JP2013072973A - Language learning teaching material providing system, sentence transformation method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a function to convert a first sentence learned into a second sentence according to level information of a language learner.SOLUTION: In a language learning teaching material providing system, there are provided a sentence acquisition unit for acquiring a first sentence, a sentence conversion unit for converting words and/or idioms and/or a sentence pattern which compose the first sentence into a second sentence composed in the same language as the first sentence according to a conversion rule, a difficulty evaluation unit for evaluating a difficulty of the first sentence on the basis of skill information of a user registered at the time of access, and a conversion rule management unit for managing the conversion rule on the basis of the skill information and purpose of the user registered at the time of access and the evaluation result of the difficulty.

Description

  The present invention relates to a technique for providing a language learning material corresponding to a learner's level.

  There is an English learning method that improves reading comprehension by reading a lot of English. With the spread of the Internet, an environment where many English sentences can be easily accessed has been established.

  FIG. 21 shows an outline of a conventional system. FIG. 21 is a schematic diagram of a system that translates and presents Japanese sentences presented on the Internet into English. The system shown in FIG. 21 provides a host system 10003 that converts Japanese text into English, terminals that receive the converted English text (mobile terminal apparatuses 10002a, 1000b, and 10002n, and terminal equipment 10001), and Japanese text before conversion. The other host system 10004 is configured. The host system 10003 is provided with another host system information acquisition unit 100031, a translation unit 100032, a translation rule DB 10005, and a corpus DB 10006.

  The mobile terminal apparatuses 10002a, 10002b, and 10002n are connected to the base station 10002 through wireless lines. The base station 10002 is connected to a network 10008 which is a wired public line network. The terminal device 10001 is connected to a network 10008 which is a wired public line network. A host system 10003 is also connected to the network 10008.

  In the system shown in FIG. 21, an English sentence corresponding to a Japanese sentence that is a reference target is transmitted to the terminal by the following procedure. First, the mobile terminal device 10002a, 10002b, 1200n, or the terminal device 10001 is given an address on the network where information composed in Japanese that the user wants to refer to exists.

  The host system 10003 uses the other host system information acquisition unit 100031 to acquire the requested information from the other host system 10004, and passes the acquired Japanese information to the translation unit 100032. The translation unit 100032 converts the passed Japanese information into English based on the rule information for converting Japanese acquired from the translation rule DB 10005 and the corpus DB 10006 into English.

  Thereafter, the translation unit 100032 returns English information to the other host system information acquisition unit 100031. The other host system information acquisition unit 100031 returns the acquired English information to the mobile terminal devices 10002a, 10002b, and 1000n or the terminal device 10001. The mobile terminal apparatuses 10002a, 10002b, 10002n, or the terminal apparatus 10001 display English sentences acquired via the network 10008 on the screen.

The feature of this system is that the translation unit 100032 for translating from Japanese to English translates English sentences equivalent to Japanese sentences in a 1: 1 relationship.
In addition, there exists the patent document 1 shown below as a well-known technical document relevant to this invention.

JP 2002-32367 A

  As described above, English extensive reading is one of the most effective learning methods for improving English reading comprehension. However, there are English sentences of various difficulty levels on the Internet. For this reason, referring to English sentences on the Internet for the purpose of learning English is not necessarily an English sentence suitable for learners.

  An object of the present invention is to provide a mechanism that can be used to improve the reading comprehension of a learner by converting it into a sentence at a level corresponding to the learner when the language learner refers to the original sentence described in the learning target word. It is to provide.

  In order to achieve the above object, according to the present invention, a sentence acquisition unit that acquires a first sentence, and words and / or idioms and / or sentence patterns that constitute the first sentence are converted according to a conversion rule. A sentence conversion unit that converts the sentence into the second sentence that is configured in the same language as the sentence, and a difficulty evaluation unit that evaluates the difficulty level of the first sentence based on the skill information of the user registered at the time of access And a language learning teaching material providing system having a conversion rule management unit for managing the conversion rule based on the user skill information registered at the time of access and the user's purpose and difficulty evaluation result. Moreover, the text conversion method performed with the system is provided.

  According to the present invention, an original sentence can be converted into sentences having different levels in the same original word according to the language level (skill information) of the user, the purpose, and the difficulty level of the original sentence. Thereby, the reading comprehension ability of a user's learning language can be improved efficiently. Problems, configurations, and effects other than those described above will be clarified by the following description of embodiments.

The figure which shows the function structure of the language learning teaching material provision system which concerns on embodiment. The figure which shows a part of data structure stored in the conversion rule database. The figure which shows a part of data structure stored in the conversion rule database. The figure which shows a part of data structure stored in the conversion rule database. The figure which shows a part of data structure stored in the conversion rule database. The figure which shows a part of data structure stored in the conversion rule database. The figure which shows a part of data structure stored in the learning condition / plan database. The figure which shows a part of data structure stored in the learning condition / plan database. The figure which shows a part of data structure stored in the learning condition / plan database. The figure which shows a part of data structure stored in corpus database. The figure which shows a part of data structure stored in corpus database. The figure which shows a part of data structure stored in corpus database. The figure explaining the classification | category of English according to a user skill. The flowchart explaining the conversion process of English sentences. The flowchart explaining the conversion process to the English sentence for the purpose of learning. The flowchart explaining the conversion process to English for the purpose of content understanding. The flowchart explaining the conversion process of a word and a idiom. The flowchart explaining the production | generation process of a conversion rule. The flowchart explaining the count process of the appearance frequency of a corpus. The figure which shows the example of a screen display. The block diagram which shows the outline | summary of a conventional system.

  In the following embodiment, processing functions necessary for realizing the search system according to the embodiment will be described by being divided into a plurality of sections. In the following embodiments, when referring to the number of elements, etc. (including the number, numerical value, quantity, range, etc.), unless otherwise specified and in principle limited to a specific number in principle, It is not limited to the specific number, and may be more or less than the specific number. In the following embodiments, the constituent elements (including element steps and the like) are not necessarily indispensable unless otherwise specified or apparently essential in principle.

