system

Abstract

We provide the system. [Solution] A user input method for users to enter the content and emotions of their dreams in text format, An input data transmission means that sends data entered by the user to a server, A natural language processing means that analyzes text data sent by a user and converts it into structured data, A generative AI model analysis means that generates dream interpretation results using generative AI based on naturally language processed data, A means for returning the interpretation results of the generated dream to the user's device, Interpretation result display means for displaying the interpretation results of dreams received on the user terminal, A system that includes a mechanism for users to input additional questions regarding the interpretation of their dreams, and then re-analyze those questions.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003] [[ID=2,2]] [[ID=2,3]]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Dream interpretation has been an interesting theme for people since ancient times. However, conventional dream interpretation methods are subjective and often lack reliability and accuracy. In addition, interpretations by experts are time-consuming and costly, and not easily accessible to the general public. Furthermore, it is difficult to provide a consistent analysis for personal dreams and to offer personalized interpretations. Thus, means for improving the overall reliability and accessibility of dream interpretation are required.

Means for Solving the Problems

[0005] The present invention solves the above problems with a system that includes a user input means, an input data transmission means, a natural language processing means, a generative AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. Specifically, the user inputs the content of a dream and the emotions associated with it, and sends it to the server. The server analyzes the input data using natural language processing technology and generates a dream interpretation result using a generative AI model. This interpretation result is returned to the user terminal, and the user can immediately check the result. Furthermore, the user can input additional questions to obtain additional interpretation results again through the generative AI model. With such a system configuration, it is possible to quickly provide highly reliable, personalized dream interpretations.

[0006] "User input means" refers to a device or software that provides an interface for a user to input the content and emotions of their dreams in text format.

[0007] "Input data transmission means" refers to a device or software that includes network communication means and protocols for transmitting data entered by a user to a server.

[0008] "Natural language processing means" refers to a device or software that uses algorithms and techniques to analyze text data sent by a user and convert it into structured data.

[0009] "Generative AI model analysis means" refers to a device or software that uses algorithms and techniques to generate dream interpretation results using generative AI based on naturally language processed data.

[0010] "Interpretation result return means" refers to a device or software that includes network communication means and protocols for returning the generated dream interpretation results to the user's terminal.

[0011] "Interpretation result display means" refers to a device or software that has a screen display function for displaying the interpretation results of dreams received on the user's terminal.

[0012] An "additional questioning mechanism" is a device or software that provides an interface for users to input additional questions regarding the interpretation of their dreams and then re-analyze them. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained. <� <�

[0016] <� In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc. <� <�

[0017] <� In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. <� <�

[0018] <� In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] The present invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. This system includes user input means, input data transmission means, natural language processing means, generation AI model analysis means, interpretation result reply means, interpretation result display means, and additional question means.

[0035] 1. System Overview

[0036] User input means

[0037] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications.

[0038] Input data transmission means

[0039] The data entered by the user (the content and emotions of the dream) is sent to the server via the internet. This transmission typically uses an HTTP POST request.

[0040] Natural language processing means

[0041] The text data received by the server is analyzed using natural language processing techniques. In this step, the text data is converted into structured data, and semantic analysis is performed.

[0042] Generative AI Model Analysis Method

[0043] The naturally processed data is fed into a generative AI model. Specifically, this generative AI model uses a deep learning model to generate dream interpretations based on this data.

[0044] Means of responding to interpretation results

[0045] The dream interpretation results generated by the generative AI model are sent back from the server to the user's terminal. This reply is usually sent as an HTTP response.

[0046] Means for displaying interpretation results

[0047] The user's terminal displays the dream interpretation results received from the server on the screen. This allows the user to confirm the dream interpretation.

[0048] Additional questioning methods

[0049] If the user requests a more detailed interpretation, they can enter additional questions. These additional questions are sent back to the server, and the process described above is repeated to generate a new interpretation, which is then sent back to the user.

[0050] 2. Specific Examples

[0051] Consider an example where a user enters information about a dream they had last night. The user enters the dream content as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. When the user presses the submit button, this data is sent to the server.

[0052] The server receives the input data and analyzes it using natural language processing. The analyzed data is then analyzed by a generative AI model, which generates the following interpretation of the dream: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0053] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[0054] The following describes the processing flow.

[0055] Step 1:

[0056] User: Enter the content of your dream and the emotions associated with it into the application's input form as text. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0057] Step 2:

[0058] Terminal: When the user presses the submit button, the entered dream content and emotions are converted into JSON data and sent to the server as an HTTP POST request.

[0059] Step 3:

[0060] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes the content and emotions of the dream.

[0061] Step 4:

[0062] Server: The received dream content and emotions are passed to a natural language processing system for text data analysis. This analysis converts the text data into structured data and then analyzes its meaning.

[0063] Step 5:

[0064] Server: Inputs naturally language processed data into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform complex text analysis and pattern recognition.

[0065] Step 6:

[0066] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[0067] Step 7:

[0068] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[0069] Step 8:

[0070] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0071] Step 9:

[0072] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[0073] Step 10:

[0074] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[0075] Step 11:

[0076] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[0077] Step 12:

[0078] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[0079] Step 13:

[0080] Terminal: Displays the new interpretation results in the user interface.

[0081] Step 14:

[0082] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[0083] (Example 1)

[0084] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0085] In modern society, users often seek to interpret the content and emotions of their dreams to deepen their self-understanding. However, traditional dream interpretation methods are subjective, making it difficult to obtain consistent interpretations. Furthermore, when users ask additional questions, they have to re-enter information, hindering quick responses. New technologies and systems are needed to solve these problems.

[0086] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0087] In this invention, the server includes means for the user to input the content and emotions of their dream in text format, means for transmitting the input data to the server via the internet, natural language processing means for analyzing the text data received by the server, generative AI model analysis means for generating a dream interpretation based on the naturally language processed data, means for returning the generated dream interpretation result to the user terminal, means for the user terminal to display the dream interpretation result, and means for the user to input additional questions to request a more detailed interpretation. This enables the user to quickly obtain a consistent dream interpretation and to appropriately respond to additional questions.

[0088] "Input method" refers to the interface of a device or application that allows a user to input the content and emotions of their dreams in text format.

[0089] "Transmission means" refers to the mechanism for sending input data to a server via the internet.

[0090] "Natural language processing means" refers to the technologies and processes used by a server to analyze text data received and convert it into structured data.

[0091] "Generative AI model analysis means" refers to a system that uses a deep learning algorithm to generate dream interpretations based on data structured using natural language processing.

[0092] "Reply method" refers to the process of sending the generated dream interpretation results to the user's device.

[0093] "Display means" refers to devices or software that allow a user terminal to display the dream interpretation results received from the server on a screen.

[0094] "Additional questioning mechanism" refers to a mechanism for users to input additional questions to request further detailed interpretations and send those questions to the server.

[0095] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain a dream interpretation result. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. Specifically, the invention is implemented as follows.

[0096] User input means

[0097] Users input the content and feelings of their dreams in text format using a smartphone or computer application. For example, a user might type "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application's interface and select "happy" as their emotion.

[0098] Input data transmission means

[0099] The data entered by the user (the content and emotions of the dream) is sent to the server over the internet using an HTTP POST request. When the user presses the submit button, this data is sent to the server. For example, the payload of the HTTP request includes {"dream": "Last night I dreamt I was swimming with dolphins in a big ocean. I felt very happy", "emotion": "happy"}.

[0100] Natural language processing means

[0101] The server passes the received text data to a natural language processing module, which analyzes the text data and converts it into structured data. In this step, the text data is semantically analyzed, and keywords and emotions are extracted. For example, keywords such as "sea," "dolphin," and "swimming," and the emotion "happiness" are recognized.

[0102] Generative AI Model Analysis Method

[0103] The structured data, processed using natural language processing, is fed into a generative AI model. This model employs deep learning algorithms to generate dream interpretations based on the input data. For example, it might generate an interpretation such as, "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0104] Means of responding to interpretation results

[0105] The generated dream interpretation is sent from the server to the user's terminal as an HTTP response. The server compiles the analysis results and sends them to the user. For example, the server includes the interpretation {"interpretation": "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."} in the payload of the HTTP response.

[0106] Means for displaying interpretation results

[0107] The user terminal parses the dream interpretation received from the server and displays it on the user interface. For example, the screen might display an interpretation such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0108] Additional questioning methods

[0109] If the user requests a more detailed interpretation, they can enter additional questions through the interface. For example, if the user enters "I want to know how this dream will affect my future" and presses the submit button, an HTTP POST request containing the additional question will be sent back to the server.

[0110] The server receives the additional question, interprets it again through the natural language processing module, and generates a new interpretation using a generative AI model. The new interpretation is then sent back to the user. For example, the interpretation "In the future, you may have a higher chance of forming strong bonds with new people" is generated and sent back to the user.

[0111] Example of a prompt

[0112] Examples of prompts a user might enter into the system include questions like, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy. What does this dream mean?" or, "Please tell me how this dream will affect my future."

[0113] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0114] Step 1:

[0115] The user enters the content and emotions of their dream.

[0116] Input: Users use a smartphone or computer application to input the content and emotions of their dreams in text format.

[0117] Operation: The user enters "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application interface and selects "Happy" as the emotion.

[0118] Output: Text data entered in the input field.

[0119] Step 2:

[0120] The terminal sends the input data to the server.

[0121] Input: Text data of the dream content and emotions entered by the user in Step 1.

[0122] Action: The terminal creates an HTTP POST request and sends a payload containing the entered data to the server. This action is triggered when the user presses the submit button.

[0123] Output: The HTTP request payload ({"dream": "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy", "emotion": "happy"}) is sent to the server.

[0124] Step 3:

[0125] The server analyzes the received data using a natural language processing module.

[0126] Input: Text data received by the server in Step 2.

[0127] Operation: The server passes the received data to the natural language processing module. The natural language processing module analyzes the text data and converts it into structured data. This analysis includes semantic analysis and keyword extraction.

