KR20200058909A - Method and apparatus for learning language, thereof system - Google Patents

Abstract

The present invention relates to a language learning system and a method thereof. The language learning system comprises: a service server that transmits service data required for configuring a virtual environment; a user terminal that receives the service data to provide the virtual environment to a user, and transmits a user conversation with a virtual object in the virtual environment to the service server; and a learning server that determines the language ability, language learning habit, and language level of the user from the user conversation and user personal information in the virtual environment, and selects or generates a customized learning content based on at least one of the language ability, language learning habit, language level, and personal information to provide the same through the service server.

Description

METHOD AND APPARATUS FOR LEARNING LANGUAGE, THEREOF SYSTEM}

The present invention relates to a language learning method and apparatus and a system thereof, and more particularly, to a language learning method and apparatus and system capable of learning a user-specific contextual language through a user terminal.

It is not easy for anyone to learn a language in a country other than their native language. Alternative language learning methods are self-taught, taking, and 1: 1 interactive learning based on textbooks, but all of these conventional learning methods are different from the way they learn their native language.

Unilateral learning, such as self-study or course attendance, is useful within the scope of the intended study (such as language exams), but it is not easy to apply in a variety of other real-world environments, so even a person with a high score in the language such as TOEIC or TOEFL can speak everyday. There are many vulnerable cases. Also, in the case of 1: 1 interactive learning, there is no shortage of absolute amount of time to contact unless you live together, so it takes a long time to study.

The most effective way to learn a language is to learn the native language. Specifically, in everyday life, while encountering various surrounding environments through the five senses, you can naturally encounter language by context, memorizing by repetition while touching words, phrases, and sentences. It becomes possible to use the words memorized appropriately according to each situation.

However, this environment is difficult to encounter unless you live in a country that actually speaks the language, and because of this, many people suffer from language learning.

Due to this aspect, a learning method and a system are required to make it easy and versatile to access the language you want to learn through as many sensory channels as possible (visual, auditory, tactile, etc.). The system is absent.

Moreover, each user will have different language acquisition abilities, language habits, current language level, gender, and age. Accordingly, effective language learning is possible only when content to be learned is provided, but there is also no systematic learning method or system.

Accordingly, the present invention has been proposed to solve the above-described problems, and its purpose is to provide a method and apparatus and system for providing customized language learning according to various situations regardless of a user's location or time through a user terminal. There is this.

In addition, the present invention is a language learning method and apparatus that enables a user to communicate with a virtual object in various situations in real-time, thereby allowing language to be rapidly improved by learning the language through as many sense channels as possible. In providing a system.

In addition, the present invention provides learning contents in consideration of a user's learning situation as well as language acquisition ability, language habits, current language level, gender, and age, so that quick learning of parts requiring learning such as pronunciation correction or step-by-step grammar is provided. It is to provide a language learning method and apparatus and a system for making it possible.

The objects of the present invention are not limited to those mentioned above, and other objects not mentioned will be clearly understood by those skilled in the art from the following description.

The language learning system according to the present invention for achieving the above object includes a service server that transmits service data necessary for configuring a virtual environment, and provides a virtual environment to a user by receiving the service data, and a virtual entity in the virtual environment. The user terminal for transmitting the user's conversation to the service server, and the user's language ability, language learning, and language level from the user's conversation and user personal information in the virtual environment are determined, and the language ability, language learning, language level and personal And a learning server that selects or generates user-specific learning content based on at least one of the information and provides it to the user through the service server.

In addition, the language learning method according to the present invention, the service server providing a virtual environment for the situation selected by the user, extracting a user conversation with a virtual object under the virtual environment, and based on the extracted user conversation And determining at least one of language ability and language learning level, and selecting and providing learning content in consideration of at least one of the determined language ability, language learning, and language level.

According to the present invention, the user terminal enables the user to learn a language based on a desired location regardless of the actual location.

In addition, according to the present invention, the user can communicate with a virtual object in various situations in real time, so that the learning effect on the language can be rapidly improved.

In addition, according to the present invention, by providing learning content according to a user's learning situation, it is possible to quickly learn a part requiring learning, such as pronunciation correction or grammar.

The effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a block diagram showing a network configuration of a language learning system according to the present invention,
2 is a flowchart showing a language learning method according to the present invention,
3 is a block diagram showing the configuration of a user terminal according to the present invention.
4 is a flowchart illustrating a language learning method in a user terminal according to the present invention.
5 is a detailed configuration diagram of a learning server according to the present invention.
6 is a flowchart of a language learning method according to another embodiment of the present invention.

