JP2004077995A - Apparatus, program, and method for assisting language acquisition - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus for language acquisition assistance that is very suitable to a user for mastering a certain language by using verse capping, and a program and a method therefor. <P>SOLUTION: Input of a word presented by the user is received, candidate words, other than words which are already received or already outputted, which include the ending character of the presented word as their initials are automatically extracted from a specified word dictionary according to the ending character of the presented word, and choice preference showing the degree of advantage in verse capping depending upon characters is computed by the candidate words according to specified quantitative static data for winning the verse capping as to each character included in the word dictionary is computed, so that a candidate word which can be an answer word is determined according to the computed choice preference and then outputted. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a language acquisition support device useful for learning a language by applying a play game, and a program and a method therefor.
[0002]
[Prior art]
Siritori play, which everyone has become accustomed to since childhood, exists in many countries and not only has the aspect of enjoying the fun of games, but also allows children to learn native language words and foreigners to speak foreign languages. It also has an educational aspect of being useful for learning and an academic aspect of being a research subject on the theme of communication between humans and machines. In recent years, for example, there has been developed Siritori game software for the purpose of assisting language acquisition as an educational aspect. In addition, research on when humans enjoy pleasure has shown that even if the opponent of the Siritori is game software, it is interesting to learn that it is a human being. ing.
[0003]
[Problems to be solved by the invention]
By the way, there is no word in the Siritori that has the letter "n" at the beginning of the word in Japanese. There are certain rules for each language. Under these rules, there are advantages and disadvantages depending on characters, such as many words starting with a certain letter but few words starting with another letter. The game is progressing in a way that is beneficial to you. However, since it is not easy to convert the advantages and disadvantages of each character into quantitative statistical data, even in the development and research of the above-mentioned game software, simply collect a large number of vocabulary words, It only uses the result of extracting the suffix.
[0004]
Therefore, the present invention provides an apparatus, a program, and a method that are useful for language acquisition by using a siritori based on a quantitative research study on what kind of strategy is advantageous or disadvantageous in a siritori. Is what you do.
[0005]
[Means for Solving the Problems]
The present invention provides a language based on a rule related to a predetermined series that outputs an answer word other than the already input or output word, which is different from the present word having the initial character as the initial character of the input present word. As shown in a schematic functional configuration diagram in FIG. 1, an acquisition support device A1 includes an input receiving unit 1 that receives an input of a presentation word, and an ending character based on the ending character of the presentation word that has received the input. And a candidate word extraction unit 2 for automatically extracting from the predetermined word dictionary DB1 candidate words excluding words that have already been input or already output, with as the initial letter, and that each character included in the word dictionary DB1 wins the series. Is calculated for each candidate word extracted by the candidate word extraction unit 2 based on the plurality of quantitative statistical data DB2. Preference calculation unit 3, response word determination unit 4 that determines candidate words having the highest or minimum preference as response words, and an answer word output unit that outputs the determined candidate words as response words 5 is a basic feature. Such a language acquisition support device A1 realizes an intended function by operating a dedicated computer or a general-purpose computer according to a program based on a predetermined method.
[0006]
In other words, when the user and the language acquisition support device, which is a computer, alternately advance the list, the highest preference calculated to win the presented word input by the user with the list whose initial character is the first letter is used. The language acquisition support device outputs a word having a degree, that is, an optimum answer word. Therefore, the user inputs the presented word, and the language acquisition support device repeatedly outputs the answer word in response thereto, thereby forming a series of series, whereby the user is output in addition to the vocabulary of the user. Learn to enjoy words. It should be noted that the rules of the directory can be appropriately determined before starting a series of directories, and the word dictionary and the corresponding statistical data are suitable as long as they can be built in or connected to a computer. Things can be used. Also, when calculating the preference level, words that have already been received or words that have already been output are excluded from the quantitative statistical data, and calculations are performed, or calculations are performed without excluding such words. Variations are possible.
[0007]
By the way, the language acquisition support device, which is a computer, employs a strategy that is advantageous for the computer itself and disadvantageous for the other user as long as words that can be output as answer words remain in the word dictionary. Thus, the siritori can be advanced without defeating a human user. Therefore, since the present invention utilizes quantitative statistical data based on a word dictionary, words having the same ending are continuously output as answer words using the quantitative statistical data, and words that can be used by the user are output. It can be said that it is preferable to adopt the following method, specifically, as a basic strategy of reducing the number of tactics. First, the quantitative statistical data DB2 has the ending character of the candidate word with respect to the number of words having the ending character of the candidate word as the initial character, and has the ending character of the character that means losing in the rule of Siritori. Assuming that the ratio of the number of words is a preference element value, the preference computation unit 3 calculates a preference obtained by an arithmetic expression indicating that a candidate word having a larger preference element value has a greater degree of advantage. It is conceivable to perform the calculation. In other words, as the number of words ending with a character losing is larger than the total number of words starting with a certain character, the more the user answers with a word ending with a character, the other user will recognize the character losing as a ending. This is advantageous for the computer side because it is easy to input words to be performed. In the rules of the Siritori, the character that means losing is, for example, the character "n" in Japanese in principle, but any rule that loses when ending with other characters is used. Can be set.