[0128] Output: Natural language processed structured data (e.g., keywords "sea", "dolphin", "swim", emotion "happy").

[0129] Step 4:

[0130] The server generates dream interpretations using a generative AI model.

[0131] Input: Structured data obtained in Step 3.

[0132] Operation: Natural language processed data is fed to a generative AI model. The generative AI model uses a deep learning algorithm to generate dream interpretations. This process outputs dream interpretations based on the analysis results.

[0133] Output: The generated dream interpretation (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[0134] Step 5:

[0135] The server returns the interpretation result to the user's terminal.

[0136] Input: The dream interpretation result generated in Step 4.

[0137] Operation: The server sends the generated interpretation results to the user's terminal in the form of an HTTP response.

[0138] Output: The HTTP response payload ({"interpretation": "Dreaming of swimming with dolphins in the sea symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that the user is satisfied with their current life."}) reaches the user's terminal.

[0139] Step 6:

[0140] The terminal displays the interpretation result.

[0141] Input: Interpretation result received from the server in Step 5.

[0142] Operation: The device parses the interpretation of the received dream and displays it in the user interface.

[0143] Output: The dream interpretation results displayed on the screen (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[0144] Step 7:

[0145] The user enters and submits additional questions.

[0146] Input: Data entered by the user in the input field for additional questions.

[0147] Operation: The user enters an additional question, such as "I want to know how this dream will affect my future," and presses the submit button. The device then sends an HTTP POST request to the server containing this additional data.

[0148] Output: The HTTP request payload ({"question": "I want to know how this dream will affect my future"}) is sent to the server.

[0149] Step 8:

[0150] The server performs the analysis again, generates a new interpretation, and sends it back.

[0151] Input: Text data of the additional questions received by the server in Step 7.

[0152] Operation: The server receives additional questions, structures them again through the natural language processing module, and inputs them into the generative AI model. The generative AI model generates a new interpretation and sends it to the user's terminal as an HTTP response.

[0153] Output: A new interpretation (e.g., "In the future, you may have a higher chance of forming strong bonds with new people") reaches the user's terminal.

[0154] (Application Example 1)

[0155] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0156] Traditional conversational systems primarily provided static interpretations of user input, which limited their ability to deliver personalized services. Furthermore, they lacked the means to reflect customers' psychological states and emotions in real time and provide useful information to store staff. Therefore, there was a growing need for a system that could provide information more tailored to individual customer needs in real time, thereby improving the customer experience.

[0157] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0158] In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means. This enables the analysis of customers' dreams and emotions, the presentation of the analysis results to store staff in real time, and more personalized customer service and product suggestions.

[0159] A "user input device" is a device or interface for a user to input the content and emotions of their dreams in text format.

[0160] "Input data transmission means" refers to a means for sending data entered by a user to a server.

[0161] A "natural language processing system" is a mechanism that analyzes text data received by a server and converts it into structured data.

[0162] The "generative AI model analysis method" is a means of supplying naturally language processed data to a deep learning model to generate dream interpretations.

[0163] The "interpretation result reply method" is a means of sending the generated dream interpretation results from the server to the user's terminal.

[0164] The "interpretation result display means" is a mechanism that displays the dream interpretation results received from the server on the user's terminal.

[0165] An "additional questioning mechanism" is a means for users to input and submit additional questions to seek further detailed interpretations.

[0166] A "customer input method" refers to a device or interface that allows customers to provide the content and emotions of their dreams through voice or text input.

[0167] "Customer data transmission means" refers to a means of sending data entered by a customer to a server.

[0168] A "customer analysis tool" is a system that analyzes data entered by customers and converts it into structured data.

[0169] "Staff presentation tools" refer to devices or interfaces that display information to enable store staff to make appropriate suggestions to customers based on analyzed data.

[0170] The system for realizing this invention consists of the following means: a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means.

[0171] System Configuration

[0172] 1. User input means

[0173] Users input the content of their dreams and related emotions using smart glasses or a smartphone. This is done via voice recognition or text input.

[0174] 2. Input data transmission means

[0175] The data entered by the user is sent from smart glasses or a smartphone to a backend server via the internet. This transmission is primarily done using HTTP POST requests.

[0176] 3. Natural Language Processing Means

[0177] The server analyzes the received text data using natural language processing technologies (e.g., Google Cloud Natural Language, Microsoft Azure Cognitive Services) and converts it into structured data.

[0178] 4. Generative AI Model Analysis Method

[0179] The naturally processed data is fed into a generative AI model (e.g., OpenAI GPT-4) to generate dream interpretation results.

[0180] 5. Means of responding to interpretation results

[0181] The dream interpretation results generated by the generative AI model are sent back to the user's terminal from the server as an HTTP response.

[0182] 6. Means for displaying interpretation results

[0183] The user's device displays the interpretation results received from the server on the screen of smart glasses or a smartphone. This allows the user to check the interpretation of their dream.

[0184] 7. Additional questioning methods

[0185] If the user requests a more detailed interpretation, they can enter additional questions via voice or text. These questions are sent back to the server, and a new interpretation is generated using the same procedure.

[0186] 8. Customer Input Methods

[0187] Customers input the content and emotions of their dreams through smart glasses within the store, using either voice recognition or text input.

[0188] 9. Means for transmitting customer data

[0189] The data entered by the customer is sent from the smart glasses to the server via the internet. It is sent using an HTTP POST request.

[0190] 10. Customer analysis methods

[0191] The server analyzes the data entered by the customer using natural language processing technology and converts it into structured data.

[0192] 11. Staff presentation methods

[0193] The analyzed data is displayed on smart glasses worn by store staff, allowing them to suggest suitable products and services to customers in real time.

[0194] Specific example

[0195] When a customer inputs, "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it was happiness. What does this mean?", this data is analyzed through a series of steps. The generating AI model analysis method produces the interpretation that "Dreaming of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life."

[0196] This interpretation is displayed on the store staff's smart glasses, allowing them to suggest to customers, "It seems you are looking for freedom and adventure. We can recommend relevant ocean-related products and adventure tours."

[0197] This allows customers to receive personalized service tailored to their mental state, leading to increased satisfaction. Additionally, staff can respond to customers more effectively.

[0198] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0199] Step 1:

[0200] The user inputs the content and emotions of their dream using smart glasses or a smartphone. The user input method collects data through voice recognition or text input and converts the entered data into text format. For example, the input received is: "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it is happiness."

[0201] Step 2:

[0202] The input data transmission method sends the text data entered by the user to the server via the internet. An HTTP POST request is used to send the converted text data to the server. The input is the data collected in the previous step, and the output is the data sent to the server.

[0203] Step 3:

[0204] The server analyzes the received text data using natural language processing tools and converts it into structured data. This process utilizes natural language processing technologies such as Google Cloud Natural Language and Microsoft Azure Cognitive Services. The input is text data, and the output is structured data.

[0205] Step 4:

[0206] The generative AI model analysis method generates dream interpretation results using structured data. It uses OpenAI's GPT-4 as the generative AI model to generate interpretations based on the data. The input is naturally language processed structured data, and the output is the dream interpretation result.

[0207] Step 5:

[0208] The interpretation result return mechanism sends the generated dream interpretation result back to the user terminal from the server as an HTTP response. The input is the generated dream interpretation result, and the output is the data sent to the user terminal.

[0209] Step 6:

[0210] The user's terminal receives dream interpretation results from the server and displays them on smart glasses or a smartphone screen via an interpretation result display device. The input is the interpretation result data from the server, and the output is the screen display that the user can check.

[0211] Step 7:

[0212] If the user requests further interpretation, they can enter additional questions through an additional questioning mechanism. These additional questions are accepted via voice or text and sent back to the server. The input is the user's additional question, and the output is the additional question data sent to the server.

[0213] Step 8:

[0214] Customers input the content and emotions of their dreams using smart glasses, employing either voice recognition or text input. Data is collected via the customer's input method and converted into text format. Input is the customer's voice or text, and output is the converted text data.

[0215] Step 9:

[0216] The customer data transmission method sends the entered data to the server. Similar to the input data transmission method, it uses an HTTP POST request to send the data. The input is the converted text data, and the output is the data sent to the server.

[0217] Step 10:

[0218] The server analyzes the data received from the customer using natural language processing and converts it into structured data. This step is the same as in step 3. The input is the customer's text data, and the output is structured data.

[0219] Step 11:

[0220] The customer analysis system generates dream interpretation results based on an AI model and displays them on the smart glasses of store staff via a staff presentation system. This information allows staff to suggest suitable products and services to customers. The input is the analyzed data, and the output is the display data for staff.

[0221] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0222] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. Furthermore, it incorporates an emotion engine that automatically recognizes the user's emotions, improving the accuracy and personalization of the interpretation. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion engine means, an interpretation result reply means, an interpretation result display means, and an additional question means.

[0223] 1. System Overview

[0224] User input means

[0225] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided.

[0226] Emotional Engine Means

[0227] The system automatically detects emotions based on text data entered by the user, voice input, and facial recognition data. For example, text analysis uses natural language processing technology to infer emotions from the tone and content of the entered words. Voice analysis uses voice tone and pitch to detect emotions, and facial recognition determines emotions from facial expressions.

[0228] Input data transmission means

[0229] The system sends information such as the content of the dream entered by the user and the detected emotion data to the server. This transmission typically uses an HTTP POST request.

[0230] Natural language processing means

[0231] The server analyzes the received text data. During the analysis, the text data is converted into structured data, which is then combined with sentiment data from the sentiment engine for a more detailed analysis.

[0232] Generative AI Model Analysis Method

[0233] Natural language processing data and emotion engine data are input into a generative AI model. Specifically, the generative AI model uses a deep learning model to generate dream interpretations by combining complex text analysis with emotion data.

[0234] Means of responding to interpretation results

[0235] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response.

[0236] Means for displaying interpretation results

[0237] The user's terminal receives an HTTP response from the server and analyzes the dream interpretation results. The analysis results are displayed on the user interface. The interpretation results include a detailed analysis based on the dream's content and emotions.

