JP2022117805A - Pronunciation training program and terminal device - Google Patents

Abstract

To provide a pronunciation training program and a terminal device, which can effectively use a result of a listening test for a pronunciation test.SOLUTION: A pronunciation training program causes a processor 11 to execute: extracting a word or a sentence including the word from a database of pronunciation questions on the basis of a result of a listening test executed on a user; and executing a pronunciation test on the basis of the extracted word or sentence on the user.SELECTED DRAWING: Figure 1

Description

The present invention relates to a pronunciation training program and a terminal device.

Some terminal devices such as electronic dictionaries are installed with a pronunciation training application program for English or the like. In this type of pronunciation training program, a pronunciation test is conducted in which the user actually pronounces English words, etc., and it is determined whether or not the pronunciation is correct. By notifying the user of the correct/incorrect result together with the correct pronunciation, it is expected that the user's pronunciation ability in English or the like will be improved.

On the other hand, some terminal devices such as electronic dictionaries are installed with a listening training application program for English or the like. In this type of listening training program, a listening test is conducted in which the user listens to English words, etc., and it is determined whether or not the English words have been correctly heard. By notifying the user of the correct/wrong result together with the correct answer, it is expected that the user's listening ability in English or the like will be improved.

Japanese Patent Application Laid-Open No. 2002-175006

Here, it is considered that there is a correlation between the pronunciation ability of English and the like and the listening ability. Therefore, it is expected that the results of the listening test will be used in the pronunciation test to further improve the pronunciation ability.

SUMMARY OF THE INVENTION An object of the present invention is to provide a pronunciation training program and a terminal device that can effectively use the results of a listening test for a pronunciation test.

A pronunciation training program according to the first aspect of the present invention extracts words or sentences containing words from a database of pronunciation problems based on the results of a listening test conducted on the user; and conducting a pronunciation test based on the words or sentences.

A terminal device according to a second aspect of the present invention includes an extraction unit that extracts words or sentences containing words from a database of pronunciation questions based on the results of a listening test conducted on the user; and a test unit for performing a pronunciation test based on the words or said sentences.

ADVANTAGE OF THE INVENTION According to this invention, the pronunciation training program and terminal device which can utilize the result of a listening test effectively for a pronunciation test can be provided.

FIG. 1 is a diagram showing an example of the system configuration according to one embodiment of the present invention. FIG. 2 is a diagram illustrating an example of an attribute value DB; FIG. 3 is a diagram showing an example of a listening question sentence DB. FIG. 4 is a diagram showing an example of a listening answer DB. FIG. 5 is a diagram illustrating an example of a priority DB; FIG. 6 is a diagram showing an example of a pronunciation problem DB. FIG. 7 is a flow chart showing the operation during listening training. FIG. 8 is a flow chart showing the operation during pronunciation training. FIG. 9 is a flowchart showing update processing of the priority DB. FIG. 10 is a diagram showing an example of the mode selection screen. FIG. 11 is a diagram showing a display example of pronunciation problems in the recommendation mode. FIG. 12 is a flowchart showing update processing of the priority DB.

An embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing an example of the configuration of a system 1 according to one embodiment of the invention. The system 1 includes a server 10 and terminals 20 . The server 10 and the terminal 20 are communicably connected via a network 30 . Network 30 is, for example, the Internet. Although only one terminal 20 is shown in FIG. 1, the number of terminals 20 is not limited to one. That is, the number of terminals 20 may be two or more.

The server 10 is a terminal device having a processor 11 , a ROM 12 , a RAM 13 , a storage 14 and a communication device 15 . Each of these is connected to each other via a system bus 19 .

The processor 11 may be an integrated circuit including a CPU (Central Processing Unit) and the like. As the processor 11, a processor other than the CPU, such as an ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), GPU (Graphic Processing Unit), etc., may be used.

The ROM 12 records information used for the operation of the processor 11 and the like. A RAM 13 is a main storage device for the operation of the processor 11 and the like.