  Further, in the following embodiments, each configuration, function, processing unit, processing unit, and the like may be partially or entirely realized as, for example, an integrated circuit or other hardware. Further, each configuration, function, and the like described above may be realized by a processor interpreting and executing a program that realizes each function. That is, it may be realized as software. Information such as programs, tables, and files for realizing each function can be stored in a memory, a hard disk, a storage device such as an SSD (Solid State Drive), or a storage medium such as an IC card, an SD card, or a DVD.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Note that components having the same function are denoted by the same or related reference symbols throughout the drawings for describing the embodiments, and the repetitive description thereof is omitted. In the following embodiments, the description of the same or similar parts will not be repeated in principle unless particularly necessary.

[System configuration]
FIG. 1 shows the configuration of an English learning material providing system to which the present invention is applied. This system provides a host system 3 that provides an English-to-English conversion service, a plurality of mobile terminal devices 2a, 2b, and 2n and a terminal device 1 that receive converted English text from the host system 3, and an English text before conversion. The other host system 4 is configured. Here, the English sentence includes not only text written in English but also a multimedia document in which image data and other information are embedded.

  The mobile terminal devices 2a, 2b, and 2n are connected to the base station 2 through wireless lines. The base station 2 is a wireless transmission / reception device that accommodates the mobile terminal devices 2a, 2b, and 2n. For example, when the mobile terminal devices 2a, 2b, and 2n are mobile phones, the base station 2 corresponds to a base station of a mobile phone operator. For example, when the mobile terminal devices 2a, 2b, and 2n are wireless LAN slave units, the base station 2 corresponds to a wireless LAN base unit. In the case of FIG. 1, the base station 2 is connected to a network 8 by a wired public line network. The terminal device 1 is connected to a network 8 which is a wired public line network. A host system 3 is connected to the network 8. Accordingly, the mobile terminal devices 2a, 2b, and 2n and the host system 3 are connected to each other through the wireless line reaching the base station 2 and the network 8. Similarly, the terminal device 1 is connected to the host system 3 through the network 8.

  The other host system 4 is connected to the network 8 and is equivalent to a system that provides English information, for example, a WWW server.

[Functional configuration of the host system]
The host system 3 includes an other host system information acquisition unit 31, an English → English conversion unit 32, a conversion rule management unit 33, a learning status / plan information management unit 34, a corpus management unit 35, a conversion rule DB 5, a learning status / plan DB 6, It has a corpus DB7.

  The other host system information acquisition unit 31 is a processing function called from the English → English conversion unit 32 and the conversion rule management unit 33, and is connected between the terminal device 1, the mobile terminal devices 2 a, 2 b, 2 n, and the other host system 4. Relay communication.

  The English-to-English conversion unit 32 is a functional unit that converts an English sentence read from the other host system 4 into an English sentence corresponding to the language level (learning skill) of the user of the terminal device 1 or the mobile terminal device 2a, 2b, 2n. The conversion rule management unit 33 is a functional unit that manages the conversion rule DB 5. The learning status / plan information management unit 34 is a functional unit that manages the learning status / plan DB 6. The corpus management unit 35 is a functional unit that manages the corpus DB 7.

[Conversion rule DB]
The conversion rule DB 5 includes user-set word phrase conversion rules 210 shown in FIG. 2, user-set host system access information 220 shown in FIG. 3, verb utilization statistical information 230 shown in FIG. 4, and FIG. A word idiom conversion rule 310 and a user-set syntax conversion rule 410 shown in FIG. 6 are stored.

  The user-defined word phrase conversion rule 210 (FIG. 2) includes a rule ID 211, a word phrase (before conversion) 212, and a word phrase (after conversion) 213, and is registered for each rule. Words and idioms are stored in the word idioms.

  The other host system access information 220 (FIG. 3) set by the user is composed of access information 221 to the other host system 4 used for evaluation, and is registered for each other host system 4. For example, a network address is stored in the access information 221.

  The verb utilization statistical information 230 (FIG. 4) includes a verb utilization example 231, a noun 232, and an appearance count 233, and is registered for each combination of verb and noun. In the appearance count 233, the number of times that the combination of the corresponding verb and noun is used in the English sentence acquired from the access information 221 to the other host system used for evaluation is registered.

  The word idiom conversion rule information 310 (FIG. 5) includes a rule ID 311, a word idiom (before conversion) 312, and a word idiom (after conversion) 313. The word idiom conversion rule information 310 is registered for each rule in which the verb utilization form shown in FIG. 12 is individually applied to the rule of FIG. Here, a case where the rule ID 211 in FIG. 2 is “10000003” will be described. In “10000003”, “get rid of [1]” is registered as the word phrase (before conversion) 212, and “throw [1] away” is registered as the word phrase (after conversion) 213. At this time, in the rule ID 311 “10000003”, combinations of utilization forms shown in FIG. 12 are registered in the verbs of the word idiom (before conversion) 312 and the word idiom (after conversion) 313. For example, "get rid of [1]" and "throw [1] away", "gets rid of [1]" and "throws [1] away", "got rid of [1]" and "threw [1] away , “Gotten rid of [1]” and “thrown [1] away”, “getting rid of [1]” and “throwing [1] away” are registered.

  The user-set syntax conversion rule information 410 (FIG. 6) includes a syntax rule ID 411, a syntax (before conversion) 412, and a syntax (after conversion) 413, and is registered for each rule. For example, for the syntax “[S] [V] [O] [C]”, the syntax “[S] [V] [O] and [O] is [C]” is registered.

[Learning status / plan DB]
The learning situation / plan DB 6 stores a word acquisition situation 510 shown in FIG. 7, an idiom acquisition situation 520 shown in FIG. 8, and a syntax acquisition situation 530 shown in FIG.

  The word acquisition status information 510 (FIG. 7) includes a user name 511, a word ID 512, a word 513, and an acquisition status 514, and is registered for each user and for each word. In the acquisition status 514, “Acquired” is registered if the user has already acquired the word, and “Acquisition” is registered if the user is to acquire the next word.

