Foreign language writing learning system using image-associative characters and artificial intelligence and foreign language writing learning method using the same

Abstract

The present invention relates to a foreign language writing learning system utilizing image association characters and artificial intelligence, and a foreign language learning method using the same. More specifically, it relates to a foreign language writing learning system utilizing image association characters and artificial intelligence and a foreign language writing learning method using the same, which improves memorization ability regarding words and sentence structures through an image association memory method by remembering words and sentence structures through image association characters that convert words into specific images or abbreviations when remembering words or sentence structures during the process of learning a foreign language other than one's native language, and improves writing as well as speaking ability by detecting words spoken by the learner and determining whether they are correct.

Description

Technology Field

[0001] The present invention relates to a foreign language writing learning system utilizing image association characters and artificial intelligence, and a foreign language writing learning method using the same. More specifically, it relates to a foreign language writing learning system utilizing image association characters and artificial intelligence and a foreign language writing learning method using the same, which improves memorization ability regarding words and sentence structures through an image association memory method by remembering words and sentence structures through image association characters that convert words into specific images or abbreviations when remembering words or sentence structures during the process of learning a foreign language other than one's native language, and can improve not only writing but also speaking ability by detecting words spoken by the learner and determining whether they are correct. Background Technology

[0002] In terms of foreign language learning methods, traditional approaches utilize five-sense skills such as sound, writing, and repetition, which involve memorizing by continuously repeating a single word or sentence while reading it out loud or writing it down.

[0003] However, while these traditional learning methods are effective for short-term memory, they have the problem of being difficult to transfer learning results to long-term memory, and fixed learning methods have the drawback of easily exhausting the brain.

[0004] Here, short-term memory and long-term memory relate to human memory; long-term memory includes episodic memory, which involves recalling memories; semantic memory, which involves retaining knowledge; and procedural memory, which is the memory of the sequence of actions memorized through the body.

[0005] In long-term memory, episodic and procedural memories are more intense and last longer than semantic memories. This is because episodic memories are generally accompanied by emotions, which provide stronger stimulation to the brain, while procedural memories utilize a wider area of ​​the brain.

[0006] Therefore, when learning a foreign language, it is more desirable to use a method that leads to long-term memory rather than relying on short-term memory through traditional repetitive learning.

[0007] In particular, learning a foreign language is often likened to memorizing words, and various word memorization methods have been proposed for this purpose.

[0008] For example, the image association memory method, also known as the Roman Room memory method, is known to have been handed down from the Roman era and is a method of creating a memory room in one's mind using familiar places and objects within them, and then associating the content one wants to memorize with each of the objects.

[0009] However, the image association method, which involves matching sentences or content to be remembered with related objects, has the problem of not being suitable for memorizing words. Furthermore, when associating one object with each word, the number of objects increases as the number of words to be remembered increases; consequently, not only are there few objects available for actual memory, but there are also cases where only the word represented by a single object is remembered, making it unsuitable for learning words or sentences.

[0010] In addition, Korean Published Patent No. 10-2014-0077144 proposed an 'English education method and online game method using chunks,' and Korean Published Patent No. 10-2010-0078375 proposed a 'word matching game method using speech recognition technology.'

[0011] Among the aforementioned prior art, Korean Published Patent No. 10-2010-0078375 includes a step of displaying a selected set of words with native speaker pronunciation and having the user memorize them for a certain period of time, and a speech recognition step of collecting user pronunciation data, performing speech recognition, and notifying the speech recognition result.

[0012] The aforementioned conventional technology involves providing a word selected according to the user's request and simultaneously pronouncing the word with native pronunciation to enable the user to learn, thereby allowing the user to memorize words by utilizing both eyes and ears. However, this method of memorization is merely an addition of native pronunciation to the aforementioned traditional learning method, and thus, it could not be expected to have a significant effect in improving word memorization ability. Prior art literature

[0013] Republic of Korea Published Patent No. 10-2014-0077144 Republic of Korea Published Patent No. 10-2010-0078375 The problem to be solved

[0014] The present invention aims to provide a foreign language writing learning system utilizing image association characters and artificial intelligence, which solves the above-mentioned problems and, in particular, enhances memorization effectiveness by enabling learners to connect words and sentences to long-term memory during the process of memorizing and learning, as well as a foreign language writing learning method using the same.

[0016] In particular, the present invention aims to provide a foreign language writing learning system utilizing image association characters and artificial intelligence, and a foreign language writing learning method using the same, wherein the learner is provided with image association characters consisting of specific images or abbreviations for each word, and together with this, a native speaker pronounces and provides a learning text, thereby recognizing the image association characters composed of images or abbreviations as well as visual and auditory senses, and associative memory is achieved by substituting the image association characters into the original text to remember them, so that the word and sentence structure can be led into long-term memory.

