Information processing device, method, and program

Abstract

The present invention provides an information processing device, method, and program capable of identifying the taste of an object. [Solution] The information processing device includes an acquisition unit 51 that acquires information relating to the taste image of an object as image information, an identification unit 52 that analyzes the image information to identify the taste corresponding to the object and converts it into taste information, and an output unit 53 that outputs the taste information corresponding to the object.

Description

Technical Field

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

Background Art

[0002] Measuring the taste of foods and the like with a taste sensor is conventionally performed.

[0003] For example, Patent Document 1 discloses a taste sensor whose membrane potential changes in response to a substance in a liquid to be measured.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, taste sensors require that the actual food or other item to be measured is prepared. In contrast, it is difficult to measure abstract tastes such as the taste of fictional food and drink that appear in animations, dramas, comics, movies and the like, or the taste of one's hometown, using a taste sensor. For this reason, identifying the taste of such food and drink has been a technical problem.

[0006] In view of the above problems, the present disclosure aims to provide an information processing apparatus, method, and program that are capable of identifying the taste of a target object.

Means for Solving the Problems

[0007] To solve the above problems, the information processing device according to the first aspect of this disclosure includes an acquisition unit that acquires information relating to the taste image of an object as image information, an identification unit that analyzes the image information to identify the taste corresponding to the object and converts it into taste information, and an output unit that outputs the taste information corresponding to the object.

[0008] Furthermore, in the information processing apparatus according to the second aspect of this disclosure, in the first aspect, the acquisition unit acquires as image information information information that each of the multiple users imagines for the object.

[0009] Furthermore, in the information processing device relating to the third aspect of this disclosure, in the first to second aspects, the object is a fictional food or beverage.

[0010] Furthermore, in the information processing apparatus according to the fourth aspect of this disclosure, in the first to second aspects, the acquisition unit acquires standard information relating to a standard taste corresponding to the object, and the identification unit identifies the taste information corresponding to the object based on the standard information.

[0011] Furthermore, in the information processing apparatus according to the fifth aspect of this disclosure, in the third aspect, the acquisition unit acquires standard taste information corresponding to existing food and beverages of the same type as the object, and the identification unit identifies the taste information corresponding to the object based on the standard information.

[0012] Furthermore, in the information processing apparatus according to the sixth aspect of this disclosure, in the first to second aspects, the identifying unit identifies at least one of the following information based on the image information: information relating to a positive taste image of the object and information relating to a negative taste image of the object, and uses this information to identify the taste information.

[0013] Furthermore, in the information processing apparatus according to the seventh aspect of this disclosure, in the first to second aspects, the identification unit identifies keyword information indicating the taste characteristics of the object from the image information, and identifies the taste information using the keyword information.

[0014] Furthermore, in the information processing device according to the eighth aspect of this disclosure, in the first to second aspects, the taste information is information in which the taste corresponding to the object is quantified corresponding to each of a plurality of elements related to taste.

[0015] Furthermore, in the information processing apparatus according to the ninth aspect of this disclosure, in the first to second aspects, the acquisition unit acquires information relating to a target image of the taste of the object as image information, and the identification unit identifies the taste information based on the image information.

[0016] Furthermore, in the information processing apparatus according to the tenth aspect of this disclosure, in the ninth aspect, the acquisition unit acquires, as image information, information relating to each user's taste image of the object and information relating to the target taste image of the object, and the identification unit identifies the taste information by prioritizing the information relating to the target taste image of the object over the information relating to each user's taste image of the object.

[0017] Furthermore, in the information processing device relating to the eleventh aspect of this disclosure, in the first to second aspects, the taste information is digital data utilizing blockchain.

[0018] Furthermore, the method according to the twelfth aspect of this disclosure includes the steps of: acquiring information relating to the taste image of an object as image information; analyzing the image information to identify a taste corresponding to the object and converting it into taste information; and outputting the taste information corresponding to the object.

[0019] Further, a program according to the thirteenth aspect of the present disclosure causes a computer to function as: an acquisition unit that acquires, as image information, information relating to a taste image of a target object; a specification unit that analyzes the image information to specify a taste corresponding to the target object and sets the taste as taste information; and an output unit that outputs the taste information corresponding to the target object. [Effects of the Invention]

[0020] According to the information processing apparatus, method, and program of the present disclosure, the taste of a target object can be specified. [Brief Description of the Drawings]

[0021] [Figure 1] 1 is a schematic diagram illustrating an example of the overall configuration of a system according to a first embodiment of the present disclosure. [Figure 2] 1 is a diagram schematically illustrating an example of a hardware configuration of a server apparatus. [Figure 3] 1 is a diagram schematically illustrating an example of a hardware configuration of a terminal apparatus. [Figure 4] 3 is a block diagram illustrating an example of a functional configuration of a server apparatus. [Figure 5] 3 is a diagram illustrating an example of a reference table. [Figure 6] 3 is a diagram illustrating an example of a reference taste of food and drink. [Figure 7] 3 is a diagram illustrating an example of a screen of a terminal apparatus when an instruction to specify a target object is received. [Figure 8] 3 is a diagram illustrating an example of a screen of a terminal apparatus on which a questionnaire relating to a taste image of a target object is displayed. [Figure 9] 7 is a diagram illustrating a modification example of the reference taste in Fig. 6. [Figure 10] 3 is a diagram illustrating an example of a screen of a terminal apparatus on which a result of specifying the taste of a target object is displayed. [Figure 11] 3 is a flowchart illustrating an example of a flow of processing in a system. [Mode for Carrying Out the Invention]

[0022] Hereinafter, embodiments of the present disclosure (hereinafter referred to as "these embodiments") will be described with reference to the attached drawings. To facilitate understanding of the description, the same reference numerals are used for the same components and steps in each drawing whenever possible, and redundant explanations are omitted.