[0238] Additional questioning methods

[0239] If a user requests a more detailed interpretation, they can enter additional questions. These additional questions are also analyzed by the sentiment engine and sent to the server.

[0240] 2. Specific Examples

[0241] Consider an example where a user inputs information about a dream they had last night. The user inputs the dream's content as text: "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also used, with the user speaking in a quiet tone.

[0242] When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is then processed through a generative AI model to generate an interpretation of the dream, such as "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0243] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] User: The user enters the content of their dream and the associated feelings into the application's input form in text format. For example, they might enter, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0247] Step 2:

[0248] Terminal: While waiting for the user to press the button to send the dream content and emotions, it collects additional emotion data such as voice input and facial recognition data.

[0249] Step 3:

[0250] Terminal: When the user presses the send button, the entered dream content and emotions, along with collected voice input and facial recognition data, are converted into JSON format data and sent to the server as an HTTP POST request.

[0251] Step 4:

[0252] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes dream content, emotions, voice input, and facial recognition data.

[0253] Step 5:

[0254] Server: Passes received dream content and emotion data, voice input, and facial recognition data to natural language processing and emotion engines, which then analyze the text data. In this analysis, the text data is converted into structured data, and emotions are inferred from the voice and facial expression data.

[0255] Step 6:

[0256] Server: Inputs analysis data obtained from natural language processing and emotion engines into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform detailed analysis combining text and emotion data.

[0257] Step 7:

[0258] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[0259] Step 8:

[0260] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[0261] Step 9:

[0262] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0263] Step 10:

[0264] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[0265] Step 11:

[0266] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[0267] Step 12:

[0268] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[0269] Step 13:

[0270] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[0271] Step 14:

[0272] Terminal: Displays the new interpretation results in the user interface.

[0273] Step 15:

[0274] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[0275] (Example 2)

[0276] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0277] While systems currently exist that analyze dream content and associated emotions to provide detailed, individualized interpretations, their accuracy and personalization capabilities are limited. Furthermore, they do not adequately address users' desires for further details based on dream analysis results. This invention aims to solve these problems.

[0278] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the content and emotions of the user's dream, means for transmitting the input data to the server, and means for analyzing the data received by the server using natural language processing technology. This makes it possible to automatically generate and send back a highly accurate dream interpretation based on the dream content and emotion data provided by the user.

[0279] "Means for inputting the content and emotions of the user's dream" refers to a device or application for the user to input information about their dream as text, voice, or facial recognition data.

[0280] "Means for sending the input data to the server" refers to a communication protocol (e.g., HTTP POST request) for the user to send the input data to the server via the Internet.

[0281] "Means for the server to analyze the received data using natural language processing technology" refers to the technology and tools (e.g., natural language processing tools) for the server to analyze the received text data and convert it into structured data.

[0282] "Means for inputting the natural language processed data and emotion data into the generative AI model" refers to a processing method for inputting the structured text data and emotion data into the generative AI model (e.g., deep learning model) for analysis.

[0283] "Means for replying the generated dream interpretation result to the user terminal" refers to a communication protocol (e.g., HTTP response) for converting the dream interpretation result generated by the generative AI model into JSON format and sending it to the user terminal via the Internet.

[0284] "Means for the user terminal to display the interpretation result" refers to the software and hardware for the user's terminal (e.g., smartphone, personal computer) to display the received interpretation result on the user interface.

[0285] "Means for receiving additional questions from the user" refers to a device or application for the user to input additional questions seeking further details about the interpretation result and send it to the server.

[0286] This system allows the user to input the content and emotions of their dream, analyze it, and obtain the dream interpretation result. The system includes the following means.

[0287] User input means

[0288] The user inputs the content of the dream and the related emotions in text form. This input is mainly carried out through applications on smartphones or personal computers. Additionally, additional input means such as voice input and face recognition are also provided. For example, the user can input "Last night, I had a dream of swimming with dolphins in a big ocean. I felt very happy."

[0289] Emotion engine means

[0290] Automatically detects emotions based on the text data, voice input, and face recognition data input by the user. The emotion engine uses natural language processing technology (e.g., Google Cloud Natural Language API) for text analysis, the tone and pitch of the voice for voice analysis, and judges emotions from expressions for face recognition. For example, the emotion of "happy" can be detected from the input text.

[0291] Input data transmission means

[0292] Transmits the content of the dream and emotion data input by the user to the server. Usually, an HTTP POST request is used for this transmission. When the user presses the send button, these data are sent to the server.

[0293] Natural language processing means

[0294] The server analyzes the text data received. In this analysis, natural language processing tools (e.g., Google Cloud Natural Language API) are used to convert the text data into structured data. Additionally, detailed analysis is also carried out using the emotion data from the emotion engine.

[0295] Generated AI model analysis means

[0296] The server inputs naturally processed data and emotion engine data into a generative AI model (e.g., OpenAI GPT-3). This generative AI model uses deep learning to generate dream interpretations by combining complex text analysis with emotion data.

[0297] Means of responding to interpretation results

[0298] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response. The dream interpretation results generated by the server include statements such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0299] Means for displaying interpretation results

[0300] The user's device analyzes the HTTP response received from the server and displays the dream interpretation results on the user interface. Users can check the interpretation results on the screen of a smartphone or computer application.

[0301] Additional questioning methods

[0302] If the user wants a more detailed interpretation, they can enter an additional question in text. For example, they might type, "I want to know how this dream will affect my future," and submit it again. The server receives this additional question and generates a new interpretation through its generative AI model. The result of this re-analysis might be, "In the future, you may have a higher chance of forming strong bonds with new people."

[0303] Specific example

[0304] Suppose a user inputs the text "I had a dream last night that I swam with dolphins in the big ocean. I felt very happy." and specifies "happy" as the emotion. Voice input is also used, speaking in a calm tone. When the user presses the send button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing means and an emotion engine. The analyzed data passes through a generative AI model to generate a result for the dream interpretation: "A dream of swimming with dolphins in the sea means freedom, adventure, and protection. The addition of the happy emotion also suggests that the current life is satisfying." The interpretation result is sent back to the user terminal, and the user checks the interpretation result on the screen. If the user further inputs "I want to know how this dream will affect my future" as an additional question and sends it again, a new interpretation result is generated by the generative AI model analysis means and sent back to the user in the form of "In the future, you may have a higher chance of building strong bonds with new people." Through this, the user can gain deeper insights.

[0305] The flow of the specific process in Example 2 will be described using FIG. 13.

[0306] Step 1:

[0307] The user inputs the content and emotion of the dream.

[0308] Input: The user inputs the content and emotion of the dream in text, voice, or facial recognition data. For example, content like "I had a dream last night that I swam with dolphins in the big ocean. I felt very happy."

[0309] Output: The input dream content and emotion data.

[0310] Specific operation: The user uses applications on smartphones or computers to input the details and emotions of the dream through various input means.

[0311] Step 2:

[0312] Send the input data to the server.

[0313] Input: Text, voice, and facial recognition data entered by the user through an input method.

[0314] Output: Dream content and emotional data sent to the server.

[0315] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[0316] Step 3:

[0317] The server receives the data and performs natural language processing.

[0318] Input: Dream content and emotional data received by the server.

[0319] Output: Natural language processed structured data.

[0320] Specific operation: The server uses a natural language processing tool (e.g., Google Cloud Natural Language API) to analyze the received text data and convert it into structured data.

[0321] Step 4:

[0322] The server analyzes the emotional data.

[0323] Input: Received data and naturally language processed structured data.

[0324] Output: Data on which emotions were detected.

[0325] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to automatically detect emotions based on text, voice, and facial recognition data.

[0326] Step 5:

[0327] Natural language processing data and sentiment data are input into a generating AI model.

[0328] Input: Natural language processed text data and sentiment data.

[0329] Output: Analysis data input to the generating AI model.

[0330] Specific operation: The server inputs structured text data and sentiment data into a generating AI model (e.g., OpenAI GPT-3).

[0331] Step 6:

[0332] The generative AI model generates interpretations of dreams.

[0333] Input: Data entered into the generative AI model.

[0334] Output: Dream interpretation result.

[0335] Specific operation: The generative AI model combines complex text analysis and emotional data to generate dream interpretations. For example, it might output an analysis result such as, "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection."

[0336] Step 7:

[0337] The server returns the interpretation result to the user's terminal.

[0338] Input: Dream interpretation results generated by a generative AI model.

[0339] Output: Interpretation result returned to the user terminal.

[0340] Specific operation: The server converts the generated dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[0341] Step 8:

[0342] The terminal displays the interpretation result.

[0343] Input: Interpretation result received from the server.

[0344] Output: The dream interpretation results displayed in the user interface.

[0345] Specific operation: The system analyzes the HTTP response received by the user's device and displays the dream interpretation results on a smartphone or PC application.

[0346] Step 9:

[0347] The user enters additional questions.

[0348] Input: Enter questions based on the additional information the user wants to know.

[0349] Output: Additional question data.

[0350] Specific action: The user enters an additional question in text, for example, "I want to know how this dream will affect my future," and presses the submit button.

[0351] Step 10:

[0352] Send additional question data to the server.

[0353] Input: Additional questions entered by the user.

[0354] Output: Additional question data sent to the server.

[0355] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[0356] Step 11:

[0357] The server will analyze the additional questions.

[0358] Input: Additional question data received.

[0359] Output: Additional question data processed using natural language processing.

[0360] Specific operation: The server uses natural language processing tools to analyze the additional question data and convert it into structured data.

[0361] Step 12:

[0362] The generative AI model generates additional interpretation results.

[0363] Input: Additional question data processed using natural language.

[0364] Output: Additional interpretation results.

[0365] Specific operation: The generative AI model generates an interpretation of the additional question. For example, it might generate a result such as, "In the future, you may be more likely to form strong bonds with new people."

[0366] Step 13:

[0367] The server sends additional interpretation results back to the user's terminal.

[0368] Input: Additional interpretation results generated by the generative AI model.

[0369] Output: Additional interpretation results sent back to the user's terminal.