The storage 14 stores a server control program used by the processor 11, various programs such as a calculation program for executing various calculations, parameters, and the like. This program includes a training program 141 such as English. The training program 141 includes a listening training program for English words and the like, and a pronunciation training program. The processor 11 can operate as an extraction unit and a test unit by executing processing according to the training program 141 stored in the storage 14 . Note that the extraction unit and the test unit may be implemented by dedicated circuits that implement similar operations.

The storage 14 also stores a listening database (DB) 142 and a pronunciation database (DB) 143 .

The listening DB 142 is a database that stores various data related to listening training. The listening DB 142 includes an attribute value DB, a listening question DB, and a listening answer DB.

The attribute value DB is a database that stores problem attribute values. FIG. 2 is a diagram illustrating an example of an attribute value DB; As shown in FIG. 2, the attribute value DB includes L_ID, attribute value, and status as elements. L_ID is a listening ID uniquely assigned to each listening question. The attribute value is a numeric value that indicates the attribute of the problem. As shown in FIG. 2, the attribute values include numerical values of 1, 2, and 3, for example. An attribute value of 1 indicates, for example, that the corresponding listening question is a question of whether or not the speech is heard correctly. An attribute value of 2 indicates, for example, that the corresponding listening question is a question to confirm whether or not the key points in the speech are understood. An attribute value of 3, for example, indicates that the corresponding listening question is a question to check whether or not the necessary content is extracted from the long speech and understood. Here, the attribute values in the attribute value DB can be appropriately set by the creator of the listening question when creating the listening question. The status indicates whether or not the user has answered the corresponding question correctly. As shown in FIG. 2, the status includes data such as "OK", "NG", and "not yet implemented". "OK" indicates that the user has answered the corresponding question correctly. "NG" indicates that the user has answered the corresponding question incorrectly. "Not performed" indicates that the listening test for the corresponding question has not been performed on the user and neither "OK" or "NG" can be determined. Here, the initial value of the status is "unimplemented". Also, the status is data stored for each user.

The listening question sentence DB is a database that stores the contents of the question sentences of the listening test. FIG. 3 is a diagram showing an example of a listening question sentence DB. As shown in FIG. 3, the listening question sentence DB includes L_IDs, question sentences, and options as elements. L_ID is a listening ID used in common with the attribute value DB. The question sentence is text data and voice data of the question sentence given in the listening test. The options are text data and voice data of options for the user's answer to the question. In FIG. 3, there are four options. However, there may be more than two options.

The listening answer DB is a database that stores answers to listening questions. FIG. 4 is a diagram showing an example of a listening answer DB. As shown in FIG. 4, the listening answer DB includes L_IDs, answers, and key phrases as elements. L_ID is a listening ID used in common with the attribute value DB and the question sentence DB. The answer is data of answer options for the question sentence of the corresponding L_ID. A keyphrase is text data of a keyphrase included in an answer option. Key phrases are important words or sentences related to the intent of the question. For example, a question with an attribute value of 1 is a question of whether or not the word or sentence corresponding to the key phrase is correctly heard. Here, "null" in FIG. 4 means that there is no keyphrase in the corresponding cell. For example, L_ID1 in FIG. 4 indicates that there are two keyphrases. The key phrases in the listening answer DB can be appropriately set by the creator of the listening question when creating the listening question.

The pronunciation DB 143 is a database that stores various data related to pronunciation training. The pronunciation DB 143 includes a priority DB and a pronunciation problem DB.

The priority DB is a database that stores data relating to the priority of questions extracted from the pronunciation question DB. FIG. 5 is a diagram illustrating an example of a priority DB; As shown in FIG. 5, the priority DB includes S_ID, attribute, score, L_ID, and priority as elements. S_ID is a pronunciation ID uniquely assigned to each pronunciation problem. Attribute indicates the attribute of the problem. As shown in FIG. 5, the attribute value includes, for example, "word" and "sentence" data. "Word" indicates, for example, that the corresponding pronunciation problem is a word pronunciation problem. "Sentence" indicates, for example, that the corresponding pronunciation problem is a sentence pronunciation problem. The score indicates the user's score in the pronunciation test of the corresponding S_ID. Here, the initial value of the score is "unimplemented". L_ID is the L_ID associated with the S_ID. In embodiments, S_IDs and L_IDs that contain a common keyphrase are associated. The priority indicates whether or not the pronunciation problem of the corresponding S_ID should be given priority in the recommendation mode, which will be described later. As shown in FIG. 5, the priority includes "high" and "low" data. "High" indicates that the pronunciation problem of the corresponding S_ID is given a high priority. "Low" indicates that the pronunciation problem of the corresponding S_ID has a low question setting priority. Here, the priority does not necessarily have to be binary data of "high" and "low". The priority may be data of three or more values. Also, the score and priority are data stored for each user.