[0018] In addition, the present invention aims to provide a foreign language writing learning system utilizing image association characters and artificial intelligence, and a foreign language writing learning method using the same, which can objectively verify the learner's writing or speaking ability by receiving a handwritten or spoken answer as a result of learning after the learner has completed learning a learning text, determining whether it is correct, and providing only the words determined to be correct as words of the original text. means of solving the problem

[0019] To achieve the above objective, the present invention,

[0020] A database unit storing image association characters corresponding to one or more of specific images or abbreviations for each learning word;

[0021] A CAT conversion unit that, when an original text to be provided to a learner is input, extracts words included in the input original text, retrieves image association characters corresponding to the extracted words from the database unit and converts them into image association characters, generates a learning text composed of image association characters, classifies the generated learning text through one of the classification methods of difficulty, situation, or type, and then transmits it to the database unit for storage;

[0022] A passage provisioning unit that provides learning passages generated through the above-mentioned CAT conversion unit to a learner online or offline;

[0023] A learning provision unit that, after confirming the receipt of the learning text provided through the fingerprint provision unit, plays a recording file in which the original text is recorded with the original pronunciation previously stored by an instructor capable of providing the intonation and pronunciation of a native speaker or a corresponding pronunciation; and

[0024] It is characterized by including a learning confirmation unit that receives the answer text written by the learner regarding the learning text after the learner's learning through the learning provision unit is completed, and compares it with the original text stored previously to determine whether it is correct.

[0026] In addition, the above-mentioned learning verification unit is,

[0027] It is preferable to include an answer receiving unit that receives an image file of an answer passage written by a learner, captured or scanned using a camera or scanner; a word extraction unit that extracts words from the received image file; a writing verification unit that converts words determined to be correct answers into original words for learning and provides them to the learner by comparing the extracted words with the original passage; and a repetitive listening unit that plays back a sentence containing words determined to be incorrect answers through the recording file.

[0029] In addition, the above CAT converter is,

[0030] When converting words included in the input original text into corresponding image association characters, it is desirable to convert each word to include one or more image association characters, and to provide the converted image association characters to the learner according to a pre-set difficulty level, either in order from lowest to highest difficulty or according to the difficulty level set by the user.

[0032] Meanwhile, the foreign language writing learning method utilizing image association characters and artificial intelligence according to the present invention is,

[0033] A step of matching original learning words with corresponding image association characters and storing them in a database;

[0034] Step of inputting text to be provided to the learner;

[0035] A step of generating a learning audio file by having an instructor record the input text with a native speaker or equivalent intonation, pronunciation, and speed;

[0036] A step of generating a learning passage converted into image association characters that match the learning words constituting the input passage, and saving the input passage as the correct answer passage;

[0037] A step of providing the generated learning text to the learner online via a telecommunications line or in a printed state on paper via an output device;

[0038] A step of playing the above-mentioned learning recording file after the learning text has been provided to the learner;

[0039] It is characterized by including a step of checking the answer written by the learner, determining whether the image association character is correct, and scoring.

[0041] In addition, in the step of generating the above learning passage,

[0042] A new word verification step for checking whether there are new learning words among the learning words extracted from the input learning text, and

[0043] An abbreviation generation step for generating image association characters consisting of abbreviations for original learning words identified as new words, and

[0044] A verification step for obtaining verification and usage approval from the administrator for the newly generated image association characters, and

[0045] It is desirable to include a matching step in which verified and approved new image association characters are matched to new original words for learning and stored in the database. Effects of the invention

[0046] The present invention, as described above, has the advantage of improving memorization skills by providing a learner of a foreign language with image association characters consisting of specific images or abbreviations for the original words, thereby leading to long-term memory through visual stimulation, and simultaneously providing auditory stimulation through a recording file in which the learner checks the learning text consisting of image association characters with their eyes and a teacher or instructor who provides a pronunciation of the original words for the learning text by a native speaker or equivalent pronunciation, thereby increasing the efficiency of writing learning for a foreign language.

[0048] In addition, the present invention has the advantage of improving the learner's foreign language writing ability by grading the answer passage written by the learner to improve writing ability, converting only the words judged as correct among the written answer passages into words included in the original passage and providing them to the learner, and for sentences containing words judged as incorrect, repeatedly playing a recording file recorded by a native speaker, etc., to enable repetitive learning. Brief explanation of the drawing

[0049] FIG. 1 is a schematic diagram illustrating a foreign language writing learning system utilizing image association characters and artificial intelligence according to the present invention. FIG. 2 is a configuration diagram illustrating a foreign language writing learning system utilizing image association characters and artificial intelligence according to the present invention. FIG. 3 is an exemplary diagram illustrating an example of a learning text and an answer text according to the present invention. FIG. 4 is an illustrative diagram showing an example of another learning passage and answer passage according to the present invention. FIG. 5 is a configuration diagram illustrating the configuration of a CAT converter constituting the present invention. FIG. 6 is an example diagram illustrating a foreign language writing learning method using image association characters and artificial intelligence according to the present invention. FIG. 7 is an example illustrating a novel word matching step constituting the present invention. FIG. 8 is a flowchart illustrating the operation flow of the new word matching step shown in FIG. 7. FIG. 9 is an exemplary diagram illustrating a writing judgment step constituting the present invention. Specific details for implementing the invention

[0050] Hereinafter, a foreign language writing learning system utilizing image association characters and artificial intelligence according to the present invention and a foreign language writing learning method using the same will be examined in detail with reference to the attached drawings.