[0370] Specific operation: The server converts the generated additional dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[0371] Step 14:

[0372] The device displays additional interpretation results.

[0373] Input: Additional interpretation results received from the server.

[0374] Output: Additional interpretation results displayed in the user interface.

[0375] Specific operation: The system analyzes the HTTP response received by the user's device and displays additional dream interpretation results on the smartphone or PC application.

[0376] (Application Example 2)

[0377] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0378] Conventional dream analysis systems have low accuracy in generating interpretations based on the content and emotions of dreams entered by the user, and lack personalization. Furthermore, they have not made efforts to improve the user experience using head-mounted displays, smartphones, etc. This invention aims to solve these problems and provide users with accurate and personalized dream interpretations.

[0379] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion recognition means, an interpretation result reply means, an interpretation result display means, an additional question means, and a means for recognizing the user's emotions through a head-mounted display or smartphone. This makes it possible to accurately analyze the content and emotions of the user's dreams and provide personalized dream interpretation results in real time.

[0380] A "user input method" is an interface for users to input the content of their dreams and the emotions associated with them.

[0381] The "input data transmission means" is a means of sending the content and emotional data of the dream entered by the user to the server.

[0382] "Natural language processing means" refers to technical means that analyze text data received by a server and convert it into structured data.

[0383] The "generative AI model analysis method" is a method for interpreting dreams using a generative AI model based on naturally processed data and emotional data.

[0384] "Emotion recognition means" refers to a method that analyzes text data entered by the user, as well as voice and facial recognition data, to automatically detect the user's emotions.

[0385] The "interpretation result return means" is a means of returning the dream interpretation results generated by the generation AI model analysis means to the user's terminal.

[0386] The "interpretation result display means" is a means of analyzing the dream interpretation results received by the user terminal and displaying them on the interface.

[0387] An "additional questioning method" is a means by which a user enters additional questions to request a more detailed interpretation and sends those questions to the server.

[0388] A "head-mounted display" is a device that a user wears and uses as an interface for virtual reality or augmented reality.

[0389] A "smartphone" is a multi-functional mobile device capable of making calls, browsing the internet, and running applications.

[0390] This invention is an interactive system for analyzing the content of a user's dreams and the emotions experienced during those dreams, and providing a dream interpretation. The system includes a user input means, an emotion recognition means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. It also includes means for recognizing the user's emotions using a head-mounted display (HMD) or a smartphone.

[0391] Hardware and software configuration

[0392] User input means

[0393] User input means are interfaces for users to input the content and emotions of their dreams. This is provided via smartphones or head-mounted displays. Methods include text input, voice input, and facial recognition.

[0394] emotion recognition means

[0395] Emotion recognition is a method that automatically detects emotions by analyzing text data, voice, and facial recognition data entered by the user. This analysis utilizes natural language processing and speech analysis technologies. Specifically, it uses general natural language processing libraries (e.g., NLTK) and speech analysis libraries.

[0396] Input data transmission means

[0397] The input data transmission method is a means for sending the content and emotional data of dreams entered by the user to the server. The data is sent using an HTTP POST request.

[0398] Natural language processing means

[0399] Natural language processing (NLP) is a technique that analyzes text data received by a server and converts it into structured data. This analysis is performed using natural language processing libraries and APIs.

[0400] Generative AI Model Analysis Method

[0401] The generative AI model analysis method involves inputting naturally processed data and emotional data into a generative AI model to interpret dreams. This generative AI model utilizes deep learning models or large-scale language models (e.g., OpenAI APIs).

[0402] Means of responding to interpretation results

[0403] The interpretation result return method is a means of returning the dream interpretation result generated by the generation AI model analysis method to the user's terminal. This data is transmitted in JSON format.

[0404] Means for displaying interpretation results

[0405] The interpretation result display means analyzes the dream interpretation results received by the user terminal and displays them on the user interface. A smartphone screen or a head-mounted display visual interface is used for the display.

[0406] Additional questioning methods

[0407] The additional questioning feature allows users to request a more detailed interpretation of their dreams. Users enter additional questions and send them to the server. Based on this additional information, the AI ​​model is re-analyzed, and a new interpretation is generated.

[0408] Specific example

[0409] The user enters text describing their dream, such as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also available, spoken in a quiet tone. When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and emotion recognition tools. The analyzed data is then processed by a generative AI model to generate an interpretation of the dream, such as, "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life." This interpretation is then sent back from the server to the user's terminal, where the user can view the result on the screen.

[0410] Example of a prompt

[0411] The following are examples of input prompts for a generative AI model.

[0412] Here is the content of the dream: Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy.

[0413] The emotion associated with this dream is: happiness

[0414] Please interpret this dream.

[0415] This allows the system to analyze the content and emotions of the user's dreams and provide accurate and personalized dream interpretations.

[0416] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0417] Step 1:

[0418] The user inputs the content and emotions of their dream. Text input, voice input, and facial recognition data are acquired using a smartphone or head-mounted display. The input data includes dream details and associated emotions. The entered data is collected and passed on to the next processing step.

[0419] Step 2:

[0420] The device sends input data to the server using an HTTP POST request. This data includes the content of the dream entered by the user, audio data, facial recognition data, and emotional information. The server receives this data and prepares it for analysis.

[0421] Step 3:

[0422] The server analyzes the received text data using natural language processing tools. Specifically, it tokenizes the text data using a natural language processing library (e.g., NLTK) and converts it into structured data. This structured data is then generated, and the process proceeds to the next step.

[0423] Step 4:

[0424] The server uses emotion recognition capabilities to analyze the user's emotions from the input voice data and facial recognition data. This involves using a voice analysis library to estimate emotions based on tone and pitch. Additionally, a facial recognition algorithm is used to determine emotions from facial expressions. Detected emotion data is then generated.

[0425] Step 5:

[0426] The server inputs naturally processed data and emotional data into a generating AI model analysis system. A large-scale language model (e.g., OpenAI API) is used in the generating AI model to interpret the user's dreams. As a result of the analysis, dream interpretation data is generated.

[0427] Step 6:

[0428] The server converts the generated dream interpretation results into JSON format and sends them back to the terminal using the interpretation result reply method. The dream interpretation results are sent as an HTTP response. The user terminal receives this data.

[0429] Step 7:

[0430] The system analyzes the dream interpretation received by the user's device and displays it on the interface. The interpretation includes a detailed analysis based on the dream's content and emotions. The user reviews the interpretation on the screen and enters any additional questions.

[0431] Step 8:

[0432] The user enters an additional question, and the device sends that data to the server again. Similarly, the question data is sent using an HTTP POST request, and the server receives it.

[0433] Step 9:

[0434] The server uses an additional questioning mechanism to analyze the additional questions and generates new interpretation results through the AI ​​model analysis mechanism. This new data is then sent back to the terminal through the interpretation result reply mechanism.

[0435] Step 10:

[0436] The user's terminal receives the new interpretation results and displays them again on the interface. This allows the user to gain deeper insights.

[0437] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0438] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0439] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0440] [Second Embodiment]

[0441] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0442] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0443] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0444] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0445] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0446] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0447] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0448] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0449] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0450] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0451] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0452] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0453] The present invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. This system includes user input means, input data transmission means, natural language processing means, generation AI model analysis means, interpretation result reply means, interpretation result display means, and additional question means.

[0454] 1. System Overview

[0455] User input means

[0456] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications.

[0457] Input data transmission means

[0458] The data entered by the user (the content and emotions of the dream) is sent to the server via the internet. This transmission typically uses an HTTP POST request.

[0459] Natural language processing means

[0460] The text data received by the server is analyzed using natural language processing techniques. In this step, the text data is converted into structured data, and semantic analysis is performed.

[0461] Generative AI Model Analysis Method

[0462] The naturally processed data is fed into a generative AI model. Specifically, this generative AI model uses a deep learning model to generate dream interpretations based on this data.

[0463] Means of responding to interpretation results

[0464] The dream interpretation results generated by the generative AI model are sent back from the server to the user's terminal. This reply is usually sent as an HTTP response.

[0465] Means for displaying interpretation results

[0466] The user's terminal displays the dream interpretation results received from the server on the screen. This allows the user to confirm the dream interpretation.

[0467] Additional questioning methods

[0468] If the user requests a more detailed interpretation, they can enter additional questions. These additional questions are sent back to the server, and the process described above is repeated to generate a new interpretation, which is then sent back to the user.

[0469] 2. Specific Examples

[0470] Consider an example where a user enters information about a dream they had last night. The user enters the dream content as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. When the user presses the submit button, this data is sent to the server.

[0471] The server receives the input data and analyzes it using natural language processing. The analyzed data is then analyzed by a generative AI model, which generates the following interpretation of the dream: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0472] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] User: Enter the content of your dream and the emotions associated with it into the application's input form as text. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0476] Step 2:

[0477] Terminal: When the user presses the submit button, the entered dream content and emotions are converted into JSON data and sent to the server as an HTTP POST request.

[0478] Step 3:

[0479] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes the content and emotions of the dream.

[0480] Step 4:

[0481] Server: The received dream content and emotions are passed to a natural language processing system for text data analysis. This analysis converts the text data into structured data and then analyzes its meaning.

[0482] Step 5:

[0483] Server: Inputs naturally language processed data into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform complex text analysis and pattern recognition.

[0484] Step 6:

[0485] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[0486] Step 7:

[0487] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[0488] Step 8:

[0489] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0490] Step 9:

[0491] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[0492] Step 10:

[0493] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[0494] Step 11:

[0495] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[0496] Step 12:

[0497] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[0498] Step 13:

[0499] Terminal: Displays the new interpretation results in the user interface.

[0500] Step 14:

[0501] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[0502] (Example 1)

[0503] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0504] In modern society, users often seek to interpret the content and emotions of their dreams to deepen their self-understanding. However, traditional dream interpretation methods are subjective, making it difficult to obtain consistent interpretations. Furthermore, when users ask additional questions, they have to re-enter information, hindering quick responses. New technologies and systems are needed to solve these problems.