The objectives and effects of the present invention, and technical configurations for achieving them, will be clarified with reference to embodiments described below in detail together with the accompanying drawings. In describing the present invention, when it is determined that a detailed description of known functions or configurations may unnecessarily obscure the subject matter of the present invention, the detailed description will be omitted. In addition, terms to be described later are terms defined in consideration of donations in the present invention, which may vary according to a user's or operator's intention or practice.

However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms. Only the present embodiments are provided to make the disclosure of the present invention complete, and to fully inform the person of ordinary skill in the art to which the present invention pertains, the scope of the present invention being defined by the scope of the claims. It just works. Therefore, the definition should be made based on the contents throughout this specification.

Throughout the specification, when a part is said to "include" or "equipment" a component, this means that other components may be further included, not specifically excluded, unless otherwise stated. . In addition, terms such as "... unit", "... device", "... device", "... unit" or "... module" described in the specification may have at least one function or operation. Refers to a processing unit, which may be implemented in hardware or software or a combination of hardware and software.

On the other hand, in an embodiment of the present invention, each component, functional blocks or means may be composed of one or more sub-components, electrical, electronic, and mechanical functions performed by each component are electronic circuits, Integrated circuits, ASICs (Application Specific Integrated Circuits), etc. may be implemented with various known devices or mechanical elements, and may be implemented separately, or two or more may be integrated into one.

Also, combinations of each block in the accompanying block diagram and each step in the flowchart may be performed by computer program instructions. These computer program instructions may be mounted on a processor of a general purpose computer, special purpose computer, portable notebook computer, network computer, mobile device such as a smart phone, an online game service providing server or other programmable data processing equipment, and thus a computer device or other program. The instructions, which are executed through a processor of a possible data processing equipment, create a means for performing the functions described in each block of the block diagram or each step of the flow chart described below. Since these computer program instructions may be stored in computer readable memory or memory available to a computer device capable of directing a computer device or other programmable data processing equipment to implement a function in a specific manner, each block in the block diagram Alternatively, it is also possible to produce an article containing instruction means for performing the functions described in each step of the flowchart. Since computer program instructions may be mounted on a computer device or other programmable data processing equipment, each block and flow diagram in a block diagram is created by creating a process for a series of operational steps to be performed on the computer device or other programmable data processing equipment. It is also possible to provide steps for executing the functions described in each step of.

Further, each block or each step can represent a module, segment, or portion of code that includes one or more executable instructions for executing the specified logical function (s). It should also be noted that in some alternative embodiments it is possible that the functions mentioned in blocks or steps occur out of order. For example, two blocks or steps shown in succession may in fact be executed substantially simultaneously, or it is also possible that the blocks or steps are sometimes performed in reverse order depending on the corresponding function.

In the embodiment of the present invention, the client or various devices means all computing means capable of collecting, reading, processing, processing, storing, and displaying data such as a desktop computer, notebook computer, smart phone, PDA, mobile phone, and game machine. Means In particular, the client or various devices in the embodiment of the present invention are devices having a function capable of executing software written in readable code and displaying it to a user for delivery. In addition, if necessary, the software may be stored on its own, or may be read along with data from the outside.

In addition, the client or various devices in the embodiment of the present invention include functions such as input, output, and storage as well as data processing functions as described above, and for this purpose, CPUs, motherboards, and graphics cards of general computer devices, Various elements such as hard disk, sound card, speaker, keyboard, mouse, monitor, USB, communication modem, etc., as well as CPUs, motherboards, graphics chips, memory chips, sound engines, speakers, touch pads of wireless smartphone terminals, It may include an external connection terminal such as USB, a communication antenna, a communication modem capable of realizing communication such as 3G, LTE, LTE-A, WiFi, and Bluetooth. These various elements alone or two or more together, or a part of various elements can be combined to implement one or more functions, and in the embodiments of the present invention, a device indicated by one or more blocks in the drawings or detailed description, or The parts may mean that various elements included in the above-described client or various devices are singly or two or more together, or a part of various elements are combined to represent one or more functions.

The basic operating environment of the present invention is as follows.

