Information processing system, information processing method, and program

Abstract

[Problem] To provide a technology that enables a child to present to a parent, in an objective manner, the time spent on a conversation lesson, wherein the parent can have confidence in the time spent. [Solution] This information processing system that estimates the time spent on a conversation lesson in a second language in a room comprises: a learning means for constructing a trained model on the basis of environment information for learning and teacher information, the environment information for learning including at least a plurality of sound pressure levels and a plurality of pieces of time information at measuring the sound pressure levels, and the teacher information being obtained by associating behavior information with the environment information for learning; and an acquisition means for acquiring environment information for actual performance including at least a plurality of sound pressure levels and a plurality of pieces of time information at measuring the sound pressure levels. The environment information for actual performance acquired by the acquisition means is input into the trained model constructed by the learning means.

Description

Information processing system, information processing method, and program

[0001] The present disclosure relates to an information processing system, an information processing method, and a program.

[0002] In recent years, the number of dual-income couples has increased, and children are spending more time at home alone. In such circumstances, parents need to be either laissez-faire or use some kind of support tool to check whether their children are working on their assignments while they are at home alone.

[0003] Patent Document 1 discloses a system for monitoring a child's study at home, which acquires information relating to the child's emotions or level of concentration at the start of studying via a terminal device installed in the child's room, acquires detection results from a sensor that detects whether the child is sitting at a desk installed in the room, and manages the child's study time.

[0004] However, with this system, the device issues instructions to the child, and in situations where the device needs to be used for other purposes, such as taking online English conversation lessons, multiple devices are required, which takes up space on the child's desk.

[0005] In such cases, it would be preferable to move to another space rather than to study at a cramped desk, but unless students study in front of the device, the system cannot accurately reflect their study time. Furthermore, recording the time spent studying in every style requires installing a wide variety of sensors inside the room, which is costly. In such cases, the situation becomes more like "monitoring" than tracking study time, and students end up providing more personal information than necessary to the system, which can cause significant stress for students.

[0006] Japanese Patent Application Laid-Open No. 2021-26328

[0007] As globalization progresses, parents are increasingly demanding that their children learn a second language. In response to this demand, an increasing number of children are taking online foreign language conversation lessons, such as online English conversation lessons, in recent years. However, for dual-income parents, it is difficult to ensure that their children are diligently attending their conversation lessons as planned. As a result, parents are forced to rely on their children's self-reported time spent on conversation lessons.

[0008] However, parents who deal with children who are mentally immature cannot unconditionally trust the amount of time their children self-report. On the other hand, children wanted a tool that would allow them to objectively report the amount of time they spent working, rather than relying on unreliable self-reports.

[0009] The present disclosure has been made in consideration of such circumstances, and aims to provide a technology that enables a child to objectively present to a parent the time required to work on conversation lessons, and that allows the parent to trust that time.

[0010] The information processing system of the present invention is an information processing system that estimates the time spent working on a second language conversation lesson in a room, and is constructed to include: learning means for constructing a trained model based on learning environment information including at least a plurality of sound pressure levels and time information when the sound pressure levels were measured, and teacher information obtained by matching the learning environment information with behavioral information; acquisition means for acquiring actual environment information including at least a plurality of sound pressure levels and time information when the sound pressure levels were measured; discrimination means for inputting the actual environment information acquired by the acquisition means into the trained model constructed by the learning means, and determining whether or not the person was working on a conversation lesson at the time corresponding to the time information in the actual environment information; and output means for outputting to a specified output destination the conversation lesson work time calculated by accumulating the time determined by the discrimination means to be working on a conversation lesson.

[0011] This makes it possible to estimate the time spent on a second language conversation lesson in a room without any room for arbitrary manipulation by the person who conducted the conversation lesson.The present invention also takes into consideration the protection of personal information by using an information processing system consisting of a small number of sensors, mainly for sound pressure level.

[0012] It is also preferable that the apparatus further comprises a noise measurement means, and the acquisition means acquires the environmental information for the actual performance by the noise measurement means.

[0013] This allows for a more accurate estimation of the amount of time spent on conversation lessons.

[0014] It is also preferable that the noise measurement means is a noise measurement application installed in an information processing terminal.