[0505] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0506] In this invention, the server includes means for the user to input the content and emotions of their dream in text format, means for transmitting the input data to the server via the internet, natural language processing means for analyzing the text data received by the server, generative AI model analysis means for generating a dream interpretation based on the naturally language processed data, means for returning the generated dream interpretation result to the user terminal, means for the user terminal to display the dream interpretation result, and means for the user to input additional questions to request a more detailed interpretation. This enables the user to quickly obtain a consistent dream interpretation and to appropriately respond to additional questions.

[0507] "Input method" refers to the interface of a device or application that allows a user to input the content and emotions of their dreams in text format.

[0508] "Transmission means" refers to the mechanism for sending input data to a server via the internet.

[0509] "Natural language processing means" refers to the technologies and processes used by a server to analyze text data received and convert it into structured data.

[0510] "Generative AI model analysis means" refers to a system that uses a deep learning algorithm to generate dream interpretations based on data structured using natural language processing.

[0511] "Reply method" refers to the process of sending the generated dream interpretation results to the user's device.

[0512] "Display means" refers to devices or software that allow a user terminal to display the dream interpretation results received from the server on a screen.

[0513] "Additional questioning mechanism" refers to a mechanism for users to input additional questions to request further detailed interpretations and send those questions to the server.

[0514] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain a dream interpretation result. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. Specifically, the invention is implemented as follows.

[0515] User input means

[0516] Users input the content and feelings of their dreams in text format using a smartphone or computer application. For example, a user might type "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application's interface and select "happy" as their emotion.

[0517] Input data transmission means

[0518] The data entered by the user (the content and emotions of the dream) is sent to the server over the internet using an HTTP POST request. When the user presses the submit button, this data is sent to the server. For example, the payload of the HTTP request includes {"dream": "Last night I dreamt I was swimming with dolphins in a big ocean. I felt very happy", "emotion": "happy"}.

[0519] Natural language processing means

[0520] The server passes the received text data to a natural language processing module, which analyzes the text data and converts it into structured data. In this step, the text data is semantically analyzed, and keywords and emotions are extracted. For example, keywords such as "sea," "dolphin," and "swimming," and the emotion "happiness" are recognized.

[0521] Generative AI Model Analysis Method

[0522] The structured data, processed using natural language processing, is fed into a generative AI model. This model employs deep learning algorithms to generate dream interpretations based on the input data. For example, it might generate an interpretation such as, "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0523] Means of responding to interpretation results

[0524] The generated dream interpretation is sent from the server to the user's terminal as an HTTP response. The server compiles the analysis results and sends them to the user. For example, the server includes the interpretation {"interpretation": "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."} in the payload of the HTTP response.

[0525] Means for displaying interpretation results

[0526] The user terminal parses the dream interpretation received from the server and displays it on the user interface. For example, the screen might display an interpretation such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0527] Additional questioning methods

[0528] If the user requests a more detailed interpretation, they can enter additional questions through the interface. For example, if the user enters "I want to know how this dream will affect my future" and presses the submit button, an HTTP POST request containing the additional question will be sent back to the server.

[0529] The server receives the additional question, interprets it again through the natural language processing module, and generates a new interpretation using a generative AI model. The new interpretation is then sent back to the user. For example, the interpretation "In the future, you may have a higher chance of forming strong bonds with new people" is generated and sent back to the user.

[0530] Example of a prompt

[0531] Examples of prompts a user might enter into the system include questions like, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy. What does this dream mean?" or, "Please tell me how this dream will affect my future."

[0532] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0533] Step 1:

[0534] The user enters the content and emotions of their dream.

[0535] Input: Users use a smartphone or computer application to input the content and emotions of their dreams in text format.

[0536] Operation: The user enters "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application interface and selects "Happy" as the emotion.

[0537] Output: Text data entered in the input field.

[0538] Step 2:

[0539] The terminal sends the input data to the server.

[0540] Input: Text data of the dream content and emotions entered by the user in Step 1.

[0541] Action: The terminal creates an HTTP POST request and sends a payload containing the entered data to the server. This action is triggered when the user presses the submit button.

[0542] Output: The HTTP request payload ({"dream": "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy", "emotion": "happy"}) is sent to the server.

[0543] Step 3:

[0544] The server analyzes the received data using a natural language processing module.

[0545] Input: Text data received by the server in Step 2.

[0546] Operation: The server passes the received data to the natural language processing module. The natural language processing module analyzes the text data and converts it into structured data. This analysis includes semantic analysis and keyword extraction.

[0547] Output: Natural language processed structured data (e.g., keywords "sea", "dolphin", "swim", emotion "happy").

[0548] Step 4:

[0549] The server generates dream interpretations using a generative AI model.

[0550] Input: Structured data obtained in Step 3.

[0551] Operation: Natural language processed data is fed to a generative AI model. The generative AI model uses a deep learning algorithm to generate dream interpretations. This process outputs dream interpretations based on the analysis results.

[0552] Output: The generated dream interpretation (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[0553] Step 5:

[0554] The server returns the interpretation result to the user's terminal.

[0555] Input: The dream interpretation result generated in Step 4.

[0556] Operation: The server sends the generated interpretation results to the user's terminal in the form of an HTTP response.

[0557] Output: The HTTP response payload ({"interpretation": "Dreaming of swimming with dolphins in the sea symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that the user is satisfied with their current life."}) reaches the user's terminal.

[0558] Step 6:

[0559] The terminal displays the interpretation result.

[0560] Input: Interpretation result received from the server in Step 5.

[0561] Operation: The device parses the interpretation of the received dream and displays it in the user interface.

[0562] Output: The dream interpretation results displayed on the screen (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[0563] Step 7:

[0564] The user enters and submits additional questions.

[0565] Input: Data entered by the user in the input field for additional questions.

[0566] Operation: The user enters an additional question, such as "I want to know how this dream will affect my future," and presses the submit button. The device then sends an HTTP POST request to the server containing this additional data.

[0567] Output: The HTTP request payload ({"question": "I want to know how this dream will affect my future"}) is sent to the server.

[0568] Step 8:

[0569] The server performs the analysis again, generates a new interpretation, and sends it back.

[0570] Input: Text data of the additional questions received by the server in Step 7.

[0571] Operation: The server receives additional questions, structures them again through the natural language processing module, and inputs them into the generative AI model. The generative AI model generates a new interpretation and sends it to the user's terminal as an HTTP response.

[0572] Output: A new interpretation (e.g., "In the future, you may have a higher chance of forming strong bonds with new people") reaches the user's terminal.

[0573] (Application Example 1)

[0574] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0575] Traditional conversational systems primarily provided static interpretations of user input, which limited their ability to deliver personalized services. Furthermore, they lacked the means to reflect customers' psychological states and emotions in real time and provide useful information to store staff. Therefore, there was a growing need for a system that could provide information more tailored to individual customer needs in real time, thereby improving the customer experience.

[0576] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0577] In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means. This enables the analysis of customers' dreams and emotions, the presentation of the analysis results to store staff in real time, and more personalized customer service and product suggestions.

[0578] A "user input device" is a device or interface for a user to input the content and emotions of their dreams in text format.

[0579] "Input data transmission means" refers to a means for sending data entered by a user to a server.

[0580] A "natural language processing system" is a mechanism that analyzes text data received by a server and converts it into structured data.

[0581] The "generative AI model analysis method" is a means of supplying naturally language processed data to a deep learning model to generate dream interpretations.

[0582] The "interpretation result reply method" is a means of sending the generated dream interpretation results from the server to the user's terminal.

[0583] The "interpretation result display means" is a mechanism that displays the dream interpretation results received from the server on the user's terminal.

[0584] An "additional questioning mechanism" is a means for users to input and submit additional questions to seek further detailed interpretations.

[0585] A "customer input method" refers to a device or interface that allows customers to provide the content and emotions of their dreams through voice or text input.

[0586] "Customer data transmission means" refers to a means of sending data entered by a customer to a server.

[0587] A "customer analysis tool" is a system that analyzes data entered by customers and converts it into structured data.

[0588] "Staff presentation tools" refer to devices or interfaces that display information to enable store staff to make appropriate suggestions to customers based on analyzed data.

[0589] The system for realizing this invention consists of the following means: a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means.

[0590] System Configuration

[0591] 1. User input means

[0592] Users input the content of their dreams and related emotions using smart glasses or a smartphone. This is done via voice recognition or text input.

[0593] 2. Input data transmission means

[0594] The data entered by the user is sent from smart glasses or a smartphone to a backend server via the internet. This transmission is primarily done using HTTP POST requests.

[0595] 3. Natural Language Processing Means

[0596] The server analyzes the received text data using natural language processing technologies (e.g., Google Cloud Natural Language, Microsoft Azure Cognitive Services) and converts it into structured data.

[0597] 4. Generative AI Model Analysis Method

[0598] The naturally processed data is fed into a generative AI model (e.g., OpenAI GPT-4) to generate dream interpretation results.

[0599] 5. Means of responding to interpretation results

[0600] The dream interpretation results generated by the generative AI model are sent back to the user's terminal from the server as an HTTP response.

[0601] 6. Means for displaying interpretation results

[0602] The user's device displays the interpretation results received from the server on the screen of smart glasses or a smartphone. This allows the user to check the interpretation of their dream.

[0603] 7. Additional questioning methods

[0604] If the user requests a more detailed interpretation, they can enter additional questions via voice or text. These questions are sent back to the server, and a new interpretation is generated using the same procedure.

[0605] 8. Customer Input Methods

[0606] Customers input the content and emotions of their dreams through smart glasses within the store, using either voice recognition or text input.

[0607] 9. Means for transmitting customer data

[0608] The data entered by the customer is sent from the smart glasses to the server via the internet. It is sent using an HTTP POST request.

[0609] 10. Customer analysis methods

[0610] The server analyzes the data entered by the customer using natural language processing technology and converts it into structured data.

[0611] 11. Staff presentation methods

[0612] The analyzed data is displayed on smart glasses worn by store staff, allowing them to suggest suitable products and services to customers in real time.