[0023] ---First Embodiment--- First, let me describe the first embodiment.

[0024] <Overall Structure> Figure 1 is a schematic diagram showing an example of the overall configuration of System 1 according to the first embodiment of this disclosure. System 1 identifies the taste of an object.

[0025] In this embodiment, the "object" is an object used to identify a taste. That is, the object is food or beverage. Note that "food and beverage" is a general term that includes both food and drink. That is, "food and beverage" may refer to food or to drink. In this embodiment, the object is fictional food or beverage. Fictional food and beverage is, for example, imaginary food or beverage that appears in anime, dramas, comics, movies, etc. Note that the object may also be food or beverage from a specific region, such as food or beverage from one's hometown (the taste of one's hometown), or, for example, food or beverage from the past described in literature, food or beverage from a foreign country, or rare food or beverage that is difficult to obtain. In this way, the object can be applied in various ways as an object to identify a taste. The object is set in advance by the user, for example.

[0026] In this embodiment, the object in question is described as a fictional food or drink that appears in a particular anime.

[0027] Furthermore, in this embodiment, "taste" encompasses a broad meaning, referring to anything that humans can perceive through sensory organs such as the tongue. For example, taste can be perceived through the sense of taste. For instance, taste is composed of elements such as sweetness, saltiness, sourness, bitterness, and umami.

[0028] As shown in Figure 1, System 1 comprises a server device 10, one or more external devices 12, and one or more terminal devices 13. The server device 10, the external devices 12, and the terminal devices 13 are connected to each other via a communication network NT, such as an internet connection.

[0029] Server device 10 is an information processing device (computer) that identifies the taste of an object. For example, fictional food and drink or the taste of one's hometown may not have a specific taste and may be associated with various images. Therefore, server device 10 identifies the taste of such abstract tastes. Server device 10 may be cloud-based or on-premise.

[0030] External device 12 is an information processing device (computer) that communicates with server device 10. External device 12 is, for example, a server device different from server device 10. For example, external device 12 is a device that provides various services such as web pages and SNS (social networking services). Multiple external devices 12 corresponding to different services may be connected to server device 10.

[0031] Terminal device 13 is an information processing device (computer) used by the user. Terminal device 13 can be, for example, a personal computer, a smartphone, or a tablet. In this embodiment, the case where terminal device 13 is a smartphone is used as an example. Each user uses terminal device 13, and multiple terminal devices 13, such as terminal device 13A and terminal device 13B, are connected to the server device 10.

[0032] <Hardware Configuration> The hardware configuration of the server device 10 and the terminal device 13 will be explained using Figures 2 and 3.

[0033] (Hardware configuration of server device 10) Figure 2 is a schematic diagram showing an example of the hardware configuration of server device 10.

[0034] As shown in Figure 2, the server device 10 comprises a control device 20, a communication device 26, and a storage device 28. The control device 20 is mainly composed of a CPU (Central Processing Unit) 22 and memory 24.

[0035] The control device 20 functions as various functional means by having the CPU 22 execute a predetermined program stored in the memory 24 or storage device 28, etc. Details of these functional means will be described later.

[0036] The communication device 26 consists of a communication interface and the like for communicating with external devices. The communication device 26 sends and receives various types of information with, for example, the external device 12 and the terminal device 13.

[0037] The storage device 28 is composed of a hard disk or the like. The storage device 28 stores various programs and information necessary for executing processing in the control device 20, as well as information such as processing results. The storage device 28 is an example of a storage medium (a non-temporary computer-readable storage medium).

[0038] The server device 10 can be implemented using an information processing device such as a dedicated or general-purpose server computer. Furthermore, the server device 10 may consist of a single information processing device or multiple information processing devices distributed over the communication network NT. Also, Figure 2 only shows a part of the main hardware configuration of the server device 10; the server device 10 may have other configurations that are generally found in servers. For example, the server device 10 may include operating means and display devices. The hardware configuration of the external device 12 may also be similar to that of the server device 10.

[0039] (Hardware configuration of terminal device 13) Figure 3 shows an example of the hardware configuration of a smartphone, which is the terminal device 13 shown in Figure 1.

[0040] As shown in Figure 3, the terminal device 13 includes a main control unit 30, a touch panel (touchscreen) 32, a camera (front camera / rear camera) 34, a mobile communication unit 36, a wireless LAN communication unit 38, a storage unit 40, and a speaker 42.

[0041] The main control unit 30 is comprised of a CPU, memory, and other components. This main control unit 30 is connected to a touch panel 32 (which serves as a display input device), a camera 34, a mobile communication unit 36, a wireless LAN communication unit 38, a storage unit 40, and a speaker 42. The main control unit 30 also has the function of controlling these connected devices.

[0042] The touch panel 32 has both display and input functions, and consists of a display 32A that handles the display function and a touch sensor 32B that handles the input function.

[0043] Camera 34 captures still images and videos. Camera 34 also has the function of saving the captured data to the storage unit 40.

[0044] The mobile communication unit 36 ​​has the function of connecting to a mobile communication network via the antenna 36A and communicating with other communication devices connected to the mobile communication network.

[0045] The wireless LAN communication unit 38 connects to the communication network NT via the antenna 38A and has the function of communicating with other devices such as the server device 10 that are connected to the communication network NT.

[0046] The memory unit 40 stores various programs and various data.

[0047] The speaker 42 has the function of outputting sound.

[0048] Note that the hardware configuration of the server device 10 shown in Figure 2 and the hardware configuration of the terminal device 13 shown in Figure 3 are examples only and are not limited to the specific configurations shown in Figures 2 and 3.

[0049] <Functional means> The functional configuration of the server device 10 will be explained using Figure 4.