[0008]
Next, the quantitative statistical data DB2 has a number of types of initials of the words as preference element values in a set of words consisting of only two characters whose initials are the initials of the candidate words. As a method, the preference calculation unit 3 may calculate a preference obtained by an arithmetic expression indicating that a candidate word having a larger preference element value has a greater degree of advantage. That is, since a relatively short word of two letters is very easy for a human to recall, it is more advantageous to answer with a two-letter word having various characters at the beginning of the word.
[0009]
Further, the numerical statistical data DB2 is set to have the number of types of initials of the words as a preference element value in a set of words having the ending character of the candidate word as the ending character. Alternatively, a preference degree obtained by an arithmetic expression indicating that a candidate word having a larger preference element value has a greater degree of advantage may be calculated. According to this method, it is possible to answer with words starting with various characters, so that "attack" on the user can be easily continued.
[0010]
Further, the quantitative statistical data DB2 uses the ending character of the candidate word with respect to the number of words having the ending character of the candidate word as the initial character and not having the ending character in the Siritori rule as the ending character. Assuming that the ratio of the number of words is a preference element value, the preference calculation unit 3 calculates a preference obtained by an arithmetic expression indicating that a candidate word having a larger preference element value has a greater degree of advantage. A calculation method can be adopted. In this case, if there are not many types of characters at the end compared to the types of characters at the beginning of the word, "attack" for the user will not continue.
[0011]
Furthermore, it is assumed that the quantitative statistical data DB2 has the number of words having the initial character of the candidate word as the suffix as the preference element value, and the preference calculation unit 3 selects the candidate having a small preference element value. If a tactic is used that calculates the preference obtained by an arithmetic expression that indicates that a word has a greater degree of advantage, the word is cut back and output using the answer word having the same character as the ending character of the presented word. Would be struggling to recall the next word presented.
[0012]
In addition, assuming that the quantitative statistical data DB2 has the number of words having the initial letter of the candidate word as the initial character as the preference element value, the preference calculation unit 3 selects the candidate word having a small preference element value. The preference degree obtained by an arithmetic expression indicating that the degree of advantage is greater as the degree of preference may be calculated. That is, if a word having a small number of endings is output as an answer word, the user must necessarily consider the next word from words having an initial letter with a small number of types. Is difficult to continue.
[0013]
Also, from the viewpoint of "easiness of associating words", a process for outputting an appropriate answer word can be performed. For this purpose, a natural language sentence is stored in addition to the above-described basic configuration of the language acquisition support device A1, such as the language acquisition support devices A2, A3, and A4 shown in FIGS. 2, 3, and 4, for example. Associative degree calculation for calculating an associative degree obtained by a predetermined arithmetic expression including a frequency such as the number of sentences in which a presented word appears in a predetermined corpus DB3 and a frequency in which both the presented word and each candidate word appear in the corpus DB2 Unit 6 is further provided, and the answer word determination unit 4 is configured to convert the answer word based on a predetermined arithmetic expression based on the associativity obtained by the associativity calculating unit 6 and the preference obtained by the preference calculating unit 3. Is desirably determined.
[0014]
Furthermore, there is a case where the field of words that can be used in a series of series is limited to a predetermined one. In order to appropriately realize this, for example, the above-described language acquisition support device A3 shown in FIG. In addition to the basic configuration in the language acquisition support device A1, a plurality of fields of a word group that can be used as rules for the scenery are set, and an input of a field change command that specifies one of the fields is received. It is preferable to further provide a word field changing unit 7 for changing the field of the word group in the series of series. In particular, when the function of the word field change unit 7 is added to the language acquisition support device A2 shown in FIG. 2, as shown in FIG. 3, the function of the word field change unit 7 is added to the field change command that has received the input. Based on at least one of a plurality of word dictionaries set in advance for each field, a plurality of corpus storing a plurality of statistical data or a natural language sentence, a corresponding word dictionary to be referred to, a statistical data or a corpus. It may be selected.
[0015]
In some cases, depending on the user's language proficiency, it may be desirable to be able to change the difficulty level in a series of series. In this case, as in the language acquisition support device A3 shown in FIG. 3, a plurality of difficulty levels that can be used as rules of the scenery are set, and an input of a difficulty level change command that designates one of the difficulty levels is accepted. It is desirable to further provide a difficulty level changing unit 8 for changing the level of difficulty in a series of series.
[0016]
Specific preferred functions of the difficulty level changing unit 8 include a plurality of word dictionaries DB1 respectively corresponding to a plurality of predetermined difficulty levels and a word dictionary corresponding to a difficulty level change command received from the statistical data DB2. One for selecting DB1 and statistical data DB2. Further, the difficulty level changing unit 8 may change the arithmetic expression for calculating the preference level in accordance with the difficulty level change command received as input. Further, when adding the function of the word field changing unit 7 to the language acquisition support device A2 shown in FIG. 2, the difficulty changing unit 8 sets a plurality of word dictionaries DB1 corresponding to a plurality of preset difficulty levels. Alternatively, a word dictionary DB1 and a statistical data DB2 or a corpus DB3 corresponding to a difficulty level change command received from a plurality of corpus DB3 or a plurality of corpus DB3 storing natural language sentences may be selected. The word dictionary DB1, statistical data DB2, and corpus DB3 used here may be the same as or different from the word dictionary DB1, statistical data DB2, and corpus DB3 used in the field change unit 7. In addition, the difficulty level changing unit 8 can change the arithmetic expression for determining the answer word based on the preference level and the association level.
