WO2021024987A1

WO2021024987A1 - Determination method for cognitive function, program, and determination system for cognitive function

Info

Publication number: WO2021024987A1
Application number: PCT/JP2020/029682
Authority: WO
Inventors: 祐輝小川; 満春細川; 美紗吉崎; 潤一穗積; 中島　博文
Original assignee: パナソニックＩｐマネジメント株式会社
Priority date: 2019-08-05
Filing date: 2020-08-03
Publication date: 2021-02-11
Also published as: JPWO2021024987A1; JP7479013B2

Abstract

The present disclosure addresses the problem of reducing a burden at the time of license renewal. A determination method for a cognitive function is used in rendering a service to a subject (2) in a drivers' license center (1) for performing the service of issuance and/or renewal of a driver's license. The determination method comprises voice acquisition processing, estimation processing, and reflection processing. In the voice acquisition processing, by causing the subject (2) to read out a fixed sentence, voice data related to the readout is acquired. In the estimation processing, the cognitive function of the subject (2) is estimated on the basis of the voice data acquired in the voice acquisition processing. In the reflection processing, the result of the estimation processing is reflected in a procedure for rendering the service to the subject (2) in the drivers' license center (1) or a determination as to whether the rendering of the service is permitted or not.

Description

Cognitive function judgment method, program, cognitive function judgment system

The present disclosure generally relates to a cognitive function determination method, a program, and a cognitive function determination system, and more particularly, to a cognitive function determination method, a program, and a cognitive function determination system used in connection with services at a driver's license center. ..

Patent Document 1 discloses a system for managing the progress of a cognitive function test conducted for the elderly at the time of renewal of a driver's license for automobiles and the like.

The system of Patent Document 1 is composed of an inspector device used by an inspector and a plurality of terminal devices used by an examinee.

Each of the plurality of terminal devices is a tablet type terminal device, and has a display input device provided with a touch panel on the display screen. An explanation, a caution, a question, an answer column, and the like are displayed on the display screen of the terminal device. The examinee inputs an answer, etc. by touching the display screen with a finger or a special pen, or by handwriting letters, numbers, etc. The inspector device has a display device that displays information for managing the progress of the cognitive function test.

In the system of Patent Document 1, since it takes time to carry out the cognitive function test, the burden on the examinee who takes the cognitive function test at the time of renewal of the license may increase. In addition, as the elderly population increases, the number of people who need to take a cognitive function test when renewing their license is also increasing, so if it takes a long time to carry out a cognitive function test per person, the driver's license center The burden on the driver can also increase.

Japanese Patent No. 6517987

The present disclosure has been made in view of the above reasons, and an object of the present disclosure is to provide a cognitive function determination method, a program, and a cognitive function determination system that can reduce the burden of renewing a license.

The method for determining the cognitive function according to one aspect of the present disclosure is used when providing the above-mentioned service to the target person at the driver's license center that performs at least one of the services of issuing and renewing the driver's license. The determination method includes a voice acquisition process, an estimation process, and a reflection process. In the voice acquisition process, the target person is made to read a fixed phrase and acquire voice data related to the reading. In the estimation process, the cognitive function of the subject is estimated based on the voice data acquired in the voice acquisition process. In the reflection process, the result of the estimation process is reflected in the procedure for providing the service to the target person at the driver's license center or in the determination of whether or not the service can be provided.

The program according to one aspect of the present disclosure is a program for causing one or more processors to execute the above-mentioned method for determining cognitive function.

The cognitive function determination system according to one aspect of the present disclosure is used when providing the above-mentioned services to the target person at a driver's license center that performs at least one of the services of issuing and renewing a driver's license. The determination system includes a voice acquisition unit, an estimation unit, and a reflection unit. The voice acquisition unit causes the target person to read out a fixed phrase and acquires voice data related to the reading. The estimation unit estimates the cognitive function of the subject based on the voice data acquired by the voice acquisition unit. The reflection unit reflects the estimation result of the estimation unit in the procedure for providing the service to the target person at the driver's license center or in determining whether or not the service can be provided.

FIG. 1 is a block diagram showing a configuration of a determination system for executing the determination method of the cognitive function of one embodiment. FIG. 2 is a schematic diagram schematically showing the same determination system. FIG. 3 is a flowchart showing an example of the same determination method.

(1) Overview Currently, in Japan, drivers over the age of 75 are obliged to take a cognitive function test when renewing their driver's license. Currently, this cognitive function test is mainly carried out by the examinee writing the answer on the test sheet for the question given by the instructor. However, in such a method, there is a possibility that the burden on the side performing the inspection will increase in order to secure the inspection venue and the instructor, score the answer contents, and the like. In addition, the examination itself takes time, and it is necessary to go to the examination site at the designated time, which may impose a burden on the examinee side. The cognitive function determination method (hereinafter, also simply referred to as “determination method”) and the cognitive function determination system 10 (hereinafter, also simply referred to as “determination system 10”) of the present embodiment are, for example, such a cognitive function test. It is assumed that it will be used as an alternative to the above, or as a primary screening for narrowing down the candidates for cognitive function tests.

For example, a driver who is obliged to perform a cognitive function test when renewing his driver's license (hereinafter, also referred to as "target person 2") receives a notice of renewal of his driver's license by mail, etc., at the driver's license center 1. Before renewing the license, take a test according to the method for determining cognitive function of the present embodiment. This test result is used as a substitute for the above-mentioned cognitive function test when the subject 2 renews the driver's license at the driver's license center 1, or to narrow down the examinees who need to take the above-mentioned cognitive function test. Can be used for. This makes it possible to reduce the burden of renewing the license.

First, an outline of the cognitive function determination method (hereinafter, also simply referred to as “determination method”) of the present embodiment and the cognitive function determination system 10 will be described.

As described above, the determination method of the present embodiment is used when providing services to the target person 2 at the driver's license center 1 (see FIG. 2). The Driver's License Center 1 is a facility or place where at least one of the new issuance (hereinafter, also referred to as "issuance") and renewal of a driver's license (hereinafter, also simply referred to as "driver's license") is performed. Means.

The driver's license center 1 in the present embodiment may perform at least one of the services of issuing and renewing the driver's license, and is a driver's license examination center, a traffic safety (education) center, a general traffic center, and a driver's (person) education center. , Driver training center, license center, safe driving school, test center, (license) renewal center, etc. may be included. Further, the driver's license center 1 in the present embodiment may include a police station as a facility that performs the service of renewing the driver's license. The Driver's License Center 1 may further perform other services such as reissuing a driver's license.

As shown in FIG. 3, the determination method of the present embodiment includes the voice acquisition process S6, the estimation process S9, and the reflection process S12.

The voice acquisition process S6 includes having the target person 2 read out a fixed phrase and acquire voice data related to the reading out. The estimation process S9 includes estimating the cognitive function of the subject 2 based on the voice data acquired in the voice acquisition process S6. The reflection process S12 includes reflecting the result of the estimation process S9 in the procedure for providing the service to the target person 2 at the driver's license center 1 or in determining whether or not the service can be provided.