[0050] Figure 4 is a block diagram showing an example of the functional configuration of the server device 10. Various processes are executed in the server device 10 according to the functions of each block.

[0051] As shown in Figure 4, the server device 10 comprises a storage unit 50, an acquisition unit 51, a identification unit 52, and an output unit 53. Each functional unit is realized, for example, by the execution of processing by the control device 20.

[0052] The memory unit 50 stores various types of information. Specifically, the memory unit 50 stores the reference table 55.

[0053] Reference Table 55 is information that associates food and beverages with information about a standard taste. That is, Reference Table 55 contains information about a standard taste corresponding to each of several food and beverages. In this embodiment, the standard taste is referred to as "standard taste". Food and beverages in Reference Table 55 are, for example, actual food and beverages. For this reason, the taste of food and beverages is measured using, for example, a taste sensor, and the standard taste corresponding to that food and beverage is set in advance. It is preferable that the standard taste is set using the taste measurement results of several food and beverages of the same type. Several food and beverages of the same type are, for example, of the same type, but from different manufacturers (producers) or distributors (sellers). For example, the standard taste is set by averaging the taste measurement results of several food and beverages of the same type. In this way, a standard taste corresponding to a specific food and beverage is set and set as Reference Table 55. It should be noted that the standard taste is not limited to being set by measurement using a taste sensor, etc., but may also be set as the standard taste by, for example, a person setting the standard taste based on the taste they perceive of the food and beverage.

[0054] Figure 5 shows an example of a reference table 55. In Figure 5, the food and beverages are referred to as Food and Beverage A1, Food and Beverage A2, Food and Beverage A3, Food and Beverage A4, and Food and Beverage A5, respectively. Food and Beverage A1, Food and Beverage A2, Food and Beverage A3, Food and Beverage A4, and Food and Beverage A5 are all different types of food and beverages. The reference table 55 associates reference taste information with each of the food and beverages A1, A2, A3, A4, and A5. For example, reference taste B1 is set for food and beverage A1, reference taste B2 is set for food and beverage A2, reference taste B3 is set for food and beverage A3, reference taste B4 is set for food and beverage A4, and reference taste B5 is set for food and beverage A5.

[0055] Figure 6 shows an example of a standard taste B1 set in correspondence with food and beverage A1 in Figure 5. As shown in Figure 6, the standard taste B1 is represented using, for example, multiple elements related to taste. In this embodiment, one example of multiple elements related to taste is the five basic tastes: sweetness, saltiness, sourness, bitterness, and umami. As shown in Figure 6, the standard taste B1 is set as numerical information for each of the elements of sweetness, saltiness, sourness, bitterness, and umami. In the example in Figure 6, the standard taste B1 is shown as having a value of 3 for sweetness, a value of 1 for saltiness, a value of 1 for sourness, a value of 1 for bitterness, and a value of 2 for umami. Note that the standard taste is set for each food and beverage.

[0056] Returning to Figure 4, the acquisition unit 51 acquires various types of information. For this purpose, the acquisition unit 51 comprises a first acquisition unit 56, a second acquisition unit 57, and a third acquisition unit 58.

[0057] The first acquisition unit 56 receives the designation of the target object. Specifically, the first acquisition unit 56 receives the designation of the target object from the user's terminal device 13. For example, the first acquisition unit 56 receives the designation of the target object from the terminal device 13A.

[0058] Figure 7 shows an example of the screen 70 of the terminal device 13 when accepting the designation of an object. Screen 70 displays "Please enter the object whose taste you want to identify" to prompt the user to designate an object. In area 71, the user can input information to designate the object. The example of screen 70 shows the case where the user inputs "Food and drink D1 from anime C1" as the object. Note that food and drink D1 is a fictional (non-existent) food and drink that appears in anime C1. The user then completes the designation of the object by operating the confirm button 72 on screen 70. As a result, the first acquisition unit 56 acquires that the object is food and drink D1 from anime C1.

[0059] Returning to Figure 4, the second acquisition unit 57 acquires (collects) information regarding the taste image of the object. In this embodiment, the information regarding the taste image of the object is referred to as "image information." Specifically, the image information is information regarding the taste that the user imagines of the object. In other words, the image information is information regarding the taste impression of the object. In particular, it is preferable that the image information is information regarding the taste that each of multiple users imagines of the object.

[0060] Image information includes, for example, articles and user comments on the internet related to the taste of a subject. Specifically, image information includes articles on web pages related to the subject. It also includes user comments on social media about the taste of a subject. Specifically, user comments about a subject such as "looks sweet and delicious" or "looks bitter" constitute image information. Note that the above examples illustrate image information related to sweetness and bitterness, but it is not limited to the above and various types of information related to the taste of a subject can be considered image information.

[0061] The second acquisition unit 57 acquires image information from, for example, an external device 12. For example, the second acquisition unit 57 may acquire information about articles related to the taste of the object from an external device 12 that provides a web page, or it may acquire comments related to the taste of the object from an external device 12 that provides a social networking service.

[0062] For example, the second acquisition unit 57 acquires image information related to the food and beverage D1 in the animation C1, which is the target object, from the external device 12. As a result, the image information includes various information related to the taste of the target object and is acquired by the second acquisition unit 57. In other words, the second acquisition unit 57 collects various information related to the taste of the target object as image information.

[0063] In the above example, the second acquisition unit 57 acquires image information from an external device 12, but the image information is not limited to being acquired from an external device 12. For example, the second acquisition unit 57 may acquire image information from a user's terminal device 13. In this case, the second acquisition unit 57 may acquire the results of a questionnaire regarding the taste image of the target object as image information. When acquiring questionnaire results as image information, it is preferable to acquire questionnaire results from multiple users. Furthermore, the terminal devices 13 (users) targeted by the questionnaire may include terminal devices 13A that specify the target object, or they may be terminal devices 13 other than terminal device 13A.