  The idiom acquisition status information 520 (FIG. 8) includes a user name 521, a idiom ID 522, a idiom 523, and an acquisition status 524, and is registered for each user and for each idiom. In the acquisition status 524, “acquired” is registered if the user has acquired the idiom, and “under acquisition” is registered if the user is to acquire the next idiom.

  The syntax acquisition status information 530 (FIG. 9) includes a user name 531, a syntax rule ID 532, and a learning status 533, and is registered for each user and for each syntax rule. A syntax rule ID 411 is registered in the syntax rule ID 532, and “acquired” is acquired in the acquisition status 533 if the user has acquired the syntax, and “under acquisition” if the user should acquire the next syntax. Register.

[Corpus DB]
The corpus DB 7 stores word management information 610 shown in FIG. 10, idiom management information 620 shown in FIG. 11, and verb management information 630 shown in FIG.

  The word management information 610 (FIG. 10) includes a word ID 611, a word 612, an appearance count 613, and a part of speech, and is registered for each word. In FIG. 10, a noun 614, a particle 615, and an adjective 616 are described as examples of parts of speech. In the appearance count 613, the number of times the corresponding word is used is registered in the English sentence acquired from the access information 221 (FIG. 3) to the other host system 4 used for evaluation.

  The idiom management information 620 (FIG. 11) includes a idiom ID 621, a idiom 622, and the number of appearances 623, and is registered for each idiom. In the appearance count 623, the number of times that the corresponding idiom is used in the English sentence acquired from the access information 221 to the other host system 4 used for evaluation is registered.

  Verb management information 630 (FIG. 12) includes word ID 631, original form 632, third person singular present form 633, past form 634, past participle form 635, and present participle form 636, and is registered for each word. The

[Host system processing functions]
First, the English → English conversion unit 32 or the conversion rule management unit 33 inputs a method for acquiring English text from the other host system 4 to the other host system information acquisition unit 31. Next, the other host system information acquisition unit 31 connects to the other host system 4 through the network 8 to acquire English information, and returns it to the English → English conversion unit 32 or the conversion rule management unit 33.

  The English → English conversion unit 32 receives, from the mobile terminal devices 2a, 2b, 2n or the terminal device 1, a method for acquiring English text from the other host system 4 or a conversion target English text. When the method of acquiring English from the other host system 4 is specified, the other host system information acquiring unit 31 acquires the English to be converted via the network 8.

  The host system 3 uses the conversion rule DB 5, the learning status / plan DB 6, and the corpus DB 7 to convert the English text to be converted into an English text for learning purposes or an English text for understanding purposes according to the language level of the user.

  The English for learning purpose is a word whose acquisition status 514 (FIG. 7) is “acquired” or “under acquisition”, an idiom whose acquisition status 524 (FIG. 8) is “acquired” or “under acquisition”, and an acquisition status 533 (FIG. 9) is a sentence composed of the syntax “Learning” or “Learning”. The English sentence for the purpose of understanding is a word whose acquisition status 514 (FIG. 7) is “acquired”, an idiom whose acquisition status 524 (FIG. 8) is “acquired”, and an acquisition status 533 (FIG. 9) whose syntax is “acquired”. It is a sentence composed of

  As the conversion rules, verb utilization statistical information 230 (FIG. 4), word idiom conversion rules 310 (FIG. 5), and user-configured syntax conversion rules 410 (FIG. 6) are used. As the acquisition status of the user accessing the system, the word acquisition status 510 (FIG. 7), the idiom acquisition status 520 (FIG. 8), and the syntax acquisition status 530 (FIG. 9) are used.

  The conversion rule management unit 33 manages the update of the conversion rule DB 5. The conversion rule management unit 33 sends information on word idioms (before conversion), information on word idioms (after conversion), and other host systems 4 used for evaluation from the mobile terminal devices 2a, 2b, 2n and the terminal device 1. Access information, syntax (before conversion) information, and syntax (after conversion) information are input, rule ID 211 (FIG. 2), word idiom (before conversion) 212 (FIG. 2), and word idiom (conversion). After) 213 (FIG. 2), access information 221 (FIG. 3) to other host system 4 used for evaluation, syntax rule ID 411 (FIG. 6), syntax (before conversion) 412 (FIG. 6), syntax (After conversion) 413 (FIG. 6) is registered.

  In order to reduce the difficulty level of sentences by deleting adverbs, adjectives, and the like, it is assumed that no converted data can be set in the word idiom (after conversion) 213.

  The conversion rule management unit 33 creates the word idiom conversion rule information 310 (rule ID 311, word idiom (before conversion) 312, and word idiom (after conversion) 313) shown in FIG. 5 based on FIG. 2 and FIG. 12. And registered in the conversion rule DB 5. A rule ID 211 is set as the rule ID 311.

  In the word idiom (before conversion) 312 (FIG. 5), when no verb is set in the word idiom (before conversion) 212, the word idiom (before conversion) 212 is registered as it is. When a verb is set in the word idiom (before conversion) 212, the word idiom (before conversion) 312 (FIG. 5) includes the original form 632, the third person singular present form 633, the past form 634, and the past. The character part defined in the participle form 635 and the current participle form 636 is replaced and registered.

  In the word idiom (after conversion) 313 (FIG. 5), if no verb is set in the word idiom (after conversion) 213, the word idiom (after conversion) 213 is registered as it is. When a verb is set in the word idiom (after conversion) 213, the word idiom (after conversion) 313 (FIG. 5) includes the original form 632, the third person singular present form 633, the past form 634, and the past The character part defined in the participle form 635 and the current participle form 636 is replaced and registered.

  Based on the word idiom (after conversion) 313 (FIG. 5) and the access information 221 to the other host system 4 used for evaluation, the conversion rule management unit 33 uses the verb utilization statistical information 230 (verb utilization example 231) shown in FIG. , Noun 232, appearance frequency 233), and is registered in the conversion rule DB 5.

  When embedded information is set in the word idiom (after conversion) 313 (FIG. 5), the conversion rule management unit 33 is included in the English sentence acquired based on the access information 221 to the other host system 4 used for evaluation. The number of appearances of the corresponding character string is obtained, and the verb usage example 231, the noun 232, and the number of appearances 233 shown in FIG. 4 are registered in the conversion rule DB 5.

