KR20180080986A - artificial intelligence information system for emoticon service based on machine learning - Google Patents

Abstract

The present invention relates to a machine learning-based artificial intelligence emoticon service providing system. According to an embodiment of the present invention, a machine learning-based artificial intelligence emoticon providing system comprises: a first terminal into which at least one piece of first content is inputted; a server to receive the first content from the first terminal, classify text included in the first content into preset units to generate a plurality of pieces of second text, filter at least one piece of third text satisfying a preset condition among the plurality of pieces of second text, and determine at least one first emoticon matching the third text among a plurality of previously stored emoticons; and a second terminal to receive the first emoticon from the server.

Description

Technical Field [0001] The present invention relates to an artificial intelligence information providing system,

The present invention relates to a machine learning based artificial intelligent emoticons service providing system.

A terminal such as a personal computer, a notebook computer, a mobile phone, or the like can be configured to perform various functions. Examples of such various functions include a data and voice communication function, a function of photographing a video or a moving image through a camera, a voice storage function, a music file playback function through a speaker system, and an image or video display function. Some terminals include additional functions to execute games, and some other terminals are also implemented as multimedia devices. Moreover, recent terminals can receive a broadcast or multicast signal to view a video or television program.

In general, a terminal can be divided into a mobile terminal (mobile / portable terminal) and a stationary terminal according to whether the terminal can be moved. The mobile terminal can be divided into a handheld terminal and a vehicle mount terminal according to whether the user can directly carry the mobile terminal.

Such a terminal has various functions, for example, in the form of a multimedia device having multiple functions such as photographing and photographing of a moving picture, reproduction of a music or video file, reception of a game and broadcasting, etc. .

In order to support and enhance the functionality of such terminals, it may be considered to improve the structural and / or software parts of the terminal.

Meanwhile, in a mobile environment using a terminal, a method of communicating a user is gradually moving toward the center of visual communication, and an agent for visualizing and designing a message to be transmitted by the user is needed.

Currently, there are attempts to communicate with various icons, pictures, etc. in order to express their own emotions. However, the process is complicated and difficult to express delicately and richly.

Therefore, there is a need for a method of providing a pleasant user experience by adding artificial intelligence and design technology and fusing various characters.

Korea Patent Office Application No. 10-2012-0131936

SUMMARY OF THE INVENTION It is an object of the present invention to provide a system for providing an artificial intelligent emotion service based on a machine learning to a user.

Specifically, the present invention aims to provide a system and an application for analyzing emotional elements and contexts contained in a user's message using a machine learning-based artificial intelligence technology and expressing character emoticons in real time.

An object of the present invention is to provide a user with an artificial intelligence convergence that recognizes context data (emotion, environment, objects, etc.) through message analysis and re-processes the data into emoticons as visual communication tools.

It is also an object of the present invention to provide a user with an application and an API that can be used for general purposes without limiting to a specific service or application in consideration of a use environment for inputting text.

It is another object of the present invention to provide an artificial intelligence machine learning system based on a word vector that is more accurate as the user learns and uses the conversation habit pattern and provides the same to a user.

The present invention proposes a more accurate and convenient communication experience by combining artificial intelligence and design technology in messaging communication, which occupies most of mobile communication, and innovates the experience of using current emoticons, The goal is to enable intelligence to analyze the dialogue and recombine graphical elements in real time to enable unlimited expression.

It is another object of the present invention to develop a technology for designing contents that are constantly created in SNS, blog, media and the like using an input interface as well as a message application.

It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are not intended to limit the invention to the precise form disclosed. It can be understood.

According to an embodiment of the present invention, there is provided a system for providing artificial intelligence emoticons based on a machine learning method, the system comprising: a first terminal for inputting at least one first content; A second terminal for receiving the first content from the first terminal, generating a plurality of second texts by classifying the text included in the first content into a predetermined unit, A server for filtering at least one third text and determining at least one first emoticon matching the third text among a plurality of previously stored emoticons; And a second terminal for receiving the first emoticon from the server.

The first content may include text information, image information, moving image information, and audio information.

If the first content is image information or moving image information, the server extracts text included in the image information or moving image information, classifies the extracted text into the predetermined unit, If the first content is audio information, the server converts the audio information into text information, and generates the plurality of second texts by classifying the converted text information into the preset unit .

The predetermined unit may be a morpheme unit, and the server may convert at least some of the plurality of second texts to basic verbs.

In addition, the predetermined condition may be whether the text has a meaning.

The plurality of third texts may be plural, and the plurality of first emoticons matching the plurality of third texts may be plural.

The server may classify the plurality of third texts into at least one category among a plurality of predetermined categories, count the number of the classified third texts by category, Assigning a result value to a third text belonging to each category, determining a plurality of first emoticons matching the plurality of third texts among the plurality of emoticons stored in advance, The arrangement order of the plurality of first emoticons can be determined.

The server may transmit the plurality of first emoticons and the arrangement order to the first terminal, the first terminal displays the plurality of first emoticons according to the arrangement order, Transmits the information on the second emoticon to the server when the user of the first emoticon selects the second emoticon among the plurality of first emoticons, and the server can transmit the second emoticon to the second terminal.

When at least one second content is additionally input through the first terminal, the server receives the second content from the first terminal, classifies the text included in the second content into a predetermined unit Wherein the third-2-th text is generated by filtering the at least one third-2-th text satisfying a preset condition among the plurality of second-second texts, 2 < / RTI > text corresponding to the first emoticon.

Also, the first terminal includes a plurality of first terminals, data related to operations between the first terminals, the second terminals and the server are stored in the server, and the server cumulatively uses the stored data, learning can be performed.

SUMMARY OF THE INVENTION The present invention has been made to overcome the above-mentioned problems, and it is an object of the present invention to provide a system for providing an artificial intelligent emoticons service based on a machine learning to a user.