[0052] First, the foreign language writing learning system (1) utilizing image association characters and artificial intelligence according to the present invention comprises, as illustrated in FIG. 1, a database unit (10) in which image association characters (CAT) corresponding to either a specific image or an abbreviation for each learning word are stored; a CAT conversion unit (20) which, when an original text to be provided to a learner is input, extracts words included in the input original text (OT), calls the image association characters (CAT) corresponding to the extracted words from the database unit (10) and converts them into image association characters, generates a learning text (CT) composed of image association characters, classifies the generated learning text (CT) through one of the classification methods of difficulty, situation, or type, and then transmits and stores it in the database unit (10); a text unit (30) that provides the learning text (CT) generated through the CAT conversion unit (20) to the learner online or offline; and after the receipt of the learning text (CT) provided through the text unit (30) is confirmed, the original text is provided to a native speaker or It includes a learning provision unit (40) that plays a recording file recorded with original pronunciation that has been saved in advance by an instructor capable of providing corresponding intonation and pronunciation, and a learning confirmation unit (50) that receives an answer statement (AT) written by the learner regarding a learning statement (CT) after the learner's learning through the learning provision unit (40) is completed and determines whether it is correct.

[0054] The above database unit (10) electronically stores image association characters (CAT) and stores them systematically, and it is preferable that it be managed by a database management system (DBMS), which is a system that manages data storage.

[0055] The database unit (10) of the present invention is composed of hardware and software that manages it, as described above. Since the specific structure and operational relationship of the database unit (10) are well known, a detailed description will be omitted.

[0056] In addition, the above database unit (10) is connected to the learner via a wired or wireless communication means through a cloud server as shown in FIG. 1, and enables the transmission and reception of learning texts, answer texts, and the learner's voice answers.

[0057] However, in the present invention, the database unit (10) stores image association characters (CAT) corresponding to words of the language that the learner intends to learn. In the following description, the language that the learner intends to learn is English, as described and illustrated as an example, but this is merely one example, and it is obvious that it can be utilized with any foreign language other than the learner's native language, such as Spanish, French, Chinese, Japanese, or Korean.

[0058] In the following description, learning English is described as an example.

[0059] The image association character (CAT) corresponding to the English word stored in the database unit (10) consists of either an image or an abbreviation. As is known, the number of words constituting English is approximately 600,000 as of 1989, based on the Oxford English Dictionary, but the number of words actually used by native speakers is known to be about 20,000. Teachers and instructors currently teaching English to students claim that they can understand conversations, newspaper readings, movies, etc., within the range of 90-95% using only about 3,000 English words.

[0060] Accordingly, the image association characters (CAT) stored in the database unit (10) in the present invention are formed by selecting 3,000 essential words from English words and converting each word into one or more of images or abbreviations.

[0061] In Figure 3, the text placed on the left is a learning text (CT) converted into image association characters (CAT), and the composition written on the right is an answer text (AT) written in English by a learner after studying the learning text (CT).

[0062] In Figure 3, the sentence written by the learner has a 100% correct answer rate for the learning text (CT). Based on this, an example of the image association character (CAT) according to the present invention is as follows.

[0063] First, image association characters ' refers to the protagonist 'Kelly's' in the original text.

[0064] A sentence composed of a combination of the following image association characters: ' is 'family goes to a mexican restaurant' in the original text.

[0065] In other words, image association characters ' ' is 'family', and is an image association character ' is 'goes', and the image association character '→' is 'to'. And the image association character ' ' is 'mexican', and is an image association character ' ' is 'restaurant' in the original text.

[0066] As described above, in the present invention, image association characters (CAT) are formed as images or abbreviations for each word constituting a sentence, and then these are constructed as a sentence identical to the sentence of the original text to generate a learning text (CT).

[0067] There are also words here that are not transformed into Image Association Characters (CAT), such as 'It's,' the first word of the very next sentence. 'It's' is a shortened form of the possessive pronoun 'It is,' and as such, it is a basic word of the lowest difficulty level, so it was not converted separately.

[0068] Meanwhile, looking at the following sentence, abbreviations and images are mixed, and the image association characters are ' And, the words in the original text are 'It's very popular and it's always full of people'.

[0069] Although some of the image association characters (CAT) of the present invention have been illustrated through the above description and Figure 3, these image association characters (CAT) are merely one embodiment and can be modified to improve the learning efficiency of learners.

[0070] For example, when providing a learning text (CT) composed of sentences converted into the image association characters (CAT) of the present invention to a learner, if the learner is an online learner connected via a telecommunications line, when the native speaker's pronunciation provided along with the learning text (CT) is emitted through a speaker, effects such as changing the color of the image association characters being read by the native speaker or enlarging and then returning the size of the image association characters may be provided. In other words, various additional effects may be provided depending on the learner's learning environment to enhance the learner's learning efficiency.

[0072] Next, the above CAT conversion unit (20), when an original text to be provided to a learner is input, extracts words included in the input original text, calls an image association character (CAT) corresponding to the extracted words from the database unit (10) and converts it into an image association character, generates a learning text (CT) composed of image association characters, classifies the generated learning text (CT) through one of the classification methods of difficulty, situation, and type, and then transmits it to the database unit (10) for storage.

[0074] The above CAT conversion unit (20) inputs an original text to be provided by a teacher or instructor preparing a lecture for the learner's learning, and when the original text is input, it analyzes the sentences included in the text and extracts the words that make up each sentence.

[0075] An image association character (CAT) corresponding to the extracted word is called from the database unit (10), and the called image association character (CAT) is arranged to have the same sentence structure as the original text, thereby generating a learning text (CT).

[0076] The generated learning text (CT) is provided to the learner online or offline, and is simultaneously transmitted to and stored in the database unit (10).

