Information processing apparatus and information processing method

Abstract

To easily obtain effective information that can be utilized in product development by quantitatively and objectively analyzing taste preferences.SOLUTION: An information processing apparatus 10 comprises: a parameter estimation unit 11 for estimating taste parameters that represent the taste preferences of each of a plurality of individuals, based on the results of a questionnaire regarding the taste preferences of the plurality of individuals that have been acquired; a profile generation unit 12 for generating, based on the estimated taste parameters, profiles having taste preferences corresponding to the taste parameters for a predetermined number of individuals; and an information collection unit 13 for collecting information on the reactions of a predetermined number of virtual individuals having the generated profiles to a target product in a virtual space.SELECTED DRAWING: Figure 1

Description

Technical Field

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

Background Art

[0002] A technique for determining a user's taste tendency for a certain food and beverage product group, extracting products that match the taste tendency from the food and beverage product group, and presenting them to the user is described in Patent Document 1 below.

[0003] In addition, large language models (LLMs), which have been developed rapidly in recent years, are considered to contain (store) quantitative and objective information (taste parameters) regarding the tastes of various foods and beverages because they learn vast amounts of language information.

[0004] On the other hand, in the field of developing products such as foods and beverages, it is common to conduct sensory tests based on the sensations and impressions when a human actually eats or drinks the product.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, the above-mentioned sensory tests require very advanced techniques and experience. Therefore, by effectively using the aforementioned large language model, it is eagerly awaited to more easily obtain effective information for quantitatively and objectively analyzing taste preferences and applying them to product development.

[0007] Therefore, an object of the present disclosure is to more easily obtain effective information for quantitatively and objectively analyzing taste preferences and applying them to product development.

Means for Solving the Problem

[0008] An information processing apparatus according to the present disclosure includes a parameter estimation unit that estimates taste parameters representing the taste preferences of each of the plurality of people based on the results of a questionnaire regarding the taste preferences of the plurality of people that have been acquired, a profile generation unit that generates a predetermined number of profiles having taste preferences corresponding to the taste parameters based on the taste parameters estimated by the parameter estimation unit, and an information collection unit that collects information regarding the reaction of a target product in a virtual space by a virtual person having the profile generated by the profile generation unit.

Advantages of the Invention

[0009] According to the present disclosure, it is possible to more easily acquire effective information for quantitatively and objectively analyzing taste preferences and applying them to product development.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Embodiments for Carrying Out the Invention

[0011] Hereinafter, with reference to the drawings, an embodiment of an information processing apparatus and an information processing method according to the present disclosure will be described.

[0012] FIG. 1 shows the configuration of the information processing apparatus 10 and its related apparatuses. As shown in FIG. 1, the information processing apparatus 10 acquires, from an external server or the like, the results of a questionnaire on taste preferences previously conducted for a plurality of people, and based on the acquired results of the questionnaire, estimates taste parameters representing the taste preferences of each of the plurality of people by a parameter estimation unit 11, generates profiles having taste preferences corresponding to the taste parameters for a predetermined number of people (for example, the number of questionnaire respondents) based on the estimated taste parameters by a profile generation unit 12, collects information on the reactions of target products (here, food or beverages) in a virtual space (here, a metaverse space) by a predetermined number of virtual characters (here, avatars) having the generated profiles by an information collection unit 13, and includes a display unit 14 that is a display.

[0013] Specifically, the parameter estimation unit 11 learns a vast amount of language information in advance, incorporates a large language model (hereinafter referred to as "LLM") 11A that includes quantitative and objective information (taste parameters) regarding the tastes of various foods and beverages, and obtains the estimation results of the taste parameters for each of the plurality of people output from the LLM 11A by inputting an inquiry sentence including the results of the questionnaire to the LLM 11A. Note that it is not essential for the parameter estimation unit 11 to incorporate the LLM 11A, and the parameter estimation unit 11 may obtain the estimation results of the taste parameters by, for example, making an inquiry to the LLM of an external device (such as a cloud server).