Distances in augmented reality or virtual reality and specific places lined up by the user through the user terminal (for example, convenience stores, academies, schools, hospitals, pharmacies, religious facilities, etc., places that can be accessed in daily life; hereinafter collectively referred to as service shops) To selectively interact with the virtual object while ordering, making reservations and inquiries in the language you want to learn, and providing learning content based on the results of the conversation so that you can proceed with learning. In addition, even if you do not visit a specific service store, you can have a conversation by receiving a question from a virtual object encountered while walking through a virtual street. In addition, in augmented reality or virtual reality, it is possible to receive coupons and discount coupons provided by each service store or to receive information on related benefits.

On the other hand, in this specification, the service shop is a place that provides services (sales, counseling, medical treatment, etc.) that fit each feature. It is collectively referred to as the store, but this specification includes a non-profit facility such as a religious facility for a commercial purse. Therefore, it is used as a general term to describe wherever the user can stop by.

Hereinafter, a language learning apparatus and method and a system according to an exemplary embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram showing a network configuration of a language learning system according to an embodiment of the present invention.

Referring to FIG. 1, the language learning system 100 includes a user terminal 101, a service server 103, a service store server 105, and a learning server 107.

First, the user terminal 101 generates and displays a 3D image by driving a service in one of the first mode and the second mode based on the service data according to the driving environment set by the user. Here, the driving environment includes location information that is a background of a 3D image, that is, information about a virtual area where a user wants to learn a language, and the first mode and the second mode can be augmented reality mode and virtual reality mode, respectively. have.

In addition, the user terminal 101 recognizes input information such as voice, touch, movement, and gaze inputted from the user and executes a conversation with a virtual object in a 3D image based on previously learned data. Thereafter, the user terminal 101 generates result information for the executed conversation and transmits it to the service server 103, and provides learning content from the learning server 107 using the learning content information received in response thereto Receive.

The user terminal 101 may be provided with benefit information of a corresponding service store from a service store server 105 corresponding to at least one service store in a 3D image.

On the other hand, the user terminal 101 may provide a service in conjunction with a separate device such as a head mounted display (HMD).

The service server 103 transmits service data corresponding to the driving environment of the user terminal 101 among the stored service data to the user terminal 101 and analyzes result information on the conversation received from the user terminal 101. Thereafter, the service server 103 generates learning content information according to the analysis result and transmits it to the user terminal 101, so that the learning terminal body required by the user terminal 101 can be provided.

The service store server 105 transmits its benefit information to the service server 103. Although only one service store server is illustrated in FIG. 1, it may be configured for each of a plurality of service stores subscribed to the service, that is, entered.

The learning server 107 receives a request for providing learning content from the user terminal 101 and transmits the learning content requested to be provided to the user terminal 101 in response to the request.

2 is a flowchart illustrating a language learning method according to an embodiment of the present invention.

When the application is executed in the user terminal 101 (S201), a notification message indicating that the application has been executed is transmitted to the service server 103 (S203). At this time, step S203 may be omitted.

Thereafter, the user terminal 101 sets a driving environment in which the 3D image is to be driven (S205), and transmits the setting information to the service server 103 (S207). At this time, the setting information includes location information selected by the user, that is, information about an area that is a background of language learning, and mode information about whether augmented reality mode or virtual reality mode.

The service server 103 checks the setting information received from the user terminal 101 (S209), and transmits service data corresponding to the checked setting information among stored service data (S211). At this time, the service data includes data necessary for driving the service, and further includes distance information previously stored according to the location information included in the setting information and information on at least one service store.

The user terminal 101 downloads and stores service data from the service server 103 (S213), and drives a service based on the stored service data (S215). At this time, the service may be driven by a separate device worn by the user in a state interlocked with the user terminal 101.

Thereafter, the user terminal 101 recognizes user input information such as voice, touch, movement, and gaze from the user (S217), and executes a conversation with a virtual object in the 3D image based on the previously learned data, resulting information Create (S219). The user terminal 101 transmits the generated result information to the service server 103.

The service server 103 checks the result information received from the user terminal 101 (S223), and transmits the learning content information to the user terminal 101 based on the result information (S225). Although not illustrated through the drawings, specifically, the service server 103 analyzes the result information, and selects at least one or more learning contents from among various learning contents according to the analysis result and transmits the information about it.

The user terminal 101 checks the learning content based on the learning content information received from the service server 103 (S227), and requests the learning server 107 to provide the learning content using the learning content information (S229). At this time, the user terminal 101 may request to provide the learning content to the learning server 107 through the link included in the learning content information.