[0017]
In addition to the above, if the user cannot come up with a suggested word to be input next corresponding to the answer word, it is thought that if the computer outputs information that is a hint of the presented word, the usability of the language acquisition support device is improved. Can be For this purpose, in addition to the above-described basic configuration or a configuration applying the same, as in the language acquisition support devices A3 and A4 shown in FIG. 3 or FIG. A hint request receiving unit 9a that receives a request command, and a hint from a word whose initial character is the ending character of the answer word output by the answer word output unit immediately before based on the hint request command received by the hint request receiving unit 9a. It is preferable to provide a hint generation / output unit 9b for generating and outputting.
[0018]
Further, when the user wants to know the output answer word, if the meaning is also output, the usability for the user is improved. To this end, in addition to the basic configuration described above or a configuration to which it is applied, as in the language acquisition support devices A3 and A4 shown in FIG. 3 or FIG. A word meaning request receiving unit 10a that receives the input word meaning request command, and extracts and outputs the meaning of the answer word from a predetermined word meaning dictionary DB4 based on the word meaning request command received by the word meaning request receiving unit 10a. It is desirable to further provide a word meaning extraction / output unit 10b that performs the operation. It is preferable that the word meaning dictionary DB4 be associated with the word dictionary DB1 and the corpus DB3 so as to store common words.
[0019]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
[0020]
This embodiment is for assisting a user in acquiring a language using a repository. Here, an example of the language acquisition support device A3 shown in FIG. 3 described above is shown. That is, the language acquisition support device A3 in FIG. 3 has both a basic configuration and a plurality of auxiliary configurations in the language acquisition support device according to the present invention. In the following, a case will be described in which Japanese words are used as rules for the scenery.
[0021]
First, as shown in FIG. 5, the language acquisition support device A3 includes a CPU 101, a memory 102, a storage device 103 such as a hard disk (HDD), an input device 104 such as a mouse and a keyboard, an output device 105 such as a display, and the like. A general-purpose personal computer stores a software program to be described later, and further includes a database device 106 built in or externally connected to the personal computer. The language acquisition support device A3 has a communication interface connectable to the Internet, a LAN, or the like in addition to the above configuration, and operates by receiving access from a personal computer used by an external user. In the following, a mode in which a single personal computer is used as the language acquisition support device A3 will be described.
[0022]
Next, a functional configuration of the language acquisition support device A3 will be described with reference to FIG. As described above, the language acquisition support device A3 operates in accordance with the stored language acquisition support program, and thereby receives the input reception unit 1, the candidate word extraction unit 2, the preference calculation unit 3, the answer word determination unit 4, the answer word The output unit 5, the associativity calculation unit 6, the field change unit 7, the difficulty change unit 8, the hint request reception unit 9a, the hint generation / output unit 9b, the word meaning request reception unit 10a, and the word meaning extraction / output unit 10b Demonstrate function.
[0023]
The word dictionary DB1, the statistical data DB2, the corpus DB3, and the word meaning dictionary DB4 are stored in the database device 106, and include, for example, "Japanese words in general", "names of fruits", " They are classified according to fields such as "nation name", "economic terms", etc., or according to difficulty, and stored in association with each other. Specifically, for example, FIG. 6 shows, as an example, only a part of the word dictionary DB1 based on the “Classification Vocabulary Table (National Institute for Japanese Language, Hideei Shuppan, 1964)”. It belongs to the field of "Japanese words in general", and is divided into seven pieces of information (read, headword, classification number, first lower number of classification number, second lower number of classification number) , Sample usage frequency is a predetermined number (for example, 7 or more words) or not. Then, for each of the word dictionaries DB1, quantitative statistical data on 44 types of characters (hiragana) except Japanese "n" is created and stored as statistical data DB2. FIG. 7 shows an example of statistical data DB2 based on a certain word dictionary DB1. In the figure, preferences 1 to 6 indicate preference elements Px (x = 1 to 6), and indicate preference element values for each character. Here, it is assumed that the elements necessary for establishing a strategy to be advantageous in the series are determined as follows, and a preference element value for each preference element Px is obtained according to an arithmetic expression using the elements. Shall be
[0024]
That is, as the element, first, the number of words in the word dictionary DB1 having the character as the ending character is represented as “END”. In addition, the number of words having that character as an initial letter is represented as “BEGIN”. However, this "BEGIN" excludes words which have "n" as the suffix in Japanese Japanese titles. Next, the number of words having that character as the initial letter and ending with “n” is represented as “NN”. In addition, the number of words having the character as an initial character and the initial character as an end character is represented as “SAME”. Further, the number of types of characters that can be an initial character in a set of words having that character as an end character is represented as “BKIND”. Then, the number of types of characters that can be the initial character in a set of two-character words having that character as the ending character is represented as “BKIND2”. Based on these factors, a preference factor value for each preference factor Px is determined as described below. In the method described below, guiding the language acquisition support device A3 to be advantageous by processing such as reducing the number of words that can be used by the user who is the partner of the list is adopted as a concept of the basic strategy of the list. Things.
