognition technologies are augmented by the use of pixel analysis or other contour tracking and classification techniques to enhance the accuracy of facial data, particularly when identifying contour lines around the eyes and mouth, as well as personal features as scars or dots. (or alternatively) can be In still other examples, three-dimensional facial recognition techniques may also be used to capture information about the shape of the face and the dimensions of the face. For example, three-dimensional facial recognition techniques may be useful for identifying distinctive features on the surface of the face, such as (but not limited to) eye sockets, nose and/or chin contours.

According to various embodiments, the processor 310 may generate graphic data (eg, graphic data 220 of FIG. 2 ). The processor 310 may generate different graphic data according to the data type included in the input data. The data type may include a voice data type, a text data type, an emoticon data type, and a camera data type.

According to various embodiments, when there is audio data in the input data, the processor 310 may generate graphic data including graphic captions based on the audio data. The processor 310 may visualize voice data using speech to text (STT) technology. For example, the processor 310 may generate graphic data by inputting a caption having the same content as the voice data and adding various graphic effects.

According to various embodiments, when there is image data in the input data, the processor 310 may generate graphic data based on motion included in the image data. According to an embodiment, the processor 310 may analyze motion included in image data using a motion deep learning module.

According to various embodiments, when there is photo data in the input data, the processor 310 may generate graphic data based on a facial expression of a person included in the photo data. The processor 310 may determine emotion information from facial expressions using facial expression recognition technology.

According to various embodiments, the processor 310 may store the generated live message in the memory 360 . The processor 310 may directly transmit the live message generated by executing the message application, or may select and transmit one of at least one live message stored in the memory 360 . According to an embodiment, when information corresponding to the input data is stored in the memory 360, the processor 310 may generate at least a plurality of recommended graphic data based on previously generated graphic data. The processor 310 may select one of a plurality of recommended graphic data based on a user input. According to an embodiment, the processor 310 may provide an edit menu to guide the user to create a live message to which desired graphic effects are added.

According to various embodiments, the processor 310 may establish a communication connection with an external device (eg, a smart phone, a tablet, or a smart watch) using the communication module 350. there is. The processor 310 may determine the type of external device that has established a communication connection and determine at least one data type to be included in a live message to be transmitted to the external device. According to an embodiment, the processor 310 may determine the data type included in the live message according to the hardware configuration of the external device. For example, if the external device does not have a display, the live message generated by the processor 310 may not include camera data, text data, and emoticon data.

4 illustrates that an electronic device generates a live message based on video and audio data according to various embodiments.

According to various embodiments, a processor (eg, the processor 310 of FIG. 3 ) may provide a camera preview to the preview area 410 of the execution screen of the message application. The processor may execute a camera (eg, camera 340 of FIG. 3 ) function based on a user input to a camera button located in the message application. According to an embodiment, when voice data is included in the input data (eg, the input data 210 of FIG. 2 ), the processor displays a graphic object 414 indicating that voice data is being received in the preview area 410 . more can be displayed. An image capture button 412 may be further included in the preview area 410 , and the processor may start and end image capture based on a user input to the capture button 412 .

According to various embodiments, the processor may generate graphic data (eg, graphic data 220 of FIG. 2 ) based on input data. For example, referring to FIG. 4 , the processor may generate graphic data by visualizing audio of input data. When the voice of the input data is "in the mood for food", the processor may generate graphic data including a graphic caption 420 having the same content as the voice. The processor may generate graphic subtitles 420 having various visual effects. Alternatively, the processor may generate graphic data by determining emotion information of a person in input data using an emotion deep learning module and a motion deep learning module. The processor may generate a live message 430 having a selected extension (eg, .jpg, .gif, or .mp4) by synthesizing the generated graphic data with the input data. The live message 430 may include audio and video. The processor may store the generated live message 430 in a memory (eg, the memory 360 of FIG. 3 ).

According to various embodiments, the processor may transmit the generated live message 430 to an external device through a message application. The processor may provide at least one live message 430 stored in the memory to one area of the application execution screen based on a user input. The processor may store all generated live messages 430 in one area of memory. The processor may transmit the live message 430 through the message application based on user input.

5 illustrates generating a live message based on image data by an electronic device according to various embodiments.