[0015] This allows for the use of existing hardware, saving space and improving cost performance.

[0016] It is also preferable that the information processing terminal is a smartphone.

[0017] When measuring noise levels using a smartphone, students must take their hands off the smartphone and place it in a designated location. Touching the smartphone while it is placed will disrupt the measurement results, so smartphone operation can be restricted, at least while students are working on their conversation lessons. There is a concern that touching a smartphone while studying will reduce students' concentration on their studies, so creating an environment where students are less likely to touch their smartphones is expected to result in more time spent working on their conversation lessons.

[0018] Furthermore, it is preferable that the noise measurement application restricts the noise measurement means when another application is launched by the smartphone.

[0019] This allows you to completely step away from your smartphone while working on your conversation lessons, allowing you to focus on your studies.

[0020] Preferably, the learning environment information and the actual environment information include illuminance information corresponding to time information.

[0021] By combining multiple different environmental information, a more accurate trained model can be constructed, resulting in more accurate prediction of the conversation lesson time.

[0022] In addition, it is preferable that the output means outputs identification information corresponding to the smartphone to the specified output destination, along with the conversation lesson engagement time, which is the accumulated time during which the discrimination means determined that the smartphone was engaged in the conversation lesson.

[0023] As will be discussed later, the majority of people carry their smartphones with them at all times, and many people refuse to allow others to use their smartphones. By outputting the identification information for each smartphone used as part of a learning tool to the output destination, the person receiving the report at the output destination (if the learner is a child, this could be their father or mother) can trust that "the learner was present and studied without being asked to do so by another person."

[0024] The information processing method of the present invention is an information processing method executed by an information processing system, and includes: an acquisition step of acquiring environmental information for actual use, which includes at least a plurality of sound pressure levels and time information when the sound pressure levels were measured; a determination step of inputting the environmental information for actual use acquired by the acquisition step into a trained model constructed based on environmental information for learning, which includes at least a plurality of sound pressure levels and time information when the sound pressure levels were measured, and teacher information obtained by matching the environmental information for learning with behavioral information, thereby determining whether or not the subject was engaged in a conversation lesson at the time corresponding to the time information in the environmental information for actual use; and an output step of outputting to a predetermined output destination the conversation lesson engagement time, which is the accumulated time determined to be the time when the subject was engaged in a conversation lesson by the determination step.

[0025] The program of the present invention executes an acquisition step of acquiring environmental information for actual use, which includes at least a plurality of sound pressure levels and time information when the sound pressure levels were measured; a determination step of inputting the environmental information for actual use acquired by the acquisition step into a trained model constructed based on learning environmental information, which includes at least a plurality of sound pressure levels and time information when the sound pressure levels were measured, and teacher information obtained by matching the learning environmental information with behavioral information, to determine whether or not the subject was engaged in a conversation lesson at the time corresponding to the time information in the environmental information for actual use; and an output step of outputting to a predetermined output destination the conversation lesson engagement time, which is the sum of the time determined to be engaged in a conversation lesson by the determination step.

[0026] According to the present invention, a person who has participated in an online conversation lesson can objectively present the time spent on the lesson.

[0027] 1 is a diagram showing an example of a system configuration of an information processing system; 2 is a diagram showing an example of a hardware configuration of an information processing system; 3 is a block diagram showing an example of a functional configuration of an information processing system; 4 is a diagram showing the relationship between sound pressure level and the noise level perceived by humans; 5 is a diagram showing sound pressure level distribution for a predetermined time in an empty room; and 6 is a diagram showing sound pressure level distribution when online English conversation is continued for a predetermined time in a room.

[0028] Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0029] <System Configuration> An example of the system configuration of an information processing system according to this embodiment will be described with reference to FIG. 1 . The information processing system according to this embodiment provides a mechanism for ascertaining the status of a second language learner (e.g., a junior high school student) using a noise measurement device (e.g., a tablet terminal, a smartphone, etc.) connected via a network. For example, FIG. 1 shows an example of the configuration of an information processing system 1 according to this embodiment, in which the status of a room 600 (e.g., a child's room in the case of a junior high school student) is ascertained based on environmental information obtained by a noise measurement device 300. Specifically, the information processing system 1 includes a noise measurement device 300, information processing devices 100 and 200, and terminal devices 400 and 500. Note that, hereinafter, when no distinction is made between the terminal devices 400 to 500, they may be referred to as the "imaging device 400." Furthermore, the noise measurement device 300, the information processing devices 100 and 200, and the terminal devices 400 and 500 are configured to be able to transmit and receive various information and data via a network N1.