[0064] Figure 8 shows an example of screen 80 of terminal device 13 displaying a questionnaire about the taste image of a target object. Screen 80 displays "Please enter your taste image for the target object" to prompt the user to answer about the taste image of the target object. Alternatively, as shown in area 81, the specified target object (food / drink D1 in animation C1) as shown in Figure 7 may be displayed. In area 82, the user can input their taste image of the target object. The example of screen 80 shows the case where "It seems to be very sweet, with almost no bitterness" is entered. The user then completes the questionnaire input by operating the confirm button 83 on screen 80. As a result, the second acquisition unit 57 acquires the image information as the questionnaire result.

[0065] Returning to Figure 4, the third acquisition unit 58 acquires reference information regarding the standard taste corresponding to the target object. The third acquisition unit 58 acquires reference information regarding the standard taste corresponding to the target object specified by the first acquisition unit 56 from the storage unit 50. For example, if the target object is food or beverage D1 in animation C1, the third acquisition unit 58 refers to the reference table 55 in the storage unit 50 and acquires information regarding the standard taste corresponding to food or beverage D1 in animation C1 as reference information. In other words, the third acquisition unit 58 acquires reference information regarding the standard taste corresponding to an existing food or beverage of the same type as the target object. In this embodiment, let's assume that food or beverage D1 in animation C1 and food or beverage A1 in the reference information are of the same type. In this case, the third acquisition unit 58 acquires the information of the standard taste B1 of food or beverage A1 in the reference table 55 as reference information.

[0066] In this way, image information corresponding to the specified object and reference information (reference taste) corresponding to the specified object are obtained.

[0067] The identification unit 52 analyzes the image information of the object to identify the taste corresponding to the object. In this embodiment, the information relating to the taste corresponding to the object identified by the identification unit 52 is referred to as "taste information". Specifically, the identification unit 52 identifies the taste information corresponding to the object based on the image information and reference information. The identification unit 52 modifies the reference taste in the reference information using the image information to identify the taste information corresponding to the object. The analysis may be performed using AI or the like, or it may be performed by a predetermined process without using AI or the like.

[0068] Specifically, the identification unit 52 identifies at least one of the following types of information based on the image information: information relating to a positive taste image of the object, and information relating to a negative taste image of the object. Information relating to a positive taste image of the object is referred to as "positive information," and information relating to a negative taste image of the object is referred to as "negative information." For example, positive information is information relating to an image that the object looks delicious, and negative information is information relating to an image that the object does not look delicious. Information that is neither a positive nor a negative taste image is referred to as "neutral information." In this embodiment, the identification unit 52 classifies each piece of information included in the image information into positive information, negative information, and neutral information. That is, the identification unit 52 classifies each piece of information included in the image information in accordance with the user's emotions.

[0069] For example, the identification unit 52 identifies positive image information, such as a user's comment "It looks sweet and delicious," as positive information. Also, for example, the identification unit 52 identifies negative image information, such as a user's comment "It looks bitter and not delicious," as negative information. Also, for example, the identification unit 52 identifies neutral image information, such as a user's comment "I think the sweetness is average," as neutral information.

[0070] In this embodiment, the example illustrates the case where image information is classified into positive information and negative information, but it may also be classified into either positive or negative information. Furthermore, the classification of neutral information may be omitted.

[0071] Then, the identification unit 52 uses the identified information to identify taste information. The identification unit 52 identifies keyword information that indicates the taste characteristics of the object from the image information. Specifically, the identification unit 52 identifies keyword information that indicates taste characteristics in the positive information, negative information, and neutral information of the image information. For example, information related to sweetness, saltiness, sourness, bitterness, and umami are each identified as keyword information.

[0072] For example, if the positive information in the image includes a user comment such as "It looks sweet and delicious," it will be identified as keyword information related to sweetness. Similarly, if the negative information in the image includes a user comment such as "It looks bitter and not delicious," it will be identified as keyword information related to bitterness. Furthermore, if the neutral information in the image includes a user comment such as "I think the sweetness is average," it will be identified as keyword information related to sweetness.

[0073] Then, the identification unit 52 identifies the taste information using keyword information. Specifically, the identification unit 52 modifies the reference taste acquired as reference information to identify the taste of the target object. The identification unit 52 modifies the reference taste using keyword information of positive information, keyword information of negative information, and keyword information of neutral information to identify the taste of the target object.

[0074] For example, in keyword information related to sweetness, if there is a certain number of positive pieces of information, or if there is more positive information compared to negative or neutral information, it is assumed that the object is often perceived as having a strong sweetness. In such cases, the value of sweetness in the standard taste will be increased. For example, the amount of increase will be set based on the number of positive pieces of information (keyword information related to sweetness), or the number (difference) or ratio of positive pieces of information compared to negative or neutral information. Conversely, in keyword information related to sweetness, if there is a certain number of negative pieces of information, or if there is more negative information compared to positive or neutral information, it is assumed that the object is often perceived as having a weak sweetness. In such cases, the value of sweetness in the standard taste will be decreased. For example, the amount of decrease will be set based on the number of negative pieces of information (keyword information related to sweetness), or the number (difference) or ratio of negative information compared to positive or neutral information. Furthermore, in keyword information related to sweetness, if there is a certain number of neutral pieces of information or if there is a large amount of neutral information compared to positive or negative information, it is assumed that the subject is generally perceived as having an average level of sweetness. In such cases, the sweetness value of the standard taste will not be adjusted.