The pronunciation question DB is a database that stores the content of pronunciation test questions. FIG. 6 is a diagram showing an example of a pronunciation problem DB. As shown in FIG. 6, the pronunciation problem DB includes S_IDs, training texts, and key phrases as elements. S_ID is a pronunciation ID used in common with the priority DB. The training texts are text data and voice data of words or sentences that are given in the pronunciation test. A key phrase is text data of a key phrase included in a pronunciation test question. As with listening, key phrases for pronunciation are important words or sentences that relate to the intent of the question. Here, "null" in FIG. 6 means that there is no keyphrase in the corresponding cell. For example, S_ID1 in FIG. 6 indicates that there is one keyphrase. Here, key phrases in the pronunciation question DB can be appropriately set by the creator of the pronunciation question when creating the pronunciation question. Then, when there is a common key phrase in the listening question and the pronunciation question, S_ID and L_ID are associated in the priority DB. For example, comparing the listening answer DB of FIG. 4 and the pronunciation problem DB of FIG. 6, L_ID1 and S_ID3 contain the common key phrase "ride". Therefore, S_ID3 and L_ID1 are associated in the priority DB.

Communication device 15 includes circuitry for communicating with an external communication network, such as network 30 .

The terminal 20 has a CPU 21 , a ROM 22 , a RAM 23 , a storage 24 , an input device 25 , a display device 26 , a speaker 27 and a communication device 28 . Each of these are connected to each other via a system bus 29 . The terminal 20 may be an electronic device such as a personal computer (PC), tablet terminal, or smart phone. Also, the terminal 20 may be an electronic dictionary or the like having a communication function.

The CPU 21 is a processor that controls various operations of the terminal 20 . The ROM 22 records a startup program for the terminal 20 and the like. A RAM 23 is a main storage device for the CPU 21 and the like. The storage 24 stores various programs such as a terminal control program used by the CPU 21, parameters, and the like. The CPU 21 controls the operation of the terminal 20 by executing various programs according to input signals from the input device 25 and signals received by the communication device 28 . Various programs may be downloaded from a web server (not shown) to the storage 24 via the network 30 and the communication device 28 . Communication device 28 includes circuitry for communicating with an external communication network, such as network 30 .

The input device 25 includes a keyboard, mouse, touch panel, and the like. Also, the input device 25 includes an audio input device such as a microphone. A signal indicating the content of the user's operation is input to the CPU 21 via the system bus 29 according to the user's operation via the input device 25 .

The display device 26 is a liquid crystal display, an organic EL display, or the like. The display device 26 may be provided integrally with the terminal 20 or may be provided separately from the terminal 20 . Various images are displayed on the display device 26 .

The speaker 27 is an output device that outputs sound.

Next, the operation of system 1 will be described. FIG. 7 is a flow chart showing the operation during listening training. The processing in FIG. 7 is started when the terminal 20 requests the server 10 to perform listening training.

At step S<b>101 , the processor 11 activates a listening training program stored in the storage 14 .

At step S102, processor 11 conducts a listening test for the user. For example, the processor 11 extracts speech data of question sentences and speech data of corresponding options from the listening question DB. The question sentence may be extracted completely randomly, may be randomly extracted among attribute values specified by the user, or may be specified by the user. The processor 11 then transmits the extracted voice data of the question sentence and the voice data of the options to the terminal 20 . The CPU 21 of the terminal 20 emits the voice of the question from the speaker 27 based on the received voice data of the question. Subsequently, the CPU 21 sequentially emits the voices of the options from the speaker 27 based on the received voice data of the options. The user listens to the question and selects an answer option by operating the input device 25, for example. When an answer is selected, CPU 21 transmits the selected answer to server 10 . The processor 11 compares the selected answer with the answers stored in the listening answer DB to determine whether the user's answer is correct or incorrect. The processor 11 then returns the result of correctness/incorrectness determination to the terminal 20 . In response to this, the CPU 21 displays the correct/wrong result on the display device 26, for example.