According to various embodiments, when the image data 510 is included in the input data (eg, the input data 210 of FIG. 2 ), the processor (eg, the processor 310 of FIG. 3 ) is included in the image data 510 . Graphic data (eg, graphic data 220 of FIG. 2 ) may be generated by analyzing the generated motion. The processor may analyze motion included in the image data 510 using a motion deep learning module. The motion deep learning module may learn various motions in advance by capturing motions of objects in the image data 510 . The processor may create a graphic object 520 corresponding to the motion analyzed through the motion deep learning module. For example, referring to FIG. 5 , the processor may receive image data 510 based on a user input for a photographing button. At this time, if the person in the video makes a kissing motion, the motion deep learning module can detect the corresponding motion. The processor may create a heart-shaped graphic object 520 suitable for motion in the image data 510 . The processor may generate and provide at least one graphic data on the preview screen of the message application, select the optimal graphic data among them based on a user input, and display the live message 530 (eg, the live message 430 of FIG. 4 ). )) can be created.

According to various embodiments, the processor may transmit a live message 530 generated based on a user input. The live message 530 may be composed of a combination of image data 510 and graphic data. The processor may set the position of the graphic data to change along with the motion of the object in the image.

6 illustrates generating a live message based on photo data by an electronic device according to various embodiments of the present disclosure.

According to various embodiments, a processor (eg, processor 310 of FIG. 3 ) may generate a live message 630 (eg, live message 430 of FIG. 4 ) based on a facial expression of a person in photo data. According to an embodiment, the processor may determine emotion information by analyzing the expression 610 of the person using the deep emotion learning module. The processor may generate a spatial learning model by learning a convolutional neural network (CNN) with respect to spatial features of the acquired photo data. According to an embodiment, the processor may analyze the facial expression 610 using a recursive neural network including at least one of a recurrent neural network (RNN), a gated recurrent unit (GRU), and long short-term memory (LSTM). . For example, referring to FIG. 6 , the processor may analyze a facial expression 610 of a person in a photo to recognize a smiling expression 610 and determine that the facial expression 610 is a happy emotion. The processor may generate graphic data (eg, graphic data 220 of FIG. 2 ) including at least one graphic object 620 (eg, a laughing emoticon) corresponding to the analyzed facial expression 610 . According to an embodiment, graphic data generated by a processor may be disposed in an area partially overlapping input data (eg, input data 210 of FIG. 2 ). The graphic data generated by the processor may be fixed at a fixed location or the location may change over time.

According to various embodiments, the processor may generate a live message 630 by synthesizing the generated graphic data and input data, and transmit the live message 630 through a message application based on a user input.

7A and 7B illustrate a graphic UI provided to generate a real-time message in an electronic device according to various embodiments.

According to various embodiments, a processor (eg, processor 310 of FIG. 3 ) may provide a graphic UI for generating a live message (eg, live message 430 of FIG. 4 ) to a message application. Referring to FIG. 7A , the processor may provide a live message creation button 710 on one side of the message input window. The processor may provide a preview area 760 and various menus for generating a live message based on a user input to the live message creation button 710 . The processor may display a menu bar including at least one button providing functionality for creating a live message. The menu bar may include a camera button 720, and the processor may display a camera preview on one side of the message application execution screen based on a user input to the camera button 720. The processor may further include at least one of a menu for generating an emoticon, a menu for generating an image, and a menu for receiving voice data in the menu bar. The preview area 760 may include at least one button for starting camera capture. The processor may receive input data (eg, input data 210 of FIG. 2 ) based on a user input for a photographing button.

According to various embodiments, the processor may further provide a full screen button 740 and a screen reduction button 750 in the preview area 760 . The processor may adjust the size of the preview area 760 based on user inputs to the full screen button 740 and the screen reduction button 750 . For example, when the user touches the full screen button 740, the preview area 760 may be expanded to the entire display (eg, the display 320 of FIG. 3). Conversely, if the user touches the screen reduction button 750 in the full screen state, the preview area 760 may be reduced to a part of the message application execution screen again.