[0613] Specific example

[0614] When a customer inputs, "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it was happiness. What does this mean?", this data is analyzed through a series of steps. The generating AI model analysis method produces the interpretation that "Dreaming of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life."

[0615] This interpretation is displayed on the store staff's smart glasses, allowing them to suggest to customers, "It seems you are looking for freedom and adventure. We can recommend relevant ocean-related products and adventure tours."

[0616] This allows customers to receive personalized service tailored to their mental state, leading to increased satisfaction. Additionally, staff can respond to customers more effectively.

[0617] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0618] Step 1:

[0619] The user inputs the content and emotions of their dream using smart glasses or a smartphone. The user input method collects data through voice recognition or text input and converts the entered data into text format. For example, the input received is: "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it is happiness."

[0620] Step 2:

[0621] The input data transmission method sends the text data entered by the user to the server via the internet. An HTTP POST request is used to send the converted text data to the server. The input is the data collected in the previous step, and the output is the data sent to the server.

[0622] Step 3:

[0623] The server analyzes the received text data using natural language processing tools and converts it into structured data. This process utilizes natural language processing technologies such as Google Cloud Natural Language and Microsoft Azure Cognitive Services. The input is text data, and the output is structured data.

[0624] Step 4:

[0625] The generative AI model analysis method generates dream interpretation results using structured data. It uses OpenAI's GPT-4 as the generative AI model to generate interpretations based on the data. The input is naturally language processed structured data, and the output is the dream interpretation result.

[0626] Step 5:

[0627] The interpretation result return mechanism sends the generated dream interpretation result back to the user terminal from the server as an HTTP response. The input is the generated dream interpretation result, and the output is the data sent to the user terminal.

[0628] Step 6:

[0629] The user's terminal receives dream interpretation results from the server and displays them on smart glasses or a smartphone screen via an interpretation result display device. The input is the interpretation result data from the server, and the output is the screen display that the user can check.

[0630] Step 7:

[0631] If the user requests further interpretation, they can enter additional questions through an additional questioning mechanism. These additional questions are accepted via voice or text and sent back to the server. The input is the user's additional question, and the output is the additional question data sent to the server.

[0632] Step 8:

[0633] Customers input the content and emotions of their dreams using smart glasses, employing either voice recognition or text input. Data is collected via the customer's input method and converted into text format. Input is the customer's voice or text, and output is the converted text data.

[0634] Step 9:

[0635] The customer data transmission method sends the entered data to the server. Similar to the input data transmission method, it uses an HTTP POST request to send the data. The input is the converted text data, and the output is the data sent to the server.

[0636] Step 10:

[0637] The server analyzes the data received from the customer using natural language processing and converts it into structured data. This step is the same as in step 3. The input is the customer's text data, and the output is structured data.

[0638] Step 11:

[0639] The customer analysis system generates dream interpretation results based on an AI model and displays them on the smart glasses of store staff via a staff presentation system. This information allows staff to suggest suitable products and services to customers. The input is the analyzed data, and the output is the display data for staff.

[0640] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0641] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. Furthermore, it incorporates an emotion engine that automatically recognizes the user's emotions, improving the accuracy and personalization of the interpretation. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion engine means, an interpretation result reply means, an interpretation result display means, and an additional question means.

[0642] 1. System Overview

[0643] User input means

[0644] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided.

[0645] Emotional Engine Means

[0646] The system automatically detects emotions based on text data entered by the user, voice input, and facial recognition data. For example, text analysis uses natural language processing technology to infer emotions from the tone and content of the entered words. Voice analysis uses voice tone and pitch to detect emotions, and facial recognition determines emotions from facial expressions.

[0647] Input data transmission means

[0648] The system sends information such as the content of the dream entered by the user and the detected emotion data to the server. This transmission typically uses an HTTP POST request.

[0649] Natural language processing means

[0650] The server analyzes the received text data. During the analysis, the text data is converted into structured data, which is then combined with sentiment data from the sentiment engine for a more detailed analysis.

[0651] Generative AI Model Analysis Method

[0652] Natural language processing data and emotion engine data are input into a generative AI model. Specifically, the generative AI model uses a deep learning model to generate dream interpretations by combining complex text analysis with emotion data.

[0653] Means of responding to interpretation results

[0654] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response.

[0655] Means for displaying interpretation results

[0656] The user's terminal receives an HTTP response from the server and analyzes the dream interpretation results. The analysis results are displayed on the user interface. The interpretation results include a detailed analysis based on the dream's content and emotions.

[0657] Additional questioning methods

[0658] If a user requests a more detailed interpretation, they can enter additional questions. These additional questions are also analyzed by the sentiment engine and sent to the server.

[0659] 2. Specific Examples

[0660] Consider an example where a user inputs information about a dream they had last night. The user inputs the dream's content as text: "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also used, with the user speaking in a quiet tone.

[0661] When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is then processed through a generative AI model to generate an interpretation of the dream, such as "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0662] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] User: The user enters the content of their dream and the associated feelings into the application's input form in text format. For example, they might enter, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0666] Step 2:

[0667] Terminal: While waiting for the user to press the button to send the dream content and emotions, it collects additional emotion data such as voice input and facial recognition data.

[0668] Step 3:

[0669] Terminal: When the user presses the send button, the entered dream content and emotions, along with collected voice input and facial recognition data, are converted into JSON format data and sent to the server as an HTTP POST request.

[0670] Step 4:

[0671] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes dream content, emotions, voice input, and facial recognition data.

[0672] Step 5:

[0673] Server: Passes received dream content and emotion data, voice input, and facial recognition data to natural language processing and emotion engines, which then analyze the text data. In this analysis, the text data is converted into structured data, and emotions are inferred from the voice and facial expression data.

[0674] Step 6:

[0675] Server: Inputs analysis data obtained from natural language processing and emotion engines into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform detailed analysis combining text and emotion data.

[0676] Step 7:

[0677] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[0678] Step 8:

[0679] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[0680] Step 9:

[0681] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0682] Step 10:

[0683] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[0684] Step 11:

[0685] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[0686] Step 12:

[0687] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[0688] Step 13:

[0689] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[0690] Step 14:

[0691] Terminal: Displays the new interpretation results in the user interface.

[0692] Step 15:

[0693] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[0694] (Example 2)

[0695] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0696] While systems currently exist that analyze dream content and associated emotions to provide detailed, individualized interpretations, their accuracy and personalization capabilities are limited. Furthermore, they do not adequately address users' desires for further details based on dream analysis results. This invention aims to solve these problems.

[0697] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the content and emotions of the user's dream, means for transmitting the input data to the server, and means for analyzing the data received by the server using natural language processing technology. This makes it possible to automatically generate and send back a highly accurate dream interpretation based on the dream content and emotion data provided by the user.

[0698] "Means for inputting the content and emotions of a user's dreams" refers to a device or application for a user to input information about their dreams as text, voice, or facial recognition data.

[0699] "Means of sending input data to the server" refers to a communication protocol (e.g., HTTP POST request) used to send data entered by a user to a server via the internet.

[0700] "Means for analyzing data received by a server using natural language processing techniques" refers to the techniques and tools (e.g., natural language processing tools) used by a server to analyze text data received and convert it into structured data.

[0701] "Means for inputting naturally language processed data and sentiment data into a generative AI model" refers to a processing method for inputting structured text data and sentiment data into a generative AI model (e.g., a deep learning model) for analysis.

[0702] "Means for sending the generated dream interpretation results back to the user's terminal" refers to a communication protocol (e.g., HTTP response) for converting the dream interpretation results generated by the generation AI model into JSON format and sending them to the user's terminal via the internet.

[0703] "Means for a user terminal to display interpretation results" refers to software and hardware for a user's terminal (e.g., smartphone, personal computer) to display the interpretation results it has received on a user interface.

[0704] "Means for receiving additional user questions" refers to a device or application that allows a user to input additional questions seeking further details regarding an interpretation result and to send them to the server.

[0705] This system allows users to input the content and emotions of their dreams, which are then analyzed to obtain a dream interpretation. The system includes the following methods:

[0706] User input means

[0707] Users input the content of their dreams and the emotions associated with them in text format. This input is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided. For example, a user might input, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0708] Emotional Engine Means

[0709] The system automatically detects emotions based on user-entered text data, voice input, and facial recognition data. The emotion engine uses natural language processing techniques (e.g., Google Cloud Natural Language API) for text analysis, voice tone and pitch for voice analysis, and facial expressions for facial recognition to determine emotions. For example, it can detect the emotion "happiness" from entered text.

[0710] Input data transmission means

[0711] The user enters dream content and emotional data, which is then sent to the server. This transmission typically uses an HTTP POST request. When the user presses the submit button, this data is sent to the server.

[0712] Natural language processing means

[0713] The server analyzes the received text data. This analysis uses natural language processing tools (e.g., Google Cloud Natural Language API) to convert the text data into structured data. Furthermore, sentiment data from the sentiment engine is also used for a more detailed analysis.

[0714] Generative AI Model Analysis Method

[0715] The server inputs naturally processed data and emotion engine data into a generative AI model (e.g., OpenAI GPT-3). This generative AI model uses deep learning to generate dream interpretations by combining complex text analysis with emotion data.

[0716] Means of responding to interpretation results

[0717] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response. The dream interpretation results generated by the server include statements such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0718] Means for displaying interpretation results

[0719] The user's device analyzes the HTTP response received from the server and displays the dream interpretation results on the user interface. Users can check the interpretation results on the screen of a smartphone or computer application.

[0720] Additional questioning methods

[0721] If the user wants a more detailed interpretation, they can enter an additional question in text. For example, they might type, "I want to know how this dream will affect my future," and submit it again. The server receives this additional question and generates a new interpretation through its generative AI model. The result of this re-analysis might be, "In the future, you may have a higher chance of forming strong bonds with new people."