In step S103, the processor 11 associates whether the test result is OK or NG with L_ID and stores it in the RAM 13, for example.

At step S104, the processor 11 determines whether or not to end the listening test. For example, it is determined that the listening test is finished when a preset number of questions have been completed in the listening test. Alternatively, when the terminal 20 instructs the server 10 to end the listening test, it is determined that the listening test is to end. If it is determined in step S104 that the listening test is not finished, the process returns to step S102. In this case, the listening test continues. When it is determined in step S104 that the listening test is finished, the process proceeds to step S105.

In step S<b>105 , the processor 11 updates the attribute value DB based on the test results stored in the RAM 13 . That is, the processor 11 updates the status of the tested L_ID to "OK" or "NG". After that, the processor 11 terminates the processing of FIG.

FIG. 8 is a flow chart showing the operation during pronunciation training. The process of FIG. 8 is started when the terminal 20 requests the server 10 to perform pronunciation training.

At step S<b>201 , the processor 11 activates the pronunciation training program stored in the storage 14 .

At step S202, the processor 11 updates the priority DB based on the result of the listening test. After that, after updating the priority DB, the process moves to step S203. The update processing of the priority DB will be described below. FIG. 9 is a flowchart showing update processing of the priority DB.

In step S301, the processor 11 refers to the attribute value DB and extracts an L_ID whose attribute value is "1", which indicates that the corresponding listening question is a question to confirm whether or not the speech is correctly heard. . The reason for such processing is based on the idea that the ability to hear speech accurately is correlated with the ability to pronounce this speech accurately. In other words, in the embodiment, listening ability is improved by practicing pronunciation. In FIG. 2, for example, L_IDs 1, 2, and 3 are extracted.

In step S302, the processor 11 refers to the priority DB and extracts one S_ID associated with the extracted L_ID. For example, S_ID3 is extracted from L_ID1 in FIG.

In step S303, the processor 11 refers to the attribute value DB and determines whether or not the status of the L_ID corresponding to the extracted S_ID is "unimplemented". In step S303, when the status of the corresponding L_ID is not determined to be "unexecuted", the process proceeds to step S304. When it is determined in step S303 that the status of the corresponding L_ID is "unimplemented", the process proceeds to step S307.

In step S304, the processor 11 refers to the attribute value DB and determines whether the status of the extracted S_ID and the corresponding L_ID is "OK". When the status of the corresponding L_ID is not determined to be "OK" in step S304, that is, when it is determined to be "NG", the process proceeds to step S305. When it is determined in step S304 that the status of the corresponding L_ID is "OK", the process proceeds to step S307.

In step S305, the processor 11 refers to the priority DB and determines whether or not the score of the extracted S_ID is less than a threshold value, eg, 100 points. Here, when the score is "unexecuted", it is determined that the score is less than the threshold. When it is determined in step S305 that the score of the extracted S_ID is less than the threshold, the process proceeds to step S306. If it is not determined in step S305 that the score of the extracted S_ID is less than the threshold, the process proceeds to step S307. Here, the threshold for the determination in step S305 is not limited to 100 points, and may be set arbitrarily.

In step S306, the processor 11 registers "high" as the priority in the extracted S_ID. After that, the process moves to step S308. That is, in the embodiment, when the result of the listening test is NG and the result of the pronunciation test is also bad or the pronunciation test has not been performed, the priority of the corresponding S_ID becomes "high". For example, as shown in FIG. 5, the priority of S_ID3 is "high".

In step S307, the processor 11 registers "low" as the priority in the extracted S_ID. After that, the process moves to step S308. That is, in the embodiment, when the result of the listening test is OK or not performed, or the result of the pronunciation test is good, the priority of the corresponding S_ID becomes "low".