Specifically, the present invention can provide a system and an application for analyzing emotional elements and contexts contained in a user's message using a machine learning-based artificial intelligence technology and expressing character emoticons in real time.

In addition, the present invention can provide a user with artificial intelligence convergence that recognizes context data (emotion, environment, objects, etc.) through message analysis and re-processes the data into emoticons as visual communication tools.

In addition, the present invention can provide a user with an application and an API that can be used for general purposes without being limited to a specific service or application in consideration of a use environment for inputting text.

Further, according to the present invention, a word vector-based artificial intelligent machine learning system can be constructed and provided to a user as the learning habit pattern of a user is learned and used.

In addition, the present invention proposes a more accurate and convenient communication experience by combining artificial intelligence and design technology in messaging communication, which occupies most of the mobile communication, and provides the user with experience of present emoticon usage Allowing artificial intelligence to analyze the conversation and recombine graphic elements in real time to enable unlimited expression.

In addition, the present invention can develop not only a message application but also a technology for designing contents that are constantly created in SNS, blog, media using an input interface.

The present invention analyzes and combines various variables such as keywords, emotion, usage frequency, preference, climate, date, time, place, issue, and the like, unlike the conventional usage method in which the purchased character emoticon contents are repeatedly used, It is possible to use.

In addition, according to the present invention, a character emoticon expression changes in real time according to an input word or a symbol (number) element, so that a user can identify and express his / her emotions.

In addition, the present invention can reduce the technical constraints such as delays generated in the calculation process through the user-friendly UX design and communicate the communication process more intimately to the user.

Further, the present invention can continuously improve the accuracy of artificial intelligence through machine learning.

It should be understood, however, that the effects obtained by the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those skilled in the art to which the present invention belongs It will be possible.

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate a preferred embodiment of the invention and, together with the description, serve to provide a further understanding of the technical idea of the invention, It should not be construed as limited.
FIG. 1 is a block diagram of a machine learning based artificial intelligence emoticon service providing system proposed by the present invention.
2 is a block diagram of a terminal or a server according to the present invention.
FIG. 3 is a flowchart for explaining a method of providing an artificial intelligent emoticons service based on the machine learning proposed by the present invention.
FIG. 4 shows a concrete example of each step of the artificial intelligence emoticon service providing method based on the machine learning shown in FIG.
FIG. 5 shows a specific example in which the emoticon expressed in accordance with the change of the emotion of the user or the intensity of the emotion is changed, in the context of the present invention.
FIG. 6 is a flowchart illustrating a method of arranging emoticons in order of relevance and selecting by the user, according to another embodiment of the present invention.
7 is a flowchart illustrating a method for a user to select a related emoticon in real time when an additional message is input from a user before transmission of the emoticon is performed, according to another embodiment of the present invention.
FIG. 8 shows a specific example of analyzing the morpheme through the contents inputted by the user in FIG. 6 or FIG.
FIG. 9 shows a specific example of the present invention for extracting keywords based on the morpheme analyzed in FIG.
FIG. 10 shows an example of a concrete work for matching the related emoticons in the database based on the keyword extracted in FIG.
FIG. 11 shows a concrete example of arranging and matching emoticons matched in FIG. 10 to users in order of relevance.
FIG. 12 shows a specific example in which the user selects one of the plurality of emoticons displayed in FIG. 11 and transmits the selected emoticons.
FIG. 13 shows a specific example in which, when an additional message is input from the user before transmission of the emoticon in FIG. 12, it is reflected in real time.
14 and 15 show a specific example of providing a machine learning based artificial intelligence emoticone service in the case of English in connection with the present invention.

The emoji market has spread around the millennial generation and is now widely used by generations, with more than 6 billion emoticons around the world sent in a day as of last year (Oxford University in 2015).

Emoticons evolve into easy-to-use, diverse emotional expressions and evolve into new ways of communication that complement the limitations of text in ancillary means of enjoying text communication.

Emoji As a foreign market, Facebook offers free emoticons as a separate messenger application, and China Wichat sells paid emoticons.

In addition, Snapchat recently acquired Bitstrips (2016), which produces personal emoticons for $ 100 million.

The domestic market for emoji (emoji) is estimated to be 100 billion won, and the figure for character doll is estimated to be 200 billion won. The annual usage and sales are growing rapidly between 30-40% annually (2015).

The average number of emoticons used in KakaoTalk is 200 million a day, and the monthly average of visitors to the emoticons store is 27 million. Seven of 10 users of KakaoTalk use the emoticons store more than once a month (2015).

Currently, Nintendo's Miitomo, launched in 2016, is a game that creates and utilizes similar avatars, and has gained a good response, with a million downloads in three days.

In addition, many users like Fleksy and SharingGIF are using the keyboard applications Fleksy and SharingGIF, which not only include characters but also sort out GIF files that are popular on the Internet by tags and find appropriate results.

As a result, in a mobile environment using a terminal, a method of communicating a user is gradually moving toward the center of visual communication, and an agent for visualizing and designing a message to be transmitted by the user is needed.

Currently, there are attempts to communicate with various icons, pictures, etc. in order to express their own emotions. However, the process is complicated and difficult to express delicately and richly.

Therefore, it is required to add artificial intelligence and design technology and to combine various characters to provide a pleasant user experience.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made to solve the above-mentioned problems occurring in the prior art, and an object of the present invention is to provide a system for providing an artificial intelligent emoticons service based on a machine learning.

Specifically, the present invention aims to provide a system and an application for analyzing emotional elements and contexts contained in a user's message using a machine learning-based artificial intelligence technology and expressing character emoticons in real time.

An object of the present invention is to provide a user with an artificial intelligence convergence that recognizes context data (emotion, environment, objects, etc.) through message analysis and re-processes the data into emoticons as visual communication tools.

It is also an object of the present invention to provide a user with an application and an API that can be used for general purposes without limiting to a specific service or application in consideration of a use environment for inputting text.