[0075] Furthermore, in keyword information related to bitterness, if there is a certain number of negative entries or if there is a large amount of negative information compared to positive or neutral information, it is assumed that the subject is widely perceived as having a strong bitter taste. Therefore, in such cases, the value of sweetness in the standard taste profile will be increased. The direction of adjustment (increase or decrease) for positive and negative values ​​can be set as appropriate.

[0076] By comparing keywords related to positive information, negative information, and neutral information, the taste of the object is identified based on the user's perception of its taste, and the object's taste is determined based on a baseline taste.

[0077] In this way, the baseline taste is modified using keyword information, and the taste information of the target object is set. The taste information is information in which the taste corresponding to the target object is quantified, with each of the multiple elements related to taste corresponding to it. Note that the specific structure of the taste information is not limited.

[0078] Figure 9 shows examples of modifications to the standard taste. Figure 9 illustrates the case of modifying standard taste B1 in Figure 6. For example, if keyword information related to sweetness suggests that many users have a strong image of the object as being very sweet, the sweetness value is increased by 2 from standard taste B1. Similarly, if keyword information related to saltiness suggests that users have a normal image of the object as being very salty, the saltiness value is left unchanged. Similarly, if keyword information related to sourness suggests that users have a normal image of the object as being very sour, the sourness value is left unchanged. Similarly, if keyword information related to bitterness suggests that many users have a weak image of the object as being very bitter, the bitterness value is decreased by 1 from standard taste B1. Similarly, if keyword information related to umami suggests that many users have a slightly strong image of the object as being very umami, the umami value is increased by 1 from standard taste B1. In this way, the standard taste B1 is modified, and the taste information of the object is identified with a value of 5 for sweetness, 1 for saltiness, 1 for sourness, 0 for bitterness, and 3 for umami. For example, as shown in the graph (radar chart) in Figure 9, the taste information of the object is identified.

[0079] The above example illustrates one method for identifying taste information using image information, but the method for identifying taste information using image information is not limited to the above.

[0080] For example, the identification unit 52 estimates the degree of positive, negative, and neutral image of the user's object based on keyword information related to sweetness. The identification unit 52 then compares each degree and sets the taste information by identifying the direction and amount of correction for the sweetness value of the standard taste. Alternatively, for example, the sweetness value of the standard taste may be corrected using either the positive keyword information related to sweetness or the negative keyword information related to sweetness.

[0081] Furthermore, for example, the identification unit 52 may not classify each piece of information contained in the image information into positive, negative, or neutral information. That is, the identification unit 52 may extract keyword information from the image information, estimate the degree of the image for each element (e.g., sweetness), and make adjustments to the numerical value of the standard taste.

[0082] Alternatively, for example, image information may be analyzed using AI or similar technologies to identify differences from a standard taste, thereby determining the taste information.

[0083] Thus, the specific analytical method for identifying the taste information of an object is not limited, as long as the user's or other person's image of the object's taste is reflected using image information.

[0084] Furthermore, if the identification unit 52 identifies the taste information of the target object, it may set the taste information as digital data using blockchain. In other words, the identification unit 52 may set the taste information as a token. As a result, the taste information becomes data that cannot be tampered with, with the owner recorded on the blockchain. For example, the taste information as a token can be an FT or an NFT. FT stands for Fungible Token, indicating a token that can be replaced. NFT stands for Non-Fungible Token, indicating a token that cannot be replaced.

[0085] In this way, the specific unit 52 identifies the taste corresponding to the target object. In other words, the taste is digitized (taste mapping). The taste information can also be called a digital profile of the taste.

[0086] The output unit 53 outputs the taste information identified by the identification unit 52. That is, the output unit 53 outputs taste information corresponding to the target object. For example, the output unit 53 provides the user with the taste identification result by outputting the taste information to a predetermined user's terminal device 13. For example, the taste information may be output to a user's terminal device 13A that has specified the target object. Note that the target of the taste information output by the output unit 53 is not limited.

[0087] Figure 10 shows an example of the screen 100 of the terminal device 13 displaying the taste identification results (taste information) of an object. The screen 100 displays "The taste identification results for the object are as follows." Alternatively, the specified object (food / drink D1 in animation C1) may be displayed, as shown in area 101. Area 102 displays the taste information identified for the object. For example, the diagram in Figure 9 is displayed in area 102. Alternatively, the taste characteristics of the object relative to a standard taste may be displayed, as shown in area 103. For example, area 103 displays "Food / drink D1 in animation C1 is sweeter than typical food / drinks of the same type." The user then exits the display of the taste identification results for the object by operating the exit button 104.

[0088] Furthermore, the output unit 53 may output suggestion information based on taste information. Suggestion information is information that is useful, for example, for product development or marketing related to the target object. For example, the output unit 53 may identify the difference in taste between the target object and food or beverage of the same type as the actual target object, and output the difference. Alternatively, the output unit 53 may identify the degree of similarity in taste between the target object and food or beverage of the same type as the actual target object, and output the degree of similarity. Note that the suggestion information is not limited to the above.

[0089] Furthermore, the output unit 53 may output the taste information to the functional unit of the server device 10 or other devices if additional processing is to be performed using the identified taste information. Additional processing may include, for example, generating a recipe for the target object from the taste information, or further improving the taste from the taste information. For example, in the recipe generation process, once the taste of the target object is identified, the raw materials to produce that taste are identified, and a recipe is created to make the target object with that taste using the identified raw materials. For example, a basic recipe for food or drink corresponding to the target object may be stored in advance, and a recipe for making the target object with the identified taste may be created by modifying this basic recipe. Also, in the taste improvement process, the taste may be adjusted from the identified taste information so that people find it even more delicious.