The learning server 107 confirms a request to provide learning content received from the user terminal 101 (S231), and provides the requested learning content to the user terminal 101 (S233).

The user terminal 101 progresses learning through the learning content provided from the learning server 107 (S235).

Meanwhile, when the user terminal 101 visits a specific store in augmented reality or virtual reality while the service is running, the user terminal 101 may check the benefit information for the specific store. This benefit information is provided from the service store server 105 to the service server 103 as in step S202, when there is a change in information on at least one of discounts, offers and coupons provided by the service store server 105. Each time the service store server 105 can transmit to the service server 103. Meanwhile, although not shown in FIG. 2, when a request for providing a benefit is provided from the user terminal 101, the service server 103 may inform the service store server 105 to receive the benefit.

In this case, the user terminal 101 selects the benefit to be provided from the verified benefit information (S237), and transmits the benefit selection information to the service server 103 (S239).

The service server 103 checks the benefit selection information received from the user terminal 101 (S241), and provides a benefit corresponding to the checked benefit selection information to the user terminal 101.

The user terminal 101 downloads and stores the benefits received from the service server 103 (S245). The stored benefits may be for discounts, offers, or coupons, and in the case of stored coupons or discounts, they may be used for offline or online ordering of the store.

Steps S237 to 245 for providing a benefit may be executed before steps S219 to S235 for providing a learning service, or may be omitted if the user does not select them.

3 is a block diagram showing the configuration of a user terminal according to an embodiment of the present invention.

Referring to FIG. 3, the user terminal 101 includes a transmitter / receiver unit 1011, a camera unit 1013, an audio unit 1015, a recognition unit 1017, a driving unit 1019, a generating unit 1021, and a display unit ( 1023), a storage unit 1025, and a control unit 1027.

The transmitting and receiving unit 1011 transmits a setting request for a driving environment, result information for driving a service, and a request for providing learning content, and receives service data, learning content information, and learning content corresponding to the setting information. In addition, all signals, data, and information transmitted and received from the user terminal 101 are also transmitted and received by the transceiver 1011.

The camera unit 1013 may photograph the surrounding environment, and input real image information through photography. At this time, actual image information may be input in real time and provided to the generator 1019.

The audio unit 1015 includes a microphone (not shown) and a speaker (not shown), and reproduces an audio signal output from the inside of the user terminal 101 through the speaker, and is generated outside the user terminal 101 The audio signal is input through the microphone.

The recognition unit 1017 recognizes input information for at least one of voice, touch, movement, and gaze input from a user. At this time, the voice may be recognized based on input through the microphone of the audio unit 1015, and the touch may be recognized based on a user's touch made in the display unit 1017. In addition, although not illustrated through the drawings, various sensors for sensing a user's movement or biometric information may be provided, and the recognition unit 1017 may recognize the user's movement or biometric information detected through these sensors. It might be.

The driver 1019 executes an application and drives a service in one of a first mode and a second mode, that is, an augmented reality mode and a virtual reality mode, according to a driving environment. In this case, the driving unit 1019 may be executed or driven by recognizing information input from the audio unit 1015 and the display unit 1023 in the recognition unit 1017.

The generation unit 1021 generates a 3D image based on the input information recognized by the recognition unit 1017 and the service data received by the transmission / reception unit 1011.

The display unit 1023 displays the 3D image generated by the generation unit 1021.

The storage unit 1025 stores the service data and the previously learned data. Also, the storage unit 1025 may store all data and information received by the user terminal 101 as well as data and information generated by the user terminal 101.

 The control unit 1027 generates and displays a 3D image by driving a service in any one of the first mode and the second mode according to the driving environment, recognizes input information, and virtualizes the 3D image based on previously learned data. It executes a conversation with an object, generates and transmits the result information for the executed conversation, and controls to execute the learning content using the learning content information received in response to the result information.

4 is a flowchart illustrating a language learning method in a user terminal according to an embodiment of the present invention.

The application is executed by the driver 1019 (S401), and the user input information input from the audio unit 1015 and the display unit 1023 is recognized by the recognition unit 1017 to set the location and driving mode (S403). .

Thereafter, the transmission / reception unit 1011 transmits the setting information to the service server 103 (S405), receives and downloads service data received from the service server 103 in response thereto, and stores the downloaded service data in the storage unit 1025. (S407).

The driver 1019 drives the service in one of the first mode and the second mode based on the stored service data (S409).