According to various embodiments, the processor may provide an edit menu 770 providing a function for editing graphic data to be generated (eg, graphic data 220 of FIG. 2 ). The processor may display a collapse icon 730 of the edit menu 770 on one side of the preview area 760, and display the edit menu 770 on the display based on a user input for the collapse icon 730. . Referring to FIG. 7B , an edit menu 770 may include at least one of a font/size adjustment menu 772, a speech bubble menu 774, a music menu 776, and an effect menu 778.

According to various embodiments, a function of changing a size of a graphic object created by a processor or a font of graphic subtitles may be provided. The processor may edit the graphic object based on a user input to the font/size adjustment menu 772 of the edit menu 770 . For example, when the processor generates graphic data including a graphic caption such as 'good morning', the user can change the size and font of the graphic caption using the font/size adjustment menu 772 .

According to various embodiments, the processor may generate graphic captions having various forms based on a user input to the speech bubble menu 774 . For example, the processor may generate a graphic caption based on acquired voice data, and may generate a live message by combining the graphic caption generated based on a user input to the speech bubble menu 774 with the input data. According to an embodiment, the processor may generate a graphic caption and a speech bubble displaying the graphic caption together, and may provide speech bubbles of various shapes (eg, circle, rectangle, cloud shape).

According to various embodiments, the processor may determine background music for the live message based on user input to the music menu 776 . The processor may store at least a portion of the sample music in a memory (eg, the memory 360 of FIG. 3 ). According to an embodiment, the processor may determine background music in conjunction with a third party music application. According to an embodiment, the processor may adjust the volume of the background music based on a user input, and may determine a low volume of the background music when voice data is included in the input data.

According to various embodiments, the processor may add various visual effects (VFXt) to graphic data based on a user input to the effects menu 778 . Graphic effects that can be provided by the processor may include at least one of motion graphics, retouching, compositing, animation, lighting, and FX (effects). For example, the processor may analyze the motion of the image data and generate and synthesize an emoticon corresponding thereto.

According to various embodiments, the processor may further include a menu minimization button 779 in the edit menu 770 . The processor may hide the edit menu 770 based on a user input to the menu minimization button 779 .

8 illustrates data types according to types of external devices according to various embodiments.

According to various embodiments, a processor (eg, the processor 310 of FIG. 3 ) may generate a live message (eg, the live message 430 of FIG. 4 ) including at least one data type. The processor may classify the input data 810 (eg, the input data 210 of FIG. 2 ) received by the electronic device 800 into at least one data type and store the same. The processor may establish a communication connection with the external device 820 using a communication module (eg, the communication module 350 of FIG. 3 ) and determine the data type to be included in the live message according to the type of the external device 820. .

According to various embodiments, the processor may determine the data type to be transmitted according to the hardware configuration included in the external device 820 . For example, the first live message 810a to be transmitted to the first external device 820a having a display and audio interface may include voice data, text data, emoticon data, and camera data. The second live message 810b to be transmitted to the second external device 820b having only an audio interface may include only audio data. The third live message 810c to be transmitted to the third external device 820c having only a display may include text data, emoticon data, and camera data. A method of constructing data according to the hardware configuration of the external device 820 to which the processor is communicatively connected is not limited to the example of data shown in FIG. 8 .

9 illustrates generating a real-time message based on voice data in an electronic device according to various embodiments.

According to various embodiments, a processor (eg, the processor 310 of FIG. 3 ) receives input data 910 (eg, the input data 210 of FIG. 2 ) received from a user device 900 communicatively connected to the electronic device 930 . )), a live message 940 (eg, the live message 430 of FIG. 4) may be generated. The user device 900 may transmit the received input data 910 to the electronic device 930 using a communication connection. The processor may generate a live message 940 including at least one data type 920 of a voice data type, a text data type, an emoticon data type, and a camera data type based on the received input data 910 . The processor may transmit the generated live message 940 to an external device (eg, the external device 820 of FIG. 8 ). Since the processor generates the live message 940 based on the input data 910 received from the user device 900, the data type 920 included in the live message 940 is hardware included in the user device 900. It can be determined according to the configuration.