The determination system 10 (see FIG. 1) is an aspect that embodies the determination method of the present embodiment. That is, the determination system 10 is used when providing services to the target person 2 at the driver's license center 1 which performs at least one of the services of issuing and renewing the driver's license. The determination system 10 includes a voice acquisition unit F5 for executing the voice acquisition process S6, an estimation unit F7 for executing the estimation process S9, and a reflection unit F13 for executing the reflection process S12. ..

In the determination method and determination system 10 of the present embodiment, the estimation of the cognitive function of the subject 2 to be reflected in the procedure for issuing or renewing the driver's license to the subject 2 or the determination of the propriety is performed. This is done based on the voice data indicating the voice when the subject 2 reads out the fixed phrase. Therefore, compared to, for example, an inspection method in which an answer is entered on a test sheet and scored, the time and effort required for the cognitive function examination can be shortened, and the target person 2 and the driver's license center 1 can be notified when the license is renewed. It is possible to reduce such a burden. In short, according to the determination method and the determination system 10 of the present embodiment, it is possible to reduce the burden at the time of license renewal. Further, even when the cognitive function test is performed at the time of issuing the driver's license, the burden at the time of issuing the license can be reduced by using the cognitive function determination method and the determination system 10 of the present embodiment.

(2) Details Hereinafter, the determination method of the present embodiment and the details of the determination system 10 will be described with reference to FIGS. 1 to 3.

(2.1) Overall Configuration FIGS. 1 and 2 show the configuration of the determination system 10 for executing the determination method of the present embodiment.

As shown in FIG. 1, the determination system 10 includes a first server 4 and a second server 5. The determination system 10 can communicate with the communication device 3 possessed by the target person 2.

Here, the communication device 3 is assumed to be a device that can be carried by the target person 2. Further, it is assumed that the first server 4 is installed in the facility of an organization (company or the like) that provides at least a part of the determination method of the present embodiment as a service. Further, it is assumed that the second server 5 is installed in the driver's license center 1 or the facility of the organization having jurisdiction over the driver's license center 1. However, this embodiment is not limited to such an arrangement.

The call device 3 is a device for converting the voice of the target person 2 into voice data and transmitting the voice data obtained by the conversion to another device. Further, the communication device 3 is configured to convert voice data transmitted from another device into voice and output the voice data. As an example, the communication device 3 is a mobile terminal, a mobile phone, or a personal computer possessed by the subject 2. The mobile terminal is, for example, a smartphone, a tablet terminal, or the like. Here, it is assumed that the communication device 3 is a smartphone. Therefore, in the following, the communication of the communication device 3 with another device (first server 4) is also referred to as "making a call".

As shown in FIG. 1, the communication device 3 includes a communication unit 31 and a communication unit 32. Further, the communication device 3 of the present embodiment further includes a display unit 33, an operation unit 34, and a processing unit 35.

The communication unit 31 is a communication interface. In particular, the communication unit 31 is a communication interface that can be connected to the telecommunication line NT1 and has a function of performing communication through the telecommunication line NT1. As a result, the communication device 3 can communicate with the first server 4 through the telecommunication line NT1 (see FIG. 2).

The telecommunications line NT1 may include, for example, a mobile communication network, a PSTN (public switched telephone network), the Internet, and the like. The telecommunication line NT1 may be composed of not only a network compliant with a single communication protocol but also a plurality of networks compliant with different communication protocols. The communication protocol can be selected from a variety of well-known wired and wireless communication standards. Although simplified in FIG. 2, the telecommunications line NT1 may include data communication equipment such as repeater hubs, switching hubs, bridges, gateways, routers and the like.

The communication unit 31 transmits a signal to the first server 4 via the telecommunication line NT1. The signal transmitted by the communication unit 31 to the first server 4 includes, for example, voice data (voice signal) indicating the voice of the target person 2 acquired by the communication unit 32. In addition, the signal transmitted by the communication unit 31 to the first server 4 includes, for example, an operation signal output in response to the operation input of the target person 2 to the operation unit 34.

The communication unit 31 receives the signal from the first server 4 via the telecommunication line NT1. The signal received by the communication unit 31 from the first server 4 is, for example, voice data (voice signal) that the first server 4 automatically transmits in response to a request from the communication device 3 (hereinafter, also referred to as "automatic voice signal"). There is. In addition, the signal received by the communication unit 31 from the first server 4 includes, for example, an estimation result signal indicating an estimation result of the cognitive function by the estimation unit F7.

The telephone unit 32 includes a speaker and a microphone. The microphone converts the sound including the voice emitted by the subject 2 into voice data (voice signal) and outputs the sound to the outside via the communication unit 31. The speaker converts voice data (voice signal) input from the outside via the communication unit 31 into voice (sound) and outputs it.

The display unit 33 displays using the data or the like received by the communication unit 31. The display unit 33 includes, for example, an LCD (Liquid Crystal Display) or an organic EL display.

The operation unit 34 receives the operation input from the target person 2 and outputs a signal corresponding to the received operation. In the present embodiment, since the communication device 3 is a general-purpose smartphone, the display unit 33 and the operation unit 34 are integrated, for example, like a touch panel display. In the touch panel display, the call device 3 has a button or the like when an operation (tap, swipe, drag, etc.) of an object such as a button on each screen displayed on the display unit 33 is detected by the operation unit 34. Judge that the object has been manipulated. That is, the display unit 33 and the operation unit 34 function as a user interface that receives operation input from the target person 2 in addition to various displays.

The processing unit 35 is configured to control the overall control of the communication device 3, that is, the operation of the communication unit 31, the communication unit 32, the display unit 33, and the operation unit 34. The processing unit 35 can be realized, for example, by a computer system including one or more processors (microprocessors) and one or more memories. That is, one or more processors execute one or more programs (applications) stored in one or more memories, thereby functioning as the processing unit 35. Although the program is recorded in advance in the memory of the processing unit 35 here, the program may be provided by being recorded in a non-temporary recording medium such as a memory card or through a telecommunication line such as the Internet.

The communication device 3 may include a biometric information acquisition unit for acquiring the biometric information of the target person 2. The biological information acquisition unit may have, for example, a fingerprint acquisition unit that acquires fingerprint information of the subject 2. The biological information acquisition unit may have, for example, a face information acquisition unit that acquires face information of the subject 2. The fingerprint acquisition unit and / or the face information acquisition unit may be, for example, an imaging unit (camera) provided in the communication device 3. In addition, the biological information acquisition unit may have a vein information acquisition unit that acquires the vein information of the subject 2.

As shown in FIG. 1, the first server 4 includes a communication unit 41, a storage unit 42, and a processing unit 43.