[0030] The type of network N1 connecting the devices constituting the information processing system 1 is not particularly limited. As a specific example, the network N1 may be configured as a local area network (LAN), the Internet, a dedicated line, a wide area network (WAN), or the like. The network N1 may also be configured as a wired network or a wireless network. The network N1 may also include multiple networks, and some of the networks may be of a different type from the other networks. The physical configuration of the network N1 is not particularly limited as long as communication between the devices is logically established. As a specific example, communication between the devices may be relayed by other communication devices, etc. Furthermore, the series of devices constituting the information processing system 1 do not necessarily need to be connected to a common network. In other words, as long as communication between the devices that transmit and receive information and data can be established, two or more devices may be connected to different networks from the other two or more devices.

[0031] Noise measuring device 300 can be realized, for example, by a noise measuring device configured to digitize the measurement results of a so-called sound level meter and output them as numerical information. Noise measuring device 300 transmits environmental information (hereinafter also referred to as "environmental data") corresponding to the measurement results to other devices (e.g., information processing devices 100 and 200) via network N1.

[0032] The information processing devices 100 and 200 provide a mechanism that makes it possible to grasp the state of a room 600 based on environmental data transmitted from a noise measuring device 300 according to the measurement results of the room 600 by the noise measuring device 300 .

[0033] Specifically, information processing device 200 performs a predetermined analysis process on the environmental data transmitted from noise measuring device 300 to determine whether the second language learner in room 600 is engaged in a second language conversation lesson. At this time, information processing device 200 outputs notification information according to the result of the determination to a predetermined output destination (for example, terminal devices 400 and 500, described below). This makes it possible to report the state of room 600 to a user (for example, a father or mother).

[0034] The information processing device 100 constructs, based on machine learning, a trained model that the information processing device 200 uses for the above analysis processing. Any method of standard training may be used, and specific examples include a tool that is publicly available as a library for a predetermined programming language, and "Simple ML for Sheets," an add-on provided by Google that allows machine learning to be introduced into spreadsheets.

[0035] In addition, since the environment of the room 600 differs for each second language learner and the sound pressure level emitted by each learner during learning differs, it is preferable that the trained model described above be constructed based on training information (also called training data) obtained by matching behavioral information with learning environment information. This allows the information processing system 1 to make more accurate judgments tailored to each individual (correctly determining that a person is "engaged in a second language conversation lesson" when the person is "engaged in a second language conversation lesson").

[0036] <Hardware Configuration> An example of the hardware configuration of an information processing device 900 that can be used as each of the information processing devices 100 and 200 and the terminal devices 400 and 500 in the information processing system 1 according to this embodiment will be described with reference to Fig. 2. As shown in Fig. 2, the information processing device 900 according to this embodiment includes a CPU (Central Processing Unit) 910, a ROM (Read Only Memory) 920, and a RAM (Random Access Memory) 930. The information processing device 900 also includes an auxiliary storage device 940 and a network I / F 970. The information processing device 900 may also include at least one of an output device 950 and an input device 960. The CPU 910 , ROM 920 , RAM 930 , auxiliary storage device 940 , output device 950 , input device 960 , and network I / F 970 are interconnected via a bus 980 .

[0037] The CPU 910 is a central processing unit that controls various operations of the information processing device 900. For example, the CPU 910 may control the operation of the entire information processing device 900. The ROM 920 stores control programs, boot programs, and the like that can be executed by the CPU 910. The RAM 930 is the main storage memory of the CPU 910, and is used as a work area or a temporary storage area for expanding various programs.

[0038] The auxiliary storage device 940 stores various data and various programs. The auxiliary storage device 940 is realized by a storage device that can temporarily or permanently store various data, such as a non-volatile memory such as a hard disk drive (HDD) or a solid state drive (SSD).