[0025]
Specifically, the preference degree element P1 according to preference 1 is a candidate word ending character for the number of words that have the ending character of the candidate word as the initial character and do not have a ending character in the rules of the Siritori. Indicates the ratio of the number of words whose endings are, and the preference factor value for each character is obtained by calculating the total number of such candidate words by the formula {(END) / (BEGIN (END >> BEGIN))}. It is obtained by calculating based on The preference factor element P2 according to preference 2 indicates the number of words having the initial character as the initial letter, and the preference element value for each character is obtained by calculating {BEGIN} for the candidate word. Can be The preference degree element P3 according to preference 3 has the ending character of the candidate word as the initial character and the character “n” as the ending character when compared with the total number of words having the ending character of the candidate word as the initial character. It indicates the ratio of words to be performed, and the preference element value for each character is obtained by calculating candidate words based on the formula {(NN) / (BEGIN + NN)}. The preference factor element P4 related to preference 4 indicates the number of words having the ending character of the candidate word as the initial character and the ending character, and the preference element value for each character is the $ SAME value of the candidate word. It is obtained by calculating｝. The preference factor element P5 according to preference 5 indicates the number of types of ending characters of a candidate word in a set of words having the ending character of the candidate word as the ending character. It is obtained by calculating {BKIND} for a word. A preference degree element P6 according to preference 6 indicates the number of types of initials of the words in a set of words composed of only two characters having the ending character of the candidate word as the ending character. Is obtained by calculating {BKIND2} for the candidate word. FIG. 7 shows characters in preference 1 in order from the character having the largest preference element value.
[0026]
The corpus DB3 is a database of Japanese examples using the words included in the corresponding word dictionary DB1, but all the words included in the word dictionary DB1 are not necessarily included in the corpus DB3. Not necessarily. Then, the examples stored in the corpus DB3 are automatically subjected to morphological analysis processing, and the number of times each word appears in all the examples of the corpus DB3 is calculated. Information on whether or not it is recorded in the “sample use frequency” column in the corresponding word dictionary DB1. In the word dictionary DB1, it is also possible to set so that only words having the predetermined number or more times are used in the repository. Further, since it is preferable that the corpus DB3 include words that are relatively easy for the user to think according to the level of the user, for example, if the user is an elementary school student, the corpus DB3 includes textbooks of elementary schools and examples of reading books. It is good to use what was done.
[0027]
Further, the word meaning dictionary DB4 stores the meanings of the words included in the word dictionary DB1 in association with the words. A plurality of the word meaning dictionary DB4 may be provided in correspondence with each word dictionary DB1, or all the words included in all the possible word dictionaries DB1 may be stored in one database. You may.
[0028]
Hereinafter, the function of each unit will be briefly described in any order.
[0029]
The field change unit 7 determines the word dictionary DB1 and the statistical data DB2 to be used based on a field change command specifying one field input by the user, and also determines the corpus DB3 and the word meaning dictionary DB4 in some cases. By doing so, it changes the domain of words that can be used in a series of siritoris as siritori rules. In order to allow the user to easily input a field change command, for example, a screen that allows the user to select one field from a plurality of fields is displayed on a display or the like that is the output device 105 in advance. Good.
[0030]
The difficulty level change unit 8 determines a word dictionary DB1 and statistical data DB2 or a corpus DB3 to be used based on a difficulty level change command specifying one difficulty level input by the user, or a preference level described later. The arithmetic unit 3, the association degree arithmetic unit 6, or the answer word determining unit 4 performs a process of changing an arithmetic expression used in the process of determining an answer word, and determines a difficulty level of a word used in a series of serials as a rule of the serial. change. In order to allow the user to easily input the difficulty change command, for example, a screen is displayed in advance on a display or the like as the output device 105 so that one difficulty can be selected from a plurality of difficulty levels. Good.
[0031]
The input receiving unit 1 performs a process of receiving a presented word W input by a user. In order to allow the user to easily input the presented word W, for example, a presented word input field or the like may be displayed on a display or the like as the output device 105 in advance.
[0032]
The candidate word extracting unit 2 searches the word dictionary DB1 based on the presented word W received by the input receiving unit 1, and finds a candidate word Wi that can be a candidate for an answer word whose initial character is the ending character of the presented word W. Extract all. At this time, in the series of series, a presentation word whose input has been received first and an answer word which has been output first are excluded from the candidate words Wi to be extracted. When the ending character of the presented word is a long sound, the ending character is assumed to be “U”, and when the ending character is a voiced sound or semi-voiced sound, the ending character is excluded from its voiced point or semi-voiced voice. A process based on the rules of the series, such as a character, can be executed in the candidate word extraction unit 2.
[0033]
The preference calculation unit 3 refers to the statistical data DB2 for each of the candidate words Wi (i = 1, 2,..., N) extracted by the candidate word extraction unit 2, and selects each of the preference elements 1 to 6. By calculating the preference degree element values Px_i (x = 1 to 6) related to P1 to P6 based on the above-mentioned rules, the preference Pi related to each candidate word is calculated by an arithmetic expression [Pi = Cp1xP1_i + Cp2xP2_i + Cp3xP3_i + Cp4xP4_i + Cp5xP5_i + Cp5_P6_i + . Here, in the equation, Cpx (x = 1 to 6) is a predetermined constant that can be appropriately determined. Here, the equation for calculating the preference Pi is a simple linear sum function as in the above equation, but it is more complicated than a quadratic term, a logarithmic term (log P1_i) or a reciprocal term. (1 / P1_i) or a function to which a combination thereof is added may be used. In the case where the difficulty level is changed by weighting a predetermined preference factor Px in the above-described difficulty level changing section 8, the constant Cpx in the arithmetic expression may be changed.