[0090] Furthermore, the output unit 53 may output the taste information to the creator, original designer, production organization, business operator (business organization), administrator (management organization), broadcasting organization, publishing organization, etc., related to the object. In other words, the output unit 53 may output the taste information to the provider that delivers the object to the user, the management organization that manages the object, etc. In this case, the server device 10 may acquire feedback on the taste information and use that feedback to modify the taste information of the object. In other words, the identification unit 52 may modify the taste information of the object by reflecting the opinions on the taste from the provider or management organization of the object.

[0091] <Processing flow> Next, an example of the processing flow related to System 1 according to this embodiment will be described.

[0092] Figure 11 is a flowchart showing an example of the processing flow in System 1 according to this embodiment. The following steps are initiated, for example, when a user issues a start command. For example, the following steps are initiated when a dedicated application is launched on the user's terminal device 13. The order and content of the following steps can be changed as appropriate.

[0093] Figure 11 shows the processing performed by the terminal device 13 and the server device 10, respectively. Specifically, steps SP10 to SP12 are executed by the terminal device 13, and steps SP20 to SP24 are executed by the server device 10.

[0094] (Step SP10) Terminal device 13 accepts the designation of an object. For example, when a dedicated application is launched on terminal device 13, screen 70 shown in Figure 7 is displayed on terminal device 13, and the user makes input to designate an object. Then, the process moves to step SP11.

[0095] (Step SP11) The terminal device 13 outputs information about the specified object to the server device 10. Then, the process proceeds to step SP20.

[0096] (Step SP20) In the server device 10, the first acquisition unit 56 receives the designation of an object. Specifically, the first acquisition unit 56 acquires information about the designated object from the terminal device 13. Then, the process proceeds to step SP21.

[0097] (Step SP21) In the server device 10, the second acquisition unit 57 acquires taste image information for the target object, for example, from an external device 12. Then, the process moves on to step SP22.

[0098] (Step SP22) In the server device 10, the third acquisition unit 58 acquires reference information regarding the reference taste corresponding to the target object. Then, the process proceeds to step SP23.

[0099] (Step SP23) In the server device 10, the identification unit 52 analyzes the image information of the object to identify its taste information. For example, the identification unit 52 modifies the reference taste using the image information to identify the taste information of the object. In this way, taste information corresponding to the object is generated. Then, the process moves on to step SP24.

[0100] (Step SP24) In the server device 10, the output unit 53 outputs the identified flavor information to the terminal device 13. Then, the process proceeds to step SP12.

[0101] (Step SP12) The terminal device 13 displays the identified taste information. For example, screen 100 in Figure 10 is displayed on the terminal device 13, and the user is provided with taste information corresponding to the object. Then the process ends.

[0102] <Effects> As described above, the server device 10 according to this embodiment includes an acquisition unit 51 that acquires information relating to the taste image of an object as image information, an identification unit 52 that analyzes the image information to identify the taste corresponding to the object and converts it into taste information, and an output unit 53 that outputs the taste information corresponding to the object.

[0103] This configuration makes it possible to identify the taste of an object from its image information. Therefore, it can even identify the taste of fictional food and beverages.

[0104] For example, by identifying the taste of fictional food and beverages, organizations such as companies can develop products that recreate the taste imagined by fans. Furthermore, users may have the opportunity to actually experience these fictional foods and beverages. For instance, they might be able to experience anime or other media featuring the subject, making the world feel more tangible. Additionally, the digitization of taste data could create highly engaging content.

[0105] Furthermore, by identifying the taste of an object from image information, it becomes possible to identify the taste through information processing. Additionally, using image information allows for efficient identification of the taste of an object, leading to improved computer processing efficiency and reduced processing load. In other words, it can be expected to enhance the performance of computers while keeping their complexity under control.

[0106] Furthermore, in this embodiment, the acquisition unit 51 acquires information about the taste that each of the multiple users imagines for the object as image information.

[0107] This configuration allows for setting the taste information of an object by reflecting the images of multiple users. By reflecting the users' images, the taste information can be set to come closer to the taste that the users expect.

[0108] Furthermore, in this embodiment, the object in question is a fictional food or beverage.

[0109] This configuration makes it possible to identify the taste of fictional food and drink items.

[0110] Furthermore, in this embodiment, the acquisition unit 51 acquires reference information relating to a standard taste corresponding to the target object, and the identification unit 52 identifies the taste information corresponding to the target object based on the reference information.

[0111] This configuration makes it possible to identify taste information based on a reference taste, thereby improving the accuracy of taste information identification. Furthermore, it allows for more efficient processing.

[0112] Furthermore, in this embodiment, the acquisition unit 51 acquires standard taste information corresponding to existing food and beverages of the same type as the target object, and the identification unit 52 identifies the taste information corresponding to the target object based on the standard information.

[0113] This configuration allows for the efficient identification of the taste of fictional food and beverages by basing it on the standard taste of real-world food and beverages.

[0114] Furthermore, in this embodiment, the identification unit 52 identifies at least one of the following information based on image information: information relating to a positive taste image of the object and information relating to a negative taste image of the object, and uses this information to identify taste information.

[0115] This configuration allows for more efficient processing of taste information by classifying it into positive and negative taste images. Furthermore, it efficiently reflects the user's emotions in the taste information identification process.

[0116] Furthermore, in this embodiment, the identification unit 52 identifies keyword information indicating the taste characteristics of the object from the image information, and uses the keyword information to identify taste information.

[0117] This configuration allows for the efficient identification of taste information by using keyword information to identify the taste information.

[0118] Furthermore, in this embodiment, the taste information is information in which the taste corresponding to the object is quantified, with each of the multiple elements related to taste being represented numerically.

[0119] This configuration allows for the taste to be effectively presented as data.

[0120] Furthermore, in this embodiment, the taste information is digital data utilizing blockchain technology.

[0121] This configuration enhances the added value of flavor information.

[0122] ---Second Embodiment--- Next, a second embodiment will be described.