[0014] Also, the information collection unit 13 cooperates with a virtual space control server 20 that controls the metaverse space as a whole, displays the metaverse space on the display unit 14 as shown in FIG. 5, further provides a tasting and sampling corner for the target product in the metaverse space, allows each avatar having the profile to taste and sample the corresponding target product, and collects information on the reactions of the target product (here, food or beverages) by the avatar. Note that as the target product, a new product or a product with known taste parameters is assumed.

[0015] The following describes the processing executed by the information processing apparatus 10 in accordance with the flowchart of FIG. 2. As a premise, at the start of the processing, a questionnaire regarding the taste preferences of a plurality of people has already been conducted, and the questionnaire results are stored in an external server or the like.

[0016] First, the parameter estimation unit 11 acquires the questionnaire results regarding the taste preferences of a plurality of people from an external server or the like (step S1), and by inputting an inquiry sentence including the questionnaire results into the LLM 11A, estimates the taste parameters for each of the plurality of people output from the LLM 11A (step S2).

[0017] Here, an example of a questionnaire and an example of estimating taste parameters will be described with reference to FIGS. 3 and 4. As shown in FIG. 3, the questionnaire includes questions (A), (B), (C), (D), (E)... set based on the paired comparison method, and also includes questions covering at least the five basic tastes of sour, sweet, salty, bitter, and spicy.

[0018] For example, question (A) is "Which do you prefer, 'caramel popcorn' or'salted popcorn'?", and the respondent is asked to evaluate the degree of preference on a scale from 1 (prefer caramel popcorn) to 10 (prefer salted popcorn). Other examples of questionnaire questions include (B) "Which do you prefer, 'curry rice' or 'hayashi rice'?" (C) "Which do you prefer, 'cream puff' or 'chocolate cake'?" (D) "Which do you prefer,'spicy chicken' or 'garlic shrimp'?" (E) "Which do you prefer, 'beer' or 'wine'?" and so on.

[0019] Since LLM11A has learned a large amount of the characteristics of each food at the language level, for example, regarding "curry rice" and "Hamburger steak" mentioned in the above problem (B), it understands the spiciness and spiciness of curry rice and the rich taste of Hamburger steak. By making a comparison between two points based on the paired comparison method, it is possible to compare the internal parameters of the food (information on the five basic tastes and various other tastes) that LLM11A understands, extract the fine taste preferences, and obtain the estimation results of taste parameters as shown in FIG. 4.

[0020] FIG. 4 shows an example of the estimation results when estimating taste parameters on a scale of 1 to 10 for a certain person. The scale of 1 to 10 means that 1 is the most disliked and 10 is the most liked, representing the degree of preference or dislike according to the numerical value. As described above, since the questionnaire includes questions covering at least the five basic tastes of sour, sweet, salty, bitter, and spicy tastes, the estimation results shown in FIGS. 4(a) to 4(e) include the estimation results regarding the above five basic tastes. In addition, the estimation results of taste parameters regarding various tastes such as (f) aroma, (g) turbidity, (h) carbonation feeling, (i) richness, and (j) texture are included.

[0021] Returning to FIG. 2, the taste parameters estimated in step S2 are passed to the profile generation unit 12, and the profile generation unit 12 generates profiles with taste preferences corresponding to the taste parameters for a predetermined number of people (the number of questionnaire respondents) (step S3). The generated profile information is passed to the information collection unit 13.

[0022] The information collection unit 13 cooperates with the virtual space control server 20 to give the target product to a predetermined number of avatars with the above profiles in the metaverse space (step S4), and collects information on the reaction of the avatars to the target product (step S5). Here, as shown in FIG. 5, the information collection unit 13 displays the metaverse space on the display unit 14, and in the tasting / sampling corner of the target product provided in the metaverse space, each avatar with the above profile is allowed to taste / sample the corresponding target product, and information on the reaction of each avatar to the target product (here, food or beverage) is collected. For example, user A is displayed in association with the tasting corner of food X among the target products (near the tasting corner of food X), and user A is allowed to taste food X, and information on the reaction is collected. Similarly, user B is allowed to sample beverage Y in the sampling corner of beverage Y, and information on the reaction is collected, and user C is allowed to taste food Z in the tasting corner of food Z, and information on the reaction is collected.