For example, referring to FIG. 9 , the processor may receive voice data 910 from a user device 900 equipped with an audio interface. The processor may generate graphic data including text data and emoticon data based on the received voice data 910 . Text data generated by the processor may be data expressing voice data 910 as graphic captions, and emoticon data may be data corresponding to a situation analyzed based on the received voice data 910 . The processor may generate a live message by synthesizing the generated graphic data and input data. The processor may generate a live message 940 including data 920 of at least one of voice data, text data, emoticon data, and camera data. At this time, since there is no input data 910 received from the camera of the electronic device 930 (eg, the camera 340 of FIG. 3 ), the generated live message 940 may not include camera data. The processor may transmit the live message 940 through the message application.

An electronic device according to various embodiments includes a display, a microphone, a camera, a memory, and a processor operatively connected to the display, the microphone, the camera, and the memory, wherein the processor executes a message application and , Based on a user input for a menu provided on the message application execution screen, input data received by at least one of the microphone and the camera is acquired, an emotional state of a person included in the input data is analyzed, and the analysis An electronic device configured to generate graphic data including at least one graphic object based on one emotional state, and generate a live message based on the input data and the graphic data.

According to various embodiments, the electronic device further includes a communication module, and the processor establishes a communication connection with an external device using the communication module, and includes at least one message included in a live message based on the type of the external device. An electronic device configured to determine one data type, generate a live message including the determined at least one data type, and transmit the live message to the external device.

According to various embodiments, when the external device includes a display, an electronic device configured to generate a live message including at least one of camera data, text data, and emoticon data.

According to various embodiments, an electronic device configured to generate a live message including a voice data type when the external device includes an audio interface.

According to various embodiments, the processor is configured to generate graphic data including at least one of an emoticon, text, and graphic effect.

According to various embodiments, the processor is configured to store the live message in the memory and transmit the live message through a message application based on a user input.

According to various embodiments, the electronic device configured to generate graphic data based on STT (Speech To Text) based graphic subtitles and voice context when the input data includes voice.

According to various embodiments of the present disclosure, the electronic device configured to generate graphic data based on motion included in the image, when the input data includes an image.

According to various embodiments, the processor is configured to generate at least one graphic data and select one of the at least one graphic data based on a user input.

According to various embodiments of the present disclosure, the electronic device configured to generate graphic data based on a pre-generated live message when a live message corresponding to the motion is pre-generated and stored in the memory.

According to various embodiments, the processor is configured to analyze at least one of a facial expression of a person included in a picture of the input data, a position of the person, and a surrounding object, and generate graphic data corresponding thereto.

According to various embodiments, when the input data includes a smiling person, the processor determines an emotional state by recognizing at least one of voice, motion, and facial expression of the person, and laughs based on the determined emotional state. An electronic device configured to generate graphic data including at least an emoticon, and to generate a live message by synthesizing the input data and the graphic data.

10 is a flowchart of a method of generating a message in real time by an electronic device according to various embodiments.

The method shown in FIG. 10 may be performed by the electronic device (e.g., the electronic device 101 of FIG. 1) described with reference to FIGS. 1 to 9, and descriptions of the technical features described above are omitted below. I'm going to do it.

According to various embodiments, in operation 1002, the electronic device may execute a message application. An electronic device may exchange messages with an external device (eg, the external device 820 of FIG. 8 ) connected through communication through a message application.

According to various embodiments, in operation 1004, the electronic device receives input data (eg, input data of FIG. 2 (eg, the camera 340 of FIG. 3) or a microphone (eg, the microphone 330 of FIG. 3). 210)) can be received. According to an embodiment, the electronic device may obtain input data received through a user device connected to the electronic device through short-range communication. The input data may include at least one of audio, video and pictures.

According to various embodiments, the electronic device may analyze input data using an emotion deep learning module and a motion deep learning module. The emotion deep learning module can determine the character's emotion information by analyzing the voice, facial expression, and voice data of the character appearing in the input data. The electronic device may determine at least one emotion information (eg, joy, sadness, excitement, anger, fear, tenderness) by controlling the emotion deep learning module. The motion deep learning module can determine emotion information by analyzing motions of characters appearing in input data.

According to various embodiments, in operation 1006, the electronic device may generate a live message (eg, the live message 430 of FIG. 4 ) based on the input data and store it in a memory (eg, the memory 360 of FIG. 3 ). there is. The electronic device may generate different graphic data (eg, graphic data 220 of FIG. 2 ) according to the type of data included in the input data. The data type may include voice data, text data, emoticon data, and camera data.