When the driving unit 1019 is driven in the first mode, that is, the augmented reality mode, the generator 1021 generates a 3D virtual object according to 3D image information included in the service data and the actual image photographed from the camera unit 1013. 3D images are generated by synthesis (S411). Meanwhile, when the driver 1019 is driven in the second mode, that is, the virtual reality mode, the generator 1021 generates a 3D image based on the 3D image information included in the service data (S413).

Thereafter, the recognition unit 1017 determines whether user input information input from the audio unit 1015 or the display unit 1023 is detected (S415). For example, when a user's voice is input through the audio unit 1015, a conversation is performed based on pre-trained data stored in the storage unit 1025. If there is no more input voice, the conversation is ended. Is considered. That is, steps S411 to S415 may be repeatedly performed.

As a result of the confirmation, if user input information is detected, a 3D image is generated and output according to the detected user input information, and when user input information is not detected, result information according to steps S411 and S413 is generated. It transmits to the service server 103 (S417). This is the step S411 to step S415 is to transmit the result information for the repeated conversation. To this end, conversation information performed in steps S411 to S415 may be stored in the storage unit 1025.

The transceiver 1011 receives the learning content information from the service server 103 in response to the result information, and the display unit 1023 displays the received learning content information, so that the user confirms it.

Based on this, the user selects whether or not the learning content is connected. The recognition unit 1017 recognizes whether the learning content is connected by the user's selection (S421).

If it is recognized that the recognition unit 107 does not connect to the learning content, the process proceeds to step S415, and when the recognition unit 1017 recognizes that the learning content is connected, the transmitting / receiving unit 1011 receives the corresponding learning content. A request for providing a service is transmitted to the service server 103 (S423).

Thereafter, the transmission / reception unit 1011 receives the corresponding learning content from the service server 103 in response thereto, and progresses learning through the driving unit 1019 (S425).

As another embodiment of the learning method , the service server 103 stores a plurality of pre-written scenarios and a virtual environment created accordingly, and provides one of them to a user terminal according to a user's selection.

In the virtual environment, a user stops at a service store with his intention or talks with another object existing in the virtual environment.

This conversation is passed through the service server 103 or directly to the learning server 107 to determine the user's language ability, language habits, and language level in consideration of personal information such as the user's age / gender / resident area, and this determination Depending on the results, user-specific learning content is selected and provided or a learning guide is provided.

In addition, the selection criteria are adjusted while continually verifying whether judgment and selection of content and guides are appropriate.

Hereinafter, one embodiment described above will be described in more detail with reference to FIGS. 5 and 6.

5 is a detailed configuration diagram of the learning server 107. As shown, the learning server 107 includes a language ability determining unit 1071, a language learning habit determining unit 1072, a language level determining unit 1073, and personal information. It includes a storage unit 1074, a learning content selection unit 1075, a learning guide generation unit 1076, and a verification unit 1077.

The language ability determining unit 1071 infers the language ability of the user from the user's conversation in each situation in the virtual environment. For example, even though the vocabulary used is small and there are many grammatical errors due to a short learning period for the foreign language, the language ability itself possessed or currently formed may be high.

The user's language ability can be judged by using the response delay time to answering the question, the suitability / appropriateness of the response to the question, the novelty of the response, and the originality of the phrase as the main evaluation factors.

In addition, it is preferable to judge language ability in consideration of the age / gender / region of the user included in the personal information storage unit. This is because it is appropriate to judge that the original language ability is higher than the case where the user's age is high when the user's age is low even though the same response is made.

The reasoning engine of the language ability judging unit 1071 is preferably configured to manage conversations of multiple users with big data using self-learning and deepen accuracy by using AI networks capable of deep learning. The reasoning engine of the habit determination unit and the language level determination unit are the same.

The language learning judging unit 1072 is a word like 'now ..', 'you know', such as' Ah? ',' Me? ',' E ..... I grasp the frequency of use of phrases. Also, find out whether you use verbose, verbose, concise and straightforward language.

Understanding language learning habits, including language, is an important factor that can have a great impact on learning effectiveness. For example, if a user who uses a concise and straightforward language provides learning content that mainly includes a long description language, the user feels bored and consequently has a low learning effect.

Conversely, providing learning contents that mainly contain short-answered short-formed words to users who use explanatory language can lead to a feeling of lack of learning content and lead to disappointment, leading to lower learning effects.