[0023] Thereafter, the processes of steps S4 and S5 are performed for each of the pre-determined tasting / sampling patterns (a plurality of combination patterns of each avatar and the target product for which the reaction of each avatar should be observed). Therefore, if there are unperformed patterns (NO in step S6), the process proceeds to step S7, and the information collection unit 13 cooperates with the virtual space control server 20 to switch the environment of the metaverse space to a different pattern to be performed next, and performs the processes of steps S4 and S5 in the environment after the switching. Note that the environment of the metaverse space to be changed by the switching includes, for example, at least one of conditions such as the location of the product (placement location in the store, above / center / below the shelf, etc.), date (by day of the week, target sales period, etc.), time zone (morning, noon, night, late at night, etc.), type of product, congestion status, and presence or absence of companions of the avatar, and may include two or more.

[0024] In this way, the processes of steps S4 and S5 are performed for each of the pre-determined tasting / sampling patterns, and when all patterns have been performed (YES in step S6), the process ends.

[0025] In the embodiment described above, the information processing apparatus 10 inputs an inquiry sentence including the questionnaire results regarding taste to the LLM 11A, estimates taste parameters for each of a plurality of persons, generates a profile having a taste preference corresponding to the taste parameters for a predetermined number of persons, and further collects information regarding the reaction to the target product in the metaverse space by avatars having the generated profiles for a predetermined number of persons. As a result, effective information for quantitatively and objectively analyzing taste preferences and utilizing them for product development can be obtained more easily without conducting a conventional sensory test that requires advanced technology and experience.

[0026] Also, the environment of the metaverse space related to the target product can be changed in a plurality of ways, and information regarding the reaction of the avatar in each environment can be collected. Examples of the environment to be changed include the location of the product, the date, the time zone, the type of the product, the congestion situation, and whether there is a companion of the avatar, and one or a combination of a plurality of these may be used. As a result, regarding a product in the prototype stage, a product before release, etc., information regarding the reaction of an avatar having a profile according to taste parameters can be collected in various environments in the metaverse space.

[0027] Also, the questionnaire includes questions set based on the two-point preference method, and includes questions covering at least the five basic tastes of taste, namely sourness, sweetness, saltiness, bitterness, and spiciness. By performing the two-point comparison based on the two-point preference method as described above, the internal parameters of the food (information regarding the five basic tastes and various other tastes) understood by the LLM 11A can be compared, and fine taste preferences can be extracted to obtain the estimation result of taste parameters as shown in FIG. 4.

[0028] The gist of the present disclosure resides in the following [1] to [7]. [1] A parameter estimation unit that estimates taste parameters representing the taste preference of each of the plurality of persons based on the results of a questionnaire regarding the taste preference of the plurality of persons obtained; A profile generation unit that generates, based on the taste parameters estimated by the parameter estimation unit, profiles with taste preferences corresponding to the taste parameters for a predetermined number of people; An information collection unit that collects information regarding the reaction of a target product in a virtual space by a predetermined number of virtual characters having the profiles generated by the profile generation unit; An information processing apparatus comprising the above. [2] The parameter estimation unit Pre-learns a vast amount of language information, and inputs an inquiry sentence including the result of the questionnaire into a large language model that includes information on quantitative and objective taste parameters regarding the tastes of various foods and beverages, thereby obtaining the estimation results of the taste parameters for each of the plurality of people output from the large language model. The information processing apparatus according to [1]. [3] The information collection unit changes the environment of the virtual space related to the target product in a plurality of ways, and collects information regarding the reaction in each environment. The information processing apparatus according to [1] or [2]. [4] The environment of the virtual space to be changed includes at least one of the location of the product, the date, the time zone, the type of the product, the congestion situation, and the presence or absence of companions of the virtual character. The information processing apparatus according to [3]. [5] The questionnaire includes questions set based on the two-alternative forced choice method. The information processing apparatus according to any one of [1] to [4]. [6] The questionnaire includes questions covering at least the five basic tastes of taste, namely sour, sweet, salty, bitter, and spicy. The information processing apparatus according to any one of [1] to [5]. [7] A step in which the information processing apparatus estimates taste parameters representing the taste preferences of each of the plurality of people based on the results of a questionnaire regarding the taste preferences of the plurality of people obtained; A step in which the information processing apparatus generates, based on the estimated taste parameters, profiles with taste preferences corresponding to the taste parameters for a predetermined number of people; The step in which the information processing apparatus collects information regarding the reaction of a target product in a virtual space by the predetermined number of virtual characters having the generated profile; An information processing method comprising the same.

