Information processing device, information processing method, and computer-readable storage medium

Abstract

The information processing device according to the present disclosure includes a generation unit, which generates a model about content generation by using data provided by a user subject of a service about content creation; the user subject has one of multiple authority levels of the service; and a determination unit, which determines a usage pattern of the model generated by the generation unit according to one authority level of the user subject.

Description

Technical Field

[0001] The present disclosure relates to an information processing device, an information processing method, and an information processing program. Background Art

[0002] With the advancement of artificial intelligence (AI), the application of computers in the field of art has been promoted. For example, a technology is known in which machine learning is performed on existing music as learning data to generate a learning model for generating music, and then a computer is caused to compose new music (for example, Patent Document 1). In this technology, by using a Markov model, it is possible to imitate the characteristics of existing music or generate more natural melodies.

[0003] Reference List

[0004] Patent Literature

[0005] Patent Document 1: U.S. Patent No. 9110817 Summary of the Invention

[0006] Technical issues

[0007] According to the conventional technology, since music data proposed (generated) by artificial intelligence (AI) can be used in a composition work, users can compose music based on more diverse viewpoints.

[0008] However, in the above-mentioned prior art, it is not always possible to appropriately determine the usage pattern of a model used to generate content such as music. For example, in the above-mentioned prior art, a model such as a Markov model is used to generate only music, without considering what kind of users use the model for generating content such as music and in what patterns. Therefore, it is desirable to appropriately determine the usage pattern of a model used to generate content such as music.

[0009] Therefore, the present disclosure proposes an information processing apparatus, an information processing method, and an information processing program capable of appropriately using a model according to data for generating the model.

[0010] Solution to the problem

[0011] According to the present disclosure, an information processing device includes: a generation unit that generates a model about content generation by using data provided by a user subject of a service about content creation, the user subject having one of multiple authority levels of the service; and a determination unit that determines a usage pattern of the model generated by the generation unit according to a permission level of the user subject. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a schematic diagram illustrating an example of information processing according to an embodiment of the present disclosure.

[0013] Figure 2 is a schematic diagram illustrating an example of a usage pattern of a model according to an embodiment of the present disclosure.

[0014] Figure 3 is a schematic diagram illustrating an example of a usage pattern of a model according to an embodiment of the present disclosure.

[0015] Figure 4 is a schematic diagram illustrating an example of a usage pattern of a model according to an embodiment of the present disclosure.

[0016] Figure 5 is a schematic diagram illustrating an example of a usage pattern of a model according to an embodiment of the present disclosure.

[0017] Figure 6 is a schematic diagram illustrating an example of a usage pattern of a model according to an embodiment of the present disclosure.

[0018] Figure 7 is a schematic diagram illustrating a configuration example of an information processing system according to an embodiment of the present disclosure.

[0019] Figure 8 is a schematic diagram illustrating a configuration example of an information processing apparatus according to an embodiment of the present disclosure.

[0020] Figure 9 is a schematic diagram illustrating an example of a user information storage unit according to an embodiment of the present disclosure.

[0021] Figure 10 is a schematic diagram illustrating an example of a work information storage unit according to an embodiment of the present disclosure.

[0022] Figure 11 is a schematic diagram illustrating an example of a learning model information storage unit according to an embodiment of the present disclosure.

[0023] Figure 12 is a schematic diagram illustrating an example of a sales management information storage unit according to an embodiment of the present disclosure.

[0024] Figure 13 is a schematic diagram illustrating an example of a shared information storage unit according to an embodiment of the present disclosure.

[0025] Figure 14 is a schematic diagram illustrating an example of a purchase information storage unit according to an embodiment of the present disclosure.

[0026] Figure 15 is a schematic diagram illustrating an example of an operation history information storage unit according to an embodiment of the present disclosure.

[0027] Figure 16is a schematic diagram illustrating a configuration example of a system administrator terminal according to an embodiment of the present disclosure.

[0028] Figure 17 is a schematic diagram illustrating a configuration example of a store manager terminal according to an embodiment of the present disclosure.

[0029] Figure 18 is a schematic diagram illustrating a configuration example of a general user terminal according to an embodiment of the present disclosure.

[0030] Figure 19 is a flowchart illustrating an information processing procedure according to an embodiment of the present disclosure.

[0031] Figure 20 is a flowchart illustrating an information processing procedure according to an embodiment of the present disclosure.

[0032] Figure 21 is a flowchart illustrating an information processing procedure according to an embodiment of the present disclosure.

[0033] Figure 22 is a flowchart illustrating an information processing procedure according to an embodiment of the present disclosure.

[0034] Figure 23 is a flowchart illustrating an information processing procedure according to an embodiment of the present disclosure.

[0035] Figure 24 is a schematic diagram illustrating an example of a conceptual diagram of a configuration of an information processing system.

[0036] Figure 25 is a diagram illustrating an example of a user interface according to an embodiment.

[0037] Figure 26 is a diagram illustrating an example of a user interface according to an embodiment.

[0038] Figure 27 is a schematic diagram showing an example of display information.

[0039] Figure 28 is a schematic diagram showing an example of display information.

[0040] Figure 29 is a schematic diagram showing an example of display information.

[0041] Figure 30 is a schematic diagram showing an example of display information.

[0042] Figure 31 is a hardware configuration diagram showing an example of a computer that realizes the functions of an information processing device and a terminal device. DETAILED DESCRIPTION

[0043] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. Note that the information processing device, information processing method, and information processing program according to the present application are not limited to the embodiments. In the following embodiments, the same parts are represented by the same reference numerals to omit repeated descriptions.

[0044] The present disclosure will be described according to the following item order.

[0045] 1. Example

[0046] 1-1. Overview of Information Processing According to Embodiments of the Present Disclosure

[0047] 1-1-1. Example of usage pattern of model according to embodiment

[0048] 1-1-2. Example of Model According to Embodiment

[0049] 1-1-3. Model selection example

[0050] 1-1-4. Model sales and sharing model

[0051] 1-1-5. Automatic generation of metadata

[0052] 1-1-6. Providing models for data providers

[0053] 1-1-7. Providing information to users

[0054] 1-1-8. Listening Service

[0055] 1-1-9. User-Provided Data

[0056] 1-2. Configuration of Information Processing System According to Embodiment

[0057] 1-3. Configuration of Information Processing Device According to Embodiment

[0058] 1-4. Configuration of Terminal Device According to Embodiment

[0059] 1-4-1. Configuration of the System Administrator Terminal According to the Embodiment

[0060] 1-4-2. Configuration of the Store Manager Terminal According to the Embodiment

[0061] 1-4-3. Configuration of a general user terminal according to an embodiment

[0062] 1-5. Information Processing Process According to the Embodiment

[0063] 1-5-1. General user registration and sharing of learning model information

[0064] 1-5-2. Registration and sales registration of learning model information by the system administrator

[0065] 1-5-3. The process of browsing and selecting shared lists of learning model information by ordinary users

[0066] 1-5-4. Process of store manager entrusting sales and system administrator accepting entrustment

[0067] 1-6. Information Processing System Configuration Concept Diagram

[0068] 1-6-1. Overall configuration

[0069] 1-6-2. Server Equipment

[0070] 1-6-3. System Administrator

[0071] 1-6-4. Store Manager

[0072] 1-6-5. Ordinary users

[0073] 1-6-6. Configuration and Effect

[0074] 1-7. User Interface (UI)

[0075] 1-8. Information Display

[0076] 1-8-1. Screen example of the created score data list

[0077] 1-8-2. Example of creating a StylePallete

[0078] 1-8-3. Screen example showing a list of sales registration templates

[0079] 1-8-4. Screen example showing a list of self-managed style sheets

[0080] 2. Other embodiments

[0081] 2-1. Other configuration examples

[0082] 2-2. Others

[0083] 3. Effects of the present disclosure

[0084] 4. Hardware Configuration

[0085] [1. Example]

[0086] [1-1. Overview of Information Processing According to an Embodiment of the Present Disclosure]

[0087] Figure 1is a schematic diagram showing an example of information processing according to an embodiment of the present disclosure. The information processing according to an embodiment of the present disclosure is implemented by an information processing device 100. In the following example, a case will be described in which the information processing device 100 is a server device (service device) that provides services related to the creation of content as a work (also simply referred to as "service"). Note that in the following description, music (music content) will be described as an example of content, but the content is not limited to music and can be various types of content, including video content such as movies and text content such as books (novels, etc.). In addition, the music referred to herein is not limited to a complete piece of music (whole music), but includes a concept of a part of the sound source that constitutes a piece of music (music) and various other music information (such as a small piece of sound for sampling).

[0088] In addition, Figure 1 In the example in FIG. 1 , the information processing device 100 uses a network N such as the Internet (see FIG. Figure 7 ) communicates with the terminal device of the user who uses the service provided by the information processing device 100.

[0089] Hereinafter, as an example, a case will be described in which three levels of authority are granted to each user according to the usage pattern of each user subject (user) of the service provided by the information processing device 100. Among the users, a user having system administrator authority is specifically described as a system administrator, a user having store manager authority is specifically described as a store manager, and a user having ordinary user authority is specifically described as an ordinary user.

[0090] The system administrator authority corresponds to the first level of authority (also referred to as "first authority") granted to the administrator (system administrator) of the services provided by the information processing device 100. For example, a system administrator with first authority operates and manages the entire information processing system 1 as a learning model information sharing and sales system. The information processing device 100 communicates with the system administrator terminal 10 used by the system administrator.

[0091] The store manager authority corresponds to the second level of authority (also referred to as "second authority") granted to sellers (store managers) who sell content through the services provided by the information processing device 100. If the content (work information) is music (music information), store managers with second authority are, for example, music publishers, record labels, and DAW software distributors. The information processing device 100 communicates with the store manager terminal 20 used by the store manager.

[0092] Ordinary user authority corresponds to the third authority level (also referred to as "third authority") granted to users (ordinary users) who use the services provided by the information processing device 100. Ordinary users with the third authority are, for example, ordinary users who use the service. Ordinary users include various users, including so-called end users, users who use services (tools) for free, and users who subscribe to use services. The information processing device 100 communicates with the ordinary user terminal 30 used by ordinary users. In the following, it will be described that the first authority level has the broadest authority, the second authority level has more restricted authority than the first authority level, and the third authority level has more restricted authority than the second authority level. As mentioned above, the case where the first authority level to the third authority level have a hierarchical relationship will be described below. Note that the relationship between the authority levels is not limited to the above case, and the authority levels may not have overlapping ranges.

[0093] It is assumed that software (also referred to as "application" or "app") for realizing an integrated music production environment is installed in the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. Note that, when not specifically distinguished, the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30 may be referred to as terminal devices. For example, the application may be an application (music application) related to various types of music, such as a digital audio workstation (DAW). It should be noted that the application referred to here is not limited to music applications such as DAW, and may be any software as long as it is applicable, or may be an operating system (OS) such as Android (registered trademark) or iOS (registered trademark).

[0094] In addition, the terminal device has an AI-based automatic music composition function by using the extended functions of applications such as DAWs. The terminal device has an AI-based automatic music composition function by using plug-ins (extension applications) added to applications such as DAWs through plug-in functions. For example, plug-ins (extension applications) can be in the form of Steinberg Virtual Studio Technology (VST) (registered trademark), Audio Compound, Avid Audio Extensions (AAX), etc.

[0095] The following will be combined Figure 1 Explain the specific process. Figure 1 In the example of , the description will be based on the case where a DAW is installed as an example of an application in each user's terminal device. Figure 1 Describes the overview of information processing in each device. Figures 2 to 7 Describes the specific details of the usage pattern.

[0096] Figure 1The example in FIG shows a case where the information processing device 100 generates a learning model (also referred to as a "model") using data provided by a user and determines the usage mode of the generated model according to the authority of the user who provided the data. The learning model here can be any model, Figure 1 The example in shows a case where the learning model is a model (style palette) for automatically composing music. The details of the learning model such as the style palette (StylePallete) will be described later.

[0097] The information processing device 100 acquires data for generating a learning model from the system administrator terminal 10 used by the system administrator SM1 (step S11). The system administrator SM1 operates the system administrator terminal 10 to send the data for generating a learning model to the information processing device 100. Figure 1 In the example of FIG. 1 , the system administrator terminal 10 sends data DT11 (see FIG. 1 ) to the information processing device 100. Figure 2 ). Therefore, the information processing apparatus 100 acquires data for generating a learning model from the system administrator terminal 10 used by the system administrator SM1 having the first authority level.

[0098] Then, the information processing device 100 generates a learning model using the data provided by the system administrator SM1 (step S12). Figure 1 In the example of FIG. 1 , the information processing device 100 generates a learning model MD11 using data DT11 provided by the system administrator SM1 (see FIG. 1 ). Figure 2 ).

[0099] Then, the information processing device 100 determines the usage pattern of the generated learning model (step S13). The information processing device 100 determines the usage pattern of the generated learning model according to the authority level of the system administrator SM1 as the data provider. Figure 1 In the example of , the information processing device 100 determines the usage pattern of the learning model MD11 according to the first authority level which is the authority level of the system administrator SM1. The information processing device 100 determines that the learning model MD11 can be used in the service corresponding to the first authority level.

[0100] For example, the information processing device 100 can determine the usage pattern of the generated learning model by using information (authority range information) indicating the available range corresponding to each of the first to third authority levels. In this case, the information processing device 100 can determine the usage pattern of the generated learning model by using the information stored in the storage unit 120 (see Figure 6 ) determines the usage mode of the generated learning model. For example, as a usage mode of the first permission level, a model generated using data of a user (system administrator) assigned the first permission level can be sold and shared.

[0101] Furthermore, for example, in a usage mode of the second permission level, for a model generated using data from a user assigned the second permission level (store manager), it is possible to delegate sales and sharing. For example, in a usage mode of a model generated using data from a user assigned the second permission level (store manager), the sales of the model can be delegated to a user assigned the first permission level (system administrator), or the model can be shared by the user himself / herself. In a usage mode of a model generated using data from a user assigned the third permission level, only sharing is possible.

[0102] In this case, in the permission range information, information indicating that sales and sharing are possible is associated with a first permission level, information indicating that sales and sharing can be delegated is associated with a second permission level, and information indicating that sharing is possible is associated with a third permission level. For example, the permission range information includes first information associated with the first permission level using the modes "sales" and "sharing", second information associated with the second permission level using the modes "delegated sales" and "sharing", and third information associated with the third permission level using the mode "sharing".

[0103] Since learning model MD11 is assigned the first permission level, which is the permission level of system administrator SM1, information processing device 100 determines that learning model MD11 can be sold or shared. For example, information processing device 100 uses permission range information to determine that learning model MD11 can be sold or shared. For example, information processing device 100 may store information indicating that the usage mode is selling and sharing in association with learning model MD11 in storage unit 120.

[0104] Furthermore, the information processing device 100 acquires data for generating a learning model from the store manager terminal 20 used by the store manager SP1 (step S21). The store manager SP1 operates the store manager terminal 20 to send the data for generating a learning model to the information processing device 100. Figure 1 In the example of FIG. 1 , the store manager terminal 20 sends data DT12 to the information processing device 100 (see FIG. Figure 2 ). Therefore, the information processing apparatus 100 acquires data for generating a learning model from the store manager terminal 20 used by the store manager SP1 assigned the second authority level.

[0105] Then, the information processing device 100 generates a learning model using the data provided by the store manager SP1 (step S22). Figure 1 In the example of FIG. 1 , the information processing device 100 generates a learning model MD12 using data DT12 provided by the store manager SP1 (see FIG. 1 ). Figure 2 ).

[0106] Then, the information processing device 100 determines the usage pattern of the generated learning model (step S23). The information processing device 100 determines the usage pattern of the generated learning model according to the authority level of the store manager SP1 as the data provider. Figure 1 In the example of , the information processing device 100 determines the usage pattern of the learning model MD12 according to the second authority level which is the authority level of the shop manager SP1. The information processing device 100 determines that the learning model MD12 can be used in the service corresponding to the second authority level.

[0107] Since the learning model MD12 is assigned the second permission level, which is the permission level of the store manager SP1, the information processing device 100 determines that it is feasible to entrust the sale or sharing of the learning model MD12 to the first permission level user (system administrator). For example, the information processing device 100 uses the permission range information to determine that the learning model MD12 can be entrusted to the first permission level user (system administrator) for sale or sharing. For example, the information processing device 100 can store in the storage unit 120 information indicating that the usage mode is to entrust the sale or sharing to the first permission level user (system administrator) in association with the learning model MD12.