In the conventional language learning method, it is common to educate the beginners to learn short conversations for the beginners and long conversations for the advanced language according to the language level, however, depending on the language learning habits of the user, no matter how high the language level is, even if the language is familiar, the language is short and concise. A learner who has a speaking language learning preference does not prefer a long sentence, and a learner who prefers an explanatory language has a tendency to try to make a long sentence hard even in a situation where the language level is low, but in the end, there is a tendency to be unable to communicate with a completed sentence.

The present invention is to provide a customized learning method and system in consideration of language learning in consideration of these points.

The language ability determining unit 1071 and the language learning habit determining unit 1072 continuously judge all the conversations that the user is learning or evaluating in the virtual environment and detect the development or change.

On the other hand, since the accuracy may be low when reasoning based only on the conversation of the user speaking in the language to be learned, it is advantageous in terms of improving accuracy by inferring the content of the conversation in the user's native language. Therefore, the service server is provided with a separate evaluation mode, and it is preferable to conduct a conversation in a virtual environment in the user's native language in the evaluation at the first use.

The language level determining unit 1073 determines the language level of the corresponding language. This is because it is necessary to consider the aspect of how fluently the corresponding foreign language is used as a learning object, so the user's language level can be grasped relatively easily compared to the above-described language ability and language learning habits.

The number of words to be used, the grade of the expression (beginner / intermediate / advanced), response delay time, grammatical errors, words to be used, and the type and level of idioms are considered.

The personal information storage unit 1072 stores personal information of the user, that is, information provided by the user among various personal information such as gender, age, residential area, occupation, education level, marital status, and interests. The information stored in the personal information storage unit 1072 is used as a reference when inferring the language ability determining unit, language learning habit determining unit, and language level determining unit. The more personal information received and stored, the more detailed the language ability determining unit, language learning habit determining unit In addition, the accuracy of the reasoning result of the language level judging unit may be increased.

The learning content selection unit 1075 selects the most suitable learning content at the current time of the user based on the results and / or personal information inferred by the language ability determining unit, the language learning determining unit, and the language level determining unit.

For example, based on the judgment result and personal information, the user is born or acquired and prefers the currently equipped language ability, short and concise language, but because the learning period is short, the current language level for the current language is a low user, and he / she is specialized in IT fields. Imagine a man in his 30s who is engaged in history and is interested in history.

To this user, the contents of science and technology, the history of ancient Rome, etc. are added to each situation, and the contents of the dialogue provided in the virtual environment in a short and concise language are set high, and the level of the contents provided is raised in a short period of time by raising the learning goals. To provide.

Providing content with the same or similar content for beginner level words to users with high knowledge level for a long time will quickly prove it, so increase the speed of the content level up to a level that is considered to be a little rough compared to the user's language level. .

In the above description, it has been assumed and assumed that the language ability determination unit, the language learning habit determination unit, and the language level determination unit are separately configured determination units, but the language system according to the present invention allows one determination unit to determine language ability, language learning habits, and language level. In addition to being configurable, it can also be implemented by judging only a part of language skills, language learning habits, and language levels.

Also, for the same purpose, the learning content selection unit 1075 also selects the learning content in consideration of both the inference result and the personal information of the language ability determination unit, the language learning decision unit, and the language level determination unit, but the language ability determination unit However, it does not exclude the selection of learning content based on the results of the language learning judgment unit, the language level judgment unit's reasoning, and only a part of personal information.

Meanwhile, it is preferable that the learning content selection unit 1075 not only selects content suitable for the user's current level, but also sets learning objectives suitable for the user and selects content for each future learning schedule accordingly.

The learning guide selection unit 1076 selects a guide from two main aspects.

First, it is possible to present a guide to refrain from arranging undesirable language habits that the user himself is not aware of, such as unnecessary intercourse or meaningless repeated expressions.

Second, based on the user's learning history and current learning achievement, it is possible to present learning methods and goals for more efficient learning in the future while accurately presenting the learning situation at the present time.

The learning content selection unit 1075 and the learning guide selection unit 1076 are also preferably configured to manage conversations of multiple users with big data using self-learning and self-learning and increase accuracy by using deep learning AI neural networks.

Here, the selection of learning content may include selecting suitable content from content already secured, as well as generating new learning content through the AI module. The newly generated learning content may be stored in a learning content DB (not shown) and provided to other users. The same applies to the selection of study guides.

The verification unit 1077 is determined by the language ability determining unit 1071, language learning habit determining unit 1072, language level determining unit 1073, learning content selection unit 1075, learning guide selection unit 1076 Based on the personal information stored in the and personal information storage unit 1074, it is verified whether each judgment unit and the selection unit have produced the correct results.