In step S308, the processor 11 determines whether or not to end the priority DB update process. When the processing of steps S303 to S307 is completed for the S_ID associated with the L_ID whose attribute values are all 1, it is determined that the update processing of the priority DB is finished. If it is determined in step S308 that the priority DB update process is not terminated, the process returns to step S302. In this case, processor 11 extracts another S_ID and performs similar processing. When it is determined in step S308 that the priority DB update process is finished, the processor 11 completes the process of FIG.

Now, return to the description of FIG. In step S203 after the priority DB update process, the processor 11 determines whether or not the pronunciation test mode is the "recommended mode". The pronunciation test mode can be selected by the user on a mode selection screen displayed on the display device 26 of the terminal 20, for example. For example, the pronunciation test modes include "random mode", "vowel mode", "consonant mode", and "recommended mode". Random mode is a mode in which questions are presented at random. The vowel mode is a mode in which pronunciation questions for vowel training are presented. The consonant mode is a mode in which pronunciation questions are given for consonant training. The recommendation mode is a mode in which pronunciation questions that the user is considered to be weak in are given. Pronunciation problems that are considered to be difficult for users are problems with poor listening test results, that is, problems with "high" priority. FIG. 10 is a diagram showing an example of the mode selection screen. As shown in FIG. 10, the mode selection screen displays a random button 261, a vowel button 262, a consonant button 263, and a recommended button 264 corresponding to each mode. When the user selects any button, a description 265 of the selected mode is displayed. Furthermore, a practice button 266 is displayed in the explanation 265 . It is determined that the corresponding mode is selected when the user selects practice button 266 . That is, in step S203, when the user selects the recommendation button 264 and the practice button 266, it is determined that the pronunciation test mode is the "recommendation mode". If it is determined in step S203 that the pronunciation test mode is not the "recommended mode", the process proceeds to step S204. When it is determined in step S203 that the pronunciation test mode is the "recommended mode", the process proceeds to step S207.

In step S204, the processor 11 conducts pronunciation tests in modes other than the "recommendation mode". For example, the processor 11 extracts training text corresponding to the mode from the pronunciation problem DB. Processor 11 transmits text data of the extracted training text to terminal 20 . The CPU 21 of the terminal 20 displays the word or sentence in question on the display device 26 based on the received text data. The user pronounces the word or sentence using the microphone of the input device 25 . When the voice is input, the CPU 21 transmits voice data based on the input voice to the server 10 . The processor 11 compares the speech data received from the terminal 20 with the speech data of words or sentences corresponding to the questions stored in the pronunciation question DB, and calculates a score according to the comparison result. The processor 11 then returns the calculated score to the terminal 20 . In response to this, the CPU 21 displays the score on the display device 26, for example.

In step S205, the processor 11 associates the score as the test result with the S_ID and stores it in the RAM 13, for example.

In step S206, processor 11 determines whether or not to end the pronunciation test. For example, when the pronunciation test for a preset number of questions is completed, it is determined that the pronunciation test is finished. Alternatively, when the terminal 20 instructs the server 10 to end the pronunciation test or instructs the server 10 to change the mode, it is determined to end the pronunciation test. If it is determined in step S206 that the pronunciation test is not finished, the process returns to step S204. In this case, the pronunciation test continues. When it is determined in step S206 that the pronunciation test is finished, the process proceeds to step S212.

In step S207, the processor 11 refers to the priority DB and extracts an S_ID with a "high" priority. In step S207, all S_IDs registered in the priority DB and having a priority of "high" may be extracted, or some S_IDs may be extracted. When some S_IDs are extracted, for example, those with "untested" scores or those with low pronunciation test scores may be preferentially extracted. Also, when the priority has three or more values, the higher priority may be preferentially extracted.