[0029] [Explanation of terms, explanation of hardware configuration (Fig. 6), etc.] Note that the block diagrams used in the above description of the embodiments show blocks of functional units. These functional blocks (components) are realized by an arbitrary combination of at least one of hardware and software. Also, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one physically or logically combined device, or two or more physically or logically separated devices may be directly or indirectly (for example, using wired, wireless, etc.) connected and realized using these multiple devices. The functional block may be realized by combining software with the above one device or the above multiple devices.

[0030] Functions include, but are not limited to, judgment, decision, determination, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, solution, selection, selection, establishment, comparison, assumption, expectation, regarded as, notification (broadcasting), notification (notifying), communication (communicating), transfer (forwarding), configuration (configuring), reconfiguration (reconfiguring), allocation (allocating, mapping), assignment (assigning), etc. For example, a functional block (component) that functions as transmission is called a transmission unit, a transmitter. In any case, as described above, the realization method is not particularly limited.

[0031] For example, an information processing apparatus or the like in an embodiment of the present disclosure may function as a computer that executes the processing of the present disclosure. FIG. 6 is a diagram showing an example of the hardware configuration of an information processing apparatus 10 according to an embodiment of the present disclosure. Physically, the above-described information processing apparatus 10 may be configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like.

[0032] In the following description, the term "apparatus" can be read as a circuit, a device, a unit, or the like. The hardware configuration of the information processing apparatus 10 may be configured to include one or more of each apparatus shown in the figure, or may be configured without including some apparatuses.

[0033] Each function in the information processing apparatus 10 is realized by causing the processor 1001 to perform operations by loading a predetermined software (program) onto hardware such as the processor 1001 and the memory 1002, controlling communication by the communication device 1004, or controlling at least one of reading and writing data in the memory 1002 and the storage 1003.

[0034] The processor 1001 controls the entire computer by operating an operating system, for example. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic device, a register, and the like.

[0035] Also, the processor 1001 reads a program (program code), software module, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes according to these. As the program, a program that causes a computer to execute at least a part of the operations described in the above-described embodiments is used. Although it has been described that various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. Note that the program may be transmitted from a network via a telecommunication line.

[0036] The memory 1002 is a computer-readable recording medium and may be constituted by at least one of, for example, ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. The memory 1002 may be referred to as a register, cache, main memory (main storage device), etc. The memory 1002 can store a program (program code), software module, etc. executable for implementing the wireless communication method according to an embodiment of the present disclosure.

[0037] Storage 1003 is a computer-readable recording medium, and may be composed of, for example, at least one of an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-described storage medium may be, for example, a database, a server, or other appropriate medium including at least one of the memory 1002 and the storage 1003.

[0038] The communication device 1004 is hardware (a transmission / reception device) for performing communication between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include, for example, a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. in order to implement at least one of frequency division duplex (FDD: Frequency Division Duplex) and time division duplex (TDD: Time Division Duplex).