[0077] At this time, multiple image association characters (CATs) may correspond to one word constituting the original text, and preferably, when multiple image association characters (CATs) correspond to one original word, the image association characters (CATs) are composed of abbreviations.

[0078] In other words, abbreviations are shortened words that have a relatively smaller number of letters compared to the original word, and the probability of a learner getting the correct answer varies depending on the number of letters omitted from a word.

[0079] Therefore, as an example of setting the difficulty level, the lowest difficulty level is one where the number of characters omitted is within the range of 1 to 3, the middle difficulty level is one where the number of characters omitted is 3 to 5, and the highest difficulty level is one where the number of characters omitted is 3 to 5, but the omitted characters are in non-consecutive positions.

[0080] As described above, when multiple image association characters (CATs) with different difficulty levels are formed for a single original word, the image association characters (CATs) that match the difficulty level set by the teacher or instructor are initially exposed to the learner during the process of converting the original text containing the original word into a learning text (CT).

[0081] Subsequently, when the difficulty level is changed at the request of a learner or by the teacher or instructor, the difficulty-adjustable Image Association Character (CAT) provides the learner with an Image Association Character (CAT) corresponding to the adjusted difficulty level to maintain the learner's interest in learning.

[0082] Meanwhile, when forming image association characters (CAT), if the input original word consists of an idiom (English idiom) which is a combination of two or more words used differently from the original meanings, a separate image association character (CAT) to express the idiom may be applied to the learning text (CT).

[0083] The present invention separately stores 100 idioms that are typically used in the CAT conversion unit (20), and when a word extracted from the original text is determined to be an idiom, calls the image association character (CAT) corresponding to the idiom and applies it to the learning text (CT).

[0084] In other words, as previously mentioned, idioms are combinations of two or more words and can be classified into preposition + noun, noun + preposition, idioms used in the form of verb + object + preposition using specific verbs and prepositions, idioms used in the form of verbs, and be verb + past passive voice; depending on the classification, representative multiple examples of these idioms are provided as separate image association characters.

[0085] At this time, the teacher or instructor can choose to provide the word recognized as an idiom as an idiom-specific image association character or as a general image association character.

[0086] In addition, for collocations that are fixed combinations of words in idioms and have the same meaning as combinations of individual words, one can choose to provide each word as an image association character or provide an image association character dedicated to the idiom.

[0087] As an example of the above idiom, 'free of charge' means 'free of charge', and 'free of charge' can be provided as image association characters designated as individual words 'fre', ' / ', and 'chag', or as another example, '0$' can be provided as an idiom-specific image association character created in image form.

[0088] Meanwhile, the CAT conversion unit (20) classifies the learning text (CT) according to one of the categories of difficulty, situation, and type when a teacher or instructor inputs the original text or after the learning text (CT) is generated, and then transmits it to the database unit (10) so that it is stored in the database unit (10) according to the classification.

[0089] The classification-based storage of these learning passages (CTs) enhances learners' interest by providing passages according to their desired difficulty level, situation, and type, and improves learning efficiency by providing continuity of learning.

[0090] For example, as shown in FIG. 4, if the learning text (CT) stored according to classification by type is related to food, the learning text (CT) shown in FIG. 4 is provided as a recommended learning text (CT) to the learner who has studied the learning text (CT), thereby increasing learning efficiency by continuously studying food or learning texts related thereto.

[0091] Here, recommended learning passages (CT) are selected from among the learning passages stored by category in the aforementioned database unit (10) that are classified as the same type as the learning passage (CT) that the learner studied immediately before, and among the selected multiple learning passages, they are sorted sequentially according to the difficulty level of the learning passage (CT) that the learner studied immediately before, and then among the sorted learning passages, the learning passage that is first provided to the learner is provided in the order in which it is first exposed.

[0092] The provision of such recommended learning passages (CT) is provided after the learner has completed learning one learning passage (CT) through the learning confirmation unit (50) described later.

[0094] Meanwhile, the above CAT conversion unit (20) may be configured to generate a new image association character (CAT) for a new word when a new word is input or determined to be a new word in addition to the word stored in the database unit (10), and to transmit and store the new image association character (CAT) among the generated new image association characters (CAT) that has been verified by a worker who input the original text, such as a teacher or instructor, to the database unit (10).

[0095] Looking at this in more detail, it includes a new word verification unit (21) that checks whether there is a new word during the process of extracting words from the input original text, an abbreviation generation unit (22) that generates an abbreviation for the new word when it is confirmed as a new word by the new word verification unit (21), a verification unit (23) that verifies the generated abbreviation by the worker who input the original text, and a matching unit (24) that matches the image association character verified to be used as a new image association character with the new word confirmed by the new word verification unit (21) and transmits it to the database unit.

[0097] The above new word verification unit (21) identifies the word as a new word when there is no matching image association character from the database unit (10) in the step of extracting the original text input by the worker word by word and matching the extracted word with the image association character (CAT) stored in the database unit (10).

[0098] In addition, as another example, a separate new word input section (211) is provided and can be used when a worker increases the number of words stored in the database section (10).

[0099] When a new word is identified through the new word verification unit (21) above, an abbreviation is generated for the word. Since there may not be an image prepared for use as an image association character (CAT) for the new word, the abbreviation is generated first among the image and the abbreviation and provided to the image association character worker for the new word.