It is another object of the present invention to provide an artificial intelligence machine learning system based on a word vector that is more accurate as the user learns and uses the conversation habit pattern and provides the same to a user.

In addition, the present invention proposes a more accurate and convenient communication experience by combining artificial intelligence and design technology in messaging communication, which occupies most of the mobile communication, and provides the user with experience of present emoticon usage The purpose of the artificial intelligence is to analyze the conversation and to reconfigure the graphical elements in real time to enable infinite representation.

It is another object of the present invention to develop a technology for designing contents that are constantly created in SNS, blog, media and the like using an input interface as well as a message application.

FIG. 1 is a block diagram of a machine learning based artificial intelligence emoticon service providing system proposed by the present invention.

Referring to FIG. 1, a machine learning based artificial intelligence emoticon service providing system 1 proposed by the present invention can be divided into a content input unit 2, an emoticon generating unit 3, and an emoticon receiving unit 4.

The content input unit 2 provides a function of receiving contents such as text, voice, image, and moving picture from a user.

Next, the emoticon generation unit 3 provides a function of recognizing the context based on the content input through the content input unit 2, automatically converting the context into the most appropriate emoticon, and transmitting the emoticon.

The emoticon receiving unit 4 also provides a function of receiving emoticon data from the emoticon generating unit 3 and displaying it to the user.

Each of the content input unit 2, the emoticon generating unit 3, and the emoticon receiving unit 4 may be a terminal or a server.

In addition, the content input unit 2, the emoticon generation unit 3, and the emoticon reception unit 4 can exchange data with each other using short-distance communication or long-distance communication.

The local area communication applied herein may include Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), ZigBee, and Wi-Fi (Wireless Fidelity) technology.

Also, the applicable telecommunication may be a code division multiple access (CDMA), a frequency division multiple access (FDMA), a time division multiple access (TDMA), an orthogonal frequency division multiple access (OFDMA), a single carrier frequency division multiple access ) Technology.

Before describing the function of the machine learning-based artificial intelligence emoticon service providing system 1 proposed by the present invention, the contents input unit 2, the emoticon generating unit 3, or the terminal which can be the emoticon receiving unit 4 Describe the server in detail.

2 is a block diagram of a terminal or a server according to the present invention.

2, the terminal or server 100 includes a wireless communication unit 110, an A / V input unit 120, a user input unit 130, a sensing unit 140, an output unit 150, An interface unit 170, a control unit 180, a power supply unit 190, and the like.

However, the components shown in FIG. 2 are not essential, so that a terminal or server 100 device having more or fewer components may be implemented.

Hereinafter, the components will be described in order.

The wireless communication unit 110 may include one or more modules for enabling wireless communication between the terminal apparatus and the wireless communication system or between the terminal apparatus and the network in which the terminal apparatus is located. For example, the wireless communication unit 110 may include a broadcast receiving module 111, a mobile communication module 112, a wireless Internet module 113, a short range communication module 114, and a location information module 115 .

The broadcast receiving module 111 receives broadcast signals and / or broadcast-related information from an external broadcast management server through a broadcast channel.

The broadcast channel may include a satellite channel and a terrestrial channel. The broadcast management server may refer to a server for generating and transmitting broadcast signals and / or broadcast related information, or a server for receiving broadcast signals and / or broadcast related information generated by the broadcast management server and transmitting the generated broadcast signals and / or broadcast related information. The broadcast signal may include a TV broadcast signal, a radio broadcast signal, a data broadcast signal, and a broadcast signal in which a data broadcast signal is combined with a TV broadcast signal or a radio broadcast signal.

The broadcast-related information may refer to a broadcast channel, a broadcast program, or information related to a broadcast service provider. The broadcast-related information may also be provided through a mobile communication network. In this case, it may be received by the mobile communication module 112.

The broadcast-related information may exist in various forms. For example, an EPG (Electronic Program Guide) of DMB (Digital Multimedia Broadcasting) or an ESG (Electronic Service Guide) of Digital Video Broadcast-Handheld (DVB-H).

For example, the broadcast receiving module 111 may be a Digital Multimedia Broadcasting-Terrestrial (DMB-T), a Digital Multimedia Broadcasting-Satellite (DMB-S), a Media Forward Link Only And a Digital Broadcasting System (ISDB-T) (Integrated Services Digital Broadcast-Terrestrial). Of course, the broadcast receiving module 111 may be adapted to other broadcasting systems as well as the digital broadcasting system described above.

The broadcast signal and / or broadcast related information received through the broadcast receiving module 111 may be stored in the memory 160.

The mobile communication module 112 transmits and receives radio signals to at least one of a base station, an external terminal, and a server on a mobile communication network. The wireless signal may include various types of data depending on a voice call signal, a video call signal or a text / multimedia message transmission / reception.

The wireless Internet module 113 refers to a module for wireless Internet access, and may be built in or enclosed in a terminal device. WLAN (Wi-Fi), Wibro (Wireless broadband), Wimax (World Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access) and the like can be used as wireless Internet technologies.

The short-range communication module 114 refers to a module for short-range communication. Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), ZigBee, and the like can be used as a short range communication technology.

The position information module 115 is a module for obtaining the position of the terminal device, and a representative example thereof is a Global Position System (GPS) module.

Referring to FIG. 2, an A / V (Audio / Video) input unit 120 is for inputting an audio signal or a video signal, and may include a camera 121 and a microphone 122. The camera 121 processes an image frame such as a still image or moving image obtained by the image sensor in the video communication mode or the photographing mode. The processed image frame can be displayed on the display unit 151. [

The image frame processed by the camera 121 may be stored in the memory 160 or transmitted to the outside through the wireless communication unit 110. [ Two or more cameras 121 may be provided depending on the use environment.

The microphone 122 receives an external sound signal through a microphone in a communication mode, a recording mode, a voice recognition mode, or the like, and processes it as electrical voice data. The processed voice data can be converted into a form that can be transmitted to the mobile communication base station through the mobile communication module 112 when the voice data is in the call mode, and output. Various noise reduction algorithms may be implemented in the microphone 122 to remove noise generated in receiving an external sound signal.