[0034]
The associativity calculating unit 6 refers to the corpus DB 3 for each of the candidate words Wi (i = 1, 2,..., N) extracted by the candidate word extracting unit 2 and determines the ease of association of each candidate word. The associative degree Qi is calculated by an arithmetic expression [Qi = log {freq (Wi, W) / freq (W)}]. Here, freq (W) represents the number of sentences in which the presented word W appears in the corpus DB3, and freq (Wi, W) represents the number of sentences in which the presented word W and each candidate word Wi appear together in the corpus DB3. Represents. In addition, this arithmetic expression may be a more complicated function or a simpler function, similarly to the above-described arithmetic expression for calculating the preference level Pi.
[0035]
The answer word determination unit 4 calculates a candidate word Wi based on an arithmetic expression [Ri = Cp x Pi + Cq x Qi] based on the preference Pi and the associativity Qi, which are the operation results of the preference computation unit 3 and the associativity computation unit 6. The degree of goodness Ri for each is calculated. Here, Cp and Cq mean predetermined constants appropriately determined. Then, the candidate word that gives the highest degree of goodness Ri among the candidate words Wi is determined as the answer word Wans. In this case, the value obtained by adding a value obtained by multiplying the preference degree Pi and the association degree Qi by a constant, respectively, is defined as the goodness degree Ri. The degree Ri may be calculated. Further, when the difficulty level is changed by weighting either the preference level Pi or the associativity Qi in the difficulty level changing section 8 described above, either the preference level Pi or the associativity Qi or The arithmetic expression may be changed so that both powers are raised.
[0036]
The answer word output unit 5 outputs the answer word Was determined by the answer word determination unit 4 by displaying it on a display device 105 such as a display and presents it to the user. Therefore, the user inputs a new word with the suffix of the answer word Wans as the initial letter.
[0037]
If the user does not think of a presentation word suitable for inputting next, the hint request receiving unit 9a clicks a predetermined button displayed on a display or the like that is the output device 105, and the user inputs a hint. The request command is accepted, the answer word Wans output by the answer word output unit 5 immediately before is extracted from the answer word determination unit 4, and the answer word Wans is input to the input accepting unit 1 instead of the presented word. In this case, based on the answer word Wans input to the input receiving unit 1, the input is performed through a series of processes of the candidate word extracting unit 2, the preference calculating unit 3, the associative calculating unit 6, and the answer word determining unit 4. The best word for the word to be presented is determined. Then, based on the determined word, the hint generation / output unit 9b generates a hint composed of a phrase or the like that can lead to the word, and outputs the generated hint to the output device 105. This processing can be executed by the following processing, for example. That is, if the user does not think of a word beginning with “ru” when the output answer word Wans is a word having “ru” as the suffix, the answer word determination unit 4 determines “roulette” according to the above processing. Is determined, the hint generation / output unit 9b generates and outputs a hint “Rule ??”.
[0038]
When the user wants to know the meaning of the answer word Wans, the word meaning request receiving unit 10a transmits the word meaning request command input by clicking the predetermined button displayed on the display or the like as the output device 105. The word meaning extraction / output unit 10b searches the word meaning dictionary DB4 based on the input word meaning request command, extracts the meaning of the corresponding word, and outputs it to the output device 105.
[0039]
Next, the flow of operation when the language acquisition support device A3 is used will be described with reference to the flowcharts shown in FIGS.
[0040]
It is assumed that the user directly operates the language acquisition support device A3 as described above, but substantially the same operation is performed when the user uses another computer connected to the language acquisition support device A3. Can use the language acquisition support device A3. It is also assumed that the language acquisition support device A3 has already been activated and is in a usable state, and a predetermined initial screen is displayed on the display as the output device 105.
[0041]
First, as shown in FIG. 8, in a state where the initial screen is displayed (START), when a field change command is received by the user (step S1), the language acquisition support device A3 determines a predetermined word according to the field change command. The dictionary DB1 and the statistical data DB2 are set at least to those corresponding to the field (step S2), or the corpus DB3 and the word meaning dictionary DB4 are also set to those corresponding to the field (not shown). Further, as shown in FIG. 9, when the user receives a difficulty change command in a state where the initial screen is displayed (START) (step S11), the language acquisition support device A3 performs a predetermined change in accordance with the difficulty change command. The word dictionary DB1 and the statistical data DB2 are set at least to those corresponding to the difficulty level (step S12), or the corpus DB3 and the word meaning dictionary DB4 are set to those corresponding to the difficulty level (not shown). , Expression 2 or Expression 3 is changed so as to correspond to the difficulty level (not shown).