[0722] Specific example

[0723] Let's say a user types the text, "Last night I dreamt I was swimming with dolphins in the ocean. I felt very happy," and selects "happy" as the emotion. They also use voice input, speaking in a quiet tone. When the user presses the send button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is processed by a generative AI model, which generates an interpretation of the dream: "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The added feeling of happiness suggests that you are satisfied with your current life." The interpretation result is sent back to the user's device, and the user checks the result on the screen. If the user then types an additional question, "I want to know how this dream will affect my future," and sends it again, the generative AI model analyzer generates a new interpretation result, which is sent back to the user in the form of, "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[0724] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0725] Step 1:

[0726] The user enters the content and emotions of their dream.

[0727] Input: The user enters the content and feelings of their dream using text, voice, or facial recognition data. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0728] Output: Content and emotional data of the entered dream.

[0729] Specific operation: Users use smartphone or computer applications to input details and emotions about their dreams using various input methods.

[0730] Step 2:

[0731] Send the input data to the server.

[0732] Input: Text, voice, and facial recognition data entered by the user through an input method.

[0733] Output: Dream content and emotional data sent to the server.

[0734] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[0735] Step 3:

[0736] The server receives the data and performs natural language processing.

[0737] Input: Dream content and emotional data received by the server.

[0738] Output: Natural language processed structured data.

[0739] Specific operation: The server uses a natural language processing tool (e.g., Google Cloud Natural Language API) to analyze the received text data and convert it into structured data.

[0740] Step 4:

[0741] The server analyzes the emotional data.

[0742] Input: Received data and naturally language processed structured data.

[0743] Output: Data on which emotions were detected.

[0744] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to automatically detect emotions based on text, voice, and facial recognition data.

[0745] Step 5:

[0746] Natural language processing data and sentiment data are input into a generating AI model.

[0747] Input: Natural language processed text data and sentiment data.

[0748] Output: Analysis data input to the generating AI model.

[0749] Specific operation: The server inputs structured text data and sentiment data into a generating AI model (e.g., OpenAI GPT-3).

[0750] Step 6:

[0751] The generative AI model generates interpretations of dreams.

[0752] Input: Data entered into the generative AI model.

[0753] Output: Dream interpretation result.

[0754] Specific operation: The generative AI model combines complex text analysis and emotional data to generate dream interpretations. For example, it might output an analysis result such as, "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection."

[0755] Step 7:

[0756] The server returns the interpretation result to the user's terminal.

[0757] Input: Dream interpretation results generated by a generative AI model.

[0758] Output: Interpretation result returned to the user terminal.

[0759] Specific operation: The server converts the generated dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[0760] Step 8:

[0761] The terminal displays the interpretation result.

[0762] Input: Interpretation result received from the server.

[0763] Output: The dream interpretation results displayed in the user interface.

[0764] Specific operation: The system analyzes the HTTP response received by the user's device and displays the dream interpretation results on a smartphone or PC application.

[0765] Step 9:

[0766] The user enters additional questions.

[0767] Input: Enter questions based on the additional information the user wants to know.

[0768] Output: Additional question data.

[0769] Specific action: The user enters an additional question in text, for example, "I want to know how this dream will affect my future," and presses the submit button.

[0770] Step 10:

[0771] Send additional question data to the server.

[0772] Input: Additional questions entered by the user.

[0773] Output: Additional question data sent to the server.

[0774] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[0775] Step 11:

[0776] The server will analyze the additional questions.

[0777] Input: Additional question data received.

[0778] Output: Additional question data processed using natural language processing.

[0779] Specific operation: The server uses natural language processing tools to analyze the additional question data and convert it into structured data.

[0780] Step 12:

[0781] The generative AI model generates additional interpretation results.

[0782] Input: Additional question data processed using natural language.

[0783] Output: Additional interpretation results.

[0784] Specific operation: The generative AI model generates an interpretation of the additional question. For example, it might generate a result such as, "In the future, you may be more likely to form strong bonds with new people."

[0785] Step 13:

[0786] The server sends additional interpretation results back to the user's terminal.

[0787] Input: Additional interpretation results generated by the generative AI model.

[0788] Output: Additional interpretation results sent back to the user's terminal.

[0789] Specific operation: The server converts the generated additional dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[0790] Step 14:

[0791] The device displays additional interpretation results.

[0792] Input: Additional interpretation results received from the server.

[0793] Output: Additional interpretation results displayed in the user interface.

[0794] Specific operation: The system analyzes the HTTP response received by the user's device and displays additional dream interpretation results on the smartphone or PC application.

[0795] (Application Example 2)

[0796] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0797] Conventional dream analysis systems have low accuracy in generating interpretations based on the content and emotions of dreams entered by the user, and lack personalization. Furthermore, they have not made efforts to improve the user experience using head-mounted displays, smartphones, etc. This invention aims to solve these problems and provide users with accurate and personalized dream interpretations.

[0798] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion recognition means, an interpretation result reply means, an interpretation result display means, an additional question means, and a means for recognizing the user's emotions through a head-mounted display or smartphone. This makes it possible to accurately analyze the content and emotions of the user's dreams and provide personalized dream interpretation results in real time.

[0799] A "user input method" is an interface for users to input the content of their dreams and the emotions associated with them.

[0800] The "input data transmission means" is a means of sending the content and emotional data of the dream entered by the user to the server.

[0801] "Natural language processing means" refers to technical means that analyze text data received by a server and convert it into structured data.

[0802] The "generative AI model analysis method" is a method for interpreting dreams using a generative AI model based on naturally processed data and emotional data.

[0803] "Emotion recognition means" refers to a method that analyzes text data entered by the user, as well as voice and facial recognition data, to automatically detect the user's emotions.

[0804] The "interpretation result return means" is a means of returning the dream interpretation results generated by the generation AI model analysis means to the user's terminal.

[0805] The "interpretation result display means" is a means of analyzing the dream interpretation results received by the user terminal and displaying them on the interface.

[0806] An "additional questioning method" is a means by which a user enters additional questions to request a more detailed interpretation and sends those questions to the server.

[0807] A "head-mounted display" is a device that a user wears and uses as an interface for virtual reality or augmented reality.

[0808] A "smartphone" is a multi-functional mobile device capable of making calls, browsing the internet, and running applications.

[0809] This invention is an interactive system for analyzing the content of a user's dreams and the emotions experienced during those dreams, and providing a dream interpretation. The system includes a user input means, an emotion recognition means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. It also includes means for recognizing the user's emotions using a head-mounted display (HMD) or a smartphone.

[0810] Hardware and software configuration

[0811] User input means

[0812] User input means are interfaces for users to input the content and emotions of their dreams. This is provided via smartphones or head-mounted displays. Methods include text input, voice input, and facial recognition.

[0813] emotion recognition means

[0814] Emotion recognition is a method that automatically detects emotions by analyzing text data, voice, and facial recognition data entered by the user. This analysis utilizes natural language processing and speech analysis technologies. Specifically, it uses general natural language processing libraries (e.g., NLTK) and speech analysis libraries.

[0815] Input data transmission means

[0816] The input data transmission method is a means for sending the content and emotional data of dreams entered by the user to the server. The data is sent using an HTTP POST request.

[0817] Natural language processing means

[0818] Natural language processing (NLP) is a technique that analyzes text data received by a server and converts it into structured data. This analysis is performed using natural language processing libraries and APIs.

[0819] Generative AI Model Analysis Method

[0820] The generative AI model analysis method involves inputting naturally processed data and emotional data into a generative AI model to interpret dreams. This generative AI model utilizes deep learning models or large-scale language models (e.g., OpenAI APIs).

[0821] Means of responding to interpretation results

[0822] The interpretation result return method is a means of returning the dream interpretation result generated by the generation AI model analysis method to the user's terminal. This data is transmitted in JSON format.

[0823] Means for displaying interpretation results

[0824] The interpretation result display means analyzes the dream interpretation results received by the user terminal and displays them on the user interface. A smartphone screen or a head-mounted display visual interface is used for the display.

[0825] Additional questioning methods

[0826] The additional questioning feature allows users to request a more detailed interpretation of their dreams. Users enter additional questions and send them to the server. Based on this additional information, the AI ​​model is re-analyzed, and a new interpretation is generated.

[0827] Specific example

[0828] The user enters text describing their dream, such as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also available, spoken in a quiet tone. When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and emotion recognition tools. The analyzed data is then processed by a generative AI model to generate an interpretation of the dream, such as, "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life." This interpretation is then sent back from the server to the user's terminal, where the user can view the result on the screen.

[0829] Example of a prompt

[0830] The following are examples of input prompts for a generative AI model.

[0831] Here is the content of the dream: Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy.

[0832] The emotion associated with this dream is: happiness

[0833] Please interpret this dream.

[0834] This allows the system to analyze the content and emotions of the user's dreams and provide accurate and personalized dream interpretations.

[0835] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0836] Step 1:

[0837] The user inputs the content and emotions of their dream. Text input, voice input, and facial recognition data are acquired using a smartphone or head-mounted display. The input data includes dream details and associated emotions. The entered data is collected and passed on to the next processing step.

[0838] Step 2:

[0839] The device sends input data to the server using an HTTP POST request. This data includes the content of the dream entered by the user, audio data, facial recognition data, and emotional information. The server receives this data and prepares it for analysis.

[0840] Step 3:

[0841] The server analyzes the received text data using natural language processing tools. Specifically, it tokenizes the text data using a natural language processing library (e.g., NLTK) and converts it into structured data. This structured data is then generated, and the process proceeds to the next step.

[0842] Step 4:

[0843] The server uses emotion recognition capabilities to analyze the user's emotions from the input voice data and facial recognition data. This involves using a voice analysis library to estimate emotions based on tone and pitch. Additionally, a facial recognition algorithm is used to determine emotions from facial expressions. Detected emotion data is then generated.

[0844] Step 5:

[0845] The server inputs naturally processed data and emotional data into a generating AI model analysis system. A large-scale language model (e.g., OpenAI API) is used in the generating AI model to interpret the user's dreams. As a result of the analysis, dream interpretation data is generated.