[0123] The second embodiment describes a case in which taste information is set using information about the target image of the taste of the object as image information. In the second embodiment, the differences from the first embodiment will be mainly described below. The points that are not described below in the second embodiment are the same as in the first embodiment.

[0124] In this embodiment, the second acquisition unit 57 acquires information regarding the taste image of the object for each user as image information, similar to the first embodiment. Furthermore, the second acquisition unit 57 acquires information regarding the target image of the taste of the object as image information.

[0125] In this embodiment, information relating to the target taste image of the object is referred to as "target image information." Separately from the target image information, information relating to each user's taste image of the object is referred to as "user image information."

[0126] Target image information is information about the taste that should be targeted in relation to the object. Specifically, target information is information about the taste image of the object as presented (published) by the creator of the object. The creator of the object is, for example, the creator of the anime, etc., in which the object appears if the object is a fictional food or drink. Furthermore, target image information is not limited to the creator of the object, but may also be information about the taste of the object presented (published) by the original creator, production organization, business operator (business organization), manager (management organization), broadcasting organization, publishing organization, etc. In other words, target image information is information about the taste of the object as presented by the provider or manager of the object. To put it another way, target image information is officially announced information about the taste of the object (official information).

[0127] For example, the second acquisition unit 57 acquires target image information corresponding to the object from an external device 12 that provides services such as a web page or social networking service where target image information is displayed. For example, if the author posts a comment on social networking service about the taste of the object, such as "It's very sweet and delicious," that comment is acquired as target image information.

[0128] Thus, the second acquisition unit 57 acquires not only user image information but also target image information as image information corresponding to the object. Furthermore, the third acquisition unit 58 acquires reference information related to the reference taste corresponding to the object.

[0129] The identification unit 52 then uses image information, including user image information and target image information, to identify taste information corresponding to the target object. Specifically, the identification unit 52 identifies taste information corresponding to the target object from the image information, similar to the first embodiment. That is, the identification unit 52 uses the image information to modify the reference taste of the reference information and identifies taste information corresponding to the target object. As a result, the target information (official information) is reflected in the taste information.

[0130] Furthermore, if user image information and target image information are acquired as image information, the identification unit 52 may prioritize the target image information over the user image information to identify the taste information. "Prioritizing" means giving higher importance (influence) to the target image information than the user image information in order to identify the taste information.

[0131] For example, the specific unit 52 sets the sweetness value in the taste information by giving a higher importance (influence) to the keyword information in the target image information than to the keyword information in the user image information in the keyword information related to sweetness. For example, the specific unit 52 may also modify the number by multiplying the number of keyword information in the target image information by a predetermined number. The predetermined number is a number greater than 1. Furthermore, for example, the specific unit 52 modifies the sweetness value of the standard taste by increasing it when there is a predetermined number or more of positive information in the keyword information related to sweetness, or when there is more positive information compared to negative or neutral information. The amount of increase in the value is set by, for example, the number of positive information, or the number (difference) or ratio of positive information compared to negative or neutral information. In other words, the modification is made by increasing the importance of the target image information. In addition, the specific unit 52 may also estimate the degree of positive image of sweetness, etc., and set the sweetness value by giving a higher importance to the keyword information in the target image information than to the user image information in the keyword information for sweetness. Increasing importance (influence) can also be described as assigning a higher weight to something. Furthermore, if the importance (influence) of the target image information is given a higher value than the user image information when setting the taste information, the specific methods are not limited.

[0132] In the above example, both user image information and target image information are acquired as image information and used for analysis. However, it is also possible to acquire only target image information as image information and use it for analysis. In this case, the second acquisition unit 57 acquires the target image information as image information, and the identification unit 52 uses the target image information as image information to identify the taste information.

[0133] In this way, the taste information of the target object is identified by reflecting the target information. The output unit 53 then outputs the identified taste information.

[0134] <Effects> In this embodiment, the acquisition unit 51 acquires information relating to the target image of the taste of the object as image information, and the identification unit 52 identifies the taste information based on the image information.

[0135] This configuration makes it possible to identify taste information by reflecting the target image of the object's taste.

[0136] Furthermore, in this embodiment, the acquisition unit 51 acquires, as image information, information relating to the taste image of the object for each user and information relating to the target taste image of the object. The identification unit 52 identifies the taste information by prioritizing the information relating to the target taste image of the object over the information relating to the taste image of the object for each user.

[0137] This configuration allows for setting taste information with a greater influence from the target image of the object's taste. In other words, the taste information can be set to approach the target image of the object's taste.

[0138] <Variation> This disclosure is not limited to the above-described examples. In other words, designs modified by those skilled in the art to the above-described examples are also included within the scope of this disclosure, as long as they retain the features of this disclosure. Furthermore, the elements of the embodiments described above and the modifications described later can be combined to the extent that it is technically possible, and such combinations are also included within the scope of this disclosure, as long as they retain the features of this disclosure.

[0139] For example, in the above embodiment, the elements of taste were exemplified as sweetness, saltiness, sourness, bitterness, and umami, but the elements of taste are not limited to those above. For example, taste may be defined as elements such as astringency, off-flavors, richness, cleanliness, refreshingness, intensity of flavor, aftertaste (initial taste), complexity, breadth, persistence, and aroma. Alternatively, the degree of similarity (taste similarity) to a specific food or beverage (which may be of the same or different type as the subject) may be used as an element of taste. Furthermore, elements other than taste that affect taste may be included. For example, elements other than taste may include texture (softness, etc.) and aroma (smell). Thus, as long as the elements are related to taste, various indicators can be applied without being limited to those above.