[0108] In addition, the information processing device 100 acquires data for generating a learning model from the ordinary user terminal 30 used by the ordinary user U1 (step S31). The ordinary user U1 operates the ordinary user terminal 30 to send the data for generating a learning model to the information processing device 100. Figure 1 In the example of FIG. 1 , the ordinary user terminal 30 sends data DT13 to the information processing device 100 (see FIG. Figure 2 ). Therefore, the information processing device 100 acquires data for generating a learning model from the general user terminal 30 used by the general user U1 assigned the third authority level.

[0109] Then, the information processing device 100 generates a learning model using the data provided by the general user U1 (step S32). Figure 1 In the example of FIG. 1 , the information processing device 100 generates a learning model MD13 using data DT13 provided by an ordinary user U1 (see FIG. 1 ). Figure 2 ).

[0110] Then, the information processing device 100 determines the usage pattern of the generated learning model (step S33). The information processing device 100 determines the usage pattern of the generated learning model according to the authority level of the general user U1 as the data provider. Figure 1In the example of , the information processing device 100 determines the usage pattern of the learning model MD13 according to the third authority level which is the authority level of the general user U1. The information processing device 100 determines that the learning model MD13 can be used in the service corresponding to the third authority level.

[0111] Since the learning model MD13 is assigned the third permission level, which is the permission level of the ordinary user U1, the information processing device 100 determines that only sharing is available for the learning model MD13. For example, the information processing device 100 uses the permission range information to determine that only sharing is available for the learning model MD13. For example, the information processing device 100 may store information indicating that the usage mode is shared in association with the learning model MD13 in the storage unit 120. Note that steps S11 to S33 are convenient reference marks for explaining the process. For example, the process in steps S31 to S33 may be performed before steps S11 to S23, or the process in steps S21 to S23 may be performed before steps S11 to S13.

[0112] As described above, the information processing device 100 determines the usage mode of the generated model according to the authority level of the provider of the data used to generate the model. Therefore, the information processing device 100 can appropriately use the model according to the data used to generate the model.

[0113] [1-1-1. Example of usage pattern of model according to embodiment]

[0114] The following will be combined Figures 2 to 6 The usage mode of the model according to the embodiment will be described in detail. Figures 2 to 6 is a diagram showing an example of a usage pattern of a model according to an embodiment of the present disclosure. Figures 2 to 6 In, with Figure 1 The same points are denoted by the same reference numerals and the like, and description thereof will be appropriately omitted.

[0115] First, refer to Figure 2 An overview of the usage pattern of a model that uses data for each user is described. Figure 2 is a schematic diagram illustrating a usage example of domains (areas) in the information processing apparatus 100 .

[0116] like Figure 2 As shown, the system administrator terminal 10, which is a terminal device used by a system administrator with a first authority level, provides the information processing device 100 with data DT11 for generating a learning model (step S41). For example, the system administrator inputs information into the Figure 28The screen IM21 shown is displayed, thereby providing the information processing device 100 with data DT11 for generating a style plate (learning model). Therefore, the information processing device 100 accepts the data DT11. The information processing device 100 that has accepted the provided data DT11 uses the data DT11 to generate a learning model MD11 (step S42). Here, since the provider of the data DT11 is a system administrator with a first authority level, the information processing device 100 generates a learning model MD11 in the administrator area AR11. The administrator area AR11 is an area (domain) that can be used by users of the first authority level. For example, the administrator area AR11 is an area that cannot be accessed by users with authority levels other than the first authority level. For example, an administrator area AR11 can be provided for each first authority level user. For example, in the case where there are multiple first authority level users, multiple administrator areas AR11 can be provided. In this case, each administrator area AR11 can be a domain that can only be accessed by users of the corresponding first authority level.

[0117] Note that the areas (domains) referred to here may be physically divided areas or logically divided areas. For example, each of the shared area AR1, the administrator area AR11, the personal area AR12, and the personal area AR13 may be an area (partition) obtained by virtually (logically) dividing the physical hard disk included in the information processing device 100 into a plurality of hard disks.

[0118] Then, the information processing device 100 determines the usage pattern of the learning model MD11 (step S43). For example, the information processing device 100 determines to sell the learning model MD11 based on the designation of the system administrator as the data provider. The information processing device 100 configures the learning model MD11 as the learning model MD11 for sale in the shared area AR1. In this way, the system administrator can create learning data and sell the learning data in the shared area. For example, the shared area AR1 is a shared area that can be used by all users with the first authority level to the third authority level. For example, the data arranged in the shared area AR1 can be accessed by all users with the first authority level to the third authority level.

[0119] Furthermore, the store manager terminal 20, which is a terminal device used by a store manager with the second authority level, provides the information processing device 100 with data DT12 for generating a learning model (step S44). For example, the store manager inputs information into the Figure 28The screen IM21 shown thereby provides the information processing device 100 with data DT12 for generating a style plate (learning model). Therefore, the information processing device 100 accepts the data DT12. The information processing device 100, having accepted the provided data DT12, uses the data DT12 to generate a learning model MD12 (step S45). Here, since the provider of the data DT12 is a store manager with a second authority level, the information processing device 100 generates a learning model MD12 in the personal area AR12. It is assumed that the personal area AR12 is an area (domain) available to users with a second authority level. For example, the personal area AR12 is a domain that cannot be accessed by users with an authority level other than the second authority level. For example, a personal area AR12 can be provided to each second authority level user. For example, when there are ten users with a second authority level, ten personal areas AR12 can be provided. In this case, each personal area AR12 is an area that can only be accessed by the corresponding second authority level user.

[0120] The information processing device 100 then determines the usage pattern of the learning model MD12 (step S46). For example, the information processing device 100 determines to make the learning model MD12 public based on the designation of the store manager as the data provider. The information processing device 100 determines to enable sharing of the learning model MD12 based on the designation of the store manager as the data provider. The information processing device 100 configures the learning model MD12 as a public learning model MD12 in the sharing area AR1. In this way, the store manager can create and publish learning data.

[0121] Furthermore, the general user terminal 30, which is a terminal device used by a general user having the third authority level, provides the information processing device 100 with data DT13 for generating a learning model (step S47). Figure 28The screen IM21 shown inputs information, thereby providing the information processing device 100 with data DT13 for generating a style plate (learning model). Therefore, the information processing device 100 accepts the data DT13. The information processing device 100, which has accepted the provided data DT13, uses the data DT13 to generate a learning model MD13 (step S48). Here, since the provider of the data DT13 is an ordinary user with a third authority level, the information processing device 100 generates a learning model MD13 in the personal area AR13. The personal area AR13 is an area (domain) that can be used by users of the third authority level. For example, the personal area AR13 is a domain that users with authority levels other than the third authority level cannot access. For example, a personal area AR13 can be provided for each third authority level user. For example, when there are 500 third-level authority users, 500 personal areas AR13 can be provided. In this case, each personal area AR13 is a domain that can only be accessed by the corresponding third authority level user.

[0122] Then, the information processing device 100 determines the usage pattern of the learning model MD13 (step S49). For example, the information processing device 100 determines to make the learning model MD13 public based on the designation of the ordinary user as the data provider. The information processing device 100 determines to enable sharing of the learning model MD13 based on the designation of the ordinary user as the data provider. The information processing device 100 configures the learning model MD13 as a public learning model MD13 in the sharing area AR1. In this way, ordinary users can create and disclose learning data. Note that steps S41 to S49 are convenient reference marks for explaining the process. For example, the processes in steps S47 to S49 can be performed before steps S41 to S46, or the processes in steps S44 to S46 can be performed before steps S41 to S43.

[0123] Next, we will refer to Figure 3 Describes how ordinary users use the store manager model. Figure 3 is a diagram showing an example of a general user using a store manager model. Figure 2 The same points are denoted by the same reference numerals and the like, and description thereof will be appropriately omitted.

[0124] exist Figure 3In the example, an ordinary user with a third authority level requests to use the public learning model MD12 disclosed by a store manager with a second authority level. In addition, when an ordinary user discloses his or her own learning model, the ordinary user can also use the learning models disclosed by other users. For example, when an ordinary user discloses one learning model, the ordinary user can use, for example, three learning models. In this case, the ordinary user can use three times the number of learning models disclosed by other users as the number of learning models disclosed by him / herself. Each user can browse information, etc. without restriction, such as by searching through a directory. For example, the information processing device 100 stores the learning model disclosed by each ordinary user and the learning model used by another user in association with each other in the storage unit 120. For example, the information processing device 100 can provide various types of information (such as Figures 27 to 30 The screens IM11 to MI41 shown are sent to the ordinary user terminal 30.

[0125] exist Figure 3 In the example, since the general user has disclosed the public learning model MD13, the use of the public learning model MD12 is permitted. Therefore, the information processing device 100 provides the general user with the public learning model MD12 (step S51). For example, the information processing device 100 provides the public learning model MD12 to the personal area AR13 corresponding to the general user. Therefore, the general user can use the public learning model MD12 generated by the store manager.

[0126] Next, refer to Figure 4 , which will explain that the store manager has entrusted the system administrator to sell the model. Figure 4 This is a diagram showing an example of a store manager entrusting a system administrator to sell a model. Figure 2 and Figure 3 The same points are denoted by the same reference numerals and the like, and description thereof will be appropriately omitted.

[0127] exist Figure 4 In the example shown in FIG. 1 , the store manager terminal 20, which is a terminal device used by a store manager with the second level of authority, provides the information processing device 100 with data DT22 for generating a learning model (step S61). Therefore, the information processing device 100 accepts the data DT22. Having accepted the provided data DT22, the information processing device 100 generates a learning model MD22 using the data DT22 (step S62). The information processing device 100 generates the learning model MD22 in the personal area AR12.

[0128] The store manager then requests the system administrator, who has the first level of authority, to consign the learning model MD22 for sale (step S63). In this way, the store manager can create learning data and consign the sales to the system administrator. For example, in response to a request from the store manager for consignment sale of the learning model MD22, the information processing device 100 notifies the system administrator of the existence of the consignment sale request for the learning model MD22. The information processing device 100 can then obtain information from the system administrator indicating that the consignment sale of the learning model MD22 has been accepted.

[0129] Then, the system administrator requests the information processing device 100 to sell the learning model MD22 entrusted for sale. The information processing device 100 configures the learning model MD22 entrusted for sale as the learning model MD22 for sale in the shared area AR1 (step S64). In this way, the system administrator (system management user) can sell the learning data entrusted by the store manager (special user) in the shared area. In this way, the system administrator can sell the learning data entrusted by the store manager. Then, the information processing device 100 distributes the income obtained from the sale of the learning model MD22 for sale to the store manager based on the sales volume of the learning model MD22 for sale (step S65). The store manager can obtain income based on the sales volume of the learning model MD22 for sale.

[0130] Next, we will refer to Figure 5 Indicates that a normal user purchases another user's model. Figure 5 is a diagram showing an example of a general user purchasing a system administrator model. Figures 2 to 4 The same points are denoted by the same reference numerals and the like, and description thereof will be appropriately omitted.

[0131] exist Figure 5 In the example shown in FIG2 , a regular user with the third permission level requests to purchase the learning model MD11 sold by the system administrator with the first permission level. Alternatively, regular users can purchase learning models sold. Note that the purchase mode can be a single purchase or a subscription purchase of individual learning models. Note that every user can browse sales data without restriction.

[0132] exist Figure 5In the example, the ordinary user purchases the learning model MD11 by paying the selling price of the learning model MD11 for sale. Note that the payment is performed through an appropriate settlement process, such as electronic payment. Then, the information processing device 100 provides the learning model MD11 for sale to the ordinary user (step S71). For example, the information processing device 100 provides the learning model MD11 for sale to the personal area AR13 corresponding to the ordinary user. Therefore, the ordinary user can use the learning model MD11 for sale sold by the system administrator. Note that the same process is also performed in the case where the model purchased by the ordinary user is the learning model MD22 for sale commissioned by the system administrator.

[0133] Next, we will refer to Figure 6 Describes a store manager's use of another user's model. Figure 6 is a diagram showing an example of a store manager using a system administrator's model and a general user's model. Figures 2 to 5 The same points are denoted by the same reference numerals and the like, and description thereof will be appropriately omitted.

[0134] exist Figure 6 In the example of , a store manager with a second authority level requests to use the learning model MD11 for sale sold by a system administrator with a first authority level. Here, the store manager can use all public learning data and learning data for sale without restriction. Therefore, the information processing device 100 provides the learning model MD11 for sale to the store manager (step S81). For example, the information processing device 100 provides the learning model MD11 for sale to the personal area AR12 of the corresponding store manager. Therefore, the store manager can use the learning model MD11 for sale sold by the system administrator.

[0135] In addition, Figure 6 In the example of , the store manager requests to use the public learning model MD13 disclosed by an ordinary user with the third authority level. As described above, the store manager can use all public learning data and learning data for sale without restriction. Therefore, the information processing device 100 provides the public learning model MD13 to the store manager (step S82). For example, the information processing device 100 provides the public learning model MD13 to the personal area AR12 corresponding to the store manager. Therefore, the store manager can use the public learning model MD13 disclosed by ordinary users.

[0136] As described above, the information processing device 100 shares and sells the learning model according to the authority level of each user. Therefore, the information processing device 100 can provide each user with a service corresponding to the authority level of each user.

[0137] Conventional technology lacks a means for sharing only learning data (learning models) while securely protecting the work itself. Furthermore, there is no means for selling or consigning learning data (learning models). Furthermore, there is no means for granting store managers, who are users other than ordinary users and system administrators, the authority to execute processing based on each authority.

[0138] On the other hand, in information processing system 1, learning models generated using content can be shared while securely protecting the content itself, such as works created by users themselves. Furthermore, in information processing system 1, any of the first to third permission levels are granted to users based on their attributes, allowing them to sell or share each model according to their permission level. Consequently, information processing system 1 is able to appropriately use the model based on the data used to generate it.

[0139] [1-1-2. Example of model according to embodiment]

[0140] As described above, the learning model applicable to the information processing system 1 can be any model. The information processing device 100 can use various technologies related to machine learning to generate a learning model. For example, the information processing device 100 can use a music generation algorithm that utilizes a Markov chain. The information processing device 100 can generate a learning model using Markov chain technology. In addition, the information processing device 100 can use a music generation algorithm that utilizes deep learning. For example, the information processing device 100 can use a recursive neural network technology such as a recursive neural network (RNN) to generate a learning model. For example, the information processing device 100 can generate a learning model using reinforcement learning technology. Note that the description of model generation is an example, and the generation of the model can be performed by a suitable learning method selected based on available information, etc. First, a style board is described as an example of a learning model.

[0141] A style plate is a learning model generated based on data. For example, a style plate is a learning model generated based on music score data including melody, chord progression, and the like. The information processing device 100 can generate a style plate by using data (learning music data) including information such as melody, chord progression, and bass as a data set (learning data set). The information processing device 100 stores the data set in association with the style plate. The information processing device 100 can generate a style plate for automatically creating music data (also referred to as "music") in response to input of predetermined information. For example, the music data automatically created by the style plate may include information such as chord progression, melody, and bass progression. The music data may be standard data, such as Musical Instrument Digital Interface (MIDI) data, waveform data, or DAW unique standard data.

[0142] For example, the user can instruct the information processing device 100 to generate a style plate (learning model) by inputting information in the generation screen of the style plate (learning model), such as Figure 28 For example, the user can select music data (learning music data) for generating a pattern board from his / her music data list, as shown in FIG. Figure 27 shown.

[0143] For example, the information processing device 100 can generate a style plate (cheerful tune plate) for automatically creating music data with cheerful melodies by using music data with cheerful melodies as learning music data. Furthermore, for example, the information processing device 100 can generate a style plate (melancholic tune plate) for automatically creating music data with melancholic melodies by using music data with melancholic melodies as learning music data. Furthermore, for example, the information processing device 100 can generate a style plate (melody plate for automatically creating music data corresponding to a predetermined chord progression) by using music data corresponding to a predetermined chord progression as learning music data. Note that the style plate is not limited to the above case, and it can be a tune plate corresponding to a music category or type (e.g., "American"), or a tune plate corresponding to a music configuration, such as "verse → bridge → chorus".

[0144] For example, each style board automatically creates music having features corresponding to the data (music) used for generation. Here, each style board is a learning model generated based on music data having various features. For example, the cheerful tune board is a learning model generated by machine learning using music data having cheerful melodies, while the melancholic tune board is a learning model generated by machine learning using music data having melancholic melodies, and the two are different. Therefore, the music to be automatically created changes according to the style board selected by the user. Therefore, the user can automatically create the desired music by selecting a style board according to his / her needs.