The verification method can be achieved through analysis of past and present big data collected at the present time.

Alternatively, when the learning content and the learning guide are generated according to the determination results of the language ability determining unit 1071, the language learning habit determining unit 1072, and the language level determining unit 1073, the learning content selection unit 1075, the learning guide After the selection unit 1076 generates and provides learning contents and learning guides differently to multiple users having similar personal information, the learning achievement of each user after a predetermined period of time is examined to determine which learning contents and learning guides are most effective. By determining whether or not, it is possible to continuously verify and correct learning contents and learning guides suitable for each user.

6 is a flowchart of a user-customized learning method according to an exemplary embodiment of the present invention.

The service server 103 provides a prepared situation list to the user (S610). Examples of each situation included in the situation list include short and fragmented situations such as shopping at a department store, ticketing at an airport, and check-in at a hotel, as well as long and complex situations such as discussions on specific topics and user speeches on specific topics. Situation.

When the user selects a situation from the situation list, the service server 103 provides a virtual environment for the selected situation (S620). The situation may be selected through the UI of the user terminal, or a situation selection virtual environment may be separately provided and configured to be selected by the user in this virtual environment.

When the situation is selected and provided to the user in the virtual environment, the service server 108 allows the user to have a conversation with the virtual object based on the prepared conversation. Interactive AI modules can be used.

The learning server 107 extracts the user's conversation in the provided virtual environment (S630). It is preferable to extract the dialogue in real time, but it is also possible to extract the user dialogue from the stored dialogue after the dialogue is completed in consideration of the communication load.

Based on the extracted dialogue and personal information, the language ability determining unit 1071, the language learning habit determining unit 1072, and the language level determining unit 1073 respectively determine and evaluate the user's language ability, language learning habits, and language level (S640) ). Each judgment is learned by AI using AI technology and continuously increases reliability and accuracy.

When determining the language ability and language learning for the first time, it is more accurate to extract the user's native language conversation and make a judgment from it rather than the target language.

In other words, when judging language ability and language learning based on foreign language conversations that are not yet fluent, there is a high possibility that inaccurate results may occur. Therefore, it is desirable to conduct the provided conversation in the native language in the process of judging the best.

 The class content selection unit 1075 selects and provides appropriate learning content in consideration of personal information when the language ability, language learning habits, and language level are identified (S650). Along with this, a learning guide is selected and provided (S655). What guides are provided is as described above.

It is desirable to consider all language skills, language learning habits, language level, and personal information for the selection of learning contents or learning guides, but only some of them can be selected. Even considering only a part of language ability, language learning habits, language level, and personal information, it will be able to produce significantly higher results than the conventional language learning method.

The selection of learning content may include selecting suitable content from already secured content, as well as generating new learning content through the AI module. The newly generated learning content may be stored in a learning content DB (not shown) and provided to other users. The same applies to the selection of study guides.

According to the provided learning contents, the user has a conversation in the virtual environment, and according to whether the user selects the termination (S660), if the termination is not selected, the decision is again made from the dialogue extraction step (S630) (S640), and selection and provision of new learning contents Through the course of (S650), the actual high-level language educator can make the effect of changing the subject, content, and level of the dialogue into small pieces according to the level and shape of the student.

In this circulatory structure, language ability, language learning, language level evaluation, and selection and provision of learning content and learning guides are all or at least some individuals, such as gender, age, residential area, occupation, educational level, marital status, interests, etc. Because information is considered, a better language learning effect can be expected than that of a human language educator.

On the other hand, if the user selects the end in the end selection step (S660), the judgment result, the selection result of the learning content and the learning guide is stored (S670). The saved results can be reflected in later judgment and selection.

Although not shown, the above-described learning content selection and provision step (S650) and the learning guide selection and provision step (S655) are verified in real time by the verification unit 1077 or after learning is finished.

Moreover, this verification is performed by selecting and providing slightly different learning contents and learning guides to a plurality of users who have the same category of personal information, and also verifying the learning performance for a certain period of time, thereby increasing the reliability of verification. , It is possible to provide learning contents and learning guides customized for each user. The personal information of the same category may be, for example, users within 3 years of age, and users having the same residential area.

In addition, the subject of verification is not only the learning content selection and provision step (S650) and the learning guide selection and provision step (S655), but also the language ability determination unit 1071, language learning habit determination unit 1072, and language level determination unit 1073 It is better if the determination step (S640) is made.