The first server 4 constitutes the main body of the determination system 10 that executes the determination method of the present embodiment. The first server 4 has "target person identification process S2", "attribute acquisition process S3", "identity verification process S4", "presentation process S5", and "voice acquisition process" among the processes of the determination method (see FIG. 3). "S6", "recording process S7", "feature amount acquisition process S8", "estimation process (cognitive function estimation process) S9", and "output process S10" are executed.

The communication unit 41 is a communication interface. The communication unit 41 is a communication interface that can be connected to the telecommunication line NT1 and has a function of performing communication through the telecommunication line NT1. The first server 4 can communicate with the communication device 3 through the telecommunication line NT1. Further, the first server 4 can communicate with the second server 5 through the telecommunication line NT1. The communication protocol for the communication unit 41 to communicate with the communication device 3 may be the same as or different from the communication protocol for the communication unit 41 to communicate with the second server 5.

The communication unit 41 transmits a signal to the communication device 3 via the telecommunication line NT1. The signals transmitted by the communication unit 41 to the communication device 3 include the above-mentioned automatic voice signal, estimation result signal, and the like. Further, the communication unit 41 receives the signal from the communication device 3 via the telecommunication line NT1. The signals received by the communication unit 41 from the communication device 3 include the above-mentioned voice signals, operation signals, and the like.

The communication unit 41 transmits a signal to the second server 5 via the telecommunication line NT1. The signal transmitted by the communication unit 41 to the second server 5 includes, for example, a request signal that requests identity verification information used for verifying the identity of the target person 2. In addition, the signal transmitted by the communication unit 41 to the second server 5 includes an estimation result signal indicating an estimation result of the cognitive function by the estimation unit F7.

The communication unit 41 receives the signal from the second server 5 via the telecommunication line NT1. The signal received from the second server 5 by the communication unit 41 includes, for example, a signal indicating identity verification information transmitted from the second server 5 in response to a request signal.

The storage unit 42 is a device for storing information. The storage unit 42 may include a ROM (Read Only Memory), a RAM (Random Access Memory), an EEPROM, and the like. The storage unit 42 stores voice data of automatic voice that is automatically transmitted in response to a request (call by telephone) from the calling device 3. Further, the learned model (described later) is stored in the storage unit 42. Further, the storage unit 42 has an area for storing the voice data (voice signal) of the target person 2 transmitted from the communication device 3.

The processing unit 43 can be realized by, for example, a computer system including one or more processors (microprocessors) and one or more memories. That is, one or more processors execute one or more programs (applications) stored in one or more memories, thereby functioning as the processing unit 43.

The processing unit 43 is configured to control the overall control of the first server 4, that is, the operations of the communication unit 41 and the storage unit 42. Further, as shown in FIG. 1, the processing unit 43 estimates that the target person identification unit F1, the attribute acquisition unit F2, the identity verification unit F3, the presentation unit F4, the voice acquisition unit F5, and the recording unit F6. A unit F7 and an output unit F8 are provided. The target person identification unit F1, the attribute acquisition unit F2, the identity verification unit F3, the presentation unit F4, the voice acquisition unit F5, the recording unit F6, the estimation unit F7, and the output unit F8 do not show a substantive configuration. It shows the function realized by the processing unit 43.

The target person identification unit F1 identifies the target person 2 who is talking on the call device 3. In the present embodiment, the target person identification unit F1 identifies the target person 2 in cooperation with the response unit F11 (described later) of the second server 5.

When the target person identification unit F1 receives a request (call by telephone) from the communication device 3, for example, the target person identification unit F1 transmits the voice data (automatic voice signal) of the automatic voice stored in the storage unit 42 via the communication unit 41. Is transmitted to the communication device 3.

The automatic voice transmitted by the target person identification unit F1 may include a content prompting the input of the target person information for identifying the target person 2. The target person information may include, for example, the license number of the target person 2. Alternatively, the target person information may include the name, address, and the like of the target person 2.

Note that the target person information may be the telephone number of the calling device 3, and in this case, the target person 2 does not need to further input the target person information.

The target person identification unit F1 receives the target person information input from the target person 2 to the call device 3 for the automatic voice from the call device 3, and identifies the target person 2 based on the received target person information. The target person 2 is specified by the target person identification unit F1, for example, by comparing the received target person information with the personal information stored in the predetermined information database DB1. In the present embodiment, the information database DB 1 including the personal information is stored in the storage unit 52 of the second server 5.

The target person identification unit F1 transmits the target person information to the second server 5, and receives the comparison result between the target person information and the information database DB1 from the second server 5. The control result includes information indicating the subject 2 identified by the second server 5. As a result, the target person identification unit F1 identifies the target person 2. The target person identification unit F1 itself (that is, the processing unit 43 of the first server 4) may specify the target person 2 by comparing the target person information with the personal information. For example, the target person identification unit F1 receives a part or all of the information of the information database DB1 from the second server 5, and compares the received information of the information database DB1 with the target person information to obtain the target person 2. You may specify.

That is, the determination method of the present embodiment includes the target person identification process S2 for specifying the target person 2.

When the communication device 3 has a biometric information acquisition unit such as a fingerprint acquisition unit, the target person information may include biometric information such as the fingerprint of the target person 2. Alternatively, the subject information may include voiceprint information obtained from the voice of the subject 2 as the biological information of the subject 2. In this case, the target person identification process S2 may be performed using the biological information (fingerprint, voiceprint, etc.) of the target person 2.

The attribute acquisition unit F2 acquires the attribute data related to the attributes of the target person 2 specified by the target person identification unit F1. The attributes of the subject 2 include, for example, race, gender, age (age), educational history, and the like. The attribute data is stored, for example, in the above-mentioned information database DB1 in association with the personal information. The attribute acquisition unit F2 acquires the attribute data of the target person 2 from the second server 5 via the communication unit 41.

That is, the determination method of the present embodiment includes the attribute acquisition process S3 for acquiring the attribute data related to the attributes of the target person 2.

The identity verification unit F3 confirms that the person who is actually talking on the call device 3 is the two target persons specified by the target person identification unit F1. That is, since there is a possibility that the person talking on the calling device 3 mistakenly inputs the target person information (license number, etc.) of another person who is not his / her own, the identity verification unit F3 is making a call. Confirm that the person is the two subjects. When the target person 2 is identified by the target person identification unit F1, the identity verification unit F3 transmits a request signal to the second server 5 via the communication unit 41, and the second server 5 sends the request signal as a response to the request signal. (Control information) is acquired. The identity verification information is, for example, voice data obtained by pre-recording the voice of the subject 2 (hereinafter referred to as “control voice data”). By comparing the voice data obtained from the call device 3 with the control voice data, the identity verification unit F3 determines that the voice speaker (the person who is talking) indicated by the voice data is the two target persons. Check. For example, the identity verification unit F3 confirms the identity by comparing the voiceprints of the voices indicated by the voice data and determining the degree of matching.

That is, the determination method of the present embodiment includes the identity verification process S4 for confirming that the subject 2 is the principal. The identity verification process S4 is performed using the biological information of the subject 2, and more specifically, the voiceprint of the subject 2.