[0100] Here, if an image association character for a new word is prepared as an image, an upload window (not shown in the drawing) for uploading the image to be used as the image association character may be provided to the operator. This upload window is provided through the display of a terminal operated by the operator and is configured as a platform in which operations necessary for image uploading are controlled through input means such as a keyboard, mouse, and pen. Since the specific structure and operational relationship of such a platform are known, a detailed description will be omitted.

[0101] It is preferable for the abbreviation generation unit (22) to generate multiple abbreviations for a single new word and provide them to the worker, because the spelling to be emphasized may differ for each English word.

[0102] For example, if the new word is 'comprehensible', the abbreviations for the word are generated as 'compreh~le', 'compre~sibl', and 'comprehen~le', and then provided to the worker so that they can select the appropriate abbreviation.

[0103] The verification unit (23) provides a plurality of abbreviations generated through the abbreviation generation unit (22) to the worker for verification, and the worker selects one of the plurality of abbreviations provided through the verification unit (23) as an image association character for a new word.

[0104] The above matching unit (24) matches a new word and an abbreviation selected as an image association character for it through the above verification unit (23), and then transmits and stores it to the above database unit (10).

[0106] The next fingerprint unit (30) provides the learning fingerprint (CT) generated through the CAT conversion unit (20) to the learner online or offline. To this end, the fingerprint unit (30) is connected to an electrical communication line such as a wired or wireless communication means and transmits the learning fingerprint (CT) to an authenticated learner through a login server (not shown) or an authentication server (not shown).

[0107] Here, offline provision of the fingerprint study (30) means providing the learning fingerprint (CT) to multiple users through an external device, such as a beam projector installed in a classroom, for example.

[0109] The next learning provision unit (40) plays a recording file containing the original pronunciation of the original text that was previously saved for the original text by a native speaker or an instructor capable of providing the original text, after the learning text (CT) has been provided to the learner through the text provision unit (30) and after it has been confirmed that the learner has received the learning text (CT).

[0110] The above-mentioned learning provider (40) provides a learning text (CT) composed of image association characters (CAT) to a learner using the original text, which is the correct answer to the learning text (CT), with the original text recorded by a native speaker or an equivalent instructor. At this time, the recording file is provided repeatedly at regular intervals.

[0111] In other words, the learner infers and remembers the original words for the image association characters (CAT) that constitute the learning text (CT) by using sight to verify the learning text (CT) while listening to the audio file through hearing.

[0112] Through this, learners can improve memorization skills by matching images or abbreviations constituting Image Association Characters (CAT) to the original word, thereby facilitating long-term memory compared to conventional memorization by writing. Additionally, since learners can remember the original word by listening to its pronunciation along with the images or abbreviations of the Image Association Characters (CAT), they can simultaneously experience both image-based and auditory association methods, enabling them to remember the original word.

[0114] Next, the above-mentioned learning confirmation unit (50) receives the answer text (AT) written by the learner regarding the learning text (CT) after the learner's learning through the above-mentioned learning provision unit (40) is completed, and determines whether it is correct.

[0116] The above learning verification unit (50) receives the answer text (AT) written by the learner from the teacher or instructor who provided the learning text (CT) and performs scoring on the written answer text (AT).

[0117] Here, the answer text (AT) can be submitted by handwriting on paper, or it can be written on paper and then captured and saved using equipment such as a camera or scanner for transmission.

[0118] The learning verification unit (50) for this purpose includes an answer receiving unit (51) that receives an image file of an answer text (AT) written by a learner, which is captured or scanned using a camera or scanner; a word extraction unit (52) that extracts words from the received image file; a writing verification unit (53) that converts words determined to be correct answers into original words for learning and provides them to the learner by comparing the extracted words with the original text; and a repetitive listening unit (54) that plays back a sentence containing words determined to be incorrect answers through the recording file.

[0119] The above-mentioned answer receiving unit (51) can receive an answer written by a learner that has been converted into a digital data file by taking a picture of it using a camera or scanning it using a scanner, and an answer written by the learner by hand on paper can also be used as an answer if the teacher or instructor can determine whether it is the correct answer.

[0120] Here, the above-mentioned response receiving unit (51) receives a digital data file that the learner directly transmits online via a telecommunications line. Since the transmission and reception of such digital data files are well known, a detailed description of the structure and operational relationship is omitted.

[0121] The above word extraction unit (52) extracts words from the received answer text, and the conversion and extraction from the image into text is performed using an optical character recognition (OCR) program.

[0122] Such optical recognition character programs acquire images of characters written by humans or printed by machines using an image scanner and convert them into machine-readable characters; as this is a well-known process, a detailed description of its structure and operation will be omitted.

[0123] The next writing verification unit (53) compares the words extracted through the word extraction unit (52) with the original text to determine whether each word is correct, and converts only the words determined to be correct into original learning words that constitute the original text, and then provides them to the learner.

[0124] In other words, only the words written as correct answers in the learner's response text are converted into original learning words and provided to the learner, while words judged as incorrect remain in the image extended text state.

[0125] The next repeated listening section (54) plays a recording file for a word or sentence containing a word that was judged to be incorrect, so that the learner can learn the word or sentence repeatedly.

[0126] The above-mentioned repeated listening section (54) is preferably repeated until the answer written by the learner is judged to be 100% correct, and the number of playbacks, playback intervals, etc. can be arbitrarily set by the teacher or instructor.