Although not shown, it is more preferable to prepare a learning target and a schedule setting unit for setting a learning target and a learning schedule based on the judgment result, and to select a learning content and a learning guide to be provided to the user based on the setting. .

The set learning objectives and schedule can be provided directly to the user, and this alone enables goal-oriented learning to improve the learning effect, and more preferably, the learning system according to the present invention is set and presented to the user. By managing the schedule according to the schedule, it helps the user to continue learning continuously.

On the other hand, the learning system of the present invention is further equipped with a learning achievement evaluation unit (not shown), it is better to continuously evaluate whether or not it meets or exceeds the set learning goals and schedule.

The evaluation results of the learning achievement evaluation unit are sent back to the verification unit and used to verify the adequacy of the learning model described above. For example, if the learning is insufficient, the user is lazy or does not make effort, so the evaluation is not good, or the learning system does not make appropriate judgment in the judgment step (S640) and the selection and provision step (S650), or the appropriate learning content or guide is not selected. It is used to verify that it has failed.

If the learning achievement is highly evaluated, the learning model for that user is applied to other users, and if the learning achievement for other users is high by checking the learning achievement for other users, the corresponding learning model is selected as the best learning model It is applied preferentially afterwards.

In this specification, the learning model means not only the content of the selected learning content (guide) or the generation method and result of the learning content (guide), but also the language ability determination unit 1071, language learning habit determination unit 1072, and language level. It is a concept including the determination method of the determination unit 1073.

That is, the user-customized learning method and system according to the present invention is a self-evolving method and system that continuously develops itself by continuously performing various verifications.

As described above, some preferred embodiments of the present invention have been disclosed in the present specification and drawings, although specific terms are used, they are merely used in a general sense to easily describe the technical contents of the present invention and to understand the invention. The contents of the examples are not intended to limit the scope of the invention. It is apparent to those skilled in the art to which the present invention pertains that other modifications based on the technical spirit of the present invention can be implemented in addition to the embodiments disclosed herein.

Claims (10)

As a customized language learning system,
A service server that transmits service data necessary for configuring a virtual environment,
A user terminal receiving the service data, providing a virtual environment to a user, and transmitting a user conversation with a virtual object in the virtual environment to the service server;
Determines the user's language ability, language learning, and language level from user conversation and user personal information in the virtual environment, and selects or creates user-specific learning content based on at least one of language ability, language learning, language level, and personal information Learning server provided to the user through the service server
Language learning system comprising a.
The method of claim 1, wherein the learning server
A determination unit that determines at least one of the user's language ability, language learning habits, and language level,
A storage unit for storing user's personal information,
A learning content selection unit that selects learning content based on at least one of a user's language ability, language learning habits, language level, and personal information transmitted from the determination unit and the storage unit
Language learning system that includes.
The method of claim 2, wherein the learning server
A language learning system further comprising a learning guide selection unit that provides a learning guide based on the determination result of the language habit of the determination unit.
The method of claim 2, wherein the learning server
Language learning system further comprises a verification unit for verifying the suitability of the learning content selection results.
The method of claim 4,
The verification unit verifies the suitability of the determination result of the determination unit and the learning content selection result, and feedbacks the verification result to the learning content selection unit,
The learning content selection unit re-selects learning content to be provided to a user by reflecting the feedback result of the verification.
As a customized language learning method,
A step in which the service server provides a virtual environment for a situation selected by the user;
Extracting a user conversation with a virtual object under a virtual environment,
Determining at least one of language ability and language learning language level based on the extracted user conversation;
Selecting and providing learning contents considering at least one of the determined language ability, language learning habits, and language level
Language learning method comprising a.
The method of claim 6, wherein the determining step
When the language ability and language learning are first judged, a language learning method in which a user's native language conversation is extracted and judged therefrom.
According to claim 6, until the user completes the learning, extracting the conversation, and repeating the determining step and selecting and providing the learning content while changing the subject, content, and level of the learning content Language learning method.
The method of claim 6, further comprising: selecting and providing slightly different learning contents to a plurality of users having personal information within the same category, and then tracking the learning performance for a predetermined period of time to verify the suitability of selecting the learning contents. How to learn language.
The method of claim 6,
Performing a learning achievement assessment,
Steps to verify the adequacy of the learning model described above based on the evaluation results
Language learning method further comprising a.

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