[0042]
Then, as shown in FIG. 10, from this state (START), the language acquisition support device A3 accepts the input of the presented word W by the user (step S31). Here, in the case where the user cannot input the presented word W without thinking of it, cannot enter the presented word W later, or has entered an impossible word such as a coined word appropriately created (step S31) NO), the retry cannot be continued, so the process ends without accepting the presented word, and the user loses. On the other hand, when the presented word W is received (step S31; YES), first, it is determined whether or not the ending character of the presented word W is “n” (step S32). The searched word dictionary DB1 is searched to extract candidate words Wi having the ending character of the presentation word W as the initial character (step S33). Here, if there is no candidate word Wi that can be extracted in the word dictionary DB1 (step S33; NO), the process ends because the language acquisition support device A3 cannot continue the retrieving, and the language acquisition support device A3 returns “ You lose. " On the other hand, if the candidate word Wi has been extracted (step S33; YES), the preference level Pi is calculated for each of the extracted candidate words Wi in accordance with the formula 1 with reference to the statistical data DB2 (step S34). Further, for each of the extracted candidate words Wi, the associativity Qi is calculated in accordance with the above-described equation 2 with reference to the corpus DB3 (step S35). Then, based on the calculated preference degree Pi and associativity Qi, the degree of goodness Ri for each candidate word Wi is calculated according to Equation 3 (step S36). Next, the degrees of goodness Ri for all the candidate words Wi are compared (step S37), the candidate word having the highest degree of goodness Ri is determined as the answer word Wans (step S38), and the answer word Wans is output. (Step S39). Here, it is determined whether or not the suffix of the answer word Wans is "n" (step S40). If the ending character is not "n", the above process is repeated, so that the series of the user and the language acquisition support device A3 is connected. Is established. If the ending character of the input presented word is "n" (step S32; YES) or if the ending character of the answer word is "n" (step S40; YES), the rule of the serialization is used. In this case, the series is ended (END). However, as a rule of the Siritori, when a character other than "n" is set to be "losing" even if it is the ending character, in step S32 and step S40, the character is the ending character of the presented word or the answer word. It can be set to determine whether or not there is.
[0043]
In addition, when the user requests a hint, as shown in FIG. 11, when receiving a hint request command from the user (step S41), the language acquisition support device A3 extracts the answer word WANs determined and output immediately before (step S41) ( (Step S42), based on the ending character of the answer word Wans, through the same process as in Steps S31 to S37 (Step S43), and determines a word that can be a presentation word as in Step S38 (Step S44). A hint is generated based on the word (step S45), and the hint is output (step S46).
[0044]
On the other hand, when the user requests the meaning of the answer word Wans, as shown in FIG. 12, when the language acquisition support device A3 receives the word meaning request command from the user (step S51), the determined and output answer word WANs is received. , The word meaning dictionary DB4 is searched, and the meaning of the corresponding word is extracted (step S52) and output (step S53).
[0045]
As described above, according to the method of language acquisition based on the scenery using the language acquisition support device A3 of the present embodiment, the user can appropriately learn Japanese words while having fun through a kind of game called the scenery. . In particular, on the side of the language acquisition support device A3, when deciding the most suitable word for answering the presented word input by the user, that is, the best word in the case of aiming to win in the scenery game, It uses six types of advantageous preferences and can output the most suitable words as answer words, and preferentially selects words that are easily associated with humans. In addition to selecting words, it is configured to take into account the fun of being able to output associative, which is close to the selection made by humans. In addition, since the field and difficulty of the scenery are changed, and hints and meanings of words are presented to the user, it is possible to suitably improve the user's feeling of use.
[0046]
Note that the present invention is not limited to the above embodiment. For example, it is not necessary to use all of the six preferences. For example, any one of them can be selectively used, and whether or not to use the degree of association is arbitrary. Also, the arithmetic expression used to determine the answer word can be changed as appropriate. Further, since the change in the field, the change in the degree of difficulty, the output of the hint, and the output of the word meaning are associated with the basic configuration of the present invention, whether or not to apply them is also arbitrary. Other specific configurations are not limited to the above embodiment, and various modifications can be made without departing from the spirit of the present invention.
[0047]
【The invention's effect】
The present invention, as described in detail above, is greatly useful for learning a language, particularly words, through the play of a scene. That is, when the user inputs a certain word, a word that is most suitable for an answer with the ending of the word as an initial letter can be output, and this is alternately repeated between the user and the computer, whereby the serial number is output. Until the rule is violated, a series of scenes can be established, during which the user can know many words presented by the user or outputted from the computer, and as a result, It is possible to learn a lot of words in the language you were in.
[Brief description of the drawings]
FIG. 1 is a functional configuration diagram showing a basic mode of a language acquisition support device according to the present invention.
FIG. 2 is a functional configuration diagram showing an application aspect of the language acquisition support device according to the present invention.
FIG. 3 is a functional configuration diagram showing another applied aspect of the language acquisition support device according to the present invention.
FIG. 4 is a functional configuration diagram showing another applied aspect of the language acquisition support device according to the present invention.
FIG. 5 is a schematic device configuration diagram of a computer constituting the language acquisition support device according to one embodiment of the present invention.
FIG. 6 is an explanatory diagram showing a part of an example of a language dictionary used in the embodiment;
FIG. 7 is an explanatory diagram showing an example of statistical data used in the embodiment.
FIG. 8 is an exemplary flowchart showing a part of the operation of the language acquisition support device in the embodiment.
FIG. 9 is an exemplary flowchart showing a part of the operation of the language acquisition support device in the embodiment.
FIG. 10 is an exemplary flowchart illustrating a part of the operation of the language acquisition support device in the embodiment.
FIG. 11 is an exemplary flowchart showing part of the operation of the language acquisition support device according to the embodiment.
FIG. 12 is an exemplary flowchart showing a part of the operation of the language acquisition support device in the embodiment.