The user input unit 130 generates input data for a user to control the operation of the terminal. The user input unit 130 may include a key pad dome switch, a touch pad (static / static), a jog wheel, a jog switch, and the like.

The sensing unit 140 senses the current state of the terminal device, such as the open / close state of the terminal device, the position of the terminal device, the presence or absence of user contact, the orientation of the terminal device, Thereby generating a sensing signal. For example, when the terminal device is in the form of a slide phone, it is possible to sense whether the slide phone is opened or closed. It is also possible to sense whether the power supply unit 190 is powered on, whether the interface unit 170 is connected to an external device, and the like. Meanwhile, the sensing unit 140 may include a proximity sensor 141.

The output unit 150 is for generating an output relating to visual, auditory or tactile sense and includes a display unit 151, an acoustic output module 152, an alarm unit 153, a haptic module 154, 155), and the like.

The display unit 151 displays (outputs) information processed by the terminal apparatus. For example, when the terminal device is in the call mode, a UI (User Interface) or GUI (Graphic User Interface) associated with the call is displayed. When the terminal device is in the video communication mode or the photographing mode, the photographed and / or received video or UI and GUI are displayed.

The display unit 151 may be a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), a flexible display display, and a 3D display.

Some of these displays may be transparent or light transmissive so that they can be seen through. This can be referred to as a transparent display, and a typical example of the transparent display is TOLED (Transparent OLED) and the like. The rear structure of the display unit 151 may also be of a light transmission type. With this structure, the user can see an object located behind the terminal body through the area occupied by the display unit 151 of the terminal body.

There may be two or more display units 151 depending on the implementation of the terminal apparatus. For example, in the terminal device, the plurality of display portions may be spaced apart or arranged integrally on one surface, and may be disposed on different surfaces, respectively.

(Hereinafter, referred to as a 'touch screen') in which a display unit 151 and a sensor for sensing a touch operation (hereinafter, referred to as 'touch sensor') form a mutual layer structure, It can also be used as an input device. The touch sensor may have the form of, for example, a touch film, a touch sheet, a touch pad, or the like.

The touch sensor may be configured to convert a change in a pressure applied to a specific portion of the display unit 151 or a capacitance generated in a specific portion of the display unit 151 into an electrical input signal. The touch sensor can be configured to detect not only the position and area to be touched but also the pressure at the time of touch.

If there is a touch input to the touch sensor, the corresponding signal (s) is sent to the touch controller. The touch controller processes the signal (s) and transmits the corresponding data to the controller 180. Thus, the control unit 180 can know which area of the display unit 151 is touched or the like.

The proximity sensor 141 may be disposed in an inner region of the terminal device to be wrapped by the touch screen or in the vicinity of the touch screen. The proximity sensor refers to a sensor that detects the presence or absence of an object approaching a predetermined detection surface or a nearby object without mechanical contact using the force of an electromagnetic field or infrared rays. The proximity sensor has a longer life span than the contact sensor and its utilization is also high.

Examples of the proximity sensor include a transmission type photoelectric sensor, a direct reflection type photoelectric sensor, a mirror reflection type photoelectric sensor, a high frequency oscillation type proximity sensor, a capacitive proximity sensor, a magnetic proximity sensor, and an infrared proximity sensor. And to detect the proximity of the pointer by the change of the electric field along the proximity of the pointer when the touch screen is electrostatic. In this case, the touch screen (touch sensor) may be classified as a proximity sensor.

Hereinafter, for convenience of explanation, the act of recognizing that the pointer is positioned on the touch screen while the pointer is not in contact with the touch screen is referred to as "proximity touch & The act of actually touching the pointer on the screen is called "contact touch. &Quot; The position where the pointer is proximately touched on the touch screen means a position where the pointer is vertically corresponding to the touch screen when the pointer is touched.

The proximity sensor detects a proximity touch and a proximity touch pattern (e.g., a proximity touch distance, a proximity touch direction, a proximity touch speed, a proximity touch time, a proximity touch position, a proximity touch movement state, and the like). Information corresponding to the detected proximity touch operation and the proximity touch pattern may be output on the touch screen.

In addition, the color sensor 142 is a sensor that provides a function of identifying a color included in an external object.

The color detection sensor 142 is a color identification sensor configured by combining a photodiode and a color filter. There are a monochromatic color sensor for measuring the amount of light of a specific color and an integrated color sensor capable of identifying a neutral color.

The monochromatic color sensor is a non-crystalline, adhered filter having a specific color transmission characteristic on the front surface of a Si photodiode. The incident light reaches a photodiode only through a wavelength in a certain range by a color filter.

In the integrated color sensor, red (R), green (G), and blue (B) filters corresponding to the three primary colors of light are bonded to the front surfaces of three photodiodes integrated on one substrate.

Therefore, since only the R, G, and B components reach the respective photodiodes, the original color can be identified according to the principle of the three primary colors of light.

In addition, the color sensing sensor 142 according to the present invention may provide a function of sensing at least one color included in an object photographed through the camera 121. [

Also, the display unit 151 may provide a light output function for emitting light to the outside.

Currently, the light output function in the terminal or the server 100 is provided as a flashlight function or the like.

Such a light output function may be provided through a structure using an LED.

However, the present invention is not limited thereto, and it is obvious that all the technical contents for emitting light to the outside can be applied.

The audio output module 152 may output audio data received from the wireless communication unit 110 or stored in the memory 160 in a call signal reception mode, a call mode or a recording mode, a voice recognition mode, a broadcast reception mode, The sound output module 152 also outputs sound signals related to functions (e.g., call signal reception tones, message reception tones, etc.) performed in the terminal device. The audio output module 152 may include a receiver, a speaker, a buzzer, and the like.