[0145] For example, the information processing device 100 can generate a pattern plate for automatically creating a plurality of music data at random in response to an instruction for automatic creation. For example, the information processing device 100 can generate a pattern plate (cheerful tune plate) that automatically creates a plurality of music data with cheerful melodies at random in response to an instruction for automatic creation. For example, the information processing device 100 can generate a pattern plate (melancholic tune plate) that automatically creates a plurality of music data with melancholic melodies at random in response to an instruction for automatic creation. For example, the information processing device 100 can generate a pattern plate (melody tune plate created based on chord progression) that automatically creates music data corresponding to a plurality of predetermined chord progressions at random in response to an instruction for automatic creation.

[0146] The information processing device 100 can use Figure 25The information processing device 100 can generate a pattern plate using information (parameters) corresponding to the setting information ST12 to ST14 shown in FIG. The information processing device 100 can generate a pattern plate using parameters corresponding to harmony, note duration, etc. For example, the information processing device 100 can generate a pattern plate using predetermined information as input. For example, the information processing device 100 can generate a pattern plate using parameters corresponding to Figure 25 The information (parameters) corresponding to the setting information ST12 to ST14 shown are used as input to generate a pattern plate. For example, by inputting parameters, the information processing device 100 can generate a pattern plate for automatically composing a plurality of pieces of music data at random. Note that the above description is an example, and the pattern plate can be a learning model that outputs any information, as long as the user can automatically compose music using the learning model.

[0147] Next, various types of information processing using a learning model (eg, a pattern board) will be described.

[0148] [1-1-3. Model selection example]

[0149] First, the selection of a learning model (style board) to be used by the user will be explained. Figure 29 and Figure 30 The user selects the style palette they wish to use from the displayed style palette list. The user then selects an image that matches the music automatically created using the style palette. For example, if the user wishes to automatically create music with an upbeat melody, the user selects an upbeat palette. For example, if the user wishes to automatically create music with a melancholic melody, the user selects a melancholic palette. For example, if the user wishes to automatically create music corresponding to a predetermined chord progression, the user selects a palette created based on that chord progression.

[0150] Note that the user can select multiple style plates when selecting a style plate. For example, the user can select a first style plate to compose a portion of music (e.g., the first eight bars) and use a second style plate different from the first style plate to compose a different portion of the music (e.g., the middle eight bars). Information including such multiple style plates is hereinafter referred to as a style plate sequence. In other words, a style plate sequence is combined designation information created by combining designation information for specifying a piece of music called a style plate. The user can compose music by setting a style plate sequence, making it easy to compose various music data with multiple features in one piece of music.

[0151] [1-1-4. Model sales and sharing model]

[0152] The information processing device 100 can sell or share each learning model (style board) individually. In addition, the information processing device 100 can sell or share multiple style boards as a bundle. The information processing device 100 can sell or share 20 style boards generated based on the music of a specific artist as a bundle. For example, the information processing device 100 can sell or share a bundle corresponding to the name #002, including Figure 30 Multiple style plates are shown, such as style plates SP#101, SP#055, SP#007 and SP#300.

[0153] [1-1-5. Automatically generate meta information]

[0154] The information processing device 100 can generate meta-information for the learning model. For example, the information processing device 100 generates meta-information corresponding to the model based on data provided by a user. For example, if the provided music data is music with a melancholic melody, the information processing device 100 can generate meta-information including information indicating the melancholic melody as meta-information for the style board to be generated. For example, if the provided music data is music corresponding to a specific chord progression, the information processing device 100 can generate meta-information including information indicating the specific chord progression as meta-information for the style board to be generated.

[0155] [1-1-6. Providing models to data providers]

[0156] The information processing device 100 may transmit the model to the terminal device used by the user subject acting as the data provider. Upon completion of model generation, the information processing device 100 may transmit the model to the terminal device used by the user subject acting as the data provider. For example, the information processing device 100 may generate the model upon receiving data, and upon generation, transmit the model to the terminal device used by the user subject acting as the data provider.

[0157] For example, information processing device 100 can generate a style sheet upon receiving data and, upon generating the style sheet, send the style sheet to a terminal device used by a user entity serving as a data provider. In this manner, upon receiving a request to generate a style sheet, information processing device 100 generates the style sheet and sends the generated style sheet to the terminal device. For example, because generating a style sheet takes less time than, for example, learning another generated model, information processing device 100 can execute the process from receiving a request to generating and sending the style sheet in a short period of time.

[0158] [1-1-7. Providing information to users]

[0159] The information processing device 100 can provide various types of information to the user. For example, the information processing device 100 can provide various types of information to the user in response to a request from the user. The information processing device 100 can determine the information to be provided to the user based on the user's service usage history.

[0160] The information processing device 100 may determine a plurality of models based on the user's service usage history to provide information to the user. In this case, the information processing device 100 generates list information of the determined plurality of models and transmits the list information to the user's terminal device.

[0161] The information processing device 100 can determine a model (recommended model) recommended to the user based on the behavior history or preference of each user. The information processing device 100 determines a recommended model recommended to the user from among a plurality of models.

[0162] [1-1-8. Listening Service]

[0163] As described above, when the content is music, the information processing device 100 can provide a listening service to the user. For example, the information processing device 100 can provide a listening service for music produced while using a model.

[0164] In the case of providing a listening service, the information processing device 100 can accept the user's selection of a style board and allow the user to listen to music automatically composed using the accepted style board. Therefore, the user can confirm what kind of music will be composed.

[0165] [1-1-9. User-provided data]

[0166] If the user-provided data meets the predetermined conditions, the information processing device 100 may not register the data. For example, if a user requests to register content that has copyrights owned by another entity as user-provided data, the information processing device 100 may not perform the registration. For example, if a user requests to register a certain artist's music (Music X) as user-provided data, the information processing device 100 may reject the registration.

[0167] In this case, the information processing device 100 may notify the user who requested registration that the registration was rejected. For example, the information processing device 100 may determine whether the content for which the user requested registration is copyrighted by another entity by referencing a predetermined database. For example, the information processing device 100 may provide the content for which the user requested registration to an external service provider that provides a service for determining whether copyright exists, and the information processing device 100 may determine whether another entity owns the copyright to the content by using the determination result received from the external service provider.

[0168] [1-2. Configuration of information processing system according to embodiment]

[0169] The following will explain Figure 7 The information processing system 1 shown. Figure 7 : is a schematic diagram showing a configuration example of an information processing system according to an embodiment of the present disclosure. Figure 7 As shown, information processing system 1 includes information processing device 100, system administrator terminal 10, store manager terminals 20-1 to 20-3, and general user terminals 30-1 to 30-3. Information processing system 1 functions as a work management system, a learning model information management system, a learning model information sharing system, a learning model information sales system, and a learning model information sharing and sales system.

[0170] exist Figure 7 In the example in FIG, three store manager terminals 20-1, 20-2, and 20-3 are shown, but they are referred to as store manager terminals 20 when not specifically distinguished. The number of store manager terminals 20 included in the information processing system 1 is not limited to three, and may be more or less than three. Figure 7 In the example of FIG, three general user terminals 30-1, 30-2, and 30-3 are shown, but when not specifically distinguished, they are referred to as general user terminals 30. The number of general user terminals 30 included in the information processing system 1 is not limited to three, and may be more or less than three. In addition, the information processing system 1 may include a plurality of information processing devices 100 and a plurality of system administrator terminals 10. The information processing devices 100, the system administrator terminals 10, the store manager terminals 20, and the general user terminals 30 are communicably connected in a wired or wireless manner via a predetermined communication network (network N).

[0171] The information processing device 100 provides services related to content creation. The information processing device 100 generates a model for content creation using data provided by a service user subject, and determines a usage pattern for the generated model based on the user subject's authority level. The information processing device 100 sends information to and receives information from a system administrator terminal 10 used by a system administrator who is a service user subject. The information processing device 100 sends information to and receives information from a store manager terminal 20 used by a store manager who is a service user subject. The information processing device 100 sends information to and receives information from an ordinary user terminal 30 used by an ordinary user who is a service user subject.

[0172] The system administrator terminal 10 is a terminal device (information processing device) used by a system administrator with first authority. The system administrator terminal 10 is used, for example, by the system administrator to operate and manage the entire information processing system 1. The system administrator terminal 10 may be, for example, a device such as a smartphone, a tablet terminal, a laptop computer (PC), a desktop computer, a mobile phone, or a personal digital assistant (PDA). Figures 1 to 6 The example shows a case where the system administrator terminal 10 is a notebook computer.

[0173] The store manager terminal 20 is a terminal device (information processing device) used by a store manager with the second authority. For example, a store manager uses the store manager terminal 20 to entrust the sale of music. The store manager terminal 20 can be, for example, a smartphone, tablet terminal, laptop computer, desktop computer, mobile phone, or personal digital assistant. Figures 1 to 6 The example shows a case where the store manager terminal 20 is a notebook computer.

[0174] The general user terminal 30 is a terminal device (information processing device) used by general users with the third permission. For example, general users use the general user terminal 30 to share or purchase music. The general user terminal 30 can be a device such as a smartphone, tablet terminal, laptop computer, desktop computer, mobile phone, or personal digital assistant. Figures 1 to 6 The example shows a case where the general user terminal 30 is a notebook computer.

[0175] Store manager authority corresponds to the second level of authority (also referred to simply as "second authority") granted to sellers (store managers) who sell content through the services provided by the information processing device 100. If the content (work information) is music (music information), store managers with second authority are, for example, music publishers, record labels, and DAW software distributors. The information processing device 100 communicates with the store manager terminal 20 used by the store manager.

[0176] The general user authority corresponds to the third level of authority (also referred to as "third authority") granted to users (general users) who use services provided by the information processing device 100. General users with the third authority are, for example, general users who use services. General users include various users, including so-called end users, users who use services (tools) for free, and users who subscribe to use services. The information processing device 100 communicates with the general user terminal 30 used by general users.

[0177] [1-3. Configuration of Information Processing Device According to Embodiment]

[0178] Next, a configuration of the information processing apparatus 100 as an example of an information processing apparatus that performs information processing according to the embodiment will be described. Figure 8 1 is a schematic diagram illustrating a configuration example of the information processing apparatus 100 according to an embodiment of the present disclosure.

[0179] like Figure 8 As shown, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. Note that the information processing device 100 may include an input unit (e.g., a keyboard or a mouse) for receiving various operations from an administrator of the information processing device 100 or the like, and a display unit (e.g., a liquid crystal display) for displaying various types of information.

[0180] The communication unit 110 is implemented by, for example, a network interface card (NIC) or the like. Then, the communication unit 110 is connected to the network N (see Figure 7 ) and sends and receives information with other information processing devices (such as the system administrator terminal 10, the store manager terminal 20 and the general user terminal 30).

[0181] The storage unit 120 is implemented by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. Figure 8 As shown, the storage unit 120 according to the embodiment includes a user information storage unit 121, a work information storage unit 122, a learning model information storage unit 123, a sales management information storage unit 124, a shared information storage unit 125, a purchase information storage unit 126, and an operation history information storage unit 127. Note that, although not shown, the storage unit 120 can store various types of information, such as images to be provided as image sources to the system administrator terminal 10.

[0182] The user information storage unit 121 according to an embodiment stores various types of information (user information) about a user. Figure 9 is a schematic diagram illustrating an example of a user information storage unit according to an embodiment of the present disclosure.

[0183] The user information storage unit 121 stores user information including a user ID, user meta information, and authority information. The user information storage unit 121 stores the user meta information and authority information corresponding to each user ID in association with each user ID.

[0184] The user ID represents identification information for uniquely specifying each user. For example, the user ID indicates identification information for uniquely specifying a user such as a system administrator, a store manager, or an ordinary user. User meta information is, for example, additional information about the user, such as the user's name and address.

[0185] The permission information stores, for example, values ​​for identifying permissions, such as system administrator permission information, store manager permission information, and ordinary user permission information. The permission information stores, for example, values ​​for identifying permissions, such as a value "1" for identifying a system administrator, a value "2" for identifying a store manager, and a value "3" for identifying an ordinary user. For example, when the corresponding user is a system administrator, a value corresponding to the system administrator permission information (for example, 1) is stored in the permission information. For example, when the corresponding user is a store manager, a value corresponding to the store manager permission information (for example, 2) is stored in the permission information. For example, when the corresponding user is an ordinary user, a value corresponding to the ordinary user permission information (for example, 3) is stored in the permission information.

[0186] Note that user information storage unit 121 is not limited to the above and can store various types of information depending on the purpose. User meta-information is not limited to name and address, and various information related to the user can be stored. For example, when the user is a natural person, user meta-information can store demographic information such as gender and age, as well as psychological attribute information.

[0187] The work information storage unit 122 according to the embodiment stores various information related to works (work information). Figure 10 is a schematic diagram illustrating an example of a work information storage unit according to the embodiment.

[0188] The work information storage unit 122 stores work information including a work ID, a creator ID, work meta information, and work content information. The work information storage unit 122 stores the creator ID, work meta information, and work content information corresponding to each work ID in association with each work ID.

[0189] The work ID is identification information used to uniquely identify a work. The creator ID is identification information used to uniquely identify the creator of the work. For example, the creator ID is identification information used to uniquely identify a user such as a system administrator, store manager, or ordinary user. Work meta-information includes information such as the song title, composer, age, and genre. Work content information includes information about the melody and chord progression of the music.

[0190] Note that the work information storage unit 122 is not limited to the above and can store various types of information according to the purpose. For example, the work meta information can store various additional information related to the work, such as information related to the date and time of creation of the work.

[0191] The learning model information storage unit 123 according to the embodiment stores information about the training model (learning model information). Figure 11is a schematic diagram illustrating an example of a learning model information storage unit according to an embodiment of the present disclosure.

[0192] The learning model information storage unit 123 stores learning model information including a learning model information ID, creator ID, meta-information of the learning model information, learning result information, work ID, sharing permission information, and sales permission information. The learning model information storage unit 123 stores the creator ID, meta-information of the learning model information, learning result information, work ID, sharing permission information, and sales permission information corresponding to each learning model information ID in association with each learning model information ID.

[0193] The learning model information ID indicates identification information for uniquely specifying the learning model information. The creator ID indicates identification information for uniquely specifying the creator of the corresponding learning model information. For example, the creator ID indicates identification information for uniquely specifying a user such as a system administrator, a store manager, or an ordinary user.

[0194] The meta-information of the learning model information is, for example, information indicating the characteristics of the piece to be learned. This meta-information includes information such as tempo, genre, and musical tones of cheerful or melancholic melodies; song structures such as hymns, bridge, and choruses; chord progressions, scales, and church music. The learning result information stores the results of processing performed by the learning processing unit (generation unit 132) and the like included in the information processing device 100. The piece ID indicates identification information for uniquely specifying each of the multiple pieces to be learned.

[0195] The sharing permission information indicates, for example, whether the corresponding learning model can be shared. For example, the sharing permission information stores a value that specifies and identifies whether the corresponding learning model can be shared. For example, if the corresponding learning model can be shared, a value of "1" indicating that sharing is possible is stored, and if the corresponding learning model cannot be shared, a value of "2" indicating that sharing is not possible is stored.

[0196] The sales availability information indicates, for example, whether the corresponding learning model can be sold. For example, the sales availability information stores a value for specifying and identifying whether the corresponding learning model can be sold. For example, when the corresponding learning model can be sold, a value "1" indicating that it can be sold is stored, and when the corresponding learning model cannot be sold, a value "2" indicating that it cannot be sold is stored.

[0197] Note that the learning model information storage unit 123 is not limited to the above and can store various types of information depending on the purpose. For example, in the meta-information of the learning model information, various types of additional information related to the learning model, such as information related to the date and time when the learning model was created, can be stored.

[0198] The sales management information storage unit 124 according to the embodiment stores various types of information (sales management information) regarding sales. Figure 12 is a schematic diagram illustrating an example of a sales management information storage unit according to an embodiment of the present disclosure.

[0199] The sales management information storage unit 124 stores sales management information including sales management information ID, sales price information, sales meta information, and learning model information ID. The sales management information storage unit 124 stores the sales price information, sales meta information, and learning model information ID corresponding to each sales management information ID in association with each sales management information ID.

[0200] The sales management information ID represents identification information for uniquely specifying the sales management information. The sales price information is, for example, information such as the sales price, tax, etc. The sales meta information is, for example, information such as the name of the sales product, the name of the sales company, etc.

[0201] The learning model information ID indicates identification information used to uniquely specify learning model information. For example, when the sales management information identified by the corresponding sales management information ID is a single product with one piece of learning model information, one learning model information ID is associated with that sales management information ID. For example, when the sales management information identified by the corresponding sales management information ID is a bundled product with multiple pieces of learning model information, multiple learning model information IDs are associated with that sales management information ID.