[0039] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives an external input. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that performs an output to the outside. Note that the input device 1005 and the output device 1006 may have an integrated configuration (e.g., a touch panel).

[0040] Also, each device such as the processor 1001 and the memory 1002 is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses for each device.

[0041] Further, the information processing apparatus 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and part or all of each functional block may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these hardware components.

[0042] The notification of information is not limited to the modes / embodiments described in the present disclosure, and other methods may be used. For example, the notification of information may be performed by physical layer signaling (e.g., downlink control information (DCI), uplink control information (UCI)), upper layer signaling (e.g., radio resource control (RRC) signaling, medium access control (MAC) signaling, notification information (master information block (MIB), system information block (SIB))), other signals, or a combination thereof. Further, the RRC signaling may be referred to as an RRC message, and may be, for example, an RRC connection setup message, an RRC connection reconfiguration message, or the like.

[0043] Each aspect / embodiment described in the present disclosure may be applied to at least one of systems using LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (x is, for example, an integer or a decimal), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, UWB (Ultra-WideBand), Bluetooth (registered trademark), and other appropriate systems, and next-generation systems extended, modified, created, and defined based on these. Further, multiple systems may be combined (for example, a combination of at least one of LTE and LTE-A and 5G, etc.) and applied.

[0044] The processing procedures, sequences, flowcharts, etc. of each aspect / embodiment described in the present disclosure may be reordered as long as there is no contradiction. For example, for the methods described in the present disclosure, the elements of various steps are presented using an exemplary order and are not limited to the specific order presented.

[0045] The input / output information etc. may be stored in a specific location (e.g., memory), or may be managed using a management table. The information etc. to be input / output may be overwritten, updated, or appended. The output information etc. may be deleted. The input information etc. may be transmitted to other devices.

[0046] The determination may be made by a value represented by 1 bit (0 or 1), may be made by a boolean value (Boolean: true or false), or may be made by a numerical comparison (e.g., comparison with a predetermined value).

[0047] Each aspect / embodiment described in the present disclosure may be used alone, may be used in combination, or may be switched and used during execution. Also, the notification of predetermined information (e.g., notification of "being X") is not limited to being explicitly performed, and may be performed implicitly (e.g., not performing the notification of the predetermined information).

[0048] As described above in detail, it is obvious to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure can be implemented as modifications and variations without departing from the spirit and scope of the present disclosure determined by the description of the claims. Therefore, the description of the present disclosure is for the purpose of exemplification and has no restrictive meaning for the present disclosure.

[0049] Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, etc., whether called by the name of software, firmware, middleware, microcode, hardware description language, or other names.

[0050] Also, software, instructions, information, etc. may be transmitted and received via a transmission medium. For example, when software is transmitted from a website, server, or other remote source using at least one of wired technologies (such as coaxial cables, optical fiber cables, twisted pairs, digital subscriber lines (DSL), etc.) and wireless technologies (such as infrared rays, microwaves, etc.), at least one of these wired technologies and wireless technologies is included within the definition of the transmission medium.

[0051] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc., which may be referred to throughout the above description, may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0052] In addition, for the terms described in this disclosure and the terms necessary for understanding this disclosure, they may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Also, a signal may be a message. Also, a component carrier (CC) may be referred to as a carrier frequency, a cell, a frequency carrier, etc.

[0053] The terms "system" and "network" used in this disclosure are used interchangeably.

[0054] Also, the information, parameters, etc. described in this disclosure may be represented using absolute values, relative values from a predetermined value, or corresponding other information. For example, a radio resource may be indicated by an index.

[0055] The names used for the above-mentioned parameters are not limiting in any way. Further, the mathematical formulas and the like using these parameters may be different from those explicitly disclosed in this disclosure. Since various channels (e.g., PUCCH, PDCCH, etc.) and information elements can be identified by any suitable names, the various names assigned to these various channels and information elements are not limiting in any way.