The identity verification process S4 may be performed at an arbitrary timing, for example, when voice data is received from the calling device 3. For example, the identity verification process S4 may be performed in parallel with the target person identification process S2. That is, the target person 2 is specified by using the biological information (voiceprint information) of the target person 2 in the target person identification process S2, and the biological information (voiceprint information) of the target person 2 is used in the identity verification process S4. In the case of the configuration in which the identity verification is performed, the identity verification process S4 can be performed in parallel with the target person identification process S2. Further, the identity verification process S4 may be performed at any time using the voice data acquired by the voice acquisition process S6 during and after the execution of the determination method.

The identity verification process S4 may be performed using information other than voice data. For example, the identity verification process S4 may be performed using biometric information other than the voiceprint such as the fingerprint of the subject 2, or may be performed using information other than the biometric information such as the driver's license number. Further, the identity verification process S4 may be performed using the same information as the target person identification process S2.

After the target person 2 is identified by the target person identification unit F1, the presentation unit F4 transmits the voice data (automatic voice signal) of the automatic voice stored in the storage unit 42 to the communication device 3 via the communication unit 41. ..

The automatic voice transmitted by the presentation unit F4 includes an instruction content that prompts the target person 2 to read a fixed phrase. The instruction content may include, for example, a fixed phrase to be read aloud to the subject 2 and a sound (for example, a “pi” sound) indicating the start point and the end point of the period in which the fixed phrase should be read aloud.

The instruction content may include a plurality of different fixed phrases. For example, the instruction content may include content for sequentially reading out six types of fixed phrases. The fixed phrase may include, for example, five or more characters consisting of a closed consonant and a subsequent vowel. As an example of a fixed phrase, there is a sentence such as "Kitakara Kita Tataki".

Further, the instruction content may include a content instructing the reading of the same fixed phrase a plurality of times. In this case, the instruction content may include the number of times the fixed phrase should be read aloud.

That is, the determination method of the present embodiment includes the presentation process S5 that presents the information prompting the reading of the fixed phrase to the target person 2. In addition, the presentation process S5 includes reproducing an automatic voice prompting the target person 2 to read a fixed phrase.

The voice acquisition unit F5 transmits the voice data transmitted from the call device 3 via the communication unit 41, which is data indicating the voice emitted from the target person 2 in response to the automatic voice transmitted by the presentation unit F4. get. That is, the determination method of the present embodiment includes the voice acquisition process S6 in which the target person 2 reads out a fixed phrase and acquires the voice data related to the reading. In the voice acquisition process S6, voice data is acquired through the telecommunication line NT1.

The recording unit F6 causes the storage unit 42 to record (record) the voice data acquired by the voice acquisition unit F5. That is, the determination method of the present embodiment includes the recording process S7 for recording the voice data acquired in the voice acquisition process S6.

The estimation unit F7 estimates the cognitive function of the subject 2 by processing the voice data (voice data acquired by the voice acquisition unit F5) recorded in the storage unit 42. That is, the determination method of the present embodiment includes an estimation process S9 that estimates the cognitive function of the subject 2 based on the voice data acquired in the voice acquisition process S6.

The estimation unit F7 estimates the cognitive function of the subject 2 by using, for example, the feature amount extracted from the voice data. That is, the determination method of the present embodiment includes the feature amount acquisition process S8 for extracting the feature amount from the voice data. Further, the estimation process S9 executed by the estimation unit F7 includes estimating the cognitive function using the feature amount extracted from the voice data.

In the determination system 10 of the present embodiment, the estimation unit F7 further uses the attribute data acquired by the attribute acquisition unit F2 to estimate the cognitive function. That is, the estimation process S9 executed by the estimation unit F7 includes estimating the cognitive function by further using the attribute data related to the attributes of the subject 2 in addition to the voice data.

In the determination system 10 of the present embodiment, the estimation unit F7 estimates the cognitive function of the subject 2 by using the learned model M1. In the determination system 10 of the present embodiment, the trained model M1 is, for example, a logistic regression model. That is, in the estimation process S9 executed by the estimation unit F7, the cognitive function of the subject 2 is estimated using the learned model M1 generated by machine learning.

The trained model M1 is designed to output a value indicating the degree of cognitive function of the subject 2 with respect to a given input (feature amount). The estimation unit F7 gives the feature amount obtained from the voice data to the trained model M1, and estimates the degree of the cognitive function of the subject 2 based on the value obtained from the trained model M1. Such a trained model M1 can be generated by supervised learning using learning data (data set) that defines the relationship between a value indicating the degree of cognitive function and a feature amount. The trained model M1 is stored in the storage unit 42.

In the present embodiment, the feature amount used in the estimation process S9 may include an amount related to the first formant frequency or the second formant frequency of the vowel in the syllable included in the voice of the subject 2 indicated by the voice data.

Here, the first formant frequency is the frequency corresponding to the lowest frequency peak among the frequency peaks included in the voice emitted from a person. The second formant frequency is a frequency corresponding to the second lowest frequency peak among the frequency peaks included in the voice emitted from a person.

In one example, the quantity is the first formant frequency, the second formant frequency, or the second formant frequency relative to the first formant frequency of a plurality of vowels in a plurality of vowels included in the voice of the subject 2 represented by voice data. It can include variations in ratio. The variability is, for example, the standard deviation.

In one example, the above amount may include a change in the first formant frequency or the second formant frequency of a plurality of vowels in a plurality of syllables included in the voice of the subject 2 indicated by voice data.

In one example, the amount may include the time required to change the first formant frequency or the second formant frequency of a plurality of vowels in a plurality of syllables included in the voice of the subject 2 indicated by voice data.

In one example, the above amount is the rate of change, which is the ratio of the amount of change of the first formant frequency or the second formant frequency of a plurality of vowels in a plurality of syllables included in the voice of the subject 2 represented by the voice data to the required time. May include.

In one example, the quantity is the first formant of a plurality of vowels in a plurality of vowels included in the voice of the subject 2 represented by voice data in a coordinate space formed by a second formant frequency relative to the first formant frequency of the vowel. It may include the positional relationship between the plotted points, or the shape or area of the polygon formed by those points, when plotting the value of the second formant frequency with respect to the frequency.

Further, the feature amount used in the estimation process S9 includes the sound pressure difference between the sound pressure of the consonant in the open syllable included in the voice of the subject 2 indicated by the voice data and the sound pressure of the vowel following the consonant. obtain.

The feature amount used in the estimation process S9 is the difference in sound pressure between the sound pressure of a consonant and the sound pressure of a vowel following the consonant in a plurality of open syllables included in the voice of the subject 2 indicated by voice data. , May include variability.

The feature amount used in the estimation process S9 may include the total time required for the subject 2 to read aloud the fixed phrase.

The feature amount used in the estimation process S9 may include the amount of change in the time required for each of the multiple readings of the same fixed phrase when the same fixed phrase is read a plurality of times.