[0039] The output device 950 is a device that outputs various types of information and is used to present various types of information to a user. In this embodiment, the output device 950 is realized by a display device such as a display. The output device 950 presents information to a user by displaying various types of display information. However, as another example, the output device 950 may be realized by an audio output device that outputs sounds such as voices and electronic sounds. In this case, the output device 950 presents information to a user (e.g., "The second language learning time on April 1, 2024 is 35 minutes") by outputting sounds such as voices and telegrams. Furthermore, the device used as the output device 950 may be changed as appropriate depending on the medium used to present information to a user.

[0040] The input device 960 is used to receive various instructions from the user. In this embodiment, the input device 960 includes input devices such as a mouse, a keyboard, and a touch panel. However, as another example, the input device 960 may include a sound collection device such as a microphone, which collects the voice uttered by the user. Furthermore, multiple types of devices may be applied as the input device 960.

[0041] The network I / F 970 is used for communication with external devices via a network. Note that the device used as the network I / F 970 may be changed as appropriate depending on the type of communication path and the communication method used.

[0042] The CPU 910 expands a program stored in the ROM 920 or the auxiliary storage device 940 into the RAM 930 and executes this program, thereby realizing the functional configurations of the information processing devices 100 and 200 shown in Figure 3 and the processing of the information processing devices 100 and 200.

[0043] <Functional Configuration> An example of the functional configuration of the information processing system 1 according to this embodiment will be described with reference to FIG.

[0044] First, an example of the functional configuration of the information processing device 100 will be described. As described above, the information processing device 100 constructs, based on machine learning, a trained model that is used by the information processing device 200 (described later) to perform a predetermined analysis process on the actual environmental information transmitted from the noise measuring device 300. The learning processing unit 110 schematically shows components that execute various processes related to the construction of the trained model. In other words, the learning processing unit 110 is an example of a configuration that serves as a "learning means" related to the construction of the trained model.

[0045] In this specification, "environmental information" includes at least sound pressure level and time information when the sound pressure level was measured. In addition to sound pressure level and time information, environmental information may also include illuminance and other physical quantities. By acquiring illuminance as environmental information, using it to train a trained model, and then using it to make a judgment as described below, it becomes possible to more accurately determine whether a second-language conversation lesson is in progress. Note that "sound pressure level" is a quantity that indicates the level of the strength of air pressure fluctuations caused by a sound source at an observation point, and is expressed in units of dB (decibels). It is a quantity expressed as the common logarithm of the ratio of the square of the sound pressure to the square of the reference sound pressure, and is given by 10 times the common logarithm of the value obtained by dividing the square of the sound pressure by the square of the reference sound pressure.

[0046] In this specification, "environmental information" has two meanings. First, environmental information used when constructing a trained model is referred to as "training environmental information." Second, environmental information input to a trained model and used to determine whether a second language conversation lesson is in progress is referred to as "production environmental information." Although these two types of environmental information are used in different phases, they may be acquired by a common noise measurement means (in this embodiment, noise measurement is performed using noise measurement device 300).

[0047] The learning processing unit 110 constructs a learned model based on teacher information (also called teacher data) obtained by matching behavioral information with learning environment information including at least sound pressure level and time information when the sound pressure level was measured.

[0048] In this specification, "behavioral information" is categorized into at least two types of information: "during a second language lesson" and "during other activities."

[0049] "Second language" refers to a language other than the native language. For example, if the native language is Japanese, the second language would be English, French, Spanish, Chinese, or another language other than Japanese. Furthermore, "other activities" may be registered separately for actual activities, such as "sleeping," "reading," and "studying." A trained model constructed using such labeled training information can determine which of the activity information used for labeling actually took place in relation to the input environmental information for actual use. The degree of specificity with which "other activities" are labeled is adjusted based on how specifically the information processing system needs to grasp the activities in the room.

[0050] According to the website of the Japan Noise Survey (SOCH), the proportions of noise perceived by humans are as shown in Figure 4. Preliminary experiments showed that in a typical home, noise levels were around 20-30 dB when no one was in the room, and 25-35 dB even when an air purifier was running constantly. Even when someone was in the room, the level was 35-40 dB if they were quietly concentrating on reading or studying. Furthermore, the level was around 20-35 dB when sleeping. In contrast, it was found that when people were taking second language conversation lessons in the room, the level fluctuated between 30-70 dB.