[0140] Furthermore, while the above embodiment exemplifies the case where image information is user comments, etc., the image information is not limited to the above. For example, the image information may include images or videos related to the taste of the object (e.g., images or videos of someone eating it deliciously), or actions on social media (e.g., "likes" or "shares" on social media). Images or videos related to the taste of the object, for example, images or videos of someone eating a sweet treat in a sweet and delicious way, would be image information indicating that the object is sweet and delicious. Also, if there are a predetermined number of actions related to the object on social media, it would be image information indicating that the object has a taste that people like (is delicious). In this way, various types of information can be applied as image information, as long as they relate to the image of the taste of the object.

[0141] Furthermore, in the above embodiment, the identification unit 52 is shown as an example of identifying the taste information of an object by modifying reference information (reference taste). However, the identification unit 52 may also identify taste information without using reference information (reference taste). For example, the identification unit 52 uses image information to identify the numerical values ​​of each of several elements related to taste and sets the taste information. In other words, the identification unit 52 is not limited to identifying taste information as relative information to a reference taste, but may also identify it as absolute information without using a reference taste. For example, in keyword information related to sweetness, if there is a predetermined number or more of positive information, or if there is more positive information compared to negative or neutral information, it is assumed that the object is perceived as having a strong sweetness. For this reason, a numerical value corresponding to sweetness is set based on the number of positive information (keyword information related to sweetness), or the number (difference) or ratio of positive information compared to negative or neutral information. Alternatively, for example, the degree of the user's image of sweetness towards the object may be estimated from the keyword information related to sweetness, and the numerical value of sweetness in the taste information may be set accordingly.

[0142] Furthermore, while the above embodiment uses the case where the object is fictional food or beverage as an example, the object is not limited to that. For example, the object may be food or beverage from a specific region, such as hometown food or beverage (taste of home), or it may be old food or beverage described in literature, foreign food or beverage, or rare food or beverage that is difficult to obtain. In other words, the object may be food or beverage that actually exists (or could potentially exist) but does not have a specific taste (no specific recipe), such as hometown food or beverage from a specific region. The object may also be food or beverage that existed in the past but does not exist now, such as old food or beverage. The object may also be food or beverage that is difficult to actually prepare, such as foreign food or beverage or rare food or beverage that is difficult to obtain. It is also possible for the object to be food or beverage that actually exists (can be prepared). In this way, various foods and beverages can be applied as the object. In particular, hometown food or beverage (taste of home) may have variations in taste depending on the household or restaurant, making it difficult to identify the taste of an actual product, but it becomes possible to identify the taste from image information. Therefore, it becomes easier to promote local food and beverages (tastes of one's hometown) to other regions. By identifying recipes based on specific tastes, even more effective promotion becomes possible. For example, when targeting local food and beverages such as local food and beverages (tastes of one's hometown), the second acquisition unit 57 may acquire image information targeting residents or people from that region (users related to that region).

[0143] Furthermore, while the above embodiment exemplifies cases where the taste elements are sweetness, saltiness, sourness, bitterness, and umami, the taste elements may be pre-set or automatically set. For example, the server device 10 may analyze the taste characteristics (taste-related keywords) imagined for the object from the image information and set multiple elements (e.g., sweetness) that constitute these characteristics as taste elements. [Explanation of Symbols]

[0144] 10: Server device (information processing device) 51: Acquisition part 52: Specific part 53: Output section D1: Food and beverages (object)

Claims

1. An acquisition unit that acquires information regarding the taste image of an object as image information, A unit that analyzes the aforementioned image information to identify the taste corresponding to the object and converts it into taste information, An output unit that outputs the taste information corresponding to the object, An information processing device equipped with the following features.

2. The acquisition unit acquires information regarding the taste that each of the multiple users imagines for the object as image information. The information processing apparatus according to claim 1.

3. The aforementioned object is a fictional food or drink. The information processing apparatus according to claim 1 or 2.

4. The acquisition unit acquires standard taste information corresponding to the target object. The identifying unit identifies the taste information corresponding to the target object based on the reference information. The information processing apparatus according to claim 1 or 2.

5. The acquisition unit acquires standard taste information corresponding to existing food and beverages of the same type as the object, The identifying unit identifies the taste information corresponding to the target object based on the reference information. The information processing apparatus according to claim 3.

6. The identifying unit identifies at least one of the following information based on the image information: information relating to a positive taste image of the object and information relating to a negative taste image of the object, and uses this information to identify the taste information. The information processing apparatus according to claim 1 or 2.

7. The identifying unit identifies keyword information indicating the taste characteristics of the object from the image information, and identifies the taste information using the keyword information. The information processing apparatus according to claim 1 or 2.

8. The aforementioned taste information is information in which the taste corresponding to the object is quantified, with each of the multiple elements related to taste corresponding to it. The information processing apparatus according to claim 1 or 2.

9. The acquisition unit acquires information relating to the target image of the taste of the object as image information, The specified unit identifies the taste information based on the image information. The information processing apparatus according to claim 1 or 2.

10. The acquisition unit acquires, as image information, information relating to each user's taste image of the object and information relating to the target taste image of the object. The identifying unit identifies the taste information by prioritizing information regarding the target taste image of the object over information regarding the taste image of each user for the object. The information processing apparatus according to claim 9.

11. The aforementioned taste information is digital data using blockchain technology. The information processing apparatus according to claim 1 or 2.

12. A process for acquiring information regarding the taste image of an object as image information, A step of analyzing the aforementioned image information to identify the taste corresponding to the object and convert it into taste information, A step of outputting the taste information corresponding to the object, A method of having.

13. Computers, An acquisition unit that acquires information regarding the taste image of an object as image information. A unit that analyzes the aforementioned image information to identify the taste corresponding to the object and converts it into taste information. An output unit that outputs the taste information corresponding to the object, A program that makes it function as such.

Images