  In the example, “[1]” of “get rid of [1]” represents the embedded information. Information on word idioms (after conversion) 313 is registered in the verb utilization example 231. In the noun 232, a character string corresponding to the embedded character is registered. When the character string corresponding to the embedded character is composed of a plurality of words, the part of speech other than the noun is deleted. For example, “paper” is treated as an embedded character if “a paper” and “paper” is treated as “the paper”. In the appearance count 233, the appearance count of the character string in which the embedded character of the verb utilization example 231 is replaced with the noun 232 is registered.

  The learning status / plan information management unit 34 updates the learning status / plan DB 6. The learning status / plan information management unit 34 inputs word acquisition status information, predicate acquisition information, syntax acquisition information, and user information from the mobile terminal devices 2a, 2b, and 2n and the terminal device 1, and the user name 511 (FIG. 7), word ID 512 (FIG. 7), word 513 (FIG. 7), acquisition status 514 (FIG. 7), user name 521 (FIG. 8), idiom ID 522 (FIG. 8), idiom 523 (FIG. 8), acquisition status 524 (FIG. 8), user name 531 (FIG. 9), syntax rule ID 532 (FIG. 9), and acquisition status 533 (FIG. 9) are registered.

  In the user name 511 (FIG. 7), the user name 521 (FIG. 8), and the user name 531 (FIG. 9), user names that can identify the user are registered.

  The learning state / plan information management unit 34 registers the word ID 611 in the word ID 512. The word 513 has the same contents as the word 612 and is not stored because it is shown for explanation only.

  The learning status / plan information management unit 34 registers the idiom ID 621 in the idiom ID 522. The idiom 523 has the same content as the idiom 622 and is not stored because it is only described for explanation.

  The learning status / plan information management unit 34 registers the syntax rule ID 411 in the syntax rule ID 532.

  The learning status / plan information management unit 34 registers the acquisition status information of words in the acquisition status 514, registers the acquisition status information of idioms in the acquisition status 524, and registers the acquisition status of syntax rules in the acquisition status 533. The learning status / plan information management unit 34 treats the learning status 514, the learning status 524, and the learning status 533 as “learned” if it is set, and if “learning” is set, it learns next. Treat as power word, idiom or sentence pattern.

  As for the information of the learning situation 514, the learning situation 524, and the learning situation 533, in addition to a method in which the user directly inputs information to be updated from the mobile terminal devices 2a, 2b, and 2n and the terminal device 1, English evaluation information, etc. There is a method of automatically registering and registering. In the automatic updating method, the number of words, idioms, and sentence patterns are referred to from English sentences referred to by the user, and “acquired” is registered in the acquisition status when the reference count threshold is exceeded. For words and idioms that are not yet acquired, the next number is learned in the order of the appearance frequency of the appearance count 613 if it is a word, and in the order of the appearance frequency of the appearance frequency 623 if it is a predicate. Register as power words and idioms (that is, as “learning”). As the number set in advance, for example, the number of “under acquisition” is always defined as 100.

  The corpus management unit 35 updates the corpus DB 7. The corpus management unit 35 directly inputs information to be updated by the administrator from the mobile terminal devices 2a, 2b, and 2n and the terminal device 1. The corpus management unit 35 includes (1) a word, (2) relevant part-of-speech information such as a noun, a verb and an adjective, (3) an idiom, and (4) a verb change information such as an original form and a third person singular present tense. , Past participle, past participle form, and present participle form, word ID 611 (FIG. 10), word 612 (FIG. 10), noun 614 (FIG. 10) as part of speech information, and verb 615 (FIG. 10) ), Adjective 616 (FIG. 10), idiom ID 621 (FIG. 11), idiom 622 (FIG. 11), word ID 631 (FIG. 12), verb change information 632 (FIG. 12), and third person singular. The present tense 633 (FIG. 12), the past tense 634 (FIG. 12), the past participle form 635 (FIG. 12), and the present participle form 636 (FIG. 12) are registered.

  In addition, the corpus management unit 35 obtains the number of appearances of the word 612 and the idiom 622 included in the English sentence acquired based on the access information 221 to the other host system 4 used for the evaluation, and the appearance number 613 and the appearance number 623 are obtained. Register in DB7.

  For the word ID 611 and the idiom ID 621, unique numbers are generated and registered by the system. The same value as the word ID 611 is registered as the word ID 631.

  The user may be a real person or a non-existent person. For example, when the user is a real person, an English conversion service is provided for a specific individual. In this case, the learning situation / plan DB 6 is updated as needed. When the user is a non-existing person, a model user of a specific skill is registered and used by the same user information from an unspecified number of people. In this case, the learning situation / plan DB 6 is not updated.

  FIG. 13 shows the relationship among words, idioms, sentence patterns, words managed by this system, idioms, and sentence patterns included in English sentences. The classification 701 is a classification of words, idioms, and sentence patterns handled by the system. The classification 701 is composed of unmanaged words / idioms / sentence patterns 702, unlearned words / idioms / sentence patterns 703, next learned words / idioms / sentence patterns 704, and learned words / idioms / sentence patterns 705. Is done. A word / idiom / sentence type 706 managed by the system is a set of an unlearned word / idiom / sentence type 703, a word / idiom / sentence type 704 to be learned next, and a learned word / idiom / sentence type 705.

  FIG. 13 also shows a representative example in which English to be converted is classified according to words included therein, idioms, and sentence patterns. The English sentence A711 is an English sentence including all the classifications of the classification 701. The English sentence B 712 is an English sentence composed of a word / idiom / sentence type 702 that is not a management target, a word / idiom / sentence type 704 to be learned next, and a learned word / idiom / sentence type 705. The English sentence C713 is an English sentence composed of unmanaged words / idioms / sentence patterns 702 and mastered words / idioms / sentence patterns 705. The English sentence D714 is an English sentence composed of unacquired words / idioms / sentence patterns 703, words / idioms / sentence patterns 704 to be learned next, and learned words / idioms / sentence patterns 705. The English sentence E715 is an English sentence composed of a word / jukugo / sentence pattern 704 to be learned next and a mastered word / idiom / sentence pattern 705. The English sentence F716 is an English sentence composed only of learned words, idioms, and sentence patterns 705.