The alarm unit 153 outputs a signal for notifying the occurrence of an event of the terminal device. Examples of events that occur in a terminal device include receiving a call signal, receiving a message, inputting a key signal, and touch input. The alarm unit 153 may output a signal for notifying the occurrence of an event in a form other than the video signal or the audio signal, for example, vibration. The video signal or the audio signal may be output through the display unit 151 or the audio output module 152 so that they may be classified as a part of the alarm unit 153.

The haptic module 154 generates various tactile effects that the user can feel. A typical example of the haptic effect generated by the haptic module 154 is vibration. The intensity and pattern of the vibration generated by the hit module 154 can be controlled. For example, different vibrations may be synthesized and output or sequentially output.

In addition to the vibration, the haptic module 154 may include a pin arrangement vertically moving with respect to the contact skin surface, a spraying force or a suction force of the air through the injection port or the suction port, a touch on the skin surface, contact with an electrode, And various tactile effects such as an effect of reproducing a cold sensation using an endothermic or exothermic element can be generated.

The haptic module 154 can be implemented not only to transmit the tactile effect through the direct contact but also to allow the user to feel the tactile effect through the muscular sensation of the finger or arm. At least two haptic modules 154 may be provided according to the configuration of the portable terminal.

The projector module 155 is a component for performing an image project function using the terminal device and may have the same or at least a part of the image displayed on the display part 151 in accordance with a control signal of the control part 180 Can display other images on an external screen or wall.

Specifically, the projector module 155 includes a light source (not shown) that generates light (for example, laser light) for outputting an image to the outside, a light source And a lens (not shown) for enlarging and outputting the image at a predetermined focal distance to the outside. Further, the projector module 155 may include a device (not shown) capable of mechanically moving the lens or the entire module to adjust the image projection direction.

The projector module 155 can be divided into a CRT (Cathode Ray Tube) module, an LCD (Liquid Crystal Display) module and a DLP (Digital Light Processing) module according to the type of the display means. In particular, the DLP module may be advantageous for miniaturization of the projector module 151 by enlarging and projecting an image generated by reflecting light generated from a light source on a DMD (Digital Micromirror Device) chip.

Preferably, the projector module 155 may be provided on the side, front or back side of the terminal device in the longitudinal direction. It goes without saying that the projector module 155 may be provided at any position of the terminal device as needed.

The memory unit 160 may store a program for processing and controlling the control unit 180 and temporarily store the input / output data (e.g., telephone directory, message, audio, For example. The memory unit 160 may also store the frequency of use of each of the data (for example, each telephone number, each message, and frequency of use for each multimedia). In addition, the memory unit 160 may store data on vibration and sound of various patterns output when the touch is input on the touch screen.

The memory 160 may be a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (for example, SD or XD memory), a RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM A disk, and / or an optical disk. The terminal device may operate in association with a web storage that performs a storage function of the memory 160 on the Internet.

The interface unit 170 serves as a path for communication with all external devices connected to the terminal device. The interface unit 170 receives data from an external device, receives power from the external device, transfers the data to each component in the terminal device, or transmits data in the terminal device to an external device. For example, a wired / wireless headset port, an external charger port, a wired / wireless data port, a memory card port, a port for connecting a device having an identification module, an audio I / O port, A video input / output (I / O) port, an earphone port, and the like may be included in the interface unit 170.

The identification module is a chip for storing various kinds of information for authenticating the use right of the terminal device and includes a user identification module (UIM), a subscriber identity module (SIM), a universal user identity module Module, USIM), and the like. Devices with identification modules (hereinafter referred to as "identification devices") can be manufactured in a smart card format. Therefore, the identification device can be connected to the terminal through the port.

The interface unit may be a path through which power from the cradle is supplied to the mobile terminal when the mobile terminal is connected to an external cradle or a channel through which various command signals input from the cradle by the user are transmitted to the mobile terminal . The various command signals or the power source input from the cradle may be operated as a signal for recognizing that the mobile terminal is correctly mounted on the cradle.

The controller 180 typically controls the overall operation of the terminal device. For example, voice communication, data communication, video communication, and the like. The control unit 180 may include a multimedia module 181 for multimedia playback. The multimedia module 181 may be implemented in the control unit 180 or may be implemented separately from the control unit 180. [

The controller 180 may perform a pattern recognition process for recognizing handwriting input or drawing input performed on the touch screen as characters and images, respectively.

The power supply unit 190 receives external power and internal power under the control of the controller 180 and supplies power necessary for operation of the respective components.

The various embodiments described herein may be embodied in a recording medium readable by a computer or similar device using, for example, software, hardware, or a combination thereof.

According to a hardware implementation, the embodiments described herein may be implemented as application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays May be implemented using at least one of a processor, controllers, micro-controllers, microprocessors, and other electronic units for performing other functions. In some cases, The embodiments described may be implemented by the control unit 180 itself.

According to a software implementation, embodiments such as the procedures and functions described herein may be implemented with separate software modules. Each of the software modules may perform one or more of the functions and operations described herein. Software code can be implemented in a software application written in a suitable programming language. The software code is stored in the memory 160 and can be executed by the control unit 180. [

The specific functions of the present invention will be described based on the elements of the contents input unit 2, the emoticon generation unit 3 and the terminal of the emoticon reception unit 4 or the server 100 constituting the above-described emoticon service providing system 1. [

In addition, after compilation, it converts to native APIs corresponding to iOS and Android respectively, and proposes a structure that can efficiently cope with various devices.

In addition, the present invention stores chat data of a user as a DB in the form of analyzed key token, and DB accumulated user data contributes again to enhancement of artificial intelligence based on a word vector. As the usage increases, accuracy of artificial intelligence (Word Vector based Machine Learning).

The present invention analyzes and combines various variables such as keywords, emotion, usage frequency, preference, climate, date, time, place, issue, and the like, unlike the conventional usage method in which the purchased character emoticon contents are repeatedly used, It is possible to use.