Please refer to Japanese Patent No. 6337362 for the amount of voice features of subject 2 that can be used for the examination of cognitive function using the determination method of the present embodiment.

Further, the feature amount used in the estimation process S9 may include the attribute of the target person 2 acquired by the attribute acquisition unit F2.

The estimation unit F7 outputs the estimation result of the cognitive function of the subject 2. The estimation result is indicated by, for example, a numerical value indicating the degree of cognitive function of the subject 2. The estimation unit F7 may output, for example, a numerical value (for example, the second stage out of the five stages) indicating which stage of the plurality of predetermined stages the estimated degree of cognitive function belongs to.

The output unit F8 outputs an estimation result signal indicating result information based on the estimation result of the estimation unit F7 to the communication device 3 and the second server 5 via the communication unit 41. The result information output by the output unit F8 may be the estimation result (for example, a numerical value) output from the estimation unit F7 itself, or may be in another form. The result information output by the output unit F8 is, for example, information indicating the next action to be taken by the subject 2 based on the estimation result (for example, information prompting the patient to undergo a cognitive function test by a doctor at a hospital), precautions ( Information that promotes improvement of cognitive function) or the like. When the calling device 3 receives the estimation result signal from the first server 4, the calling device 3 may notify the target person 2 by outputting the estimation result by voice by the calling unit 32 or displaying it as an image by the display unit 33. Good.

As shown in FIG. 1, the second server 5 includes a communication unit 51, a storage unit 52, and a processing unit 53. As shown in FIG. 2, the second server 5 is installed in, for example, the driver's license center 1.

The second server 5 executes the "recording process S11" and the "reflection process S12" among the processes of the determination method (see FIG. 3).

The communication unit 51 is a communication interface. The communication unit 51 is a communication interface that can be connected to the telecommunication line NT1 and has a function of performing communication through the telecommunication line NT1. The second server 5 can communicate with the first server 4 through the telecommunication line NT1.

The communication unit 51 transmits a signal to the first server 4 via the telecommunication line NT1. The signal transmitted by the communication unit 51 to the first server 4 includes, for example, the above-mentioned signal indicating the identity verification information. Further, the communication unit 51 receives the signal from the first server 4 via the telecommunication line NT1. The signals received by the communication unit 51 from the first server 4 include, for example, the above-mentioned request signal, estimation result signal, and the like.

The storage unit 52 is a device for storing information. The storage unit 52 may include a ROM, RAM, EEPROM, and the like. The above-mentioned information database DB1 is stored in the storage unit 52.

The processing unit 53 can be realized by, for example, a computer system including one or more processors (microprocessors) and one or more memories. That is, one or more processors execute one or more programs (applications) stored in one or more memories, thereby functioning as the processing unit 53.

The processing unit 53 is configured to control the overall control of the second server 5, that is, the operations of the communication unit 51 and the storage unit 52. Further, as shown in FIG. 1, the processing unit 53 includes a response unit F11, a registration unit F12, and a reflection unit F13. The response unit F11, the registration unit F12, and the reflection unit F13 do not show a substantive configuration, but show a function realized by the processing unit 53.

The response unit F11 makes a predetermined response according to the signal transmitted from the first server 4.

For example, the response unit F11 identifies the target person 2 indicated by the target person information according to the signal indicating the target person information transmitted from the first server 4. The response unit F11 identifies the target person 2 by, for example, comparing the received target person information with the information database DB1. The response unit F11 transmits information indicating the control result (identified subject 2) to the first server 4. That is, the response unit F11 collaborates with the target person identification unit F1 of the first server 4 to specify the target person 2. At this time, the response unit F11 also transmits the attribute data related to the attributes of the specified target person 2.

Further, the response unit F11 responds to the request signal transmitted from the first server 4 and transmits the identity verification information. As described above, the identity verification information is control voice data which is voice data obtained by pre-recording the voice of the subject 2. The control voice data may be recorded, for example, when a driver's license is issued (newly issued) to the target person 2, may be recorded when a past driver's license is renewed, or the driver's license may be recorded. It may be recorded regardless of the delivery or update of.

When the registration unit F12 receives the estimation result signal from the first server 4, the registration unit F12 registers the estimation result of the cognitive function of the subject 2 indicated by the estimation result signal in the information database DB1. The information of the estimation result is registered in the information database DB1 in association with the personal information of the corresponding target person 2. When the information of the estimation result is already registered in the information database DB1, the registration unit F12 may rewrite (update) the already registered information with new information, or leave the already registered information. You may add new information while doing so.

It is preferable that an expiration date is set for the estimation result of the cognitive function of the subject 2 registered in the information database DB1. The expiration date is not particularly limited, but may be, for example, one year, half a year, three months, one month, half a month, one week, or the like.

The reflection unit F13 has a cognitive function of the subject 2 registered in the information database DB1 for the procedure of issuing or renewing the driver's license to the subject 2 at the driver's license center 1 and determining whether or not the license can be issued or renewed. Reflect the estimation result of.

The reflection unit F13 makes the procedure for the subject 2 to renew the driver's license at the driver's license center 1 different depending on, for example, the degree of the estimation result of the cognitive function. For example, when the cognitive function of the subject 2 is deteriorated (for example, when the numerical value indicating the degree of the cognitive function is the worst stage among the five stages), the reflection unit F13 has the driver's license of the subject 2. A doctor may be required to perform a cognitive function test when renewing the license. On the other hand, when there is no problem in the cognitive function of the subject 2 (for example, when the numerical value indicating the degree of the cognitive function is the best stage among the five stages), the reflection unit F13 indicates that the subject 2 has a driver's license. You may omit the cognitive function test when you go to the Driver's License Center 1 to renew your driver's license.

The specific means by which the reflection unit F13 reflects the estimation result is not particularly limited. For example, the reflection unit F13 may notify the staff of the driver's license center 1 of information indicating whether or not it is necessary for the doctor to carry out a cognitive function test for each subject 2. For example, the reflection unit F13 may cause the display device connected to the second server 5 to display for each subject 2 whether or not it is necessary to carry out a cognitive function test by a doctor. The staff of the Driver's License Center 1 shall refer to this information on the display device to determine whether or not it is necessary to carry out a cognitive function test when renewing the driver's license of each subject 2. Is possible.

In the information database DB1, when a plurality of cognitive function estimation results are linked to the personal information of a certain subject 2, the reflection unit F13 may reflect only the latest estimation results, which is effective. Multiple estimation results within the deadline may be reflected.

(2.2) Operation Next, the determination method of the present embodiment will be briefly described with reference to FIG.

The subject 2, who is obliged to take a cognitive function test when renewing his driver's license, uses the telephone device 3 at home, for example, before going to the driver's license center 1 to renew his driver's license. 1 Call the server 4 by telephone (call processing S1).