  English for learning purposes is a word / jukugo / sentence type 704 to be learned next, a learned word / jukugo / sentence type 705, a word classified into an unmanaged word / idiom / sentence type 702, a idiom, and a sentence type The words, idioms, and sentence patterns 704 to be acquired next are necessarily included. For example, English sentence B712 and English sentence E715 correspond.

  An English sentence for the purpose of understanding is an English sentence that is composed of a word / jukugo / sentence type 705 that has been learned, a word classified into a word / idiom / sentence type 702 that is not subject to management, a idiom, and a sentence type. -Words of idioms / sentence patterns 705 or idioms / sentence patterns are always included. For example, English sentence C713 and English sentence F716 correspond.

  In this system, not only English with high difficulty is converted into English with low difficulty but also English with low difficulty is converted into English with high difficulty. For example, the English text F716 for understanding is converted into the English text E715 for learning.

  The word / idiom / sentence type 706 managed by the system includes (1) the word 612 shown in FIG. 10, (2) the original form 632 shown in FIG. 12, the third person singular present form 633, the past form 634, and the past participle form 635. And a word defined in the present participle form 636, (3) an idiom defined in idiom 622 shown in FIG. 11, and (4) a syntax (before conversion) 412 shown in FIG. It is a sentence pattern.

  The acquired words / jukugo / sentence type 705 are: (1) In the word acquisition situation 510 shown in FIG. 7, the user name 511 matches the user to be processed, and the acquisition situation 514 corresponds to the word 513 corresponding to “learning”; 2) In the idiom acquisition situation 520 shown in FIG. 8, the user name 521 matches the user to be processed, the idiom 523 in which the acquisition situation 524 is “acquired”, the user name 531 and the user to be processed match, and is acquired. Situation 533 is a sentence type defined in the syntax (before conversion) 412 of the syntax rule ID 411 that matches the syntax rule ID 532 corresponding to “learning”.

  Next, the word / jukugo / sentence pattern 704 to be acquired is as follows: (1) In the word acquisition situation 510 shown in FIG. 7, the user name 511 matches the user to be processed, and the acquisition situation 514 corresponds to “learning”. (2) In the idiom acquisition situation 520 shown in FIG. 8, the user name 521 matches the user to be processed, and the idiom 523 in which the acquisition situation 524 corresponds to “under acquisition”, the user name 531 and the user to be processed It is a sentence type defined in the syntax (before conversion) 412 of the syntax rule ID 411 that matches the syntax rule ID 532 that matches the syntax rule ID 532 corresponding to “under acquisition”.

  The unacquired words / idioms / sentence patterns 703 exist in the words / idioms / sentence patterns 706 managed by the system, and the words / idioms / sentences 704 that have not yet been learned and the words / idioms / sentence patterns 704 to be learned next.・ Sentence pattern.

[Processing of English learning material provision system]
Next, the operation of the English learning material providing system will be described. 14, 15, 16, and 17 are flowcharts showing an overview of processing operations executed by the English → English conversion unit 32. FIG. 18 is a flowchart illustrating an outline of processing operations executed by the conversion rule management unit 33. FIG. 19 is a flowchart showing an outline of the corpus management unit 35.

  FIG. 14 is a flowchart showing an outline of the English → English conversion unit 32. The English → English conversion unit 32 receives a method of acquiring English text from the other host system 4 or a conversion target English text and a conversion purpose.

  When a method for acquiring English text is input from the other host system 4 (Yes in step 801), the English → English conversion unit 32 accesses the other host system 4 input via the other host system information acquisition unit 31. Based on the information, English information is acquired from the other host system 4 (step 802).

  Next, the English → English conversion unit 32 determines whether or not the conversion purpose is a learning purpose (step 803). If the conversion purpose is a learning purpose (affirmative result in step 803), the English-to-English conversion unit 32 executes the process of FIG. 15 (step 805). When the conversion purpose is not a learning purpose but an understanding purpose (a negative result in step 803 and an affirmative result in step 804), the English-to-English conversion unit 32 executes the process of FIG. 16 (step 806). After execution of step 805 or 806, the English-to-English converter 32 returns the converted English text.

[Processing for learning purposes]
FIG. 15 shows an outline of the learning purpose English text generation processing operation executed by the English → English conversion section 32. First, the English-to-English conversion unit 32 creates a list of words to be used, idioms, and sentence patterns of English to be converted (step 901).

  Next, the English-to-English conversion unit 32 determines whether or not an unlearned word / idiom / sentence type 703 exists in the list (step 902). If there is an unlearned word / idiom / sentence 703 (Yes in step 902), the English-to-English conversion unit 32 converts the unlearned element into a character string of the next word / idiom / sentence 704 to be learned. (Step 903).

  Next, the English-to-English conversion unit 32 determines whether or not unlearned elements remain (step 94). If an unlearned word / idiom / sentence 703 remains (Yes in step 904), the English-to-English conversion unit 32 converts an unlearned element into a character string of the learned word / idiom / sentence 705. (Step 905).

  If there are no unlearned elements (negative result in step 904) or after execution of step 905, the English-to-English conversion unit 32 uses the learned word / idiom / sentence type 705 as the next learned word / idiom / sentence type. It is converted into a character string 704 (step 906).

  Thereafter, the English-to-English converter 32 creates a list of words used, idioms, and sentence patterns of the converted document (step 907).

  Next, the English-to-English conversion unit 32 determines whether or not an unlearned element exists in the created list and an element to be learned next is included (step 908). An English sentence composed of a word / jukugo / sentence type 704 to be learned, a word / jukugo / sentence type 705 that has been learned, a word classified into a word / idiom / sentence type 702 that is not managed, a idiom, and a sentence type, If the next word / jukugo / sentence type 704 word or idiom / sentence type to be acquired is included (affirmative result in step 908), the English-to-English conversion unit 32 converts the converted document into the terminal device 1 and the mobile terminal device. Return to 2a, 2b, 2c (step 909). On the other hand, if a negative result is obtained in step 908, the English-to-English conversion unit 32 returns the converted document together with the non-convertible information list (step 910).