In addition, according to the present invention, a character emoticon expression changes in real time according to an input word or a symbol (number) element, so that a user can identify and express his / her emotions.

In addition, the present invention can reduce the technical constraints such as delays generated in the calculation process through the user-friendly UX design and communicate the communication process more intimately to the user.

Further, the present invention can continuously improve the accuracy of artificial intelligence through machine learning.

FIG. 3 is a flowchart for explaining a method of providing an artificial intelligent emoticons service based on the machine learning proposed by the present invention.

Referring to FIG. 3, a step S110 of receiving a content such as a text, a voice, an image, and a moving picture from a user by the terminal or the server 100 of the content input unit 2 according to the present invention is performed first.

Then, the terminal of the emoticon generation unit 3 or the server 100 analyzes the morpheme based on the input content (S120).

In step S120, the control unit 180 of the terminal or the server 100 analyzes the morpheme and converts the expressed word into a basic type verb.

After step S120, the terminal or server 100 of the emoticon generation unit 3 performs an operation of analyzing the context of the content input in step S110 through a verb, a noun, an adjective, a punctuation mark, or the like (S130) .

The terminal of the emoticon generation unit 3 or the server 100 performs a task of matching with the emoticon based on the key token information in step S140.

In step S140, the controller 180 of the terminal or the server 100 may apply a separate emoticon tag or use a plurality of emoticons through an emoticon category.

When the emoticon matching operation is completed in step S140, the terminal of the emoticon generation unit 3 or the server 100 transmits the emoticon determined by the terminal of the emoticon receiving unit 4 or the server 100 (S150).

As a result, the present invention provides a smart application that analyzes emotions and contexts of text and voice messages and automatically transmits them to emoticons.

Through this, 1) analyzing user's emotions that can not be expressed in the existing text format with 1) artificial intelligence API, 2) designing emoticon in real time using its own agent, and providing new communication experience to communicate emotions with each other do.

FIG. 4 shows a concrete example of each step of the artificial intelligence emoticon service providing method based on the machine learning shown in FIG.

Referring to FIG. 4, as an example of step S110, contents such as " Let's go to eat chicken chicken "

4, the terminal 100 of the emoticon generation unit 3 or the server 100 may perform a morphological analysis such as "chicken," "chiki," "in," " , "Let's go", and so on.

As an example of step S120, a work of transforming into a basic verb is carried out, and the word " eat " is transformed into " eat "

In the following, FIG. 4 shows an example of step S130. In the example of step S130, the morphologically analyzed " chicken " is " hungry ", & Time "category.

As an example of step S140, API analysis of the key token extracted in step S120 shows that "pleasure is 76%", "sadness is 42%", "angry 50%", "fear is 12%", This 22% "can be extracted.

Subsequently, based on steps S130 and S140, the terminal of the emoticon generation unit 3 or the server 100 transmits the determined emoticon to the terminal of the emoticon receiving unit 4 or the emoticon determined by the server 100 (S150) .

Finally, we analyze the context and nuances of multiple textual situations (eg, 49 situations) and emotions (Joy, Sadness, Anger, Fear, Surprise) using our own algorithms and external APIs , And the emotional tone of the emoticon design can be determined.

It is also possible to generate an image matching the extracted keyword, and generate an emoticon by combining the image with a predetermined rule.

In the present invention, various variables may be combined to represent an infinite number of emoticons in step S150.

Users can experience the pleasure of communicating the convenience and emotion when their emotions and situations are converted into the most appropriate emoticons through accurate analysis.

In other words, emoticon is generated by reflecting emotion of user, overall context of conversation, used keyword, and contents of cloud are retrieved, so that it can be provided according to each situation.

Also, in the present invention, image processing is applied to the result, so that the same emoticon can be expressed differently according to the intensity of emotions, thereby enabling more delicate communication.

FIG. 5 shows a specific example in which the emoticon expressed in accordance with the change of the emotion of the user or the intensity of the emotion is changed, in the context of the present invention.

5, emoticons related to the chicken described in FIG. 4 are displayed in the same manner, but each of (a), (b), and (c) shows a change in color, size, etc. according to a change in emotion or emotion intensity The emoticons are displayed.

According to another embodiment of the present invention, a method of arranging emoticons in order of relevance and selecting by a user may be provided in addition to providing matching emoticons to a user.

FIG. 6 is a flowchart illustrating a method of arranging emoticons in order of relevance and selecting by the user, according to another embodiment of the present invention.

Referring to FIG. 6, first, a step S110 of receiving a content such as text, voice, image, and moving image from a terminal of a terminal or a server 100 of the content input unit 2 according to the present invention is performed first .

Next, the terminal of the emoticon generation unit 3 or the server 100 analyzes the morpheme based on the input content (S120).

After step S120, the terminal or server 100 of the emoticon generation unit 3 performs an operation of analyzing the context of the content input in step S110 through a verb, a noun, an adjective, a punctuation mark, or the like (S130) .

Thereafter, the terminal of the emoticon generation unit 3 or the server 100 performs a task of matching with the emoticon based on the key token information. Unlike the step S140 described above, the association with the emoticon in the database (DB) (S210).

That is, the "chicken" analyzed by the morphological analysis described in FIG. 4 is classified into categories "when hungry", "when hungry", and "when distributed" The emoticon can be matched by calculating the association with the matched category.

In addition, through the API analysis described in the example of FIG. 4, the state of "pleasure 76%", "sorrow 42%", "angry 50%", "fear 12%", "alarm 22% If extracted, the emoticon associated with the high state may be matched.

Unlike the conventional method, the terminal or server 100 of the emoticon generation unit 3 arranges the emoticons in order of relevance to the terminal of the content input unit 2 or the server 100 and provides them to the user (S220).

At this time, the terminal of the content input unit 2 or the user of the server 100 selects a specific emoticon among the emoticons arranged in order of association (S230), and transmits the selected emoticon to the terminal of the emoticon receiving unit 4 or the server 100 (S150).