[0128] Next, the foreign language writing learning method (S1) utilizing image association characters and artificial intelligence according to the present invention comprises the steps of: matching original learning words with image association characters that match them and storing them in a database (S10); inputting a passage to be provided to a learner (S20); recording the inputted passage with an accent, pronunciation, and speed equivalent to that of a native speaker or an instructor to generate a learning recording file (S30); analyzing the original learning words constituting the inputted passage to generate a learning passage converted into matched image association characters and storing the inputted passage as a correct answer passage (S40); providing the generated learning passage to the learner online via a telecommunication line or in a printed state on paper via an output device (S50); playing the learning recording file after the learning passage has been provided to the learner (S60); and checking the answer written by the learner to determine whether the image association characters are correct and scoring (S70).

[0130] The above database storage step (S10) involves matching and storing a specific image or abbreviation with an original word selected as a learning word. Here, the database is managed by a database management system (DBMS), which is a system that manages data storage. Since the specific structure and operational relationship of such a database are well known, a detailed description will be omitted.

[0132] The step of inputting a learning text to be provided to the next learner (S20) is a step in which a teacher or instructor inputs a learning text to generate a learning text to be provided to the learner.

[0133] Here, a teacher or instructor inputs learning texts through an input device connected to the above database, wherein the input device may consist of a keyboard, mouse, or optical scanner, etc.

[0134] The above-mentioned optical scanner scans learning passages written by a teacher or instructor, saves them as a digital file, and identifies and extracts words from the saved digital file, i.e., the image. Here, the identification and extraction of words from the image can be performed through a separate character recognition program (Optical Character Recognition: OCR); since such a character recognition program is a known one, detailed description and illustration will be omitted.

[0136] The step (S30) is to generate a recording file of the content of a learning text to be provided to the next learner, recorded by a native speaker of the language constituting the text or by an instructor or teacher capable of pronunciation, intonation, and speed equivalent thereto.

[0137] In other words, the teacher or instructor generates a learning audio file by having a native speaker or recording the learning passage provided to the learner directly, and simultaneously stores the learning passage so that it can be used as a criterion for determining the correct answer in the grading stage described later.

[0139] The next step (S40) is to generate a learning passage by calling image association characters that match the learning words constituting the input learning passage from the database and arranging them to have the same sentence structure as the learning passage, and to save the input learning passage as the correct answer passage.

[0140] A learning passage is generated to be provided to learners by retrieving image association characters from a database that match the learning words constituting the learning passage entered by a teacher or instructor, and arranging them to form the same sentence structure as the learning passage.

[0141] Once the generation of the learning passage is complete, the corresponding learning passage is identified as the correct answer and saved by matching it with the learning passage.

[0142] Here, the storage and retrieval of learning passages, answer passages, and learning passages are performed through the aforementioned database. Since the matching, storage, and retrieval of such data are identical to the operations of moving, storing, and loading general digital data, a detailed explanation thereof will be omitted.

[0144] Meanwhile, in the step of generating the learning passage (S40), if there is no matching image association character among the learning words constituting the learning passage, a new image association character for the corresponding learning word is generated and stored in the database.

[0145] To this end, the step of generating a learning text (S40) includes a new word verification step (S41) for verifying whether there is a new learning word among the learning original words extracted from the input learning text, an abbreviation generation step (S42) for generating an image association character consisting of an abbreviation for the learning original word identified as a new word, a verification step (S43) for verifying and obtaining approval for use of the generated new image association character from an administrator, and a matching step (S44) for matching the verified and approved new image association character to the new learning original word and storing it in the database.

[0147] The above new word verification step (S41) involves extracting the learning text input by the administrator word by word and, in the process of matching the extracted words with image association characters stored in the database, checking whether there are matching image association characters in the database, and identifying words that do not have matching image association characters as new words.

[0148] Here, a separate new word input step (S411) is provided so that an administrator can store image association characters matching the new word in the database.

[0149] The next abbreviation generation step (S42) is a step of generating an abbreviation for a word identified as a new word in the new word verification step (S41). Since there may be cases where an image to be used as an image association character is not prepared for a new word, an abbreviation is generated first among an image or an abbreviation to be used as an image association character, and provided to the administrator as an image association character for the identified new word.

[0150] Here, if an image association character for a new word is prepared as an image, an image upload step (S421) may be provided to the administrator so that the image can be used.

[0151] In addition, in the abbreviation generation step (S42), it is desirable to generate multiple abbreviations for a single new word and provide them to the worker, because the spelling to be emphasized may differ for each English word.

[0152] For example, if the new word is 'comprehensible', the abbreviations for the word are generated as 'compreh~le', 'compre~sibl', and 'comprehen~le', and then provided to the worker so that they can select the appropriate abbreviation.

[0153] The next verification step (S43) is a step in which the generated abbreviation is verified by an administrator, and approval for use is granted after verification.

[0154] In this verification step (S43), multiple generated abbreviations are each verified by the administrator, and the difficulty level for each abbreviation is set simultaneously with the verification.

[0155] Here, the difficulty level can be automatically set based on the number of letters omitted or the position of omission in the case of image association characters consisting of abbreviations. For example, the lowest difficulty level is one where the number of letters omitted is within the range of 1 to 3, the medium difficulty level is one where the number of letters omitted is 3 to 5, and the highest difficulty level is one where the number of letters omitted is 3 to 5, but the omitted positions are non-consecutive.