  In step 903, if there are unlearned words / idioms in the word idiom (before conversion) 312 (FIG. 5), the English-to-English conversion unit 32 determines that the word idiom (after conversion) 313 (FIG. 5) is next. If it is a word or idiom to learn, it is converted. On the other hand, in the same step, when an unlearned sentence type exists in the syntax (before conversion) 412 (FIG. 6), the English → English conversion unit 32 acquires the syntax (after conversion) 413 (FIG. 6) next. If it is a sentence type to be converted, it is converted. Details of the conversion operation are shown in FIG.

  In step 905, if there are unlearned words / idioms in the word idiom (before conversion) 312 (FIG. 5), the English-to-English converter 32 determines that the word idiom (after conversion) 313 (FIG. 5) has been acquired.・ If it is an idiom, convert it. On the other hand, in the same step, when an unlearned sentence type exists in the syntax (before conversion) 412, the English → English conversion unit 32 converts the syntax (after conversion) 413 (FIG. 6) if it is a learned sentence type. To do. Details of the conversion operation are shown in FIG.

  In step 906, when the learned word / idiom is present in the word idiom (before conversion) 312 (FIG. 5), the English → English conversion unit 32 learns the word idiom (after conversion) 313 (FIG. 5) next. If it is a word or idiom, convert it. On the other hand, in the same step, when the acquired sentence type exists in the syntax (before conversion) 412, the English → English conversion unit 32 determines that the syntax (after conversion) 413 (FIG. 6) is the next sentence type to be acquired. Convert. Details of the conversion operation are shown in FIG.

[Processing for understanding purposes]
FIG. 16 shows an outline of an understanding-purpose English sentence generation processing operation executed by the English-to-English converter 32. First, the English-to-English conversion unit 32 creates a list of words to be used, idioms, and sentence patterns of the English to be converted (step 1001).

  Next, the English-to-English conversion unit 32 determines whether there are unlearned words / idioms / sentence patterns 703 or next-acquired words / idioms / sentence patterns 704 in the list (step 1002). If an affirmative result is obtained in step 1002, the English-to-English conversion unit 32 converts an unlearned or next-learned element into a learned word / idiom / sentence pattern 705 (step 1003).

  Thereafter, the English-to-English conversion unit 32 determines whether or not an unlearned word / idiom / sentence 703 still remains (step 1004). If an affirmative result is obtained in step 1004, the English-to-English conversion unit 32 converts the unlearned element into a word / idiom / sentence type 704 to be learned next (step 1005).

  If a negative result is obtained in step 1004 or after execution of step 1005, the English-to-English conversion unit 32 converts the next word / idiom / sentence type 704 to be learned into a learned word / idiom / sentence type 705 (step 1006).

  Thereafter, the English-to-English conversion unit 32 creates a list of words used, idioms, and sentence patterns of the converted document (step 1007).

  Further, the English-to-English conversion unit 32 determines whether or not there are only elements that have been acquired as not being managed in the list (step 1008). If the list is composed of words, idioms / sentence patterns 705 that have been learned, words / idioms / sentence forms 702 that are not managed, idioms, and sentence patterns (Yes in step 1008) ), The English-to-English conversion unit 32 returns the converted document to the terminal device 1 and the mobile terminal devices 2a, 2b, and 2c (step 1009). On the other hand, in the case of a negative result in step 1008, the English → English conversion unit 32 returns the converted document together with the non-convertible information list to the terminal device 1 and the mobile terminal devices 2a, 2b, and 2c (step 1010). .

  In step 1003, if the word or phrase that is not yet learned or the next phrase to be learned exists in the word phrase (before conversion) 312 (FIG. 5), the English-to-English conversion unit 32 sets the word phrase (after conversion) 313 (FIG. If 5) is a learned word / idiom, convert it. On the other hand, in the same step, when there is an unlearned or next acquired sentence pattern in the syntax (before conversion) 412 (FIG. 6), the English-to-English conversion unit 32 determines the syntax (after conversion) 413 (FIG. 6). If is an acquired sentence pattern, it is converted. Details of the conversion operation will be described with reference to FIG.

  In step 1005, when there are unlearned words / idioms in the word idiom (before conversion) 312 (FIG. 5), the English → English conversion unit 32 acquires the word idiom (after conversion) 313 (FIG. 5) next. If it is a word or idiom to be converted, it is converted. On the other hand, in the same step, when an unlearned sentence type exists in the syntax (before conversion) 412 (FIG. 6), the English → English conversion unit 32 acquires the syntax (after conversion) 413 (FIG. 6) next. If it is a sentence type to be converted, it is converted. Details of the conversion operation are shown in FIG.

  In step 1006, when the next word / idiom to be learned exists in the word idiom (before conversion) 312, the English → English conversion unit 32 indicates that the word idiom (after conversion) 313 (FIG. 5) is the learned word / idiom. Convert if there is. On the other hand, in the same step, when the next sentence type to be acquired exists in the syntax (before conversion) 412 (FIG. 6), the English → English conversion unit 32 has already acquired the syntax (after conversion) 413 (FIG. 6). If it is a sentence type, convert it. Details of the conversion operation are shown in FIG.

[Word and phrase conversion process]
FIG. 17 shows an outline of the word / idiom conversion processing operation executed by the English → English conversion unit 32. First, the English-to-English conversion unit 32 determines whether or not the word or phrase to be converted is registered in the word phrase (before conversion) 312 (FIG. 5) (step 1101).

  If an affirmative result is obtained in step 1101, the English-to-English conversion unit 32 determines whether or not the content of the word idiom (after conversion) 313 (FIG. 5) is the target word or idiom (step 1102). ). If a negative result is obtained in step 1102, the English → English conversion unit 32 proceeds to step 1107.