[0051] Figure 5 shows the sound pressure level distribution when noise was measured for 30 minutes with no one in the room and the air purifier running at all times, while Figure 6 shows data from 30 minutes of continuous online English conversation in the room.

[0052] This preliminary experiment revealed that the sound pressure level increases when a second language conversation lesson is being conducted in room 600 compared to when no conversation lesson is being conducted. Therefore, if a person were to visually observe, for example by looking at a graph that correlates the time with the sound pressure level, it would be easy to determine whether a second language conversation lesson is being conducted or another activity (reading, studying, sleeping, etc.).

[0053] Therefore, by inputting environmental information about the actual environment, including the sound pressure level and the time when the sound pressure level was measured, into a trained model that has been trained based on appropriate training data, it is possible to determine whether the person is in a second language conversation lesson or is engaged in other activities (reading, studying, sleeping, etc.).

[0054] The trained model constructed based on machine learning is output to the information processing device 200. Note that the method is not particularly limited as long as the information processing device 200 can acquire the trained model. As a specific example, the information processing device 100 may transmit the trained model to the information processing device 200 via the network N1. As another example, the information processing device 100 may store the constructed trained model in a desired storage area. In this case, the information processing device 200 may acquire the trained model by reading the trained model from the storage area.

[0055] Next, a description will be given of an example of the functional configuration of the information processing device 200. The information processing device 200 includes an environmental information acquisition unit 201, a determination unit 203, and an output control unit 205.

[0056] The environmental information acquisition unit 201 acquires the actual environmental information to be grasped from the noise measurement device 300 .

[0057] The determination unit 203 assigns plausible information as behavior information to the actual environmental information obtained by the environmental information acquisition unit 201 via the trained model.

[0058] Then, the determining unit 203 outputs information according to the result of the determination to the output control unit 205 .

[0059] The output control unit 205 outputs information according to the result of the determination by the determination unit 203 to a predetermined output destination. For example, the output control unit 205 may output output information according to the result of the determination by the determination unit 203 to the terminal device 400 (500). This makes it possible to report the output information according to the result of the determination by the determination unit 203 to the user via the terminal device 400 (500). As another example, the output control unit 205 may store information according to the result of the determination by the determination unit 203 in a predetermined storage area.

[0060] Note that the above is merely an example, and the functional configuration of the information processing system 1 is not limited as long as it is possible to realize functions corresponding to the components of the information processing system 1 described above (particularly the components of the information processing devices 100 and 200). For example, the functional configurations of the information processing devices 100 and 200 may be realized by multiple devices working together. As a specific example, some of the components of the information processing device 100 may be provided in a device other than the information processing device 100. As another example, the load related to the processing of at least some of the components of the information processing device 100 may be distributed to multiple devices. The same applies to the information processing device 200.

[0061] The embodiments of the present invention have been described above from the viewpoints of the <hardware configuration> and the <functional configuration>. Hereinafter, the technical features of the present invention realized by these configurations will be described.

[0062] <Technical Features> The information processing system 1 according to this embodiment aims to estimate the time spent in a room 600 on a conversation lesson in a second language.

[0063] The information processing system 1 includes an acquisition unit, a learning unit that constructs a trained model, an acquisition unit that acquires environmental information, a discrimination unit, and an output unit. The learning unit has the function of the learning processing unit 110. The acquisition unit has the function of the environmental information acquisition unit 201.

[0064] The determination means receives the actual environment information acquired by the acquisition means and determines whether or not the conversation lesson was being conducted at the time corresponding to the time information in the actual environment information. In this embodiment, the actual environment information obtained by the noise measurement device 300 in Figure 1 is acquired by the environment information acquisition unit 201 in Figure 3.

[0065] The output means outputs the conversation lesson effort time, which is the sum of the time determined by the determination means to be the time when the conversation lesson was being undertaken, to a predetermined output destination. In this embodiment, the output control unit 205 in FIG. 3 has this function.