[0202] Note that the sales management information storage unit 124 is not limited to the above and can store various types of information according to the purpose. For example, the sales meta information can store various additional information related to sales, such as information related to the date and time of the start of sales.

[0203] The shared information storage unit 125 according to the embodiment stores various types of information (shared information) about sharing. The shared information storage unit 125 stores shared bookmark list information. For example, the shared information storage unit 125 stores list information of learning models to which shared bookmarks are added. Figure 13 is a schematic diagram illustrating an example of a shared information storage unit according to an embodiment of the present disclosure.

[0204] The shared information storage unit 125 stores shared information including user IDs and learning model information IDs. The shared information storage unit 125 stores the learning model information ID corresponding to each user ID in association with each user ID. The shared information storage unit 125 stores the learning model information ID used by the user identified by the user ID to identify the learning model added to the shared bookmark in association with each user ID.

[0205] The user ID indicates identification information for uniquely specifying each user. For example, the user ID indicates identification information for uniquely specifying a user such as a system administrator, a store manager, or an ordinary user.

[0206] The learning model information ID indicates identification information used to uniquely identify learning model information. For example, if a user identified by a corresponding user ID has added a shared bookmark to multiple learning models, the user ID is associated with multiple learning model information IDs. For example, if a user ID has not added a shared bookmark, the user ID is not associated with a learning model information ID.

[0207] Note that the shared information storage unit 125 is not limited to the above, and may store various types of information according to the purpose.

[0208] The purchase information storage unit 126 according to the embodiment stores information about purchases (purchase information). The purchase information storage unit 126 stores user purchase list information. For example, the purchase information storage unit 126 stores list information of learning models purchased by the user. Figure 14 is a schematic diagram illustrating an example of a purchase information storage unit according to an embodiment of the present disclosure.

[0209] The purchase information storage unit 126 stores purchase information including user IDs and learning model information IDs. The purchase information storage unit 126 stores the learning model information ID corresponding to each user ID in association with each user ID. The purchase information storage unit 126 stores each user ID in association with the learning model information ID used to identify the learning model purchased by the user identified by the user ID.

[0210] The user ID indicates identification information for uniquely specifying each user. For example, the user ID indicates identification information for uniquely specifying a user such as a system administrator, a store manager, or a general user.

[0211] The learning model information ID indicates identification information used to uniquely identify learning model information. For example, if a user identified by a corresponding user ID has purchased multiple learning models, the user ID is associated with multiple learning model information IDs. For example, if the user ID has not purchased any learning models, the user ID is not associated with any learning model information ID.

[0212] Note that the purchase information storage unit 126 is not limited to the above, and may store various types of information according to the purpose.

[0213] The operation history information storage unit 127 according to the embodiment stores information about the user's operation history (operation history information). The operation history information storage unit 127 stores user operation history list information. For example, the operation history information storage unit 127 stores list information of each user's operation history. Figure 15 is a schematic diagram illustrating an example of an operation history information storage unit according to an embodiment of the present disclosure.

[0214] The operation history information storage unit 127 stores operation history information. For example, the operation history information storage unit 127 stores the operation history corresponding to each user ID in association with each user ID. The operation history information storage unit 127 stores the operation history of the user identified by the user ID in association with each user ID.

[0215] The operation history information indicates the operation history of the user. For example, the operation history information may include various types of information about the user's operation, such as the details of the operation performed by the user and the date and time when the operation was performed.

[0216] Note that the operation history information storage unit 127 is not limited to the above, and may store various types of information according to the purpose.

[0217] Back to Figure 8 , the description continues. The control unit 130 is implemented by, for example, a central processing unit (CPU), a microprocessor unit (MPU), or the like, and executes a program stored in the information processing device 100 (for example, a specific program such as the information processing program according to the present disclosure) using a RAM or the like as a work area. Furthermore, the control unit 130 is a controller implemented by, for example, an integrated circuit such as an application-specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0218] like Figure 8 As shown, the control unit 130 includes an acquisition unit 131, a generation unit 132, a determination unit 133, a sending unit 134, a receiving unit 135 and a providing unit 136, and implements or executes the functions and actions of information processing as described below. Note that the internal configuration of the control unit 130 is not limited to Figure 8 The configuration shown in FIG. 1 is not limited to the configuration shown in FIG. 1 , and other configurations may be used as long as the information processing described later is performed. Figure 8 The connection relationship shown is one and another connection relationship is possible.

[0219] The acquisition unit 131 acquires various types of information. The acquisition unit 131 acquires various types of information from external information processing devices. The acquisition unit 131 acquires various types of information from other information processing devices such as the system administrator terminal 10 , the store manager terminal 20 , and the general user terminal 30 .

[0220] The acquisition unit 131 acquires various types of information from the storage unit 120. The acquisition unit 131 acquires various types of information from the user information storage unit 121, the work information storage unit 122, the learning model information storage unit 123, the sales management information storage unit 124, the shared information storage unit 125, the purchase information storage unit 126, and the operation history information storage unit 127.

[0221] The acquisition unit 131 acquires various types of information determined by the determination unit 133. The acquisition unit 131 acquires various types of information generated by the generation unit 132. The acquisition unit 131 acquires various types of information received by the acceptance unit 135.

[0222] exist Figure 1 In the example, refer to Figure 1 The acquisition unit 131 acquires data for generating a learning model from the system administrator terminal 10 used by the system administrator SM1. The acquisition unit 131 acquires data for generating a learning model from the store manager terminal 20 used by the store manager SP1. The acquisition unit 131 acquires data for generating a learning model from the general user terminal 30 used by the general user U1.

[0223] The generation unit 132 generates various types of information. The generation unit 132 generates various types of information based on information from an external information processing device and information stored in the storage unit 120. The generation unit 132 generates various types of information based on information from other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. The generation unit 132 generates various types of information based on information stored in the user information storage unit 121, the work information storage unit 122, the learning model information storage unit 123, the sales management information storage unit 124, the shared information storage unit 125, the purchase information storage unit 126, or the operation history information storage unit 127.

[0224] The generation unit 132 generates various types of information based on the various types of information acquired by the acquisition unit 131. The generation unit 132 generates various types of information based on the various types of information determined by the determination unit 133. The generation unit 132 generates various types of information based on the various types of information determined by the acceptance unit 135.

[0225] Generation unit 132 performs learning processing. Generation unit 132 functions as a learning processing unit that performs learning processing. For example, generation unit 132 is a learning processing functional unit. Generation unit 132 performs various learning operations. Generation unit 132 learns (generates) a model. Generation unit 132 learns various types of information, such as the model. Generation unit 132 generates the model through learning. Generation unit 132 uses various techniques related to machine learning to learn the model. Generation unit 132 updates the model through learning.

[0226] For example, the generation unit 132 learns various types of information based on information from an external information processing device and information stored in the storage unit 120. The generation unit 132 learns various types of information based on information from other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. The generation unit 132 learns various types of information from information stored in the user information storage unit 121, the work information storage unit 122, the sales management information storage unit 124, the shared information storage unit 125, the purchase information storage unit 126, and the operation history information storage unit 127.

[0227] The generation unit 132 learns various types of information based on the various types of information acquired by the acquisition unit 131. The generation unit 132 learns various types of information based on the various types of information determined by the determination unit 133. The generation unit 132 learns various types of information based on the various types of information determined by the acceptance unit 135.

[0228] The generation unit 132 generates a learning model using various techniques related to machine learning. The generation unit 132 may use a music generation algorithm that utilizes Markov chains. The information processing device 100 may use Markov chain technology to generate a learning model. Furthermore, the information processing device 100 may use a music generation algorithm that utilizes deep learning. The information processing device 100 may use deep learning technology to generate a learning model. The generation unit 132 may use recursive neural network technology, such as RNN, to generate a learning model. The generation unit 132 may use reinforcement learning technology to generate a learning model.

[0229] The generation unit 132 generates a model for content generation by using data provided by a service user subject having one of a plurality of permission levels for a service related to content creation. The generation unit 132 generates a model by using data provided by a user subject having one of a plurality of permission levels, the plurality of permission levels including a first permission level given to a service administrator, a second permission level given to a seller who sells in the service, and a third permission level given to an ordinary user who uses the service.

[0230] The generation unit 132 generates a model using data provided by a user subject having one of a plurality of permission levels, including a second permission level having more restricted permissions than the first permission level and a third permission level having more restricted permissions than the second permission level. The generation unit 132 generates a model using data provided by a user subject having one of a plurality of permission levels including the first permission level. The user subject having the first permission level can accept delegations from a user subject having the second permission level. The generation unit 132 generates a model using data provided by a user subject having one of a plurality of permission levels including the second permission level. The user subject having the second permission level can sell and share the model generated using the data of the user subject having the second permission level. The generation unit 132 generates a model using data provided by a user subject having one of a plurality of permission levels including the third permission level. The user subject having the third permission level can share the model generated using the data of the user subject having the third permission level.

[0231] The generation unit 132 generates meta information corresponding to the model based on the data provided by the user agent. The generation unit 132 generates the model at the timing when the reception unit 135 receives the data. The generation unit 132 generates list information of the plurality of models determined by the determination unit 133.

[0232] The generation unit 132 generates a model regarding generation of music, which is content, by using data provided by a user subject having one of a plurality of authority levels in a service regarding music composition.

[0233] The generation unit 132 generates various types of information, such as screens (image information), to be provided to the external information processing device by appropriately using various techniques. The generation unit 132 generates screens (image information) and the like to be provided to the system administrator terminal 10. For example, the generation unit 132 generates screens (image information) and the like to be provided to the system administrator terminal 10 based on the information stored in the storage unit 120.

[0234] The generation unit 132 can generate a screen (image information) or the like through any processing, as long as it can generate a screen (image information) or the like to be provided to an external information processing device. For example, the generation unit 132 generates a screen (image information) to be provided to the system administrator terminal 10 by appropriately using various technologies related to image generation, image processing, etc. For example, the generation unit 132 generates a screen (image information) to be provided to the system administrator terminal 10 by appropriately using various technologies such as Java (registered trademark). Note that the generation unit 132 can generate a screen (image information) to be provided to the system administrator terminal 10 based on a format such as CSS, JavaScript (registered trademark), or HTML. In addition, for example, the generation unit 132 can generate a screen (image information) in various formats, such as Joint Photographic Experts Group (JPEG), Graphics Interchange Format (GIF), or Portable Network Graphics (PNG). The generation unit 132 generates images IM11, IM21, IM31, IM41, etc. The generation unit 132 generates various types of information regarding user interfaces IF11 to IF13.

[0235] exist Figure 1 In the example of , the generation unit 132 generates a learning model using data provided from the system manager SM1. The generation unit 132 generates a learning model using data provided from the store manager SP1. The generation unit 132 generates a learning model using data provided from the general user U1.

[0236] The determination unit 133 determines various types of information. The determination unit 133 determines various types of information. For example, the determination unit 133 determines various types of information based on information from an external information processing device or information stored in the storage unit 120. The determination unit 133 determines various types of information based on information from the external information processing device and information stored in the storage unit 120. The determination unit 133 determines various types of information based on information from other information processing devices, such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. The determination unit 133 determines various types of information based on information stored in the user information storage unit 121, the work information storage unit 122, the learning model information storage unit 123, the sales management information storage unit 124, the shared information storage unit 125, the purchase information storage unit 126, or the operation history information storage unit 127.

[0237] The determining unit 133 determines various types of information based on the various types of information acquired by the acquiring unit 131. The determining unit 133 determines various types of information based on the various types of information generated by the generating unit 132. The determining unit 133 determines various types of information based on the various types of information received by the accepting unit 135.

[0238] The determining unit 133 determines the usage mode of the model generated by the generating unit 132 according to a permission level of the user subject. The determining unit 133 determines the usage scope of the model in the service according to a permission level. The determining unit 133 determines whether the model can be sold or shared according to a permission level.

[0239] When the user subject has a first permission level, the determining unit 133 determines that the model can be used in the service corresponding to the first permission level. When the user subject has a second permission level, the determining unit 133 determines that the model can be used in the service corresponding to the second permission level. When the user subject has a third permission level, the determining unit 133 determines that the model can be used in the service corresponding to the third permission level.

[0240] The determining unit 133 determines information to be provided to a user subject based on a service usage history of the user subject. The determining unit 133 determines a plurality of models to provide information to the user subject. The determining unit 133 determines a recommended model to be recommended to the user subject among the plurality of models.

[0241] exist Figure 1 In the example shown in FIG, the determining unit 133 determines the usage pattern of the generated learning model based on the authority level of the system administrator SM1, who is the data provider. The determining unit 133 determines the usage pattern of the generated learning model based on the authority level of the store manager SP1, who is the data provider. The determining unit 133 determines the usage pattern of the generated learning model based on the authority level of the general user U1, who is the data provider.

[0242] The transmission unit 134 provides various types of information to external information processing devices. The transmission unit 134 transmits various types of information to external information processing devices. For example, the transmission unit 134 transmits various types of information to other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. The transmission unit 134 provides the information 120 stored in the storage unit. The transmission unit 134 transmits the information stored in the storage unit 120.

[0243] The sending unit 134 provides various types of information based on information from other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. The sending unit 134 provides various types of information based on information stored in the storage unit 120, and the sending unit 134 provides various types of information based on information stored in the user information storage unit 121, the work information storage unit 122, the learning model information storage unit 123, the sales management information storage unit 124, the shared information storage unit 125, the purchase information storage unit 126, or the operation history information storage unit 127.

[0244] The sending unit 134 sends various types of information acquired by the acquiring unit 131. The sending unit 134 sends various types of information generated by the generating unit 132. The sending unit 134 sends various types of information determined by the determining unit 133. The sending unit 134 sends various types of information provided by the providing unit 136 in response to an instruction from the providing unit 136. The sending unit 134 sends the various types of information received by the accepting unit 135 to other information processing devices, such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30.

[0245] Transmitting unit 134 transmits the model to the terminal device used by the user. Transmitting unit 134 transmits the model to the terminal device at the same time as generating unit 132 generates the model. Transmitting unit 134 transmits the model to system administrator terminal 10, which is the terminal device used by the system administrator. Transmitting unit 134 transmits the model to system administrator terminal 10, which is the terminal device used by the system administrator, at the same time as generating unit 132 generates the model using data provided by the system administrator.

[0246] The sending unit 134 sends the model to the store manager terminal 20, which is a terminal device used by the store manager. The sending unit 134 sends the model to the store manager terminal 20, which is a terminal device used by the store manager, at the same time that the generation unit 132 generates the model using data provided by the store manager. The sending unit 134 also sends the model to the general user terminal 30, which is a terminal device used by general users. The sending unit 134 sends the model to the general user terminal 30, which is a terminal device used by general users, at the same time that the generation unit 132 generates the model using data provided by general users.

[0247] The accepting unit 135 accepts various types of information. The accepting unit 135 accepts registration of various types of information. The accepting unit 135 accepts requests for various types of information.

[0248] The receiving unit 135 receives various types of information. The receiving unit 135 receives various types of information from external information processing devices. The receiving unit 135 receives various types of information from other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30.

[0249] The receiving unit 135 receives data from the user. The receiving unit 135 receives data from the system administrator. The receiving unit 135 receives data from the system administrator terminal 10, which is a terminal device used by the system administrator. The receiving unit 135 receives data from the store manager. The receiving unit 135 receives data from the store manager terminal 20, which is a terminal device used by the store manager. The receiving unit 135 receives data from the general user. The receiving unit 135 receives data from the general user terminal 30, which is a terminal device used by the general user.

[0250] exist Figure 1 In the example of , the receiving unit 135 receives data DT11 provided from the system administrator terminal 10. The receiving unit 135 receives the provided data DT11. The receiving unit 135 receives data DT12 provided from the store manager terminal 20. The receiving unit 135 receives the provided data DT11. The receiving unit 135 receives data DT13 provided from the general user terminal 30.

[0251] The providing unit 136 provides various types of information. The providing unit 136 provides various types of information to other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. For example, the providing unit 136 provides various types of information based on information from external information processing devices and information stored in the storage unit 120. The providing unit 136 provides various types of information based on information from other information processing devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30. The providing unit 136 provides various types of information based on information stored in the user information storage unit 121, the work information storage unit 122, the learning model information storage unit 123, the sales management information storage unit 124, the shared information storage unit 125, the purchase information storage unit 126, and the operation history information storage unit 127.

[0252] The providing unit 136 provides various types of information based on the various types of information acquired by the acquiring unit 131. The providing unit 136 provides various types of information based on the various types of information generated by the generating unit 132. The providing unit 136 provides various types of information based on the various types of information determined by the determining unit 133. The providing unit 136 provides various types of information based on the various types of information received by the receiving unit 135. The providing unit 136 provides information by instructing the transmitting unit 134 to transmit the various types of information.