  On the other hand, if a positive result is obtained in step 1102, the English-to-English conversion unit 32 determines whether or not a verb is included in the content of the word idiom (before change) 312 (FIG. 5) (step 1103). If a negative result is obtained in step 1103, the English-to-English conversion unit 32 replaces the character string with the word idiom (after change) 313 (FIG. 5) (step 1106). If an affirmative result is obtained in step 1103, the English → English conversion unit 32 has a noun that appears after the verb in the noun 232 corresponding to the verb utilization example 231, and the appearance count 233 has a threshold value. It is determined whether it has exceeded (step 1104).

  If the result is affirmative in step 1104, the English-to-English conversion unit 32 replaces the character string with the word idiom (after change) 313 (FIG. 5) (step 1105). Here, the noun appearing after the verb is, for example, a character string excluding the article “paper” for “the paper”.

  The negative result in step 1101, the negative result in step 1102, the negative result in step 1104, or after the execution of step 1105, or after the execution of step 1106, the English → English conversion unit 32 converts the sentence pattern to be converted Is registered in the syntax (before conversion) 412 (step 1107).

  If the result is affirmative in step 1107, the English-to-English converter 32 determines whether the content of the syntax (after conversion) 413 is the target sentence pattern (step 1108). If the result is affirmative in step 1108, the English-to-English conversion unit 32 replaces the character string with the syntax (after change) 413 (step 1109).

  For example, when “I can not get rid of the paper.” Is the conversion target, the English-to-English conversion unit 32 first “I” “can” “not” “get” “rid” “of” “the” "Decompose into" paper ". Next, the English-to-English conversion unit 32 determines that “get rid of [1]” in the word idiom (before conversion) 312 corresponds (positive result in step 1101). Further, when the English-to-English conversion unit 32 determines that the word or phrase is intended for “throw [1] away” in the word phrase (after conversion) 313 (positive result in step 1102), the word phrase (before conversion) ) 312 "get rid of [1]" is judged to contain a verb (positive result in step 1103), and the article "the" from "the" and "paper" corresponding to the embedded character "[1]" And “paper” as an embedded character. Then, the English-to-English conversion unit 32 evaluates whether “paper” exists in the noun 232 corresponding to the verb utilization example 231 “throw [1] away”, and if it exists, the number of appearances 233 exceeds the threshold. (“Yes” in step 1104), “get” “rid” “of” “the” “paper” is converted to “throw” “the” “paper” “away” (step 1105).

  As a result, the English → English conversion unit 32 outputs “I”, “can”, “not”, “throw”, “the”, “paper”, and “away”. In this example, the embedded character used for evaluation is the noun “paper”, and the replacement embedded character is “the” “paper”. For example, even if it is "the" "blue" "paper", the embedded character used for evaluation is the noun "paper", and the embedded character when replacing is "the" "blue" "paper" is there.

[Counting operation of the number of appearances of verb utilization]
FIG. 18 shows an outline of the count processing operation of the number of appearances of verb utilization executed by the conversion rule management unit 33. First, the conversion rule management unit 33 acquires a word phrase (before conversion) 212 and a word phrase (after conversion) 213 (step 1201).

  Next, the conversion rule management unit 33 determines whether embedded characters are set (step 1202). When embedded characters are not set (negative result in step 1202), the conversion rule management unit 33 sets the rule ID 211 to the rule ID 311, the word phrase (before conversion) 212 to the word phrase (before conversion) 312 and the word phrase ( (After conversion) 213 is registered in the word idiom (after conversion) 313 (step 1203).

  When the embedded character is set (Yes in step 1202), the conversion rule management unit 33 sets the verb of the word idiom (before conversion) 212 as the original form 632, the third person singular present form 633, the past form 634, and the past. It is replaced with the character string defined in the participle form 635 and the present participle form 636 and registered in the word idiom (before conversion) 312 (step 1204).

  Thereafter, the conversion rule management unit 33 defines the verbs of the word idiom (after conversion) 213 as the original form 632, the third person singular present form 633, the past form 634, the past participle form 635, and the present participle form 636. And is registered in the word idiom (after conversion) 313 (step 1205).

  For example, “get” of “get rid of [1]” in the conversion rule management unit 33 word idiom (before conversion) 212 is replaced with the original form 632 “get”, the third person singular present form 633 “gets”, and the past form 634 “got”. The past participle form 635 “gotten” and the present participle form 636 “getting” are replaced with the word idiom (before conversion) 312 (step 1204), and the word idiom (after conversion) 213 “throw [1]” “throw” in “away” is replaced with the original form 632 “throw”, the third person singular present form 633 “throws”, the past form 634 “threw”, the past participle form 635 “thrown”, and the present participle form 636 “throwing” Then, it is registered in the word idiom (after conversion) 313 (step 1205).

  Thereafter, the conversion rule management unit 33 acquires the evaluation English text from the other host system 4 via the other host system information acquisition unit 31 based on the access information 221 to the other host system 4 used for the evaluation (step 1206). ), The number of appearances of the word idiom (after conversion) 313 is counted (step 1207). Specifically, the number of appearances of nouns that appear after the verbs in the evaluation English sentence is counted. For example, if it is “the paper”, the character string “paper” is counted as a noun. That is, when the evaluation English sentence is “He threw the paper away to the garbage can.”, “Paper” is counted as a noun corresponding to the word idiom (after conversion) 313 “threw [1] away”.

  When all the access information 221 to other host systems used for evaluation is evaluated (step 1208), the conversion rule management unit 33 registers the tabulated information in the verb utilization example 231, the noun 232, and the appearance count 233. (Step 1209).

[Corpus appearance count processing]
FIG. 19 shows an outline of the operation of counting the number of appearances of the corpus by the corpus management unit 35. First, the corpus management unit 35 acquires an evaluation English sentence via the other host system information acquisition unit 31 based on the access information 221 to the other host system used for evaluation (step 1301), and is set to the word 612. Character strings are counted (step 1302).