According to various embodiments, when there is audio data in the input data, the electronic device may generate graphic data including a graphic caption based on the audio data. The electronic device may visualize voice data using speech to text (STT) technology. The electronic device may generate graphic data by inputting a caption having the same content as the audio data and adding various graphic effects.

According to various embodiments, when there is image data in the input data, the electronic device may generate graphic data based on motion included in the image data. According to an embodiment, the electronic device may analyze motion included in image data using a motion deep learning module. The electronic device may generate text or emoticon corresponding to the analyzed motion.

According to various embodiments, when there is photo data in the input data, the electronic device may generate graphic data based on a facial expression of a person included in the photo data. An electronic device may determine emotion information from a facial expression using facial expression recognition technology.

According to various embodiments, the electronic device may store the created live message in memory. The electronic device may directly transmit a live message created by executing a message application, or select and transmit one of at least one live message stored in a memory. According to an embodiment, when information corresponding to input data is stored in a memory, the electronic device may generate at least a plurality of recommended graphic data based on previously generated graphic data. The electronic device may select one of a plurality of recommended graphic data based on a user input. According to an embodiment, the electronic device may provide an edit menu to guide the user to create a live message to which desired graphic effects are added.

According to various embodiments, in operation 1010, the electronic device may transmit a live message based on a user input. The electronic device may establish a communication connection with an external device using a communication module (eg, the communication module 350 of FIG. 3 ) and transmit a live message through a message application.

According to various embodiments, in operation 1012, the electronic device identifies an external device to receive the live message, and in operation 1014, the electronic device determines a data type to be included in the live message according to the external device. According to an embodiment, the electronic device may determine the type of data included in the live message according to the hardware configuration of the external device. If the external device has a display, the live message generated by the electronic device may include camera data, text data, and emoticon data. If the external device has an audio interface, the live message generated by the electronic device may include voice data.

11 is a flowchart of a method of generating live data by an electronic device according to various embodiments.

According to various embodiments, in operation 1102, the electronic device may receive input data and check whether voice data is included in the input data in operation 1110. If audio data is included in the input data, in operation 1112, the electronic device may generate a graphic caption based on the audio data. The graphic caption may have a form in which graphic effects are added based on the content of audio data.

According to various embodiments, the electronic device may map and store at least one word and at least one graphic element corresponding to the corresponding word in a memory. In operation 1114, if the input data includes a word defined in advance, the electronic device may generate a graphic element corresponding thereto. According to various embodiments, in operation 1120, the electronic device includes image data in the input data can check if there is. When video data is included in the input data, in operation 1122, the electronic device may analyze the emotion of a person appearing in the video data based on the motion included in the video data. According to an embodiment, the electronic device may learn various motions using a motion deep learning module and analyze emotions of a person based on the learning.

According to various embodiments, in operation 1130, the electronic device may analyze emotions based on facial expressions of characters in the input data. Electronic devices may use various face recognition technologies.

According to various embodiments, in operation 1140, the electronic device may generate a graphic element corresponding to emotion information analyzed based on motion and expression. The electronic device may generate graphic data to which visual effects such as emoticons and texts are added based on emotion information analyzed using the emotion deep learning module and the motion deep learning module. According to an embodiment, when a specific word is included in voice data, the electronic device may create an emoticon graphic element expressing the corresponding word. For example, if the word 'love' is included in the voice data, the processor may generate an emoticon including a shape (eg, a heart shape, a kiss, a rose) capable of expressing the word. The electronic device may express voice data including 'love' in the form of a graphic caption and display an emoticon such as a heart on one side of the graphic caption. In addition to this, the electronic device may generate a live message by synthesizing graphic data and input data generated using various visual effects, and transmit the message to an external device through a message application.

A real-time message generation method of an electronic device according to various embodiments includes an operation of executing a message application and obtaining input data received through at least one of a microphone and a camera based on a user input for a menu provided on a message application execution screen. operation of analyzing the emotional state of the person included in the input data, operation of generating graphic data including at least one graphic object based on the analyzed emotional state, operation of generating graphic data including the input data and the graphic data and generating a live message based on the

According to various embodiments, an operation of establishing a communication connection with an external device using the communication module, an operation of determining at least one data type included in a live message based on the type of the external device, and The method further comprising generating and transmitting a live message including the determined at least one data type to the external device.