[0253] The providing unit 136 provides a music listening service. The providing unit 136 provides a listening service of music generated when using the model.

[0254] [1-4. Configuration of Terminal Device According to Embodiment]

[0255] Next, a terminal device used by each user according to the embodiment will be explained.

[0256] [1-4-1. Configuration of the System Administrator Terminal According to the Embodiment]

[0257] First, the configuration of the system administrator terminal 10 as an example of a terminal device according to the embodiment will be explained. Figure 16 is a schematic diagram illustrating a configuration example of a system administrator terminal according to an embodiment of the present disclosure.

[0258] like Figure 16 As shown, the system administrator terminal 10 includes a communication unit 11 , an input unit 12 , an output unit 13 , a storage unit 14 , a control unit 15 , and a display unit 16 .

[0259] The communication unit 11 is implemented by, for example, an NIC or a communication circuit. The communication unit 11 is connected to a network N (Internet, etc.) in a wired or wireless manner, and transmits and receives information with other devices such as the information processing device 100 and other terminal devices via the network N.

[0260] The user inputs various operations to the input unit 12. The input unit 12 includes a keyboard or a mouse connected to the system administrator terminal 10. The input unit 12 receives user input. The input unit 12 receives user input via the keyboard or the mouse. The input unit 12 may have a function of detecting sound. In this case, the input unit 12 may include a microphone for detecting sound.

[0261] Various types of information can be input into the input unit 12 via the display unit 16. In this case, the input unit 12 may include a touch panel capable of performing functions equivalent to those of a keyboard or mouse. In this case, the input unit 12 utilizes the touch panel functionality implemented by various sensors to receive various user operations via the display screen. In other words, the input unit 12 receives various user operations via the display unit 16 of the system administrator terminal 10. For example, the input unit 12 receives operations such as user instructions via the display unit 16 of the system administrator terminal 10. For example, the input unit 12 functions as a receiving unit that accepts user operations using the touch panel functionality. Note that, as a method for detecting user operations by the input unit 12, a capacitive method is primarily used in tablet terminals. However, any other detection method, such as a resistive film method, a surface acoustic wave method, an infrared method, an electromagnetic induction method, or the like, may also be used, as long as it can detect user operations and implement the touch screen functionality. Furthermore, if buttons, etc., are provided in the system administrator terminal 10, the system administrator terminal 10 may also include an input unit that accepts operations using buttons, etc.

[0262] The output unit 13 outputs various types of information. The output unit 13 has a function of outputting sound. For example, the output unit 13 includes a speaker that outputs sound. Note that when sound output is not performed, the system administrator terminal 10 may not include the output unit 13.

[0263] The storage unit 14 is realized by, for example, a semiconductor storage element such as a random access memory, a flash memory, or a storage device such as a hard disk, an optical disk, etc. The storage unit 14 stores various types of information for display information.

[0264] Back to Figure 16 , and will be described further. The control unit 15 is implemented by, for example, a CPU, MPU, or the like, and executes a program stored in the system administrator terminal 10 (for example, a display program such as the information processing program according to the present disclosure) using a random access memory or the like as a workspace. Furthermore, the control unit 15 is a controller and may be implemented by, for example, an integrated circuit such as an ASIC or FPGA.

[0265] like Figure 16 As shown, the control unit 15 includes a receiving unit 151, a display operation unit 152, a processing execution unit 153 and a sending unit 154, and realizes or executes the functions and actions of the information processing described below. Note that the internal configuration of the control unit 15 is not limited to Figure 16 The configuration shown may also be other configurations as long as the information processing described later can be performed.

[0266] The receiving unit 151 receives various types of information. The receiving unit 151 receives various types of information from an external information processing device. The receiving unit 151 receives various types of information from other information processing devices such as the information processing device 100 and other terminal devices. The receiving unit 151 receives various types of information from the information processing device 100 and other terminal devices. The receiving unit 151 receives service information related to content creation, such as information about a learning model, from the information processing device 100.

[0267] Receiving unit 151 receives control information from information processing device 100. Receiving unit 151 receives images from information processing device 100. Receiving unit 151 receives images including control information from information processing device 100. Receiving unit 151 receives images IM11, IM21, IM31, IM41, etc. from information processing device 100. Receiving unit 151 receives various types of information related to user interfaces IF11 to IF13 from information processing device 100.

[0268] The display operation unit 152 controls various displays. The display operation unit 152 controls the display on the display unit 16. The display operation unit 152 controls the display on the display unit 16 in response to reception by the reception unit 151. The display operation unit 152 controls the display on the display unit 16 based on the information received by the reception unit 151. The display operation unit 152 controls the display on the display unit 16 based on the information generated by the processing execution unit 153. The display operation unit 152 controls the display on the display 16 according to the generation of the processing execution unit 153. The display operation unit 152 controls the display on the display unit 16 so that the image received from the information processing device 100 is displayed on the display unit 16.

[0269] The display operation unit 152 can control the display of the display unit 16 by using an application that displays images IM11, IM21, IM31, IM41, etc. The display operation unit 152 can control the display of the display unit 16 by using an application that displays various types of information about the user interfaces IF11 to IF13. The display operation unit 152 can be implemented by an application. The display operation unit 152 controls the display on the display unit 16 based on predetermined control information. Here, the control information is described in a scripting language such as JavaScript (registered trademark) or CSS.

[0270] The processing execution unit 153 executes various processes. The processing execution unit 153 executes various processes based on information from an external information processing device and information stored in the storage unit 14. The processing execution unit 153 executes various processes based on information from other information processing devices such as the information processing device 100 and other terminal devices. The processing execution unit 153 executes various processes based on information received by the receiving unit 151.

[0271] The transmission unit 154 transmits various types of information to external information processing devices. For example, the transmission unit 154 transmits various types of information to other information processing devices such as the information processing device 100 and other terminal devices. The transmission unit 154 transmits information stored in the storage unit 14.

[0272] The transmission unit 154 transmits various types of information based on information from other information processing apparatuses such as the information processing apparatus 100. The transmission unit 154 transmits various types of information 14 based on information stored in the storage unit.

[0273] The transmission unit 154 transmits various types of information to the information processing device 100 and other terminal devices according to the operation. The transmission unit 154 transmits various types of information to the information processing device 100 and other terminal devices according to the user's operation. The transmission unit 154 transmits information requesting the use of a model to the information processing device 100 according to the user's operation. The transmission unit 154 transmits information requesting the purchase or sharing of a model to the information processing device 100 according to the user's operation.

[0274] The display unit 16 displays various types of information. The display unit 16 is implemented, for example, by a liquid crystal display, an organic electroluminescent (EL) display, or the like. The display unit 16 can be implemented in any manner as long as it can display information provided by the information processing device 100. The display unit 16 displays various types of information under the control of the information processing device 100. The display unit 16 displays various types of information based on control information received from the information processing device 100 by the receiving unit 151. The display unit 16 displays various types of information under the control of the display operation unit 152. The display unit 16 displays images provided by the information processing device 100. The display unit 16 displays various types of information generated by the processing execution unit 153. The display unit 16 displays images IM11, IM21, IM31, IM41, and the like. The display unit 16 displays user interfaces IF11 to IF13, and the like.

[0275] Furthermore, the display control processing, generation processing, and display processing of the control unit 15 described above can be implemented by a predetermined application in each unit of the control unit 15. For example, the display control processing, generation processing, and display processing of the control unit 15 can be implemented by control information including JavaScript (registered trademark) or the like. Furthermore, in the case where the display control processing, generation processing, and display processing described above are executed by a dedicated application, the control unit 15 can include, for example, an application control unit that controls a predetermined application (e.g., a web browser, etc.) or a dedicated application.

[0276] [1-4-2. Configuration of the Store Manager Terminal According to the Embodiment]

[0277] Next, the configuration of the store manager terminal 20 as an example of a terminal device that executes information processing according to the embodiment will be described. Figure 17 1 is a schematic diagram showing an example of a configuration of a store manager terminal according to an embodiment of the present disclosure. Note that in the store manager terminal 20, a configuration identical to or corresponding to the configuration of the system administrator terminal 10 is indicated by a reference numeral beginning with "2" ("2*" or "2**") to omit redundant description.

[0278] like Figure 17 As shown, the store manager terminal 20 includes a communication unit 21 , an input unit 22 , an output unit 23 , a storage unit 24 , a control unit 25 , and a display unit 26 .

[0279] like Figure 17 As shown, the control unit 25 includes a receiving unit 251 , a display operation unit 252 , a process execution unit 253 , and a sending unit 254 .

[0280] [1-4-3. Configuration of a General User Terminal According to the Embodiment]

[0281] Next, a configuration of a general user terminal 30 as an example of a terminal device that performs information processing according to the embodiment will be described. Figure 18 1 is a schematic diagram showing an example configuration of a general user terminal according to an embodiment of the present disclosure. Note that in the general user terminal 30, a configuration identical to or corresponding to the configuration of the system administrator terminal 10 is indicated by a reference numeral beginning with "3" ("3*" or "3**") to omit redundant explanation.

[0282] like Figure 18 As shown, the general user terminal 30 includes a communication unit 31 , an input unit 32 , an output unit 33 , a storage unit 34 , a control unit 35 and a display unit 36 ​​.

[0283] like Figure 18 As shown, the control unit 35 includes a receiving unit 351 , a display operation unit 352 , a processing execution unit 353 , and a sending unit 354 .

[0284] [1-5. Information processing process according to the embodiment]

[0285] Next, we will refer to Figure 19 Various types of information processing procedures according to the embodiment are described. Figure 19 is a flowchart illustrating an information processing procedure according to an embodiment of the present disclosure.

[0286] like Figure 19As shown, the information processing device 100 generates a model for content generation by using data provided by a service user subject having one of a plurality of authority levels (step S101). Figure 1 In the example of FIG. 1 , the information processing device 100 generates a learning model MD11 using data DT11 provided by the system administrator SM1 (see FIG. 1 ). Figure 2 ).

[0287] The information processing device 100 determines the usage mode of the generated model according to a permission level of the user subject (step S102). Figure 1 In the example of , since the information processing apparatus 100 has the first authority level which is the authority level of the system administrator SM1 , it is determined that the learning model MD11 can be sold or shared.

[0288] [1-5-1. Registration and sharing of learning model information by general users]

[0289] Next, we will refer to Figure 20 Describes the registration and sharing of learning model information by ordinary users. Figure 20 is a flow chart illustrating an information processing process according to an embodiment of the present disclosure. Specifically, Figure 20 This is a schematic diagram (sequence diagram) showing the process of registration and sharing of learning model information by general users. Figure 20 The processing in each step shown can be executed by any device included in the information processing system 1 , such as the information processing device 100 or a terminal device (for example, a general user terminal 30 ).

[0290] like Figure 20 As shown, the information processing system 1 performs user registration processing (step S201). The information processing system 1 performs user registration processing in response to a request from a general user. For example, the information processing device 100 performs processing to register the user using the general user terminal 30 as a general user in the user information storage unit 121 in response to a request from the general user terminal 30.

[0291] Furthermore, the information processing system 1 performs work information registration processing (step S202). The information processing system 1 performs work information registration processing in response to a request from a general user. For example, the information processing device 100 performs processing to register work information acquired from the general user terminal 30 in the work information storage unit 122 in response to a request from the general user terminal 30.

[0292] Furthermore, the information processing system 1 performs a learning model information registration process (step S203). The information processing system 1 performs the learning model information registration process in response to a request from a general user. For example, the information processing device 100 performs a process of registering the learning model information acquired from the general user terminal 30 in the learning model information storage unit 123 in response to a request from the general user terminal 30.

[0293] Furthermore, the information processing system 1 performs learning model information sharing processing (step S204). The information processing system 1 performs learning model information sharing processing in response to a request from a regular user. For example, the information processing device 100 changes the sharing status of the learning model information obtained from the regular user terminal 30 in response to a request from the regular user terminal 30.

[0294] [1-5-2. Registration and sales registration of learning model information by the system administrator]

[0295] Next, we will refer to Figure 21 Describes the registration and sales registration of learning model information by the system administrator. Figure 21 is a flow chart illustrating an information processing process according to an embodiment of the present disclosure. Specifically, Figure 21 This is a schematic diagram (sequence diagram) showing registration of learning model information and sales registration by the system administrator. Figure 21 The processing in each step shown can be executed by any device included in the information processing system 1 , such as the information processing device 100 or a terminal device (for example, the system administrator terminal 10 ).

[0296] like Figure 21 As shown, the information processing system 1 performs work information registration processing (step S301). The information processing system 1 performs work information registration processing in response to a request from a system administrator. For example, the information processing device 100 performs processing to register work information acquired from the system administrator terminal 10 in the work information storage unit 122 in response to a request from the system administrator terminal 10.

[0297] Furthermore, the information processing system 1 performs learning model information registration processing (step S302). The information processing system 1 performs learning model information registration processing in response to a request from the system administrator. For example, the information processing device 100 performs processing to register the learning model information acquired from the system administrator terminal 10 in the learning model information storage unit 123 in response to a request from the system administrator terminal 10.

[0298] Furthermore, the information processing system 1 performs a learning model information sales registration process (step S303). The information processing system 1 performs the learning model information sales registration process in response to a request from the system administrator. For example, the information processing device 100 performs a process of registering the learning model information sold by the system administrator in the sales management information storage unit 124 in response to a request from the system administrator terminal 10.

[0299] [1-5-3. General User Browsing and Selection Processing of the Shared List of Learning Model Information]

[0300] Next, we will refer to Figure 22 This section describes how ordinary users browse and select from a shared list of learning model information. Figure 22 is a flow chart illustrating an information processing process according to an embodiment of the present disclosure. Specifically, Figure 22 This is a schematic diagram (sequence diagram) showing the process of browsing and selecting a shared list of learning model information by a general user. Figure 22 The processing in each step shown can be executed by any device included in the information processing system 1 (for example, the information processing device 100 or a terminal device (for example, a general user terminal 30)).

[0301] like Figure 22 As shown, the information processing system 1 executes a learning model information browsing process (step S401). The information processing system 1 executes the learning model information browsing process in response to a request from a general user.

[0302] When the general user's request is for browsing a shared list of learning model information, the information processing system 1 performs a process for browsing the shared list of learning model information (step S402-1). For example, in response to a shared list request from the general user terminal 30, the information processing device 100 transmits a list of learning model information to the general user terminal 30. When a request for browsing a list of learning model information that can be shared by a general user using the general user terminal 30 is received from the general user terminal 30, the information processing device 100 provides the general user terminal 30 with the list of learning model information that can be shared by the general user. Note that when the information processing device 100 receives a request for browsing a list of learning model information that was created by the general user using the general user terminal 30, the information processing device 100 may provide the general user terminal 30 with the list of learning model information that was created by the general user himself / herself. In addition, when a request for browsing a list of learning model information that has already been shared by a general user using the general user terminal 30 is received from the general user terminal 30, the information processing device 100 may provide the general user terminal 30 with the list of learning model information that has already been shared by the general user using the general user terminal 30.

[0303] The information processing system 1 performs a process for selecting a learning model information sharing list (step S403-1). For example, when a general user selects learning model information from among the learning model information that general users can share, the information processing system 1 performs a process for selecting a learning model information sharing list. Upon receiving information from the general user terminal 30 indicating that a general user using the general user terminal 30 has selected learning model information, the information processing device 100 registers information indicating that the general user has shared the learning model information. For example, the information processing device 100 registers information indicating that the general user has shared the learning model information in the shared information storage unit 125.

[0304] When the general user's request is to browse the sales list of learning model information, the information processing system 1 performs browsing of the sales list of learning model information (step S402-2). For example, in response to the sales list request from the general user terminal 30, the information processing device 100 performs processing to transmit the list information of learning model information to the general user terminal 30. The information processing device 100 provides the general user terminal 30 with the list information of learning model information for sale.

[0305] The information processing system 1 performs a selection process for the sales list of learning model information (step S403-2). For example, when a general user selects learning model information from the learning model information for sale, the information processing system 1 performs a selection process for the sales list of learning model information. When information indicating that a general user using the general user terminal 30 has selected learning model information is obtained from the general user terminal 30, the information processing device 100 registers information indicating that the general user has purchased the learning model information. For example, the information processing device 100 registers information indicating that the general user has purchased the learning model information in the purchase information storage unit 126.