At this time, since the user is highly related among the arranged emoticons, the user is more likely to select the emoticons arranged at the front end.

On the other hand, when an additional message is input from the user before the emoticon is transmitted, an event in which the content context of the user is changed may be generated.

Accordingly, in the present invention, when an additional message is input from the user before transmission of the emoticon in response to the event, the user may reflect the emoticon in real time to provide a method for the user to select the relevant emoticon.

7 is a flowchart illustrating a method for a user to select a related emoticon in real time when an additional message is input from a user before transmission of the emoticon is performed, according to another embodiment of the present invention.

The steps S110 to S130 and S210 in FIG. 7 correspond to the steps S110 to S130 and S210 described in FIG. 6, respectively, and therefore, a description thereof will be omitted for the sake of simplicity.

7, after step S210, the terminal or the server 100 of the content input unit 2 determines whether any one of text, voice, image, and moving image is additionally inputted And further includes step S310.

If there is no additional content input in step S310, the same process as in FIG. 6 is performed. However, if the additional input content exists, the terminal of the emoticon generation unit 3 or the content Analyzing the morpheme on the basis of the morpheme, a noun, an adjective, and a punctuation mark (S330).

The terminal or server 100 of the emoticon generation unit 3 matches the emoticon in step S340 in consideration of the added keyword and reflects the matching result in step S310 and the matching result in step S210 in real time And arranges the emoticons in the order of association, and transmits them to the terminal of the content input unit 2 or the server 100 (S350).

The user of the content input unit 2 or the user of the server 100 selects a specific emoticon among the emoticons arranged in order of relevancy at step S230 and transmits the selected emoticon to the terminal of the emoticon receiving unit 4 or the server 100 (S150).

Each of the steps described in FIGS. 6 and 7 will be specifically described with reference to the drawings.

FIG. 8 shows a specific example of analyzing the morpheme through the contents inputted by the user in FIG. 6 or FIG.

FIG. 8 shows a specific example of step S120 in FIG. 6 or FIG.

Referring to FIG. 8, there is shown an example in which the terminal of the content input unit 2 or the user of the server 100 inputs " What if the user mistakenly rides the bus on the way and is late today? &Quot;.

In this case, the terminal or the server 100 of the emoticon generation unit 3 can notify the emoticon generation unit 3 of the "Go", "Way", "Bus", "Bad", " The morphemes of "do" and "?" Can be analyzed.

Next, FIG. 9 shows a specific example of the present invention for extracting keywords based on the morpheme analyzed in FIG.

FIG. 9 shows a concrete example of step S130 in FIG. 6 or FIG.

9, the terminal or the server 100 of the emoticon generation unit 3 may select one of the following items as "Go", "Way", "Bus", "Bad", " A morpheme with strong semantic elements can be selected from morphemes such as "how," "do," and "?" Emotion, situation, and punctuation marks.

In Fig. 9, "bad", "late" and "how" can be selected morphemes.

FIG. 10 shows an example of a specific operation for matching the related emoticons in the database based on the keyword extracted in FIG.

FIG. 10 shows a specific example of the step S210 of FIG. 6 or FIG.

Referring to FIG. 10, a plurality of emoticons corresponding to the morpheme "bad", "late", and "how" selected in FIG. 9 are matched and displayed.

Thereafter, these plurality of emoticons may be arranged in order of relevance.

FIG. 11 shows a concrete example of arranging and matching emoticons matched in FIG. 10 to users in order of relevance.

FIG. 11 shows a specific example of step S220 of FIG. 6 or step S350 of FIG.

11, the image address URLs of the corresponding emoticon contents are listed and recommended in descending order of relevance by numerical values calculated by dividing scores of 0.0 to 1.0.

The six emoticons can be evaluated for relevance of 0.64, 0.63, 0.62, 0.71, 0.92, and 0.59, respectively.

FIG. 12 shows a specific example in which the user selects one of the plurality of emoticons displayed in FIG. 11 and transmits the selected emoticons.

Referring to FIG. 12, the emoticons are arranged in the order of 0.64, 0.63, 0.62, 0.71, 0.92, and 0.59 calculated in FIG. 11 and displayed on the terminal or server 100 of the content input unit 2, The emoticon selected in step S150 is transmitted to the terminal of the emoticon receiving unit 4 or the server 100. [

13 is a flowchart illustrating an operation S310 of determining whether the terminal of the content input unit 2 or the server 100 is additionally inputting any one of text, voice, image, and moving image after step S210 described with reference to FIG. As shown in FIG.

13, an additional text such as " I am always waiting because I have waited all the time " is inputted through the terminal of the contents input unit 2 or the server 100 before the emoticon is transmitted.

Therefore, the terminal of the emoticon generation unit 3 or the server 100 analyzes the morpheme on the basis of the content ("I am always waiting for you because of waiting") (S320) and the step of verifying the morpheme, noun, adjective, (Step S330). The emoticon is matched with the added keyword in step S340. In step S340, the matching result is compared with the matched result in step S210 And transmits the emoticons to the terminal or the server 100 of the content input unit 2 in the order of association (S350).

13, the terminal of the content input unit 2 or the user of the server 100 reflects the matched result in step S340 and the matched result in step S210 in real time, A selected emoticon is selected in step S230 and the selected emoticon can be transmitted to the terminal of the emoticon receiving unit 4 or the server 100 in step S150.

On the other hand, in the above-described configuration of the present invention, an example in which "Korean" is applied is described, but the contents of the present invention are not limited to Hangul.

14 and 15 show a specific example of providing a machine learning based artificial intelligence emoticone service in the case of English in connection with the present invention.

14, when the terminal of the content input unit 2 or the user of the server 100 inputs the text 210 of "Yes, I'm on my-" through the display unit 151, A specific example in which a plurality of related emoticons 220 are displayed on the display unit 151 according to the method of Fig. 6 or Fig. 7 is shown.