[0156] The next matching step (S44) is a step of verifying and approving the new image association character, which has a difficulty level set through the verification step (S43), matching it with the corresponding new learning word, and then storing it in the database.

[0158] Meanwhile, in the step (S40) of generating the learning text, the generated learning text is classified into one of difficulty level, situation, or type, and then transmitted to and stored in the database unit. The learning text classified into one of difficulty level, situation, or type is provided to the learner according to the learner's request or the adjustment of the teacher or instructor. As learning progresses, learning texts of higher difficulty are provided, but learning texts of similar situations or types are provided so that interest in learning can be maintained.

[0159] For example, as shown in Fig. 4, if the learning text stored according to classification by type is related to food, the learning text shown in Fig. 4 is provided to a learner who has studied the food-related learning text as the next recommended learning text to study, thereby increasing learning efficiency by continuously studying food or the learning text related thereto.

[0160] Here, recommended learning passages refer to learning passages stored by category in the aforementioned database, multiple learning passages classified as the same type as the learning passage the learner studied immediately before, and among the multiple selected learning passages, sequentially sorted according to the difficulty level of the learning passage the learner studied immediately before, and then provided in an order in which the learning passage provided to the learner for the first time among the sorted learning passages is displayed first.

[0161] The provision of such recommended learning passages is provided after the learner has completed learning one learning passage through the scoring step (S70) described later.

[0162] Of course, in addition to the method of providing learning passages according to the aforementioned classification, they may also be provided in a random form without any special rules.

[0164] Meanwhile, in the step (S40) of generating the learning text, if the original learning word extracted from the learning text during the process of converting it into an image association word consists of two or more words combined and used differently from the original meaning of the words, an idiom verification step (S45) may be further included in which an idiom association word matching the idiom is applied to the learning text.

[0165] To this end, the above database separately stores idiom-specific mnemonic characters that match 100 idioms commonly used in English, and when a source word extracted from a learning text is determined to be an idiom, the idiom-specific mnemonic character that matches the idiom is applied first to the learning text.

[0166] As previously mentioned, idioms are combinations of two or more words and can be classified into preposition + noun, noun + preposition, idioms used in the form of verb + object + preposition using specific verbs and prepositions, idioms used in the form of verbs, and be verb + past passive voice. Depending on the classification, representative examples of these idioms are provided as separate mnemonic characters dedicated to idioms.

[0167] At this time, the teacher or instructor can choose to provide the word recognized as an idiom as an idiom-specific associative character or as a general image associative character.

[0168] In addition, for collocations that are fixed combinations of words in idioms and have the same meaning as combinations of individual words, one can choose to provide each word as an image association character or as an association character dedicated to the idiom.

[0169] As an example of the above idiom, 'free of charge' means 'free of charge', and 'free of charge' can be provided as image association characters designated as individual words 'fre', ' / ', and 'chag', or as another example, '0$' can be provided as an idiom-specific image association character created in image form.

[0171] In the next step (S50) of providing the generated learning text to the learner, the generated learning text is provided to the learner online or offline.

[0172] In this case, offline provision includes providing content in the form of printouts on paper via a printer or providing it through external devices, such as beam projectors installed in classrooms for multiple learners.

[0174] The next step of playing the recording file (S60) is a step of playing the recording file generated through the step of generating the recording file (S30) so that the learner can listen to it, and the number of times it is played can be adjusted according to the difficulty level of the learning text or selected by the learner.

[0175] In the step (S60) of playing the recording file, as described above, when the learning text is provided to the learner online, that is, in the case of a device capable of displaying the learning text through a display such as a smartphone, tablet, or desktop, the color, size, brightness, etc. of the learning text can be changed in conjunction with the playback of the recording file to improve learning efficiency.

[0177] The next scoring step (S70) is a step in which the learner listens to the learning passage played back through the audio file, converts the learning passage consisting of image association characters into the original language, that is, the original language for learning, and recognizes the answer passage written to determine the correct answer.

[0179] The scoring step (S70) includes an answer receiving step (S711) for receiving an image file of an answer written by a learner that is captured or scanned using a camera or scanner, a word extraction step (S712) for extracting words from the received image file, a writing verification step (S713) for converting words determined to be correct into original words for learning by comparing the extracted words with the answer text and providing them to the learner, and a repeated listening step (S714) for playing a sentence containing words determined to be incorrect through the recording file.

[0181] Here, the answer text may be handwritten by the learner on paper and submitted, or it may be written on paper and then photographed with a camera or scanned using optical equipment such as a scanner and saved as a digital file.

[0183] The above answer receiving step (S711) is a step of receiving an answer submitted by a learner in the form of a paper or digital file. In the case of an answer submitted in paper, a teacher or instructor may photograph or scan it and save it as a digital file, and the answer text submitted in paper itself may be used for grading.

[0184] The above word extraction step (S712) extracts each word constituting the answer written in the received answer text, and in this case, if the answer text is converted into a digital file, the words are extracted through an optical character recognition program (OCR).

[0185] The extracted words are arranged in the same order as the sentence structure constituting the answer passage, but characters that are not extracted as words are displayed in their recognized form or replaced with a separate 'unrecognized' mark.