[0306] The information processing system 1 performs learning model information usage processing (step S404). For example, the information processing device 100 performs learning model information usage processing in response to a usage request for learning model information from the ordinary user terminal 30. The information processing system 1 responds to the usage request for learning model information from the ordinary user terminal 30 and provides a list of learning model information that can be used for learning by ordinary users of the ordinary user terminal 30. The required learning model information is selected using the meta-information of the learning model information in the ordinary user reference list of the ordinary user terminal 30 or the like of the learning model information. For example, the ordinary user terminal 30 sends information indicating the learning model information selected by the ordinary user using the ordinary user terminal 30 to the information processing device 100. Based on the received information indicating the learning model information selected by the ordinary user, the information processing device 100 uses the learning model information selected by the ordinary user to perform usage processing such as composing. For example, such learning model information is a style board of the AI-assisted composition system (information processing system 1), and the selected style board is used for composing.

[0307] [1-5-4. Sales commissioned by store managers and acceptance of commissions by system administrators]

[0308] Next, we will refer to Figure 23 Describes the commissioned sales by store managers and the commissioned acceptance processing by system administrators. Figure 23 is a flow chart illustrating an information processing process according to an embodiment of the present disclosure. Specifically, Figure 23 This is a schematic diagram (sequence diagram) showing the learning model information registration and consignment sales processing by the store manager and the consignment acceptance and sales registration processing by the system administrator. Figure 23 The processing in each step shown can be executed by any device included in the information processing system 1 (for example, the information processing device 100 or a terminal device (for example, the system administrator terminal 10 or the store manager terminal 20)).

[0309] like Figure 23 As shown, the information processing system 1 performs work information registration processing (step S501). The information processing system 1 performs work information registration processing in response to a request from a store manager. For example, the information processing device 100 performs processing to register work information acquired from the store manager terminal 20 in the work information storage unit 122 in response to a request from the store manager terminal 20.

[0310] Furthermore, the information processing system 1 performs learning model information registration processing (step S502). The information processing system 1 performs learning model information registration processing in response to a request from a store manager. For example, the information processing device 100 performs processing to register the learning model information acquired from the store manager terminal 20 in the learning model information storage unit 123 in response to a request from the store manager terminal 20.

[0311] Furthermore, the information processing system 1 executes a learning model information sales consignment process (step S503). The information processing system 1 executes the learning model information sales consignment process in response to a request from the store manager. For example, the information processing device 100 executes a process to notify the system administrator terminal 10 of information indicating that the learning model information has been consigned for sale in response to a request from the store manager terminal 20.

[0312] Furthermore, the information processing system 1 performs a learning model information entrustment acceptance process (step S504). The information processing system 1 performs a learning model information registration process in response to a request from the system administrator. For example, the information processing device 100 performs a learning model information entrustment acceptance process based on a response from the system administrator terminal 10 indicating that the sales have been entrusted. For example, when the information processing device 100 receives information indicating acceptance of the entrusted sales from the system administrator terminal 10, the information processing device 100 performs a learning model information entrustment acceptance process.

[0313] Furthermore, the information processing system 1 performs a learning model information sales registration process (step S505). The information processing system 1 performs the learning model information sales registration process based on the response from the system administrator. For example, when the information processing device 100 receives information indicating acceptance of the consigned sale from the system administrator terminal 10, the information processing device 100 registers information indicating that the system administrator terminal 10 is being consigned to sell the store manager's learning model into the sales management information storage unit 124.

[0314] [1-6. Conceptual diagram of the configuration of the information processing system]

[0315] Here, reference Figure 24 Each function, hardware configuration, and data in the information processing system are conceptually illustrated. Figure 24 is a schematic diagram showing an example of a conceptual diagram of the configuration of an information processing system. Specifically, Figure 24 is a schematic diagram showing a functional overview of a learning model information sharing and sales system as an application example of the information processing system 1 .

[0316] [1-6-1. Overall Configuration]

[0317] Figure 24The server device shown corresponds to the information processing device 100 in the information processing system 1 . Figure 24 The system administrator application section shown corresponds to the system administrator terminal 10 in the information processing system 1, and specifically corresponds to an application installed in the system administrator terminal 10. Figure 24 The store manager application shown in corresponds to the store manager terminal 20 in the information processing system 1 , and specifically corresponds to an application installed in the store manager terminal 20 . Figure 24 The general user application program shown corresponds to the general user terminal 30 in the information processing system 1, and specifically corresponds to the application installed in the general user terminal 30. Figure 24 In the example of FIG. 1 , one store manager application unit and one general user application unit are shown, but according to the number of corresponding store manager terminals 20 and general user terminals 30 (see FIG. Figure 7 ) can include multiple store manager application parts and multiple general user application parts.

[0318] Figure 24 The learning processing unit and control unit of the server device shown correspond to the control unit 130 of the information processing device 100. For example, the learning processing unit of the server device corresponds to the generating unit 132 of the information processing device 100. The server internal database unit of the server device corresponds to the storage unit 120 of the information processing device 100.

[0319] Figure 24 The display operation unit and control unit of the system administrator application section shown correspond to the control unit 15 of the system administrator terminal 10. For example, the display operation unit of the system administrator application section corresponds to the display operation unit 152 of the system administrator terminal 10.

[0320] Figure 24 The display operation unit and control unit in the store manager application section shown correspond to the control unit 25 of the store manager terminal 20. For example, the display operation unit of the store manager application section corresponds to the display operation unit 252 of the store manager terminal 20.

[0321] Figure 24 The display operation unit and control unit of the general user application section shown correspond to the control unit 35 of the general user terminal 30. For example, the display operation unit of the store manager application section corresponds to the display operation unit 352 of the general user terminal 30.

[0322] In the following, we will explain in more detail Figure 24 .For example, Figure 24 : is a schematic diagram showing the functional outline of the information processing system as a learning model information sharing and sales system. Figure 24As shown, the server device is connected to a system administrator application section, a plurality of store manager application sections, and a plurality of general user application sections via a network N such as the Internet.

[0323] [1-6-2. Server equipment]

[0324] First, the configuration related to the server device will be explained.

[0325] The server device includes a control unit, a learning processing unit, and an internal server database unit. The control unit manages work information, learning model information, shared information, sales information, access rights information, and user operation history information. The learning processing unit also manages machine learning and deep learning.

[0326] For example, when learning model information is registered in a database unit within a server, the learning processing unit (learning processing functional unit) can calculate the time to store the information in the learning result information, and thus store the results in the learning result information. Furthermore, multiple pieces of learning process result information can be collectively processed and stored in the learning processing unit (learning processing functional unit) through nightly batch processing, etc. Furthermore, in the case of smaller calculations, calculations can be performed as needed when the learning model information is actually used.

[0327] [1-6-3. System Administrator]

[0328] Next, configuration related to the system administrator will be explained.

[0329] The system administrator application section includes a display and operation unit and a control unit. The display and operation unit of the system administrator application section has functions for displaying work information and displaying and editing learning model information. The control unit of the system administrator application section has functions for sharing learning model information, selling learning model information, and transmitting user operation history information.

[0330] The system manager application section is, for example, music editing software (DAW, etc.), and can display, for example, music information in the work information display function. For example, if the DAW has an AI-assisted music production function, it can create new music information while using the learning model information display and editing function.

[0331] Information for identifying the system administrator is registered in the in-server database unit, and the system administrator can register a new system administrator in the in-server database unit from the display operation unit of the system administrator application unit via the network N using the access authority information management function. The system administrator can register a special administrator (store manager) in the in-server database unit using the access authority information management function via the display operation unit of the system administrator application unit and the network N.

[0332] The system administrator can register work information in the server's database using the work information display unit. The system administrator can register learning model information in the server's database using the learning model information display and edit function. The system administrator can issue an instruction to the shared information management function from the display operation unit to change the value of the learning model information's sharing permission information from disabling sharing to enabling sharing.

[0333] The system administrator creates sales management information from the display operation unit using the sales information management function of the server device via the network N. The sales management information includes a sales management information ID that uniquely specifies each piece of sales management information, sales price information, sales meta information, and a learning model information ID that uniquely specifies each piece of learning model information related to the sales management information.

[0334] After completing the registration of sales management information, the system administrator issues a sales registration completion instruction to the sales information management function, thereby changing the sales permission information corresponding to the learning model information from prohibited sales to permitted sales. For example, when the learning model information is registered, the sales permission information of the learning model information indicates prohibited sales. The system administrator confirms the completion of the commissioned sales in the sales permission information corresponding to the learning model information and issues a registration completion instruction to the sales information management function, thereby changing the sales permission information corresponding to the learning model information from commissioned sales completed to enabled sales.

[0335] The system administrator uses the learning model information display and editing function to obtain the shared learning model information list from the shared information management function of the server device. For example, the system administrator can browse all items in the shared learning information list without browsing restrictions like a normal user.

[0336] The system administrator uses the learning model display and editing function to obtain a list of sellable learning model information from the sales information management function of the server device. For example, the system administrator can browse all items in the list of sellable learning information without having to purchase them like a normal user.

[0337] The system administrator's operation history is transmitted to the user operation history information management function of the server device via the network N by the user operation history information transmission function, and is stored as user operation history list information.

[0338] [1-6-4. Store Manager]

[0339] Next, the configuration related to the store manager will be explained.

[0340] The store manager application includes a display and operation unit and a control unit. The display and operation unit displays work information and displays and edits learning model information. The control unit also shares learning model information, allows for consignment sales of learning model information, and transmits user operation history information.

[0341] The store manager application is, for example, a music editing software (DAW), and can display music information in the work information display function. For example, when the DAW has an AI-assisted music production function, new music information can be created while using the learning model information display and editing functions.

[0342] Store managers can use the work information display unit to register work information in the server's database unit. Store managers can use the learning model information display and editing function to register learning model information in the server's database unit. Store managers can issue instructions to the shared information management function from the display operation unit to change the value of the learning model information's sharing permission information from disabling sharing to enabling sharing.

[0343] The store manager uses the sales information management function of the server device to create sales management information from the display operation unit via the network N. When the store manager completes the registration of the sales management information, the store manager issues a registration completion instruction to the sales information management function, thereby changing the sales permission information corresponding to the learning model information from sales prohibition to sales completion.

[0344] By adding the learning model information ID to the shared bookmark list information, the store manager can register the favorite one in the acquired shared learning model information list as the store manager's own bookmark. The store manager can use the learning model information registered as a bookmark.

[0345] The store manager uses the learning model information display and editing function to obtain the shared learning model information list from the shared information management function of the server device. For example, the store manager does not have the browsing restrictions like ordinary users, but can browse all items in the shared learning information list.

[0346] The store manager uses the learning model display and editing function to obtain a list of sellable learning model information from the sales information management function of the server device. For example, the store manager can browse all items in the list of sellable learning information without having to make a purchase like a normal user.

[0347] The store manager's operation history is transmitted to the user operation history information management function of the server device via the network N by the user operation history information transmission function, and is stored as user operation history list information.

[0348] [1-6-5. Ordinary users]

[0349] Next, configuration related to general users will be explained.

[0350] The general user application section includes a display and operation unit and a control unit. The display and operation unit of the general user application section has functions for displaying work information and displaying and editing learning model information. The control unit of the general user application section has functions for sharing learning model information, purchasing learning model information, and transmitting user operation history information.

[0351] Common user applications are, for example, music editing software (DAW), which can display music information through the work information display function. For example, when the DAW has an AI-assisted music production function, new music information can be created while using the learning model information display and editing functions.

[0352] General users can register their own work in the server database unit from the display operation unit of the general user application section using the access authority information management function via the network N. General users create work information using the work information display unit, and the work information is registered in the server database unit via the network N by the work information management function of the server device.

[0353] A general user can create learning model information using the learning model information display and editing function to register the learning model information in the server-inside database unit via the network N through the learning model information management function of the server device.

[0354] For example, after agreeing to the terms of use, an ordinary user can issue an instruction from the display operation unit to the shared information management function of the server device through the network N to change the state of the sharing permission information of the learning model information to share the learning model information. The sharing permission information can take a value indicating, for example, disabling sharing (for example, "0") or enabling sharing (for example, "1"). For example, when registering the learning model information, the sharing permission information included in the learning model information is sharing disabled. Then, the ordinary user issues an instruction to the shared information management function to change the state of the sharing permission information corresponding to the learning model information to enabling sharing.

[0355] An ordinary user can obtain a list of learning model information associated with an author ID indicating the ordinary user himself by issuing a request to browse a list of learning model information created by the ordinary user from the learning model information display and editing function to the learning model information management function of the server device through the network N. The ordinary user can display the list of learning model information obtained from the server device through the learning model information display and editing function.

[0356] Using the learning model information display and editing function, a general user can submit a request to the shared information management function of the server device via the network N to browse a list of shared learning model information. This allows the general user to obtain a list of learning model information that is permitted to be shared from the sharing permission information corresponding to the learning model information. The general user can use the learning model information display and editing function to display the list of shared learning model information returned from the server device.

[0357] An ordinary user sends a shared bookmark request from the learning model information display and editing function to the shared information management function of the server device through the network N, thereby adding the learning model information ID to the shared bookmark list information. Therefore, an ordinary user can register the preferences in the acquired shared learning model information list as his / her own bookmarks. During the bookmark registration process, the number of bookmarks that can be registered can be limited. For example, when the number of learning model information shared by the user himself is n (n is an arbitrary number), the upper limit of the learning model information that can be registered in the bookmark can be set to n×3 (three times the number of learning models provided by the user himself). Therefore, the information processing system can set a limit on the number of registers in the bookmark registration process of the shared information management function. Note that the upper limit is not limited to three times the number of learning models provided by the user himself, but can also be two times, five times, etc.

[0358] An ordinary user requests the sales information management function of the server device to browse the list of sold learning model information from the learning model information display and editing function through the network N, thereby obtaining the sales availability information corresponding to the learning model information as a list of saleable learning model information. An ordinary user can display the list of saleable learning model information returned from the server device through the learning model information display and editing function. An ordinary user selects the desired learning model information from the list of saleable learning model information, and requests the sales information management function to purchase the required learning model information from the learning model information purchase function through the network N. When the ordinary user completes the payment according to the sales price information contained in the sales management information related to the learning model information requested to be purchased, the information processing system registers the purchased learning model information ID in the user purchase list information. For example, the information processing system adds the learning model information ID of the completed purchase to the user purchase list information associated with the information (user ID) of the designated ordinary user.

[0359] The general user submits a request to browse a list of purchased learning model information to the sales information management function of the server device via the learning model information display and editing function via the network N, thereby obtaining user purchase list information containing the general user's user ID from the user purchase list information. In this way, the general user can obtain the list of learning model information IDs contained in the general user's user purchase list information, and the learning model information display and editing function can then display the list of purchased learning model information returned from the server device.

[0360] While referring to the meta-information of the learning model information corresponding to the learning model information, the ordinary user selects the desired learning model information from the acquired learning model information list. The selected learning model information can be used by the learning processing unit included in the server device. For example, if the learning model information is a style palette of an AI-assisted composition system, the selected style palette is used for composition in the learning processing unit.

[0361] The operation history of ordinary users is transmitted by the user operation history information transmission function to the user operation history information management function of the server device via the network N and stored as user operation history list information. The user operation history list information stored in the server device is used by, for example, the learning processing unit and can be used to change the display order according to the user's preference when transmitting the learning model list to the user.

[0362] [1-6-6. Configuration and Effect]

[0363] Figure 24The illustrated information processing system is a work management system that includes a user application program with means for performing display operations and control. The user application program can communicate with a server device that includes control means and information storage means via a network device, and can transmit multiple pieces of work information to the server device via the network device. The transmitted multiple pieces of work information include means for securely storing the work information in the server device.

[0364] Figure 24 The illustrated information processing system is a learning model information management system that includes a learning method using machine learning or deep learning in a server device. The information processing system is capable of learning work information stored in the server device and includes means for storing learning model information, which is a plurality of data sets used for learning, in the server device.

[0365] Figure 24 The information processing system shown includes an access authority information management device in a server apparatus, which can identify a system administrator, a store manager, and a general user according to the user's authority and perform processing according to each authority.

[0366] Figure 24 The illustrated information processing system includes a shared information management device that controls sharing of learning model information in a server device and enables users to share the learning model information.

[0367] exist Figure 24 In the illustrated information processing system, the shared information management device included in the server device is a learning model information sharing system capable of adding a bookmark to a portion of the shared learning model information.

[0368] Figure 24 The shared information management device included in the server device shown can manage the number of pieces of learning model information and multiple bookmarks shared by ordinary users, and includes a device that can control the number of pieces of information that ordinary users can bookmark according to the number of shared information.

[0369] Figure 24 The shared information management means included in the illustrated server device includes means for allowing a system administrator and a store manager to use shared learning model information without limitation in the number of pieces.

[0370] Figure 24 The illustrated information processing system includes sales information management means that controls sales of learning model information in a server device and enables a system administrator to sell the learning model information.