[0066] The "predetermined output destination" in this specification may be any output destination that is connected via a network, such as a server on a cloud, a terminal in a remote location, etc. In this embodiment, the terminal devices 400 and 500 in Fig. 3 correspond to the predetermined output destination.

[0067] "Outputting the conversation lesson time accumulated over time" means, for example, if the time information acquired as the actual environment information is measured every second from "3:00 PM to 10:00 PM on April 12, 2024," the discrimination means estimates whether or not each second is a time spent on a second language lesson. At this time, if it is estimated that there are 3,600 counts of "second language lesson in progress," the output is "3,600 seconds (1 hour) spent on the second language lesson between 3:00 PM and 10:00 PM on April 12, 2024."

[0068] The purpose of this invention is to allow participants who have participated in online conversation lessons to objectively report the amount of time they spent studying. This improves the reliability of participants' study time because it does not rely on self-reporting by participants and leaves no room for arbitrary manipulation.

[0069] As shown in FIG. 1, the information processing system 1 may include a noise measurement device such as a noise measurement device 300. In keeping with the spirit of the present invention, the environmental information for the actual lesson in the room may be provided in any manner, and environmental information may be obtained by analogy with environmental information from other rooms, without directly measuring the sound pressure level of the room. However, it is preferable for the information processing system 1 itself to include a noise measurement device such as the noise measurement device 300, since this allows for accurate acquisition of on-site information in real time. This allows for more accurate estimation of the time spent on the conversation lesson.

[0070] Furthermore, the noise measurement means is preferably a noise measurement app installed on an information processing terminal. In the context of FIG. 1 , this means that the noise measurement device 300 is an information processing terminal and that the information processing terminal is equipped with a noise measurement app. In the case of the information processing system of the present invention, the noise measurement means is not particularly limited, and a single conventional noise meter may be provided. However, by installing a noise measurement app with a noise measurement means on existing hardware, it is possible to save space equivalent to at least one analog noise meter and improve cost performance by reducing initial investment.

[0071] The information processing terminal may be any type of terminal, such as a notebook PC, a desktop PC, a tablet, etc. However, in the present invention, it is preferable that the information processing terminal is a smartphone.

[0072] According to the Ministry of Internal Affairs and Communications' "Survey on Telecommunications Usage Trends" conducted in 2020, 83.4% of households owned information and communications devices in 2019, 69.1% had smartphones, 37.4% had personal computers, and 37.4% had tablets. Therefore, an information processing system that utilizes smartphones can reduce initial investment compared to using other information processing devices.

[0073] If you download a noise measurement app via Google Play or similar, your smartphone will function as a sound level meter, and you can output the acquired environmental information in a format that is easy to handle within an information processing system, such as CSV format. You can also use any method, such as a program or RPA, to periodically output CSV files from the app. Since such automatic processing is difficult when using an analog sound level meter, it is preferable to use a noise measurement app.

[0074] Furthermore, it is preferable that the noise measurement app restricts the noise measurement means when other apps are launched on the smartphone. While technological innovations are generally moving in the direction of eliminating the limitations of devices, in the present invention, this limitation is positioned as a very important feature in terms of increasing the learning efficiency of second language learners.

[0075] Having a smartphone nearby and ready to use makes it difficult to concentrate on second language lessons because students are unable to resist various external temptations such as watching videos or browsing social media. In fact, according to a survey released by the Cabinet Office in March 2023, 78.9% of junior high school students and 97.9% of high school students use smartphones, and the average time high school students spend on smartphones is about four hours on weekdays just for internet use.

[0076] Therefore, by forcibly realizing the seemingly inconvenient situation of not launching other apps while the noise measurement app is running, or not launching the noise measurement app while other apps are running, it is possible to limit the use of smartphones for surfing the Internet and social media, thereby establishing a system that allows users to take more lessons. This is desirable for both the so-called smartphone-addicted junior and senior high school students themselves and their parents who are worried about how to deal with their smartphone-addicted junior and senior high school students. Furthermore, it is preferable that the output means of the present invention (e.g., a function of the output control unit 205) is characterized in that it outputs to the predetermined output destination identification information corresponding to the smartphone along with the conversation lesson engagement time, which is calculated by accumulating the time when the discrimination means (e.g., a function of the environmental information acquisition unit 201) determines that the student was engaged in a conversation lesson.