[Explanation of symbols]
A1, A2, A3, A4 ... Language acquisition support device
DB1… Word dictionary
DB2: statistical data
DB3: Corpus
DB4: Word meaning dictionary
1. Input reception unit
2 ... Candidate word extraction unit
3 ... Preference calculation unit
4: Answer word determination unit
5 ... Answer word output section
6 ... Association degree calculation unit
7: Field change department
8: Difficulty change section
9a: Hint request reception desk
9b: Hint generation / output unit
10a: Word meaning request reception unit
10b Word extraction / output unit

Claims (21)

A language acquisition support device based on a rule related to a predetermined series that sets an ending character of an input presented word as an initial character and outputs an answer word excluding a word already received or already output unlike the presented word. And
An input receiving unit that receives an input of a presented word;
A candidate word extracting unit for automatically extracting from a predetermined word dictionary candidate words excluding words that have already been input or already output, with the ending character as the initial character based on the ending character of the presented word received by the input receiving unit When,
Based on a plurality of quantitative statistical data for winning the series with respect to each character included in the word dictionary, a preference degree indicating the degree of advantage in the series depending on the character for each candidate word extracted by the candidate word extraction unit A preference calculation unit for calculating
An answer word determining unit that determines a candidate word having the highest or lowest preference as an answer word based on the preference calculated by the preference calculation unit;
A language acquisition support device comprising: an answer word output unit that outputs an answer word determined by an answer word determination unit. The quantitative statistical data is a word having a suffix of the candidate word with respect to the number of words having the suffix of the candidate word as the initial character and having a suffix character that indicates a character losing in the rule of the Siritori. A preference word having a ratio of numbers as preference element values, and a preference calculation unit calculating a preference obtained by an arithmetic expression indicating that a candidate word having a larger value of the preference element value has a greater degree of advantage The language acquisition support device according to claim 1, wherein The quantitative statistical data has, as a preference factor element value, the number of types of initials of the words in a set of candidate words composed of only two characters having the ending character of the candidate word as the ending character, 3. The language according to claim 1, wherein the calculation unit calculates a preference degree obtained by an operation expression indicating that a candidate word having a larger preference element value has a greater degree of advantage. Acquisition support device. The quantitative statistical data has, as a preference element value, the number of types of initials of the words in a set of words having the ending character of the candidate word as the ending character, and the preference operation unit includes: 4. The language acquisition support apparatus according to claim 1, wherein a preference degree obtained by an arithmetic expression indicating that a candidate word having a larger value has a greater degree of advantage is calculated. The quantitative statistical data is a word having the ending character of the candidate word as the ending character with respect to the number of words having the ending character of the candidate word as the initial character and having no ending character in the rules of the Siritori. A preference word having a ratio of numbers as preference element values, and a preference calculation unit calculating a preference obtained by an arithmetic expression indicating that a candidate word having a larger value of the preference element value has a greater degree of advantage The language acquisition support device according to any one of claims 1, 2, 3, and 4. The quantitative statistical data has the number of words having the ending character of the candidate word as the initial character and the ending character as a preference factor value, and the preference calculation unit determines that the candidate word having a small value of the preference factor value The language acquisition support device according to any one of claims 1, 2, 3, 4, and 5, wherein a preference degree obtained by an arithmetic expression indicating that the degree of advantage is greater is calculated. An associative degree calculation for calculating an associative degree obtained by a predetermined arithmetic expression based on a frequency of appearance of a presented word in a predetermined corpus storing natural language sentences and a frequency of appearance of the presented word and each candidate word in the corpus. And an answer word determining unit that determines an answer word based on a predetermined arithmetic expression including the degree of association obtained by the degree of association calculation unit and the degree of preference obtained by the degree of preference calculation unit. The language acquisition support device according to any one of claims 1, 2, 3, 4, 5, 6, and 7. A word field change unit that sets a field of a word group that can be used as a rule of the directory and accepts an input of a field change command that specifies one of the fields to change the field of the word group in a series of directories is further provided. The word field changing unit includes at least any one of a plurality of word dictionaries, a plurality of statistical data, or a plurality of corpus storing natural language sentences set in advance for each field based on the field change command received. The language acquisition support device according to any one of claims 1, 2, 3, 4, 5, 6, and 7, wherein a word dictionary, statistical data, or a corpus to be referred to is selected from one of them. A plurality of difficulty levels that can be used as rules of the series are set, and a difficulty level change unit in a series of series is further provided by receiving an input of a level change command for designating any of the levels of difficulty. The degree changing unit receives a plurality of word dictionaries and a plurality of statistical data respectively corresponding to a plurality of predetermined difficulty levels, or a word corresponding to a difficulty level change command received from a plurality of corpus storing natural language sentences. 7. A method for selecting a dictionary and statistical data, a corpus, or changing an arithmetic expression for determining an answer word based on a preference and an association degree. 9. The language acquisition support device according to any one of claims 7, 7, and 8. A hint request receiving unit that receives a hint request command requesting a hint regarding a presented word to be input, and a ending character of the answer word output immediately before by the answer word output unit based on the hint request command received by the hint request receiving unit. 10. The hint generation / output unit according to claim 1, further comprising: a hint generation / output unit configured to generate and output a hint from a word as an initial letter. Language acquisition support device. A word meaning request receiving unit that receives a word meaning request command input at least with respect to the answer word output by the answer word output unit; and a word meaning request command received from the word meaning request receiving unit. The language acquisition according to any one of claims 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10, further comprising a word meaning extraction / output unit for extracting and outputting the meaning of the answer word. Support device. By operating the computer, a predetermined series that sets the suffix of the presented word input to the computer as an initial letter and outputs an answer word different from the presented word excluding the words already accepted or already output A program that functions as a language acquisition support device based on the rules according to