When the first server 4 receives a call by the telephone device 3, the first server 4 transmits an automatic voice prompting the input of the target person information for identifying the target person 2 to the call device 3. The target person 2 responds to the automatic voice and inputs the target person information such as the driver's license number via the communication device 3, and the first server 4 acquires the target person information via the telecommunication line NT1. .. The first server 4 transmits the acquired target person information to the second server 5, and the second server 5 identifies the target person 2 by comparing the received target person information with the information database DB1. The second server 5 transmits information indicating the identified target person 2 to the first server 4, and the first server 4 identifies the target person 2 by receiving this information from the second server 5 (target). Person identification process S2). Further, the second server 5 transmits the attribute data indicating the attributes of the specified target person 2 to the first server 4, and the first server 4 acquires the attribute data of the target person 2 (attribute acquisition process S3).

When the target person 2 is specified, the first server 4 sends a request signal to the second server 5 and acquires the identity verification information from the second server 5. The first server 4 confirms that the caller of the calling device 3 is the two target persons by using the identity verification information during the call with the target person 2 after the identification of the target person 2 (identity verification process). S4).

Further, when the target person 2 is specified (and it is confirmed that the caller is the two target persons), the first server 4 transmits an automatic voice prompting the reading of the fixed phrase to the call device 3 (presentation process). S5). Further, the first server 4 acquires the voice data when the target person 2 reads out the fixed phrase from the call device 3 (voice acquisition process S6), and records (records) the acquired voice data in the storage unit 42 (recording). Recording process S7). The first server 4 extracts (acquires) a feature amount from the recorded voice data (feature amount acquisition process S8).

The first server 4 estimates the cognitive function of the target person 2 by using the feature amount acquired in the feature amount acquisition process S8 and the attribute data acquired in the attribute acquisition process S3 (cognitive function estimation process (estimation process) S9). ). The first server 4 outputs the estimation result of the cognitive function obtained in the estimation process S9 to the communication device 3 and the second server 5 (output process S10).

The call device 3 notifies the target person 2 of the estimation result of the cognitive function obtained from the first server 4 via the call unit 32 or the display unit 33.

The second server 5 records the estimation result of the cognitive function obtained from the first server 4 in the storage unit 52 (recording process S11). Then, the second server 5 reflects the estimation result of the cognitive function of the target person 2 in the procedure of issuing or renewing the driver's license to the target person 2 or in the determination of whether or not the issuance or renewal is possible (reflection process S12). ..

After that, when the subject 2 goes to the driver's license center 1 to renew the driver's license, the subject 2 follows the procedure that reflects the estimation result of the cognitive function by the judgment method and the driver's license. Can be updated. Alternatively, if the estimated result of cognitive function indicates that it is not suitable for renewal of the driver's license, the staff of the driver's license center 1 informs the subject 2 to that effect and conducts a cognitive function test by a doctor. The subject 2 may be urged to take the test.

(2.3) Advantages As described above, according to the cognitive function determination method and determination system 10 of the present embodiment, the subject 2 is made to read a fixed phrase and the voice data of the read voice is processed. , The cognitive function of subject 2 is being examined. The time required to execute this inspection (read out and process the fixed phrase) is about 3 minutes even when the subject 2 reads out 6 types of fixed phrases, for example. On the other hand, for example, in the conventional inspection method in which an answer is written on a test sheet and the answer is scored, it takes at least about 30 minutes including the answer time and the scoring time. Therefore, by using the determination method and the determination system 10 of the present embodiment, it is possible to shorten the time required for the inspection as compared with the conventional inspection method.

Further, the subject 2 can take the inspection by the determination method and the determination system 10 of the cognitive function of the present embodiment as long as he / she possesses at least the communication device 3. Therefore, the subject 2 can be inspected at any place, and there is no need to go to the inspection site and undergo the inspection unlike the conventional inspection method. Therefore, according to the determination method and the determination system 10 of the present embodiment, it is possible to reduce the burden on the subject 2 as compared with the conventional inspection method.

In short, according to the cognitive function determination method and determination system 10 of the present embodiment, it is possible to reduce the burden at the time of license renewal.

Further, not only when the driver's license is renewed, but also when the cognitive function test is performed at the time of issuing the driver's license, by using the cognitive function determination method and the determination system 10 of the present embodiment, the burden at the time of issuing the license is borne. It is possible to reduce the amount.

(3) Modified Example The embodiment of the present disclosure is not limited to the above embodiment. The above-described embodiment can be changed in various ways depending on the design and the like as long as the object of the present disclosure can be achieved. Further, the same function as the cognitive function determination method according to the above embodiment may be embodied in a computer program, a non-temporary recording medium on which the computer program is recorded, or the like.

The (computer) program according to one aspect is a program for causing one or more processors to execute the determination method of the above-described embodiment.

Hereinafter, modified examples of the above-described embodiment are listed. The modifications described below can be applied in combination as appropriate.

The cognitive function determination system 10 in the present disclosure includes a computer system in, for example, a communication device 3, a first server 4, a second server 5, and the like. The main configuration of a computer system is a processor and memory as hardware. When the processor executes the program recorded in the memory of the computer system, the functions as the communication device 3, the first server 4, and the second server 5 are realized. The program may be pre-recorded in the memory of the computer system, may be provided through a telecommunications line, and may be recorded on a non-temporary recording medium such as a memory card, optical disk, hard disk drive, etc. that can be read by the computer system. May be provided. A processor in a computer system is composed of one or more electronic circuits including a semiconductor integrated circuit (IC) or a large scale integrated circuit (LSI). The integrated circuit such as an IC or LSI referred to here has a different name depending on the degree of integration, and includes an integrated circuit called a system LSI, VLSI (Very Large Scale Integration), or ULSI (Ultra Large Scale Integration). Further, an FPGA (Field-Programmable Gate Array) programmed after the LSI is manufactured, or a logical device capable of reconfiguring the junction relationship inside the LSI or reconfiguring the circuit partition inside the LSI should also be adopted as a processor. Can be done. A plurality of electronic circuits may be integrated on one chip, or may be distributed on a plurality of chips. The plurality of chips may be integrated in one device, or may be distributed in a plurality of devices. The computer system referred to here includes a microcontroller having one or more processors and one or more memories. Therefore, the microcontroller is also composed of one or more electronic circuits including a semiconductor integrated circuit or a large-scale integrated circuit.

Further, it is not an essential configuration for the determination system 10 that a plurality of functions in each of the first server 4 and the second server 5 are integrated in one housing, and the first server 4 and the second server 5 have different functions. Each component may be distributed in a plurality of housings. Further, at least a part of the functions of the determination system 10, for example, a part of the functions of the first server 4 and the second server 5 may be realized by the cloud (cloud computing) or the like.

On the contrary, in the above-described embodiment, at least a part of the functions of the determination system 10 distributed in a plurality of devices may be integrated in one housing. For example, some functions of the determination system 10 distributed in the first server 4 and the second server 5 may be integrated in one housing.