In step S208, the processor 11 refers to the pronunciation problem DB and extracts the training text of the extracted S_ID. The processor 11 then transmits the extracted text data of the training text to the terminal 20 . The CPU 21 of the terminal 20 displays the word or sentence in question on the display device 26 based on the received text data. FIG. 11 is a diagram showing a display example of pronunciation problems in the recommendation mode. As shown in FIG. 11, a mode selection button 267 for mode selection is displayed on the pronunciation problem display screen. Also, on the pronunciation problem display screen, words or sentences, which are training texts of S_IDs with a priority of "high", are displayed. For example, in FIG. 11, the training text "water" for S_ID1, the training text "ride" for S_ID3, and the training text "He is getting out of the room." for S_ID101 are displayed. Also, a check button 268 is displayed near each word or sentence. When check button 268 is selected, a pronunciation test is performed on the corresponding word or sentence.

At step S209, processor 11 performs a pronunciation test. That is, the user pronounces words or sentences using the microphone of the input device 25 . When the voice is input, the CPU 21 transmits voice data based on the input voice to the server 10 . The processor 11 compares the speech data received from the terminal 20 with the speech data of words or sentences corresponding to the questions stored in the pronunciation question DB, and calculates a score according to the comparison result. The processor 11 then returns the calculated score to the terminal 20 . In response to this, the CPU 21 displays the score on the display device 26, for example.

In step S210, the processor 11 associates the score as the test result with the S_ID and stores it in the RAM 13, for example.

At step S211, the processor 11 determines whether or not to end the pronunciation test. For example, when the pronunciation test for a preset number of questions is completed, it is determined that the pronunciation test is finished. Alternatively, when the terminal 20 instructs the server 10 to end the pronunciation test or instructs the server 10 to change the mode, it is determined to end the pronunciation test. If it is determined in step S211 that the pronunciation test is not finished, the process returns to step S209. In this case, the pronunciation test continues. When it is determined in step S211 that the pronunciation test is finished, the process proceeds to step S212.

At step S212, the processor 11 updates the priority DB based on the result of the pronunciation test. Thereafter, after updating the priority DB, the processor 11 terminates the processing of FIG. The update processing of the priority DB will be described below. FIG. 12 is a flowchart showing update processing of the priority DB.

In step S401, the processor 11 registers the results of the pronunciation test in the priority DB. That is, the processor 11 updates the scores of the S_IDs tested.

In step S402, the processor 11 refers to the priority DB and extracts S_IDs with "high" priority. In step S402, among the S_IDs for which the pronunciation test has been performed, S_IDs having a "high" priority may be extracted.

In step S403, the processor 11 determines whether or not the score of the extracted S_ID is equal to or greater than a threshold. The threshold in step S403 may be the same as the threshold in step S305. When it is determined in step S403 that the score of the extracted S_ID has reached or exceeded the threshold, the process proceeds to step S404. If it is not determined in step S403 that the score of the extracted S_ID has exceeded the threshold, the process proceeds to step S405.

At step S404, the processor 11 updates the priority of the corresponding S_ID from "high" to "low". After that, the process moves to step S405. That is, by improving the pronunciation ability of the corresponding S_ID words or sentences, the improvement of the listening ability of the corresponding L_ID words or sentences is also expected. Therefore, the corresponding S_ID is excluded from extraction targets in the recommendation mode.

In step S405, the processor 11 determines whether or not to end the priority DB update process. When the processes of steps S403 and S404 are completed for all the extracted S_IDs, it is determined that the priority DB update process is finished. If it is determined in step S405 that the update process of the priority DB is not finished, the process returns to step S402. In this case, processor 11 extracts another S_ID and performs similar processing. When it is determined in step S405 that the priority DB update process is finished, the processor 11 completes the process of FIG.

As described above, according to the present embodiment, training texts for pronunciation tests for pronunciation training are preferentially extracted based on the results of listening tests for listening training. Pronunciation ability and listening ability are considered to be correlated, and it is expected that the ability to listen to words or sentences that are difficult for the user to listen to can be improved by correctly pronouncing the words or sentences. Thus, in the embodiment, listening test results can be effectively used for pronunciation tests.

In addition, in the embodiment, if the user can correctly answer a listening test question that the user had difficulty with, or if the user can correctly pronounce a word or sentence that the user had difficulty listening to, the training text containing the corresponding word or sentence is , are excluded from extraction. This can prevent unnecessary tests from being carried out in the recommendation mode aimed at improving listening ability.