[0056] The terms "determining" and "deciding" used in this disclosure may encompass a wide variety of operations. "Determining" and "deciding" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up (e.g., searching in a table, database, or another data structure), and considering something as having "determined" or "decided" what has been ascertained. Also, "determining" and "deciding" may include considering something as having "determined" or "decided" what has been received (e.g., receiving information), transmitted (e.g., transmitting information), input, output, accessed (e.g., accessing data in a memory). Further, "determining" and "deciding" may include considering something as having "determined" or "decided" what has been resolved, selected, chosen, established, compared, etc. That is, "determining" and "deciding" may include considering that some action has been "determined" or "decided". Also, "determining (deciding)" may be read as "assuming", "expecting", "considering", etc.

[0057] As used in this disclosure, the term "based on" does not mean "based solely on" unless otherwise specified. In other words, the term "based on" means both "based solely on" and "based at least in part on".

[0058] Any reference in this disclosure to an element using terms such as "first", "second", etc. does not generally limit the quantity or order of those elements. These terms may be used in this disclosure as a convenient way to distinguish between two or more elements. Thus, a reference to a first and a second element does not mean that only two elements can be employed, or that the first element must precede the second element in any way.

[0059] In this disclosure, when terms such as "include", "including" and their variations are used, these terms are intended to be inclusive, similar to the term "comprising". Further, the term "or" used in this disclosure is not intended to be an exclusive disjunction.

[0060] In this disclosure, for example, when articles are added by translation, such as a, an and the in English, this disclosure may include that the nouns following these articles are in the plural form.

[0061] In this disclosure, the term "A and B are different" may mean that "A and B are different from each other". Note that this term may also mean that "A and B are each different from C". Terms such as "separate", "coupled", etc. may be interpreted in the same way as "different".

Description of Reference Signs

[0062] 10... Information processing device, 11... Parameter estimation unit, 11A... Large language model (LLM), 12... Profile generation unit, 13... Information collection unit, 14... Display unit, 20... Virtual space control server, 1001... Processor, 1002... Memory, 1003... Storage, 1004... Communication device, 1005... Input device, 1006... Output device, 1007... Bus.

Claims

1. A parameter estimation unit that estimates taste parameters representing the taste preferences of each of the plurality of people based on the results of a questionnaire regarding the taste preferences of the plurality of people obtained; A profile generation unit that generates a predetermined number of profiles having taste preferences corresponding to the taste parameters based on the taste parameters estimated by the parameter estimation unit; An information collection unit that collects information regarding the reaction of a target product in a virtual space by a virtual person having the profile generated by the profile generation unit; An information processing apparatus comprising the above.

2. The parameter estimation unit pre-learns a vast amount of language information, and inputs an inquiry sentence including the results of the questionnaire into a large language model that includes information on quantitative and objective taste parameters regarding the tastes of various foods and beverages, thereby obtaining the estimation results of the taste parameters for each of the plurality of people output from the large language model. The information processing apparatus according to Claim 1.

3. The information collection unit changes the environment of the virtual space related to the target product in a plurality of ways, and collects information regarding the reaction in each environment. The information processing apparatus according to Claim 1.

4. The environment of the virtual space to be changed includes at least one of the location of the product, the date, the time zone, the type of the product, the congestion situation, and the presence or absence of a companion of the virtual person. The information processing apparatus according to Claim 3.

5. The questionnaire includes questions set based on the two-alternative forced-choice method. The information processing apparatus according to Claim 1.

6. The questionnaire includes questions covering at least the five basic tastes of sour, sweet, salty, bitter, and spicy. The information processing apparatus according to Claim 1.

7. An information processing method comprising steps of: the information processing apparatus estimating taste parameters representing the taste preferences of each of the plurality of people based on the results of a questionnaire regarding the taste preferences of the plurality of people obtained; the information processing apparatus generating a predetermined number of profiles having taste preferences corresponding to the taste parameters based on the estimated taste parameters; and the information processing apparatus collecting information regarding the reaction of a target product in a virtual space by a virtual person having the generated profile. An information processing method comprising the above.

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