Input receiving means for receiving an input of a presented word;
A candidate word extracting means for automatically extracting from a predetermined word dictionary candidate words excluding a word that has already been input or already output, with the ending character as the initial character based on the ending character of the presented word received by the input receiving means When,
Preference indicating the degree of advantage in the character-dependent siritori for each candidate word extracted by the candidate word extraction means based on a plurality of quantitative statistical data for winning the siritori for each character included in the word dictionary Preference calculating means for calculating
Based on the preference calculated by the preference calculation means, the answer word determining means for determining the candidate word having the highest or lowest preference as the answer word,
A language acquisition support program that functions as answer word output means for outputting an answer word determined by an answer word determining means. The quantitative statistical data is a word having a suffix of the candidate word with respect to the number of words having the suffix of the candidate word as the initial character and having a suffix character that indicates a character losing in the rule of the Siritori. The preference calculation unit calculates a preference degree obtained by an arithmetic expression indicating that a candidate word having a larger value of the preference element value has a greater degree of advantage. 13. The language acquisition support program according to claim 12, wherein the language acquisition support program causes the language acquisition function to function. The quantitative statistical data, in a set of candidate words composed of only two characters with the ending character of the candidate word as the ending character, having the number of types of initials of those words as preference factor values, The function according to claim 12 or 13, wherein the preference calculating means is configured to calculate a preference obtained by an arithmetic expression indicating that a candidate word having a larger value of the preference element value has a greater degree of advantage. A language acquisition support program according to any of the above. The computer may further include a predetermined calculation based on a frequency at which a presented word appears in a predetermined corpus storing a natural language sentence incorporated or connected to the computer, and a frequency at which both the presented word and each candidate word appear in the corpus. Functioning as associative degree calculating means for calculating the degree of associativeness obtained by the equation, and setting the answer word determining means to include the associative degree obtained by the associative degree calculating means and the preference degree obtained by the preference degree calculating means. The language acquisition support program according to any one of claims 12, 13 and 14, wherein the answer word is determined on the basis of the operation formula. The computer further receives the input of a field change command that specifies one of a plurality of fields of the word group that can be used as preset rules of the field, thereby changing the field of the word group in the series of words, Change is made by selecting a word dictionary, statistical data, or corpus to be referenced from at least one of a plurality of word dictionaries, a plurality of statistical data, or a plurality of corpus storing natural language sentences set in advance for each field. The language acquisition support program according to any one of claims 12, 13, 14, and 15, which functions as a word field changing unit. A predetermined criterion that sets the ending character of the presented word input to the computer as the initial letter and outputs the answer word excluding the word already received or already output unlike the presented word based on the processing of the computer. A method for supporting language acquisition based on the rules,
An input receiving step of receiving an input of a presented word;
A candidate word extracting step of automatically extracting from a predetermined word dictionary candidate words excluding a word that has already been input or already output, with the ending character as the initial character based on the ending character of the presented word received in the input receiving step When,
Preference indicating the degree of advantage in a character-dependent siritori for each candidate word extracted in the candidate word extraction step based on a plurality of quantitative statistical data for winning the siritori for each character included in the word dictionary A preference calculation step for calculating
Based on the preference calculated in the preference calculation step, an answer word determination step of determining the candidate word having the maximum or minimum preference as an answer word,
And a response word output step of outputting the response word determined in the response word determination step. The quantitative statistical data is a word having a suffix of the candidate word with respect to the number of words having the suffix of the candidate word as the initial character and having a suffix character that indicates a character losing in the rule of the Siritori. In the preference calculation step, a preference word obtained by an arithmetic expression indicating that a candidate word having a larger value of the preference element value has a greater degree of advantage is calculated in a preference calculation step. 18. The language acquisition support method according to claim 17, wherein the language acquisition is performed. The quantitative statistical data, in a set of candidate words composed of only two characters with the ending character of the candidate word as the ending character, having the number of types of initials of those words as preference factor values, 19. The preference calculation step according to claim 17, wherein in the preference calculation step, a preference obtained by an arithmetic expression indicating that a candidate word having a larger value of the preference factor value has a greater degree of advantage is calculated. Language acquisition support method described. An association obtained by a predetermined arithmetic expression based on a frequency at which a presented word appears in a predetermined corpus storing a natural language sentence built in or connected to the computer, and a frequency at which the presented word and each candidate word appear together in the corpus. Further comprising an associative degree calculating step of calculating the degree, wherein the answer word determining step is based on a predetermined arithmetic expression including the associative degree obtained in the associative degree calculating step and the preference degree obtained in the preference degree calculating step. 20. The language acquisition support method according to claim 17, wherein the answer word is determined by using the method. A plurality of fields of the word group that can be used as rules of the series are set in advance, and a field change command that designates one of the fields is received, so that the fields of the word group in the series of domains are pre-set for each field. A word field changing step of changing by selecting a word dictionary, statistical data, or corpus to be referenced from at least one of a plurality of set word dictionaries, a plurality of statistical data, or a plurality of corpus storing natural language sentences The language acquisition support method according to any one of claims 17, 18, 19, and 20, further comprising:

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