[0186] The next writing verification step (S713) checks whether each character matches the correct answer based on its position relative to the learning text stored as the correct answer text, and converts the word determined to be the correct answer into a learning original word (learning original word) and provides it to the learner.

[0187] In the case of an answer that is not ultimately confirmed as 100% correct through this writing verification step (S713), the learner is requested to submit a corrected answer, and if the learner submits a corrected answer, the answer is graded by repeating from the answer reception step (S711) or the word extraction step (S712).

[0188] The next repeated listening step (S714) is a step in which, if the answer text is not 100% correct as a result of checking the answer text in the above writing verification step (S713), the recording file is played again so that the learner can perform repeated learning on the learning text.

[0190] The above scoring step (S70) is a step for verifying the learner's writing ability, and through this step, the learner can improve their foreign language writing ability by visually checking a learning text composed of image association characters and simultaneously listening to an audio file while writing.

[0192] As described above, the present invention has been explained by specific details such as specific components, limited embodiments, and drawings; however, this is provided merely to aid in a more comprehensive understanding of the invention, and the invention is not limited to the above embodiments. A person skilled in the art can make various modifications and variations from this description.

[0194] Accordingly, the scope of the present invention should not be limited to the described embodiments, and all things equivalent to or having equivalent variations to the claims set forth below, as well as the claims set forth below, shall be considered to fall within the scope of the concept of the present invention. Explanation of the symbols

[0195] 1: Foreign language writing learning system utilizing image association characters and artificial intelligence 10: Database Section 20 : CAT converter 21: New Word Verification Unit 22: Abbreviation Generation Unit 23 : Verification section 24 : Matching section 30: Studying passages 40 : Study materials 50 : Learning Confirmation Section 51 : Answer receiving unit 52 : Word extraction unit 53: Composition Check Section 54: Repetitive Listening Section S1: Foreign language writing learning method using image association characters and artificial intelligence. S10: Step of matching image association characters with original learning words and storing them in a database S20: Step for inputting text to be provided to the learner S30: A step in which an instructor records the input text with a native speaker or equivalent intonation, pronunciation, and speed to generate a learning audio file. S40: A step of generating a learning passage converted into image association characters that match the learning words constituting the input passage, and saving the input passage as the correct answer passage. S50: A step of providing the generated learning text to the learner online via a telecommunications line or in a printed state on paper via an output device. S60: A step of playing the above-mentioned learning recording file after the learning text has been provided to the learner. S70: A step for checking the answer text written by the learner, determining whether the image association characters are correct, and grading.

Claims

Claim 1 A database unit (10) in which one or more image association characters (CAT) corresponding to a specific image or abbreviation are stored for each learning word; a CAT conversion unit (20) which, when an original text to be provided to a learner is input, extracts words included in the input original text, calls the image association characters (CAT) corresponding to the extracted words from the database unit (10) to convert them into image association characters, generates a learning text (CT) composed of image association characters, classifies the generated learning text (CT) through one of the classification methods of difficulty, situation, or type, and then transmits it to the database unit (10) for storage; a text unit (30) that provides the learning text (CT) generated through the CAT conversion unit (20) to the learner online or offline; and a learning provision unit (40) that, after the receipt of the learning text (CT) provided through the text unit (30) is confirmed, plays a recording file in which the original text is recorded with the original pronunciation stored in advance by a native speaker or an instructor capable of providing the corresponding intonation and pronunciation. The learning confirmation unit (50) receives the answer voice (AT) written by the learner regarding the learning text (CT) after the learner's learning through the learning provision unit (40) is completed, and determines whether it is correct by comparing it with the original text stored previously; the learning confirmation unit (50) includes an answer receiving unit (51) that receives an image file of the answer text (AT) written by the learner by taking a picture or scanning it using a camera or scanner, a word extraction unit (52) that extracts words from the received image file, a writing confirmation unit (53) that converts the extracted words into original words for learning that are determined to be correct by comparing them with the original text and provides them to the learner, and a repetitive listening unit (54) that plays back a sentence containing words determined to be incorrect through the recording file; and the CAT conversion unit (20) converts the words included in the input original text into corresponding image association characters (CAT) by including one or more image association characters (CAT) for each word when converting.The converted image association characters (CAT) are provided to the learner according to a preset difficulty level, provided in order from lowest to highest difficulty or according to the difficulty level set by the user, and further include a new word verification unit (21) that checks whether there is a new word during the process of extracting words from the input original text, an abbreviation generation unit (22) that generates an abbreviation for the new word if it is confirmed as a new word by the new word verification unit (21), a verification unit (23) that receives verification of the generated abbreviation from the worker who input the original text, and a matching unit (24) that matches the image association characters verified to be used as new image association characters with the new word confirmed by the new word verification unit (21) and transmits it to the database unit, wherein the new word verification unit (21) specifies the word as a new word if there is no matching image association character from the database unit (10) in the step of extracting the original text input by the worker word by word and matching the extracted word with the image association characters (CAT) stored in the database unit (10), and the writing verification unit (53) A foreign language writing learning system utilizing image association characters and artificial intelligence, characterized by comparing words extracted through a word extraction unit (52) with the original text to determine whether each word is correct, converting only the words determined to be correct into original words for learning that constitute the original text, and providing them to the learner. Claim 2 delete Claim 3 delete Claim 4 delete Claim 5 delete

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