[0371] exist Figure 24In the illustrated information processing system, a store manager can delegate sales of learning model information to a system administrator through the sales information management means included in the server device, and the system administrator can sell the learning model information delegated by the store manager.

[0372] Figure 24 The illustrated information processing system is a learning model information sharing and selling system capable of making available learning model information to be shared and sold based on permission according to the authority of each user.

[0373] Figure 24 The illustrated information processing system is a learning model information sharing and sales system capable of registering a bundled product having a plurality of pieces of learning model information in one product.

[0374] Figure 24 The illustrated information processing system 24 includes means for recording a user's operation history in a server device and enabling the operation record to be used for learning.

[0375] The user can communicate with the server device via the network from the user application, and register multiple pieces of work information in the server's database unit through the work information management function of the server device. These work information is protected by the work information management function and can be prevented from being viewed by other users.

[0376] Users can be divided into system administrators, store managers and ordinary users according to each permission.

[0377] The user can register a plurality of pieces of learning model information using the work information registered in the database unit within the server through the learning model information management function of the server device.

[0378] The shared information management function of the server device allows users to individually set whether to share the learning model information they have registered in the server's database unit. While the learning model information is registered in the server's database unit, it cannot be shared. The shared information management function allows users to change the setting to share.

[0379] When learning model information is changed to enable sharing, the general user agrees to allow all users to use the learning model information. Therefore, the system administrator can freely use the learning model information of the general user.

[0380] The system administrator can use the sales information management function of the server device to individually set whether to sell the learning model information registered by the system administrator in the server's internal database unit. When the learning model information is registered in the server's internal database unit, the learning model information cannot be sold. The system administrator can use the sales information management function to add sales management information and change the learning model information to enable sales.

[0381] The information processing system can register a so-called bundled product having a plurality of pieces of learning model information 123 in one piece of sales management information 124 .

[0382] In the information processing system, a store manager can individually set whether to delegate sales of learning model information registered by the store manager in a database unit within the server using a sales information management function of a server device. When the learning model information is registered in the database unit within the server, delegation is disabled. The store manager can then add sales management information using the sales information management function and change the learning model information to delegate sales.

[0383] The information processing system can commission a bundled product having a plurality of pieces of learning model information in one piece of sales management information.

[0384] The system administrator can change the learning model information from the completed commissioned sales status to the enabled sales status by confirming that the learning model information is in the completed commissioned sales status and issuing a completion registration instruction to the sales information management function.

[0385] An ordinary user can obtain a learning model information list composed by himself / herself by making a request to browse the learning model information list composed by him / herself to the learning model information management function of the server device.

[0386] Ordinary users and store managers can obtain a list of sharable learning model information by requesting the shared learning model information list from the shared information management function of the server device. Store managers can use all sharable learning model information without restriction.

[0387] A general user can register a bookmark for a favorite learning model information by submitting a request to the shared information management function of the server device to register a bookmark for the favorite learning model information. The general user can use only the bookmarked learning model information.

[0388] When the number of pieces of learning model information shared by ordinary users is n, the information processing system may limit the number of pieces of learning model information that ordinary users can bookmark (collect), for example, up to n×3 bookmarks.

[0389] General users and store managers can obtain the list of salable learning model information by requesting the list of salable learning model information from the sales information management function of the server device.

[0390] In the information processing system, ordinary users can make a request to purchase the required learning model information to the sales information management function of the server device, and complete the payment to purchase the required learning model information based on the sales price information corresponding to the sales management information related to the required learning model information.

[0391] An ordinary user can obtain a list of purchased learning model information by requesting the list of purchased learning model information from the sales information management function of the server device.

[0392] The general user can obtain a list of currently available learning model information, select desired learning model information from the meta information of the learning model information corresponding to the learning model information, and use the learning processing unit of the server device.

[0393] The store manager can obtain a list of currently available learning model information and select desired learning model information from the meta information of the learning model information corresponding to the learning model information using the learning processing unit of the server device.

[0394] The learning processing unit can be used when generating learning model information, can be used during batch processing such as at night, or can be used for processing at any time when learning model information is selected.

[0395] In the information processing system, the user operation history is sent to the user operation history information management function of the server device and is stored in the in-server database unit as user operation history information.

[0396] The information processing system can use the user operation history information for processing in the learning processing unit.

[0397] [1-7. User Interface (UI)]

[0398] Here, we will refer to Figure 25 and Figure 26 The description includes details of the automatic composition function displayed through information of the application (music creation application). Figure 25 and Figure 26 is a diagram illustrating an example of a user interface according to an embodiment.

[0399] Figure 25 An example of a user interface when the music composition application is displayed on the screen of the user terminal 10 is shown.

[0400] exist Figure 25 In the example shown, the user interface IF11 displays music data received by the music composition application. Note that, although details will be described later, the music data in the music composition application includes three different types of data: melody, chords, and bass. Figure 25The user interface IF11 shown displays data related to the melody among three different data.

[0401] The setting information ST11 displays information on a style palette, which is an example of setting information in the automatic music composition function. The style palette is designation information for designating material music to be learning data for machine learning.

[0402] Setting information ST12 displays harmony information as an example of setting information for the automatic composition function. Harmony information is information used to determine, for example, the probability that the components of a chord will appear in the melody of the music data composed by the processing server 100. For example, if the user sets the harmony information to "strict," the probability that the components of the chord will appear in the melody of the automatically composed music data increases. On the other hand, if the user sets the harmony information to "loose," the probability that the components of the chord will appear in the melody of the automatically composed music data decreases. Figure 25 The example in indicates that the user applies "strict" to the harmony information.

[0403] Setting information ST13 displays note duration information as an example of setting information for the automatic composition function. Note duration information is information used, for example, to determine the duration of notes in the music data composed by the processing server 100. For example, when the user sets the note timing information to "long," the probability that notes with relatively long sound durations (e.g., whole notes and half notes) will appear in the automatically composed music data increases. On the other hand, when the user sets the note duration information to "short," the probability that notes with relatively short sound durations (e.g., eighth notes and sixteenth notes) will appear in the automatically composed music data increases.

[0404] The setting information ST14 displays information for determining the type and amount of material music other than the material music included in the designated information (the style palette designated by the user), which is an example of setting information in the automatic composition function. This information is, for example, information for determining whether to strictly perform learning based on the music included in the style palette designated by the user in the music data composed by the processing server 100. For example, when the user sets this information to "never", it is unlikely that music other than the music included in the style palette will be used in learning in the automatic composition. On the other hand, when the user sets this information to "only", it is likely that music other than the music included in the style palette will be used in learning in the automatic composition.

[0405] The music data MDT1 represents specific music data transmitted from the processing server 100. Figure 25In the example of , the music data MDT1 includes information indicating a chord progression such as Cm, information indicating pitches or note durations in a measure, transitions in note pitches (in other words, melody), and the like. Figure 25 As shown, the music data MDT1 may include, for example, four different types of content. In other words, the processing server 100 can transmit multiple pieces of music data as automatically created music data, rather than just one type. Thus, the user can select their favorite music data from among the multiple pieces of music data generated as candidates, or create their favorite music by combining multiple pieces of music data.

[0406] Notice, Figure 25 The user interface IF11 shown in FIG displays data related to the melody among three different data of melody, chord, and bass included in the music data, but other data are displayed on other user interfaces. This will be referred to in detail in FIG. Figure 26 Provide explanation.

[0407] like Figure 26 As shown, in addition to the user interface IF11 displaying data related to the melody, the user terminal 10 may display a user interface IF12 displaying data related to the chord and a user interface IF13 displaying data related to the bass on the screen. Figure 26 Although not shown, user interfaces IF12 and IF13 display note information different from that of the music data MDT1 in user interface IF11. Specifically, user interface IF12 displays note information related to chords corresponding to the melody of the music data (e.g., the constituent notes of the chord Cm). Furthermore, user interface IF13 displays note information related to the bass notes corresponding to the melody or chords of the music data (e.g., the note "C" for the chord Cm).

[0408] The user can select information to be copied from the displayed user interface IF11 , user interface IF12 , and user interface IF13 , and, for example, create a work such as editing a part of a bass.

[0409] [1-8. Information Display]

[0410] Terminal devices such as the system administrator terminal 10, the store manager terminal 20, and the general user terminal 30 can display various types of information. Figures 27 to 30 Explain this point.

[0411] [1-8-1. Screen example of the created score data list]

[0412] First, refer to Figure 27 This section describes the display of a list of composed score data. Figure 27is a schematic diagram showing an example of display information. Specifically, Figure 27 : is a diagram showing an example of a screen showing a list of composed musical score data. Figure 27 In the description, the case where the general user terminal 30 used by user #001 displays information is taken as an example.

[0413] exist Figure 27 , an image IM11 displaying a list of composed musical score data is shown as an example. The general user terminal 30 displays the image IM11 representing the musical score data composed by user #001. The general user terminal 30 displays a list of information indicating a plurality of pieces of musical score data composed by user #001, such as titles #001 to #015. User #001 edits or deletes the musical score data corresponding to each title by operating an edit button labeled "Edit" or a delete button labeled "Delete" displayed to the right of each title. Furthermore, user #001 adds musical score data by operating an add button labeled "Add." In this manner, the user adds, edits, or deletes musical score data by performing operations on the image IM11.

[0414] [1-8-2. Screen example for creating a Style Palette]

[0415] Next, we will refer to Figure 28 This section explains the display of a list of composed score data. Figure 28 is a schematic diagram showing an example of display information. Specifically, Figure 28 : is a diagram showing an example of a screen for creating a style palette. Figure 28 In the description, the case where a general user terminal 30 displays information is taken as an example.

[0416] Figure 28 is an example showing an image IM21 displaying information for creating a style palette. The general user terminal 30 displays an image IM21 including a field (form) for the user to input information for creating a style palette. The general user terminal 30 displays an image IM21 including a field at the top for inputting the name of the style palette corresponding to [Name], a field below for inputting the creator corresponding to [Author], and the like. In addition, the [Style Palette] column includes items such as tempo, atmosphere, structure, chord progression, mode, and the like. Tempo is information indicating the tempo of music, and fast tempo (up), slow tempo (slow), and the like are input. Atmosphere is information indicating the atmosphere of music, and cheerful (plus), melancholic (minus), and the like are input. Structure is information indicating the structure of music, and structure #001, structure #002, and the like are input. Note that in Figure 28In the example of , the structure is indicated by a character string such as structure#001, but any information can be used as long as the structure can be specified. For example, the structure may be information such as "A measure" or "B measure". The chord progression is information indicating the chord progression of the music, and chord progression#001, etc. is input. Figure 28 In the example of , the chord progression is represented by a character string such as chord progression #001, but any information can be used as long as the chord progression can be specified. For example, the chord progression can be information that specifically indicates the chord progression, such as "FCBE" or "C-Am-FG". The mode is information indicating the mode of the music, and mode #001, mode #002, etc. are input. Figure 28 In the example shown in FIG, the mode is indicated by a character string such as mode#001, but any information can be used as long as the mode can be specified. For example, the mode may be information specifically indicating a mode based on music theory. For example, the mode may be information such as "Dorian," "Phrygian," "Lydian," "Mixolydian," "Aeolian," or "Locrian."

[0417] Furthermore, the general user terminal 30 displays an image IM21, which includes fields for specifying the musical score (data) that will become an element of the style palette corresponding to the [Element] at the bottom. Within the [Element] section, a title corresponding to each piece of music (musical score), the composer, and data (such as a hash value) obtained by encoding (encrypting) predetermined data are displayed. User #001 selects or deletes the musical score data corresponding to each element by operating a select button labeled "Select Song" or a delete button labeled "Delete Row" displayed to the right of each element in the [Element]. In this way, the user operates the image IM21 to input various types of information, select musical score data, or deselect musical score data. The information items in the [Style Palette] section, such as tempo, atmosphere, structure, chord progression, and mode, can be input by a user, such as a general user, or automatically by a terminal device, such as the general user terminal 30. For example, when the general user terminal 30 automatically inputs information, the general user terminal 30 may generate information to be input into items such as tempo, atmosphere, structure, chord progression, and mode based on the music (music score) information registered in [Element]. For example, the general user terminal 30 may generate information to be input into the tempo item based on the tempo of the music (music score) registered in [Element]. If the tempo of the music (music score) registered in [Element] is slow, the general user terminal 30 inputs "slow" into the tempo item.

[0418] [1-8-3. Screen example showing the list of sales-registered style palettes]

[0419] Next, we will refer to Figure 29 This section describes the display of a list of composed score data. Figure 29 is a schematic diagram showing an example of display information. Specifically, Figure 29 : is a diagram showing an example of a screen displaying a list of style palettes registered for sale. Figure 29 In the description, the case where the general user terminal 30 used by user #001 displays information is taken as an example.

[0420] Figure 29 An example of an image IM31 showing a list of style palettes registered for sale is shown. The general user terminal 30 displays the image IM31, which includes a list of style palettes registered for sale. The general user terminal 30 displays a list including a style palette named "SP#001" (Style Palette SP#001) created by "User#001." Style Palette SP#001 has an "up" tempo, a "plus" atmosphere, a "Structure#002" structure, a "Chord Progression#005" chord progression, and a "Mode#001" mode. Users can edit or delete style palettes by operating the "Edit" button or the "Delete" button displayed to the right of each style palette. Furthermore, users can add style palettes by operating the "Add" button. In this way, users can add, edit, or delete style palettes by performing operations on the image IM31.

[0421] [1-8-4. Screen example showing the self-managed style palette list]

[0422] Next, we will refer to Figure 30 This section describes the display of a list of composed score data. Figure 30 is a schematic diagram showing an example of display information. Specifically, Figure 30 : is a diagram illustrating an example of a screen displaying a list of self-managed style palettes. Figure 30 An example is shown which will explain a case where the general user terminal 30 displays information.

[0423] Figure 30 An example of an image IM41 displaying information for managing style palettes is shown. The general user terminal 30 displays a list of style palettes. The general user terminal 30 can display a list of style palettes managed by the user using the general user terminal 30. For example, the list of style palettes shown in the image IM41 can include style palettes created by the user, bookmarked style palettes, and purchased style palettes.

[0424] [2. Other embodiments]

[0425] In addition to the above-described embodiments and modifications, the processing according to the above-described embodiments and modifications can be performed in various different forms (modifications).

[0426] [2-1. Other configuration examples]

[0427] Each of the above configurations is an example, and the information processing system 1 may have any system configuration as long as it can implement the above information processing. For example, the information processing device 100 and the system administrator terminal 10 may be integrated. For example, the system administrator terminal 10 may be an information processing device having the functions of the information processing device 100.

[0428] [2-2. Others]

[0429] In the processes described in the above embodiments, all or part of the processes that are automatically performed may be performed manually, or all or part of the processes that are manually performed may be automatically performed by known methods. In addition, unless otherwise specified, the processes, specific names, and information including various data and parameters shown herein and in the accompanying drawings may be changed arbitrarily. For example, the various types of information shown in the various figures are not limited to the information shown.

[0430] In addition, each component of each device shown in the drawings is conceptual in function and is not necessarily physically configured as shown in the drawings. In other words, the specific distribution and integration form of each device is not limited to the form shown, and all or part of it can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0431] Furthermore, the above-described embodiments and modifications can be appropriately combined within a range not contradicting the processes.

[0432] Note that the effects described in this specification are merely exemplary and non-limiting, and other effects may be provided.

[0433] [3. Effects of the present disclosure]

[0434] As described above, the information processing device according to the present disclosure (the information processing device 100 in the embodiment) includes a generation unit (the generation unit 132 in the embodiment) and a determination unit (the determination unit 133 in the embodiment). The generation unit generates a model for content generation by using data provided by a user subject having one of a plurality of permission levels for content creation services. The determination unit determines a usage pattern of the model generated by the generation unit according to the one permission level of the user subject.

[0435] Therefore, the information processing device according to the present disclosure can determine the usage mode of the model by which the data provided by the subject is used to generate the model, and can appropriately determine the usage mode of the model according to which permission level is assigned to the model based on the subject's data. Therefore, the information processing device can appropriately use the model according to the data used to generate the model.

[0436] Furthermore, the determination unit determines the scope of use of the model in the service based on a permission level. Thus, the information processing device determines the scope of use of the model in the service based on a permission level, thereby appropriately determining the scope of use based on the permission level assigned to the model based on the subject's data. Consequently, the information processing device can appropriately use the model based on the data used to generate the model.

[0437] Furthermore, the determination unit determines whether the model can be sold or shared based on a permission level. Thus, the information processing device determines whether the model can be sold or shared based on a permission level, so the information processing device can appropriately determine whether the model can be sold or shared based on the permission level assigned to the model based on the subject's data. Consequently, the information processing device can appropriately use the model based on the data used to generate the model.