Referring to FIG. 15, when the terminal of the content input unit 2 or the user of the server 100 receives the " it seems to be a little late ... when the text 230 of "because I go-" is input through the display unit 151, a plurality of related emoticons 240 are displayed on the display unit 151 according to the method of FIG. 3, FIG. 6, A specific example is shown.

Meanwhile, the machine learning-based artificial intelligence emoticons service providing system 1 according to the present invention can be applied to a system in which emoticon images are not stored in a device or an OS, but are managed in the cloud, .

In addition, the system 1 for providing an artificial intelligence service based on machine learning according to the present invention classifies the data type (emotion, situation, information) of text input to a smart phone (terminal) It can be used as a system that is automatically converted into a graphic image.

In addition, the machine learning-based artificial intelligence emoticon service providing system 1 according to the present invention includes a system for replacing a morpheme and a semantic element detected in the text of an instant message with an indirect advertisement image, .

In addition, the machine learning-based artificial intelligence emoticon service providing system 1 according to the present invention recognizes the situation and emotion in a voice message transmitted at the time of chatting, replaces it with emoticons, and transmits the voice message to the emoticon System can be utilized as a system.

When the above-described configuration of the present invention is applied, a machine learning-based artificial intelligence emoticons service providing system can be provided to a user.

Specifically, the present invention can provide a system and an application for analyzing emotional elements and contexts contained in a user's message using a machine learning-based artificial intelligence technology and expressing character emoticons in real time.

In addition, the present invention can provide a user with artificial intelligence convergence that recognizes context data (emotion, environment, objects, etc.) through message analysis and re-processes the data into emoticons as visual communication tools.

In addition, the present invention can provide a user with an application and an API that can be used for general purposes without being limited to a specific service or application in consideration of a use environment for inputting text.

Further, according to the present invention, a word vector-based artificial intelligent machine learning system can be constructed and provided to a user as the learning habit pattern of a user is learned and used.

In addition, the present invention proposes a more accurate and convenient communication experience by combining artificial intelligence and design technology in messaging communication, which occupies most of the mobile communication, and provides the user with experience of present emoticon usage Allowing artificial intelligence to analyze the conversation and recombine graphic elements in real time to enable unlimited expression.

In addition, the present invention can develop not only a message application but also a technology for designing contents that are constantly created in SNS, blog, media using an input interface.

The present invention analyzes and combines various variables such as keywords, emotion, usage frequency, preference, climate, date, time, place, issue, and the like, unlike the conventional usage method in which the purchased character emoticon contents are repeatedly used, It is possible to use.

In addition, according to the present invention, a character emoticon expression changes in real time according to an input word or a symbol (number) element, so that a user can identify and express his / her emotions.

In addition, the present invention can reduce the technical constraints such as delays generated in the calculation process through the user-friendly UX design and communicate the communication process more intimately to the user.

Further, the present invention can continuously improve the accuracy of artificial intelligence through machine learning.

The present invention can also be embodied as computer-readable codes on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and may be implemented in the form of a carrier wave (for example, transmission over the Internet) .

In addition, the computer-readable recording medium may be distributed over network-connected computer systems so that computer readable codes can be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers of the technical field to which the present invention belongs.

It should be understood that the above-described apparatus and method are not limited to the configuration and method of the embodiments described above, but the embodiments may be modified so that all or some of the embodiments are selectively combined .

Claims (10)

A first terminal for receiving at least one first content;
A second terminal for receiving the first content from the first terminal, generating a plurality of second texts by classifying the text included in the first content into a predetermined unit, A server for filtering at least one third text and determining at least one first emoticon matching the third text among a plurality of previously stored emoticons; And
And a second terminal for receiving the first emoticon from the server. The method according to claim 1,
Wherein the first content includes text information, image information, moving image information, and audio information. 3. The method of claim 2,
If the first content is image information or moving image information,
The server extracts the text included in the image information or the moving image information, generates the plurality of second texts by classifying the extracted text into the predetermined unit,
If the first content is audio information,
Wherein the server converts the voice information into text information and classifies the converted text information into the predetermined unit to generate the plurality of second texts. The method according to claim 1,
Wherein the predetermined unit is a morpheme unit,
Wherein the server converts at least some of the plurality of second texts into basic verbs. The method according to claim 1,
Wherein the predetermined condition is whether the text is text having meaning. The method according to claim 1,
The third text is plural,
Wherein the first emoticon matching the plurality of third texts is a plurality of first emoticons. The method according to claim 6,
The server comprises:
Classifying the plurality of third texts into at least one category among a plurality of predetermined categories,
Counting the number of the classified third texts by category,
Assigning a result value counted for each category to a third text belonging to each category,
A plurality of first emoticons matching the plurality of third texts among the plurality of emoticons stored in advance,
Wherein the arrangement order of the plurality of first emoticons is determined according to a result value of each of the plurality of third texts. 8. The method of claim 7,
The server comprises:
Transmitting the plurality of first emoticons and the arrangement order to the first terminal,
The first terminal,
Displaying the plurality of first emoticons according to the arrangement order,
When a user of the first terminal selects a second emoticon among the plurality of first emoticons, transmits information on the second emoticon to the server,
The server comprises:
And transmits the second emoticon to the second terminal. The method according to claim 1,
When at least one second content is additionally input through the first terminal,
The server receives the second content from the first terminal, generates a plurality of second-second texts by classifying the text included in the second content into a predetermined unit, And at least one first emoticon matching the third-second text among the plurality of emoticons stored in advance is additionally determined. Running-based artificial intelligence emoticons providing system. The method according to claim 1,
Wherein the first terminal comprises a plurality of terminals,
Data relating to operations between the first terminal, the second terminal and the server is stored in the server,
And the server accumulates and uses the stored data to perform machine learning. The machine learning based artificial intelligence emoticon providing system according to claim 1,

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