  Thereafter, the corpus management unit 35 determines whether all access information 221 to other host systems used for evaluation has been evaluated (step 1303). When the evaluation is not completed (Yes in Step 1303), the corpus management unit 35 repeats Steps 1301 and 1302. When the evaluation is completed (negative result in step 1303), the corpus management unit 35 updates the appearance count 613 (step 1304). Thereafter, the corpus management unit 35 counts up the number of appearances 233 of the verb utilization example 231 corresponding to the idiom 622 (step 1305), and updates the number of appearances 623 (step 1306).

[Display screen example]
FIG. 20 shows a screen example 1401 displayed on the display devices provided in the terminal device 1 and the mobile terminal devices 2a, 2b, and 2c using this system. The upper column is the English text before conversion, and the lower column is the English text after conversion. The converted English sentence is displayed as either an English sentence converted for the purpose of learning or understanding. Both the learning purpose and the understanding purpose may be displayed.

[Other examples]
In the above-described embodiment, the case where the language for learning and acquisition is English has been described, but it goes without saying that the type of language such as Chinese or Korean is not limited.

  In the above-described embodiment, the case where the host system 3 provides a service for converting the English level has been described. However, the host system 3 may execute the service on the user's computer.

DESCRIPTION OF SYMBOLS 1 ... Terminal device 2 ... Base station 2a, 2b, 2n ... Mobile terminal device 3 ... Host system 4 ... Other host system 5 ... Conversion rule database 6 ... Learning situation / plan database 7 ... Corpus database 8 ... Network 31 ... Other host system Information acquisition unit 32 ... English → English conversion unit 33 ... conversion rule management unit 34 ... learning status / plan information management unit 35 ... corpus management unit

Claims (16)

A sentence acquisition unit for acquiring a first sentence;
A sentence converter that converts words and / or idioms and / or sentence patterns constituting the first sentence into a second sentence composed of the same language as the first sentence according to a conversion rule;
A difficulty level evaluation unit that evaluates the difficulty level of the first sentence based on the skill information of the user registered at the time of access;
A language learning teaching material providing system comprising: a conversion rule management unit that manages the conversion rule based on the skill information of the user registered at the time of access and the evaluation result of the purpose and difficulty of the user. The language learning teaching material providing system according to claim 1,
The language learning teaching material providing system, wherein the skill information of the user is information individually set for an actual user. The language learning teaching material providing system according to claim 1,
The language learning teaching material providing system, wherein the skill information of the user is information set for a fictitious user who does not exist. In the language learning teaching material providing system according to claim 2 or 3,
The language learning teaching material providing system characterized in that the skill information of the user includes a database that stores information on the learning status and learning plan of the user, and an information management unit that manages the database. The language learning teaching material providing system according to claim 1,
A language learning teaching material providing system comprising: a function unit that adjusts the conversion rule based on a frequency of occurrence of a combination of a verb and a noun included in a sentence for evaluation. The language learning teaching material providing system according to claim 5,
The function unit for adjusting the conversion rule includes a processing unit for registering the conversion rule, and a verb registered in the conversion rule replaced with a third person singular present tense, past tense, past participle form, present participle form A processing unit for generating words and phrases, a processing unit for acquiring the evaluation sentence, a processing unit for extracting a noun related to a verb included in the evaluation sentence, and a noun related to the verb A language learning teaching material providing system comprising: a processing unit that obtains the number of appearances for a combination; and a processing unit that does not apply a corresponding conversion rule when the number of appearances of a noun combination associated with a verb is less than a threshold. The language learning teaching material providing system according to claim 1,
A language learning teaching material providing system comprising a function unit that converts or deletes words and idioms included in the first sentence into other words or idioms and adjusts the difficulty of the sentence. The language learning teaching material providing system according to claim 7,
The function unit that adjusts the difficulty level of the sentence includes a processing unit that registers a conversion rule, and a processing unit that converts or deletes a word or phrase when there is a condition that matches the first sentence. A system for providing language learning materials characterized by The language learning teaching material providing system according to claim 1,
A language learning teaching material providing system, wherein the user's purpose is a learning purpose. The language learning teaching material providing system according to claim 9,
The sentence conversion unit is configured to preferentially convert words, idioms, and sentence patterns of the first sentence classified as unlearned into words, idioms, and sentence patterns that the user learns next, and classified as unlearned. And a processing unit for converting the word, idiom, and sentence pattern of the first sentence to the learned word, idiom, and sentence pattern. The language learning teaching material providing system according to claim 1,
A language learning teaching material providing system, wherein the user's purpose is an understanding purpose. The language learning teaching material providing system according to claim 11,
The sentence conversion unit has learned the words, idioms, and sentence patterns of the first sentence classified as unlearned, and the words, idioms, and sentence patterns of the first sentence classified as objects to be learned next. A language learning teaching material provision system characterized by having a processing unit for converting into idioms and sentence patterns. The language learning teaching material providing system according to claim 1,
The difficulty level evaluation unit includes a processing unit that counts used words, idioms, and sentence patterns of the first sentence;
A language learning teaching material providing system comprising: a processing unit that classifies the used words, idioms, and sentence patterns according to the skill information of the user. The language learning teaching material providing system according to claim 1,
A language learning teaching material providing system comprising: a function unit that transmits at least the second sentence to a user terminal. Processing to obtain the first sentence;
A process of converting words and / or idioms and / or sentence patterns constituting the first sentence into a second sentence composed of the same language as the first sentence according to a conversion rule;
A process of evaluating the difficulty level of the first sentence based on the skill information of the user registered at the time of access;
A sentence conversion method comprising: processing for managing the conversion rule based on the skill information of the user registered at the time of access, the user's purpose, and the evaluation result of the difficulty level. On the computer,
Processing to obtain the first sentence;
A process of converting words and / or idioms and / or sentence patterns constituting the first sentence into a second sentence composed of the same language as the first sentence according to a conversion rule;
A process for evaluating the difficulty level of the first sentence based on the skill information of the user registered at the time of access;
A program for executing processing for managing the conversion rule based on the skill information of the user registered at the time of access and the evaluation result of the user's purpose and difficulty level.

Images