[0438] Furthermore, the generation unit generates a model using data provided by a user subject having one of a plurality of permission levels, the plurality of permission levels including a first permission level granted to a service administrator, a second permission level granted to sellers selling the service, and a third permission level granted to ordinary users using the service. When the user subject has a first permission level, the determination unit determines that the model can be used for services corresponding to the first permission level; when the user subject has a second permission level, the determination unit determines that the model can be used for services corresponding to the second permission level; and when the user subject has a third permission level, the determination unit determines that the model can be used for services corresponding to the third permission level. Thus, the information processing device can generate a model using data from a subject assigned one of the first to third permission levels, and can appropriately determine the scope of use based on the permission level assigned to the model based on the subject's data. Consequently, the information processing device is able to appropriately use the model based on the data used to generate the model.

[0439] The generation unit generates a model using data provided by a user subject having one of a plurality of permission levels, the plurality of permission levels including a second permission level having more limited permissions than the first permission level and a third permission level having more limited permissions than the second permission level. Thus, the information processing device can generate a model using data of a subject assigned one of the first to third permission levels, the authorized content of the subject being restricted according to the permission level. The information processing device can then appropriately determine the scope of use based on which permission level the model is assigned based on the subject's data. Therefore, the information processing device is able to appropriately use the model based on the data used to generate the model.

[0440] Furthermore, the generation unit generates a model using data provided by a user subject having one of a plurality of authority levels including a first authority level, and the user subject can accept a commissioned sale from a user subject having a second authority level. Thus, the information processing device enables the user subject having the first authority level to sell a model generated using data from a subject having the second authority level, thereby enabling the model to be appropriately used based on the data used to generate the model.

[0441] Furthermore, the generation unit generates a model by using data provided by a user subject having one of a plurality of permission levels including a second permission level, and the user subject can sell and share the model generated using the data of the user subject having the second permission level. Thus, the information processing device enables the subject to sell and share the model generated using the data of the subject having the second permission level, thereby enabling the model to be appropriately used according to the data used to generate the model.

[0442] Furthermore, the generation unit generates a model by using data provided by a user subject having one of a plurality of permission levels including a third permission level, and the user subject can share the model generated using the data of the user subject having the third permission level. Therefore, the information processing device enables subjects to share only the model generated using the data of the subject having the third permission level, thereby enabling the model to be appropriately used according to the data used to generate the model.

[0443] The generation unit generates meta-information corresponding to the model based on the data provided by the user. Therefore, by generating meta-information corresponding to the model, the information processing device can confirm the content of the model and promote the use of the model. As a result, the information processing device can appropriately use the model based on the data used to generate the model.

[0444] Furthermore, the information processing device includes a sending unit (sending unit 134 in this embodiment). The sending unit sends the model to the terminal device used by the user subject. Therefore, the information processing device can confirm the model generated by the user subject who provided the data by sending the model to the terminal device used by the user subject.

[0445] Furthermore, the information processing device includes an accepting unit (accepting unit 135 in the embodiment). The accepting unit accepts data from the user subject. Therefore, the information processing device can generate a model using the data accepted from the user subject.

[0446] Furthermore, the generation unit generates a model when the reception unit receives data. The transmission unit transmits the model to the terminal device when the generation unit generates the model. Thus, the information processing device can accept data from a specific entity, generate a model, and provide the model to the entity at the timing of the generation. In this way, the information processing device can provide the model to the data provider in a short period of time by generating and providing the model at the timing of a model generation request from a specific entity.

[0447] Furthermore, the determining unit determines information to be provided to a user subject based on the service usage history of the user subject.

[0448] Furthermore, the determining unit determines a plurality of models to provide information to a user subject. The generating unit generates information regarding a list of the plurality of models determined by the determining unit. Thus, the information processing device generates information regarding a list of the plurality of models to provide information to a user subject, thereby enabling information about the models to be provided to the user subject and facilitating the use of the models by the user subject.

[0449] Furthermore, the determination unit determines a recommended model to be recommended to a user subject from among the plurality of models. Thus, the information processing device determines a recommended model to be recommended to a user subject from among the plurality of models, thereby recommending the use of the model to the user subject and promoting the use of the model by the user subject.

[0450] Furthermore, the generation unit generates a model for music generation, which is content, by using data provided by a user subject having one of a plurality of permission levels for a music creation service. Therefore, the information processing device can appropriately determine a usage pattern for the model based on the permission level of the service assigned for music (i.e., content) creation based on the data of the subject to which the permission level is assigned. Therefore, the information processing device can appropriately use the model in a service related to music creation as content based on the data used to generate the model.

[0451] In addition, the information processing device includes a providing unit (providing unit 136 in this embodiment). The providing unit provides a music listening service. Therefore, the information processing device can predetermine what kind of music will be generated before purchasing and sharing the model, thereby improving user satisfaction and promoting the use of the model.

[0452] In addition, the providing unit provides a music listening service generated when using the model. Therefore, the information processing device can predetermine what kind of music is generated using the model, thereby improving user satisfaction and promoting the use of the model.

[0453] [4. Hardware Configuration]

[0454] The information processing apparatuses such as the information processing device 100, the system administrator terminal 10, the store manager terminal 20 and the general user terminal 305 according to the above-described embodiment and the modified example are composed of, for example, a computer having Figure 31 The configuration shown is implemented by a computer 1000 . Figure 31 1 is a schematic diagram showing an example of the hardware configuration of a computer 1000 that implements the functions of information processing devices such as an information processing device 100, a system administrator terminal 10, a store manager terminal 20, and a general user terminal 30. Hereinafter, the information processing device 100 according to the embodiment will be described as an example. The computer 1000 includes a CPU 1100, a RAM 1200, a read-only memory (ROM) 1300, a hard disk drive (HDD) 1400, a communication interface 1500, and an input / output interface 1600. Each unit of the computer 1000 is connected by a bus 1050.

[0455] The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. For example, the CPU 1100 expands and stores a program in the RAM 1200, the ROM 1300, or the HDD 1400 and executes processing corresponding to each program.

[0456] The ROM 1300 stores startup programs such as a basic input output system (BIOS) executed by the CPU 1100 when the computer 1000 is activated, programs depending on the hardware of the computer 1000 , and the like.

[0457] HDD 1400 is a computer-readable recording medium that non-temporarily records a program executed by CPU 1100 , data used by the program, and the like. Specifically, HDD 1400 is a recording medium that records an information processing program according to the present disclosure, which is an example of program data 1450 .

[0458] The communication interface 1500 is an interface for connecting the computer 1000 to an external network 1550 (eg, the Internet). For example, the CPU 1100 receives data from another device through the communication interface 1500 or transmits data generated by the CPU 1100 to another device.

[0459] The input / output interface 1600 is an interface for connecting the input / output device 1650 and the computer 1000. For example, the CPU 1100 receives data 1600 from an input device such as a keyboard or a mouse via the input / output interface. In addition, the CPU 1100 sends data to an output device such as a display, a speaker, or a printer via the input / output interface 1600. In addition, the input / output interface 1600 can be used as a medium interface for reading a program recorded in a predetermined recording medium (medium). The medium is, for example, an optical recording medium such as a digital versatile disk (DVD) or a phase-change rewritable disk (PD), a magneto-optical recording medium such as a magneto-optical disk (MO), a magnetic tape medium, a magnetic recording medium, a semiconductor memory, etc.

[0460] For example, in the case where the computer 1000 is used as the information processing apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control unit 130 and the like by executing the information processing program loaded on the RAM 1200. In addition, the HDD 1400 stores the information processing program and data according to the present disclosure in the storage unit 120. Note that the CPU 1100 reads the program data 1450 from the HDD 1400 and executes the program data, but as another example, these programs may be acquired from another device via the external network 1550.

[0461] Note that the present technology can also have the following configurations.

[0462] (1) An information processing device comprising:

[0463] a generating unit that generates a model regarding content generation by using data provided by a user subject regarding a content creation service, the user subject having one of a plurality of authority levels of the service; and

[0464] The determination unit determines, according to a permission level of the user subject, a usage mode of the model generated by the generation unit.

[0465] (2) The information processing device according to (1), wherein:

[0466] The determination unit determines the usage scope of the model in the service according to a permission level.

[0467] (3) The information processing device according to (1) or (2), wherein:

[0468] The determination unit determines the selling or sharing possibility of the model according to a permission level.

[0469] (4) The information processing apparatus according to any one of (1) to (3), wherein:

[0470] The generating unit generates a model by using data provided by a user subject having one of a plurality of authority levels, the plurality of authority levels including a first authority level given to an administrator of the service; a second authority level given to a seller who sells in the service; and a third authority level given to an ordinary user who uses the service, and

[0471] The determination unit determines that a model corresponding to the first permission level can be used in the service when a permission level of the user subject is the first permission level; determines that a model corresponding to the second permission level can be used in the service when a permission level of the user subject is the second permission level; and determines that a model corresponding to the third permission level can be used in the service when a permission level of the user subject is the third permission level.

[0472] (5) The information processing device according to (4), wherein:

[0473] The generating unit generates a model by using data provided by a user subject having one of a plurality of permission levels, the plurality of permission levels including a second permission level with more limited permission than the first permission level and a third permission level with more limited permission than the second permission level.

[0474] (6) The information processing device according to (4) or (5), wherein

[0475] The generating unit generates a model by using data provided by a user subject having one of a plurality of authority levels, the plurality of authority levels including the ability to accept consigned sales from a user subject having a second authority level.

[0476] (7) The information processing apparatus according to any one of (4) to (6), wherein:

[0477] The generating unit generates a model by using data provided by a user subject having one of a plurality of authority levels including a second authority level, and the user subject can sell and share the model generated using the data of the user subject having the second authority level.

[0478] (8) The information processing apparatus according to any one of (4) to (7), wherein:

[0479] The generation unit generates a model by using data provided by a user subject having one of a plurality of authority levels including a third authority level, and the user subject can share the model generated by using the data of the user subject having the third authority level.

[0480] (9) The information processing apparatus according to any one of (1) to (8), wherein:

[0481] The generating unit generates meta information corresponding to the model based on data provided by the user subject.

[0482] (10) The information processing apparatus according to any one of (1) to (9), further comprising:

[0483] The sending unit sends the model to the terminal device used by the user subject.

[0484] (11) The information processing device according to (10), further comprising:

[0485] The receiving unit receives data from the user subject, wherein:

[0486] The generating unit generates a model in response to the receiving unit's acceptance of data.

[0487] (12) The information processing device according to (11), wherein:

[0488] The generating unit generates a model at the timing when the receiving unit receives data, and

[0489] The sending unit sends the model to the terminal device at the timing when the generating unit generates the model.

[0490] (13) The information processing apparatus according to any one of (1) to (12), wherein:

[0491] The determination unit determines information to be provided to a user subject based on a history of service use by the user subject.

[0492] (14) The information processing device according to (13), wherein:

[0493] The determining unit determines a plurality of models, and information of the plurality of models is provided to a user subject, and

[0494] The generating unit generates list information of the plurality of models determined by the determining unit.

[0495] (15) The information processing device according to (13) or (14), wherein:

[0496] The determination unit determines a recommended model from a plurality of models and recommends the recommended model to a user subject.

[0497] (16) The information processing apparatus according to any one of (1) to (15), wherein:

[0498] The generation unit generates a model regarding music generation, the content being music, by using data provided by a user subject having one of a plurality of authority levels regarding a content creation service.

[0499] (17) The information processing device according to (16), further comprising:

[0500] A providing unit that provides music listening services.

[0501] (18) The information processing device according to (17), wherein

[0502] The providing unit provides a listening service of music generated when using the model.

[0503] (19) An information processing method executed by a computer, the method comprising:

[0504] generating a model regarding content generation by using data provided by a user subject of a service regarding content creation, the user subject having one of a plurality of permission levels of the service; and

[0505] Determines the usage pattern of the model generated based on one permission level of the user principal.

[0506] (20) Cause the computer to execute the following information processing program:

[0507] generating a model regarding content generation by using data provided by a user subject of a service regarding content creation, the user subject having one of a plurality of permission levels of the service; and

[0508] Determines the usage pattern of the model generated based on one permission level of the user principal.

[0509] Reference Signs List

[0510] 1 Information Processing System

[0511] 100 Information processing equipment

[0512] 110 Communication Unit

[0513] 120 storage units

[0514] 121 User information storage unit

[0515] 122 Work information storage unit

[0516] 123 learning model information storage unit

[0517] 124 sales management information storage unit

[0518] 125 shared information storage unit

[0519] 126 Purchase information storage unit

[0520] 127 Operation history information storage unit

[0521] 130 control unit

[0522] 131 Acquisition Unit

[0523] 132 generation units

[0524] 133 Determine unit

[0525] 134 sending unit

[0526] 135 receiving units

[0527] 136 units provided

[0528] 10 System Administrator Terminal

[0529] 20 Store Manager Terminal

[0530] 30 Ordinary user terminals

Claims

1. An information processing device, comprising: a generating unit configured to generate a model regarding content generation by using data provided by a user subject of a service regarding content creation, the user subject having one of a plurality of authority levels of the service; and A determining unit determines a usage mode of the model generated by the generating unit according to the one permission level of the user subject.

2. The information processing device according to claim 1, wherein: The determining unit determines a usage scope of the model in the service according to the one permission level.

3. The information processing device according to claim 1, wherein: The determining unit determines whether the model can be sold or shared according to the one authority level.

4. The information processing device according to claim 1, wherein the generating unit generates the model by using the data provided by the user subject having the one of the plurality of authority levels, the plurality of authority levels including a first authority level granted to an administrator of the service, a second authority level granted to a seller who makes sales in the service, and a third authority level granted to an ordinary user who uses the service, and The determination unit determines that the model can be used in the service corresponding to the first permission level when the one permission level of the user subject is the first permission level; determines that the model can be used in the service corresponding to the second permission level when the one permission level of the user subject is the second permission level; and determines that the model can be used in the service corresponding to the third permission level when the one permission level of the user subject is the third permission level.

5. The information processing device according to claim 4, wherein The generation unit generates the model by using the data provided by the user subject having the one authority level among the plurality of authority levels including the second authority level having more limited authority than the first authority level and the third authority level having more limited authority than the second authority level. The information processing device according to claim 4 , wherein The generation unit generates the model by using the data provided by the user subject having the one authority level among the plurality of authority levels including the first authority level, the first authority level being capable of accepting a sales commission from the user subject having the second authority level.

7. The information processing device according to claim 4, wherein The generation unit generates the model by using the data provided by the user subject having the one authority level among the plurality of authority levels including the second authority level, which enables selling and sharing of the model generated using the data of the user subject having the second authority level.

8. The information processing device according to claim 4, wherein The generation unit generates the model by using the data provided by the user subject having the one authority level among the plurality of authority levels including the third authority level, and the third authority level can share the model generated using the data of the user subject having the third authority level.

9. The information processing device according to claim 1, wherein The generating unit generates meta information corresponding to the model according to the data provided by the user subject.

10. The information processing device according to claim 1, further comprising: A sending unit sends the model to a terminal device used by the user subject.

11. The information processing device according to claim 10, further comprising: A receiving unit receives the data from the user subject, wherein The generating unit generates the model in response to the receiving unit accepting the data.

12. The information processing device according to claim 11, wherein: The generating unit generates the model at a time when the receiving unit receives the data, and The sending unit sends the model to the terminal device when the generating unit generates the model.

13. The information processing device according to claim 1, wherein: The determining unit determines information to be provided to the one user subject based on a history of the one user subject using the service.

14. The information processing device according to claim 13, wherein The determining unit determines a plurality of models, information of the plurality of models is provided to the one user subject, and The generating unit generates list information of the plurality of models determined by the determining unit.

15. The information processing device according to claim 14, wherein: The determining unit determines a recommended model from the plurality of models, and recommends the recommended model to the one user subject.

16. The information processing device according to claim 1, wherein: The content is music.

17. The information processing device according to claim 16, further comprising: A providing unit for providing a listening service of the music.

18. The information processing device according to claim 17, wherein The providing unit provides the listening service of the music generated when using the model.

19. An information processing method executed by a computer, the information processing method comprising: generating a model for content creation by using data provided by a user subject of a service for content creation, the user subject having one of a plurality of permission levels for the service; and A usage pattern of the model generated according to the one permission level of the user principal is determined.

20. A computer-readable storage medium storing an information processing program for causing a computer to execute the following steps: generating a model regarding content generation by using data provided by a user subject of a service regarding content creation, the user subject having one of a plurality of permission levels of the service; and A usage pattern of the model generated according to the one permission level of the user principal is determined.

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