In one modification, in the presentation process S5, information prompting the target person 2 to read a fixed phrase may be visually given. For example, in the presentation process S5, a sentence, an image, a video, or the like that prompts the target person 2 to read a fixed phrase may be displayed on the display unit 33 of the call device 3.

In one modification, the content (content of automatic voice, sentence, image, etc.) presented in the presentation process S5 may include a question whose answer is uniquely determined. The question may be related to a driver's license. Examples of questions include, for example, a question that asks the display unit 33 to answer the color of the stop sign, a question that causes the display unit 33 to display an image of the speedometer and answers the speed indicated by the meter, and a display unit 33 that displays an image of the number plate. There are questions that ask you to answer the place name, number, etc. The image displayed on the display unit 33 may be a moving image, for example, an image whose size gradually changes (gradually increases). Further, even if the display unit 33 temporarily displays the image and stores the content in the target person 2, the image is hidden and a question about the content shown in the image is presented to the target person 2. Good. That is, in the presentation process S5, a question related to the driver's license may be presented to the subject 2, and this question may prompt the subject 2 to read a fixed phrase as an answer to the question.

In one modification, the content presented in the presentation process S5 may further include a question whose answer is not uniquely determined. As an example of the question, for example, there is a question to answer the name, age, educational history, etc. of the subject 2.

In one modification, the feature amount used in the estimation process S9 may further include information regarding the operation input of the target person 2 to the communication device 3 (for example, the operation speed for the touch panel). That is, the determination method may further include an operation acceptance process for receiving an operation input from the target person 2 to the communication device 3. In the estimation process S9, the cognitive function of the subject 2 may be estimated by further using the result of the operation input in addition to the voice data acquired in the voice acquisition process S6.

In one modification, the information database DB1 including the personal information may be recorded in the storage unit 42 of the first server 4. In this case, the target person identification process S2, the attribute acquisition process S3, and the identity verification process S4 can be executed only by the first server 4.

In one modification, in the attribute acquisition process S3, the target person 2 may be made to input the attribute data using the communication device 3.

In one modification, it is not necessary to use the attribute data of the target person 2 as a feature amount in the estimation process S9.

In one modification, the communication device 3 is not limited to the device that the target person 2 can carry. The communication device 3 may be, for example, a so-called fixed telephone provided in the dwelling unit of the target person 2, a public telephone installed so as to be used by an unspecified number of people including the target person 2. Further, the communication device 3 is not limited to a telephone, and may be provided with a communication means such as a microphone and a speaker and a communication unit 31. The calling device 3 may be provided in the driver's license center 1. That is, the subject 2 may take the inspection by the determination method of the present disclosure at the driver's license center 1.

In one modification, the identity verification process S4 is not essential in the determination method and may be omitted. In addition, the determination method may include a proxy inspection suppression process in place of or in addition to the identity verification process S4. The proxy inspection deterrence process is a process of deterring a person other than the subject 2 from taking the inspection by the determination method on behalf of the subject 2. The identity verification process S4 also functions as a proxy test suppression process.

In one example, the proxy acceptance suppression process may include displaying a predetermined caution statement on the display unit 33 of the call device 3. As an example of a cautionary sentence, for example, there is a sentence such as "During the test, it is confirmed that the same person is always speaking by personal authentication by voiceprint".

In one example, when the calling device 3 includes an imaging unit such as a camera, the proxy acceptance suppression process includes displaying the image of the target person 2 taken by the calling device 3 on the display unit 33 of the calling device 3. It may be. In this case, it is not necessary to actually confirm the identity of the subject 2 from the processed image data of the captured image of the subject 2. Further, in this case, the determination method may include a discontinuation process for discontinuing the inspection when the subject 2 deviates from the imaging range of the imaging unit.

In one example, the proxy examination deterrence process may include monitoring by a person (for example, a person other than the staff of the Driver's License Center 1). For example, if the driver's license renewal notice is mailed, the proxy inspection deterrence process may include oversight by a post office employee who mails the renewal notice.

In one modification, the identity verification process S4 may use the second personal identification number (one-time password) used when renewing the driver's license.

In one modification, the notification of the estimation result to the target person 2 does not have to be performed immediately. For example, by accessing the predetermined server connected to the telecommunication line NT1 from the communication device 3, the target person 2 may be able to view the estimation result. Further, the notification of the estimation result may be performed via means other than the communication device 3 (for example, by mail).

(4) Summary As described above, the method for determining the cognitive function of the first aspect is the target person (2) at the driver's license center (1), which performs at least one of the services of issuing and renewing the driver's license. It is used when providing services to. The determination method includes a voice acquisition process (S6), an estimation process (S9), and a reflection process (S12). In the voice acquisition process (S6), the target person (2) is made to read aloud a fixed phrase and acquire the voice data related to the reading. In the estimation process (S9), the cognitive function of the subject (2) is estimated based on the voice data acquired in the voice acquisition process (S6). In the reflection process (S12), the result of the estimation process (S9) is reflected in the procedure for providing the service to the target person (2) at the driver's license center (1) or in the determination of whether or not the service can be provided.

According to this aspect, it is possible to reduce the burden when renewing the license.

In the method for determining the cognitive function in the second aspect, in the first aspect, in the estimation process (S9), the cognitive function is estimated using the feature amount extracted from the voice data.

In the method for determining cognitive function in the third aspect, in the second aspect, the feature amount includes one or more selected from the following groups. The above group includes a quantity related to the first formant frequency or the second formant frequency of the vowel in the syllable included in the voice of the subject (2) represented by the voice data. The above group includes a sound pressure difference between the sound pressure of a consonant in an open syllable included in the voice of the subject (2) indicated by voice data and the sound pressure of a vowel following the consonant. The above group includes variations in the sound pressure difference between the sound pressure of a consonant and the sound pressure of a vowel following the consonant in a plurality of open syllables included in the voice of the subject (2) indicated by voice data. .. The above group includes the total time required to read the above fixed phrase. The above group includes the amount of change in the time required for each of the multiple readings of the fixed phrase.

According to this aspect, it is possible to improve the accuracy of the judgment result by the judgment method.

The method for determining the cognitive function of the fourth aspect further includes a recording process (S7) for recording the voice data acquired by the voice acquisition process (S6) in any one of the first to third aspects. ..

The method for determining the cognitive function of the fifth aspect is that in any one of the first to fourth aspects, the estimation process (S9) uses the trained model (M1) generated by machine learning to recognize. Estimate function.

The method for determining the cognitive function in the sixth aspect is one of the first to fifth aspects, in which the voice acquisition process (S6) acquires voice data through a telecommunication line (NT1).

The method for determining the cognitive function in the seventh aspect is that in any one of the first to sixth aspects, in the estimation process (S9), in addition to the voice data acquired in the voice acquisition process (S6), a target is used. The cognitive function is estimated by further using the attribute data related to the attribute of the person (2).

The method for determining the cognitive function in the eighth aspect further includes, in any one of the first to seventh aspects, a presentation process (S5) for presenting information prompting the subject to read a fixed phrase.