Here, in the embodiment, the priority DB is updated based on the results of the listening test before the pronunciation test is performed. On the other hand, the update processing of the priority DB based on the result of the listening test may be performed at the end of the listening test.

In addition, in the embodiment, the listening test, the pronunciation test, and the registration of various databases are performed in the server 10 according to the training program 141 . On the other hand, if the training program 141 is stored in the terminal 20 such as an electronic dictionary, the terminal 20 may perform the listening test and the pronunciation test. In this case, the listening DB 142 and the pronunciation DB 143 may be stored in the storage 24 of the terminal 20 or stored in the storage 14 of the server 10 .

It should be noted that the present invention is not limited to the above-described embodiments, and various modifications can be made in the implementation stage without departing from the scope of the invention. Moreover, each embodiment may be implemented in combination as much as possible, and in that case, the combined effect can be obtained. Furthermore, the above-described embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements. For example, even if some constituent elements are deleted from all the constituent elements shown in the embodiments, the problems described in the column of problems to be solved by the invention can be solved, and the effects described in the column of effects of the invention is obtained, a configuration from which this constituent element is deleted can be extracted as an invention.

The invention described in the scope of claims at the time of filing of this application will be added below.
[1] extracting a word or a sentence containing the word from a database of pronunciation problems based on the results of a listening test conducted on the user;
administering a pronunciation test to the user based on the extracted words or sentences;
Pronunciation training program for computer execution.
[2] Extracting the words or sentences containing the words preferentially extracts words that were incorrect answers or sentences containing the words that were incorrect answers in a listening test conducted for the user. The pronunciation training program according to [1], comprising causing the computer to perform:
[3] Extracting the word or a sentence containing the word includes the word having a score equal to or higher than a threshold or the score equal to or higher than a threshold as a result of a pronunciation test based on the extracted word or sentence. The pronunciation training program according to [1], including causing the computer to exclude sentences containing words from extraction targets.
[4] Extracting the word or a sentence containing the word includes extracting the word that was the correct answer or the sentence containing the word that was the correct answer as a result of another listening test based on the extracted word or the sentence. The pronunciation training program according to [1], including causing the computer to exclude from extraction targets.
[5] an extraction unit that extracts a word or a sentence containing the word from a database of pronunciation problems based on the results of a listening test conducted on the user;
a testing unit that performs a pronunciation test based on the extracted words or sentences for the user;
A terminal device comprising
[6] The terminal device according to [5], wherein the terminal device is an electronic dictionary.

1 system, 10 server, 11 processor, 12 ROM, 13 RAM, 14 storage, 15 communication device, 19 system bus, 20 terminal, 21 CPU, 22 ROM, 23 RAM, 24 storage, 25 input device, 26 display device, 27 Speaker, 28 communication device, 29 system bus, 30 network, 141 training program, 142 listening database (DB), 143 pronunciation database (DB).

Claims (6)

extracting words or sentences containing said words from a pronunciation problem database based on the results of a listening test administered to a user;
administering a pronunciation test to the user based on the extracted words or sentences;
Pronunciation training program for computer execution. Extracting the words or sentences containing the words means preferentially extracting words that were incorrect answers or sentences containing the words that were incorrect answers in a listening test conducted for the user. 2. The pronunciation training program of claim 1, comprising causing the computer to execute the program. Extracting the word or a sentence containing the word includes the word that scored above a threshold or the word that scored above a threshold as a result of a pronunciation test based on the extracted word or sentence. 2. The pronunciation training program according to claim 1, comprising causing the computer to exclude sentences from being extracted. Extracting the word or a sentence containing the word includes extracting a word that was a correct answer or a sentence containing the word that was a correct answer as a result of a re-listening test based on the extracted word or the sentence. 2. The pronunciation training program of claim 1, comprising causing the computer to exclude from. an extraction unit that extracts words or sentences containing the words from a database of pronunciation questions based on the results of a listening test conducted on the user;
a testing unit that performs a pronunciation test based on the extracted words or sentences for the user;
A terminal device comprising 6. The terminal device according to claim 5, wherein said terminal device is an electronic dictionary.

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