According to various embodiments, the generating of the live message may further include generating a live message including at least one of camera data, text data, and emoticon data when the external device includes a display. .

According to various embodiments, the generating of the live message may further include generating a live message including a voice data type when the external device includes an audio interface.

According to various embodiments, the transmitting of the live message may further include storing the live message in the memory and transmitting the live message through a message application based on a user input.

According to various embodiments, the generating of the graphic data may include generating graphic data based on STT (Speech To Text) based graphic subtitles and voice context when the input data includes voice. How to include more.

According to various embodiments, the generating of the graphic data may further include, when the input data includes an image, generating the graphic data based on motion included in the image.

According to various embodiments of the present disclosure, the generating of the graphic data may include analyzing at least one of a facial expression of a person included in a picture of the input data, a position of the person, and a surrounding object, and generating graphic data corresponding thereto. How to include more.

Claims (15)

1. In electronic devices,

   display;

   MIC;

   camera;

   Memory; and

   a processor operatively connected with the display, the microphone, the camera, and the memory;

   the processor,

   Launch the Messages application,

   Obtaining input data received by at least one of the microphone and the camera based on a user input for a menu provided on the message application execution screen;

   Analyzing the emotional state of the person included in the input data;

   Based on the analyzed emotional state, graphic data including at least one graphic object is generated;

   An electronic device configured to generate a live message based on the input data and the graphic data.
2. According to claim 1,

   The electronic device further includes a communication module,

   the processor,

   Establishing a communication connection with an external device using the communication module;

   Determine at least one data type included in the live message based on the type of the external device;

   An electronic device configured to generate and transmit a live message including at least one determined data type to the external device.
3. According to claim 2,

   If the external device includes a display,

   An electronic device configured to generate a live message containing at least one of camera data, text data and emoticon data.
4. According to claim 2,

   If the external device includes an audio interface,

   An electronic device configured to generate live messages containing voice data types.
5. According to claim 1,

   the processor,

   An electronic device configured to generate graphic data containing at least one of emoticons, text and graphic effects.
6. According to claim 1,

   the processor,

   store the live message in the memory;

   An electronic device configured to transmit the live message through a message application based on a user input.
7. According to claim 1,

   the processor,

   An electronic device configured to generate graphic data based on STT (Speech To Text) based graphic subtitles and voice context when voice is included in the input data.
8. According to claim 1,

   the processor,

   An electronic device configured to generate graphic data based on motion included in the image when the input data includes an image.
9. According to claim 8,

   the processor,

   generate at least one graphic data;

   An electronic device configured to select one of the at least one graphic data based on a user input.
10. According to claim 9,

    the processor,

    An electronic device configured to generate graphic data based on a pre-generated live message when a live message corresponding to the motion is pre-generated and stored in the memory.
11. According to claim 1,

    the processor,

    An electronic device configured to analyze at least one of a facial expression of a person included in a picture of the input data, a position of the person, and a surrounding object, and generate graphic data corresponding thereto.
12. According to claim 1,

    the processor,

    If the input data includes a laughing person,

    determining an emotional state by recognizing at least one of voice, motion, and facial expression of the person;

    Generating graphic data including at least a laughing emoticon based on the determined emotional state;

    An electronic device configured to generate a live message by synthesizing the input data and the graphic data.
13. A real-time message generation method of an electronic device,

    the operation of running a message application;

    Obtaining input data received through at least one of a microphone and a camera based on a user input for a menu provided on the message application execution screen;

    Analyzing the emotional state of a person included in the input data;

    generating graphic data including at least one graphic object based on the analyzed emotional state;

    and generating a live message based on the input data and the graphic data.
14. According to claim 13,

    Establishing a communication connection with an external device using the communication module;

    determining at least one data type included in a live message based on the type of the external device; and

    The method further comprising generating and transmitting a live message including the determined at least one data type to the external device.
15. According to claim 14,

    The operation of generating the live message,

    If the external device includes a display,

    The method further comprising generating a live message including at least one of camera data, text data, and emoticon data.

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