[0077] As will be discussed later, the majority of people carry their smartphones with them at all times, and many people do not allow others to use their smartphones. By outputting the identification information for each smartphone used as part of a learning tool to the output destination, the person receiving the report at the output destination (if the learner is a child, the father or mother) can trust that "the child was present and definitely studied."

[0078] Although the present invention has been described above in conjunction with the above-mentioned embodiments, the present invention is not limited to the above-mentioned embodiments, and various modifications are possible within the scope of the technical concept of the present invention. The above-mentioned embodiments or modifications may be combined as appropriate. The present invention also includes an information processing method for realizing the functions of the above-mentioned embodiments, and a program for causing a computer to execute the functions of the above-mentioned embodiments.

[0079] The present invention is expected to be used industrially as an information processing system that is beneficial to both second language learners and observers who monitor the learning progress of those learners.

[0080] REFERENCE SIGNS LIST 1 Information processing system 100 Information processing device 101 Environmental information acquisition unit (during learning) 110 Learning processing unit 200 Information processing device 201 Environmental information acquisition unit (during discrimination) 203 Discrimination unit 205 Output control unit 300 Noise measurement device 400 Terminal device 500 Terminal device

Claims

1. An information processing system that estimates the amount of time spent working on a second language conversation lesson in a room, comprising: a learning means that constructs a trained model based on learning environment information including at least sound pressure levels and time information when the sound pressure levels were measured, and teacher information obtained by matching the learning environment information with behavioral information; an acquisition means that acquires actual environment information including at least sound pressure levels and time information when the sound pressure levels were measured; a determination means that inputs the actual environment information acquired by the acquisition means into the trained model constructed by the learning means, and determines whether or not the person was working on a conversation lesson at the time corresponding to the time information in the actual environment information; and an output means that outputs to a specified output destination the conversation lesson work time, which is the sum of the time determined by the determination means to be working on a conversation lesson.

2. The information processing system according to claim 1, further comprising a noise measurement means, wherein said acquisition means acquires said environmental information for actual use by said noise measurement means.

3. The information processing system according to claim 2, wherein the noise measurement means is a noise measurement application installed in an information processing terminal.

4. The information processing system according to claim 3, wherein the information processing terminal is a smartphone.

5. The information processing system according to claim 4, wherein the noise measurement app restricts the noise measurement means when another app is launched on the smartphone.

6. The information processing system described in claim 5, characterized in that the output means outputs to the specified output destination identification information corresponding to the smartphone along with the conversation lesson engagement time, which is the accumulated time determined by the determination means to be engaged in the conversation lesson.

7. An information processing system according to any one of claims 1 to 6, characterized in that the learning environment information and the actual environment information include illuminance information corresponding to time information.

8. An information processing method executed by an information processing system, comprising: an acquisition step of acquiring environmental information for actual use, the environmental information including at least a plurality of sound pressure levels and time information when the sound pressure levels were measured; a determination step of inputting the environmental information for actual use acquired by the acquisition step into a trained model constructed based on environmental information for learning, the environmental information including at least a plurality of sound pressure levels and time information when the sound pressure levels were measured, and teacher information obtained by matching the environmental information for learning with behavioral information, thereby determining whether or not the subject was engaged in a conversation lesson at the time corresponding to the time information in the environmental information for actual use; and an output step of outputting to a predetermined output destination the conversation lesson engagement time, which is the sum of the time determined to be engaged in a conversation lesson by the determination step.

9. A program that causes a computer to execute the following steps: an acquisition step of acquiring environmental information for actual use, which includes at least a plurality of sound pressure levels and time information when the sound pressure levels were measured; a determination step of inputting the environmental information for actual use acquired in the acquisition step into a trained model constructed based on environmental information for learning, which includes at least a plurality of sound pressure levels and time information when the sound pressure levels were measured, and teacher information obtained by matching the environmental information for learning with behavioral information, to determine whether or not the subject was engaged in a conversation lesson at the time corresponding to the time information in the environmental information for actual use; and an output step of outputting to a predetermined output destination the conversation lesson engagement time, which is the sum of the time determined to be engaged in a conversation lesson by the determination step.

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