The method for determining the cognitive function in the ninth aspect is that in the eighth aspect, in the presentation process (S5), an automatic voice prompting the target person (2) to read a fixed phrase is reproduced.

The method for determining the cognitive function in the tenth aspect is, in the eighth or ninth aspect, in the presentation process (S5), the subject (2) is visually provided with information prompting the subject (2) to read a fixed phrase.

The method for determining the cognitive function in the eleventh aspect is one of the eighth to tenth aspects, in which the presentation process (S5) presents a question related to the driver's license to the subject (2). The above-mentioned question includes a content that prompts the subject (2) to read a fixed phrase as an answer to the question.

The method for determining the cognitive function of the twelfth aspect further includes an identity verification process (S4) for confirming that the subject (2) is the person in any one of the first to eleventh aspects. ..

The method for determining the cognitive function in the thirteenth aspect is that in the twelfth aspect, the identity verification process (S4) is performed using the biological information of the subject (2).

According to this aspect, it is possible to improve the accuracy of identity verification.

In the thirteenth aspect of the method for determining the cognitive function in the fourteenth aspect, the biological information includes the voiceprint information of the subject (2).

The method for determining the cognitive function of the fifteenth aspect further includes a target person identification process (S2) for identifying the target person (2) in any one of the first to fourteenth aspects.

In the fifteenth aspect of the method for determining the cognitive function of the sixteenth aspect, the target person identification process (S2) is performed using the biological information of the target person (2).

According to this aspect, it is possible to improve the specific accuracy of the target person (2).

The method for determining the cognitive function in the 17th aspect further includes an operation acceptance process for receiving an operation input from the target person (2) in any one of the 1st to 16th aspects. The estimation process (S9) estimates the cognitive function by further using the result of the operation input in addition to the voice data acquired in the voice acquisition process (S6).

The program of the eighteenth aspect is a program for causing one or more processors to execute the method of determining the cognitive function of any one of the first to seventeenth aspects.

The cognitive function determination system (10) of the nineteenth aspect is used when providing services to the target person (2) at the driver's license center (1), which performs at least one of the services of issuing and renewing the driver's license. Be done. The determination system (10) includes a voice acquisition unit (F5), an estimation unit (F7), and a reflection unit (F13). The voice acquisition unit (F5) causes the target person (2) to read aloud a fixed phrase and acquires voice data related to the reading. The estimation unit (F7) estimates the cognitive function of the subject (2) based on the voice data acquired by the voice acquisition unit (F5). The reflection unit (F13) reflects the estimation result of the estimation unit (F7) in the procedure for providing the service to the target person (2) at the driver's license center (1) or in the determination of whether or not the service can be provided.

1 Driver's License Center 2 Target person 10 Judgment system F5 Voice acquisition unit F7 Estimate unit F13 Reflection unit S2 Target person identification processing S4 Identity verification processing S5 Presentation processing S6 Voice acquisition processing S7 Recording processing S9 Estimation processing S12 Reflection processing M1 Learned model NT1 Telecommunications line

Claims

A method for determining the cognitive function used in providing the above-mentioned services to the target person at a driver's license center that performs at least one of the services of issuing and renewing a driver's license.
A voice acquisition process in which the target person reads out a fixed phrase and acquires voice data related to the reading,
An estimation process that estimates the cognitive function of the subject based on the voice data acquired by the voice acquisition process, and an estimation process.
A reflection process that reflects the result of the estimation process in the procedure for providing the service to the target person at the driver's license center or in determining whether or not the service can be provided.
To prepare
How to judge cognitive function.
In the estimation process, the cognitive function is estimated using the feature amount extracted from the voice data.
The method for determining cognitive function according to claim 1.
The feature amount is
A quantity relating to the first formant frequency or the second formant frequency of a vowel in a syllable included in the subject's voice indicated by the voice data.
The sound pressure difference between the sound pressure of a consonant in an open syllable included in the voice of the subject and the sound pressure of a vowel following the consonant,
Variation of sound pressure difference between the sound pressure of a consonant and the sound pressure of a vowel following the consonant in a plurality of open syllables included in the voice of the subject.
Total time required for reading the above,
Includes one or more selected from the group consisting of the amount of change in the time required for each of the multiple readings of the fixed phrase.
The method for determining cognitive function according to claim 2.
A recording process for recording the voice data acquired by the voice acquisition process is further provided.
The method for determining cognitive function according to any one of claims 1 to 3.
In the estimation process, the cognitive function is estimated using a trained model generated by machine learning.
The method for determining cognitive function according to any one of claims 1 to 4.
In the voice acquisition process, the voice data is acquired through a telecommunication line.
The method for determining cognitive function according to any one of claims 1 to 5.
In the estimation process, the cognitive function is estimated by further using the attribute data related to the attributes of the target person in addition to the voice data acquired in the voice acquisition process.
The method for determining cognitive function according to any one of claims 1 to 6.
Further provided with a presentation process for presenting the information prompting the reading of the fixed phrase to the target person.
The method for determining cognitive function according to any one of claims 1 to 7.
In the presentation process, an automatic voice prompting the target person to read the fixed phrase is reproduced.
The method for determining cognitive function according to claim 8.
In the presentation process, information that prompts the subject to read the fixed phrase is visually given.
The method for determining cognitive function according to claim 8 or 9.
In the presentation process, a question related to the driver's license is presented to the subject.
The question includes a content that prompts the subject to read the fixed phrase as an answer to the question.
The method for determining cognitive function according to any one of claims 8 to 10.
Further provided with an identity verification process for confirming that the subject is the person himself / herself.
The method for determining cognitive function according to any one of claims 1 to 11.
The identity verification process is performed using the biological information of the subject.
The method for determining cognitive function according to claim 12.
The biological information includes information on the voiceprint of the subject.
The method for determining cognitive function according to claim 13.
Further provided with a target person identification process for identifying the target person.
The method for determining cognitive function according to any one of claims 1 to 14.
The target person identification process is performed using the biological information of the target person.
The method for determining cognitive function according to claim 15.
Further provided with an operation reception process for receiving operation input from the target person,
The estimation process estimates the cognitive function by further using the result of the operation input in addition to the voice data acquired by the voice acquisition process.
The method for determining cognitive function according to any one of claims 1 to 16.
A program for causing one or more processors to execute the cognitive function determination method according to any one of claims 1 to 17.
A cognitive function determination system used to provide the above-mentioned services to the target person at a driver's license center that performs at least one of the services of issuing and renewing a driver's license.
A voice acquisition unit that causes the target person to read aloud a fixed phrase and acquires voice data related to the reading.
An estimation unit that estimates the cognitive function of the subject based on the voice data acquired by the voice acquisition unit, and an estimation unit.
A reflection unit that reflects the estimation result of the estimation unit in the procedure for providing the service to the target person at the driver's license center or in determining whether or not the service can be provided.
To prepare
Cognitive function judgment system.