[0846] Step 6:

[0847] The server converts the generated dream interpretation results into JSON format and sends them back to the terminal using the interpretation result reply method. The dream interpretation results are sent as an HTTP response. The user terminal receives this data.

[0848] Step 7:

[0849] The system analyzes the dream interpretation received by the user's device and displays it on the interface. The interpretation includes a detailed analysis based on the dream's content and emotions. The user reviews the interpretation on the screen and enters any additional questions.

[0850] Step 8:

[0851] The user enters an additional question, and the device sends that data to the server again. Similarly, the question data is sent using an HTTP POST request, and the server receives it.

[0852] Step 9:

[0853] The server uses an additional questioning mechanism to analyze the additional questions and generates new interpretation results through the AI ​​model analysis mechanism. This new data is then sent back to the terminal through the interpretation result reply mechanism.

[0854] Step 10:

[0855] The user's terminal receives the new interpretation results and displays them again on the interface. This allows the user to gain deeper insights.

[0856] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0857] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0858] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0859] [Third Embodiment]

[0860] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0861] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0862] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0863] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0864] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0865] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0866] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0867] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0868] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0869] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0870] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0871] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0872] The present invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. This system includes user input means, input data transmission means, natural language processing means, generation AI model analysis means, interpretation result reply means, interpretation result display means, and additional question means.

[0873] 1. System Overview

[0874] User input means

[0875] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications.

[0876] Input data transmission means

[0877] The data entered by the user (the content and emotions of the dream) is sent to the server via the internet. This transmission typically uses an HTTP POST request.

[0878] Natural language processing means

[0879] The text data received by the server is analyzed using natural language processing techniques. In this step, the text data is converted into structured data, and semantic analysis is performed.

[0880] Generative AI Model Analysis Method

[0881] The naturally processed data is fed into a generative AI model. Specifically, this generative AI model uses a deep learning model to generate dream interpretations based on this data.

[0882] Means of responding to interpretation results

[0883] The dream interpretation results generated by the generative AI model are sent back from the server to the user's terminal. This reply is usually sent as an HTTP response.

[0884] Means for displaying interpretation results

[0885] The user's terminal displays the dream interpretation results received from the server on the screen. This allows the user to confirm the dream interpretation.

[0886] Additional questioning methods

[0887] If the user requests a more detailed interpretation, they can enter additional questions. These additional questions are sent back to the server, and the process described above is repeated to generate a new interpretation, which is then sent back to the user.

[0888] 2. Specific Examples

[0889] Consider an example where a user enters information about a dream they had last night. The user enters the dream content as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. When the user presses the submit button, this data is sent to the server.

[0890] The server receives the input data and analyzes it using natural language processing. The analyzed data is then analyzed by a generative AI model, which generates the following interpretation of the dream: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0891] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[0892] The following describes the processing flow.

[0893] Step 1:

[0894] User: Enter the content of your dream and the emotions associated with it into the application's input form as text. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[0895] Step 2:

[0896] Terminal: When the user presses the submit button, the entered dream content and emotions are converted into JSON data and sent to the server as an HTTP POST request.

[0897] Step 3:

[0898] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes the content and emotions of the dream.

[0899] Step 4:

[0900] Server: The received dream content and emotions are passed to a natural language processing system for text data analysis. This analysis converts the text data into structured data and then analyzes its meaning.

[0901] Step 5:

[0902] Server: Inputs naturally language processed data into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform complex text analysis and pattern recognition.

[0903] Step 6:

[0904] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[0905] Step 7:

[0906] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[0907] Step 8:

[0908] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0909] Step 9:

[0910] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[0911] Step 10:

[0912] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[0913] Step 11:

[0914] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[0915] Step 12:

[0916] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[0917] Step 13:

[0918] Terminal: Displays the new interpretation results in the user interface.

[0919] Step 14:

[0920] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[0921] (Example 1)

[0922] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0923] In modern society, users often seek to interpret the content and emotions of their dreams to deepen their self-understanding. However, traditional dream interpretation methods are subjective, making it difficult to obtain consistent interpretations. Furthermore, when users ask additional questions, they have to re-enter information, hindering quick responses. New technologies and systems are needed to solve these problems.

[0924] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0925] In this invention, the server includes means for the user to input the content and emotions of their dream in text format, means for transmitting the input data to the server via the internet, natural language processing means for analyzing the text data received by the server, generative AI model analysis means for generating a dream interpretation based on the naturally language processed data, means for returning the generated dream interpretation result to the user terminal, means for the user terminal to display the dream interpretation result, and means for the user to input additional questions to request a more detailed interpretation. This enables the user to quickly obtain a consistent dream interpretation and to appropriately respond to additional questions.

[0926] "Input method" refers to the interface of a device or application that allows a user to input the content and emotions of their dreams in text format.

[0927] "Transmission means" refers to the mechanism for sending input data to a server via the internet.

[0928] "Natural language processing means" refers to the technologies and processes used by a server to analyze text data received and convert it into structured data.

[0929] "Generative AI model analysis means" refers to a system that uses a deep learning algorithm to generate dream interpretations based on data structured using natural language processing.

[0930] "Reply method" refers to the process of sending the generated dream interpretation results to the user's device.

[0931] "Display means" refers to devices or software that allow a user terminal to display the dream interpretation results received from the server on a screen.

[0932] "Additional questioning mechanism" refers to a mechanism for users to input additional questions to request further detailed interpretations and send those questions to the server.

[0933] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain a dream interpretation result. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. Specifically, the invention is implemented as follows.

[0934] User input means

[0935] Users input the content and feelings of their dreams in text format using a smartphone or computer application. For example, a user might type "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application's interface and select "happy" as their emotion.

[0936] Input data transmission means

[0937] The data entered by the user (the content and emotions of the dream) is sent to the server over the internet using an HTTP POST request. When the user presses the submit button, this data is sent to the server. For example, the payload of the HTTP request includes {"dream": "Last night I dreamt I was swimming with dolphins in a big ocean. I felt very happy", "emotion": "happy"}.

[0938] Natural language processing means

[0939] The server passes the received text data to a natural language processing module, which analyzes the text data and converts it into structured data. In this step, the text data is semantically analyzed, and keywords and emotions are extracted. For example, keywords such as "sea," "dolphin," and "swimming," and the emotion "happiness" are recognized.

[0940] Generative AI Model Analysis Method

[0941] The structured data, processed using natural language processing, is fed into a generative AI model. This model employs deep learning algorithms to generate dream interpretations based on the input data. For example, it might generate an interpretation such as, "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0942] Means of responding to interpretation results

[0943] The generated dream interpretation is sent from the server to the user's terminal as an HTTP response. The server compiles the analysis results and sends them to the user. For example, the server includes the interpretation {"interpretation": "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."} in the payload of the HTTP response.

[0944] Means for displaying interpretation results

[0945] The user terminal parses the dream interpretation received from the server and displays it on the user interface. For example, the screen might display an interpretation such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[0946] Additional questioning methods

[0947] If the user requests a more detailed interpretation, they can enter additional questions through the interface. For example, if the user enters "I want to know how this dream will affect my future" and presses the submit button, an HTTP POST request containing the additional question will be sent back to the server.

[0948] The server receives the additional question, interprets it again through the natural language processing module, and generates a new interpretation using a generative AI model. The new interpretation is then sent back to the user. For example, the interpretation "In the future, you may have a higher chance of forming strong bonds with new people" is generated and sent back to the user.

[0949] Example of a prompt

[0950] Examples of prompts a user might enter into the system include questions like, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy. What does this dream mean?" or, "Please tell me how this dream will affect my future."

[0951] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0952] Step 1:

[0953] The user enters the content and emotions of their dream.

[0954] Input: Users use a smartphone or computer application to input the content and emotions of their dreams in text format.

[0955] Operation: The user enters "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application interface and selects "Happy" as the emotion.

[0956] Output: Text data entered in the input field.

[0957] Step 2:

[0958] The terminal sends the input data to the server.

[0959] Input: Text data of the dream content and emotions entered by the user in Step 1.

[0960] Action: The terminal creates an HTTP POST request and sends a payload containing the entered data to the server. This action is triggered when the user presses the submit button.

[0961] Output: The HTTP request payload ({"dream": "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy", "emotion": "happy"}) is sent to the server.

[0962] Step 3:

[0963] The server analyzes the received data using a natural language processing module.

[0964] Input: Text data received by the server in Step 2.

[0965] Operation: The server passes the received data to the natural language processing module. The natural language processing module analyzes the text data and converts it into structured data. This analysis includes semantic analysis and keyword extraction.

[0966] Output: Natural language processed structured data (e.g., keywords "sea", "dolphin", "swim", emotion "happy").

[0967] Step 4:

[0968] The server generates dream interpretations using a generative AI model.

[0969] Input: Structured data obtained in Step 3.

[0970] Operation: Natural language processed data is fed to a generative AI model. The generative AI model uses a deep learning algorithm to generate dream interpretations. This process outputs dream interpretations based on the analysis results.

[0971] Output: The generated dream interpretation (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[0972] Step 5:

[0973] The server returns the interpretation result to the user's terminal.

[0974] Input: The dream interpretation result generated in Step 4.

[0975] Operation: The server sends the generated interpretation results to the user's terminal in the form of an HTTP response.

[0976] Output: The HTTP response payload ({"interpretation": "Dreaming of swimming with dolphins in the sea symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that the user is satisfied with their current life."}) reaches the user's terminal.

[0977] Step 6:

[0978] The terminal displays the interpretation result.

[0979] Input: Interpretation result received from the server in Step 5.

[0980] Operation: The device parses the interpretation of the received dream and displays it in the user interface.

[0981] Output: The dream interpretation results displayed on the screen (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[0982] Step 7:

[0983] The user enters and submits additional questions.

[0984] Input: Data entered by the user in the input field for additional questions.

[0985] Operation: The user enters an additional question, such as "I want to know how this dream will affect my future," and presses the submit button. The device then sends an HTTP POST request to the server containing this additional data.

[0986] Output: The HTTP request payload ({"question": "I want to know how this dream will affect my future"}) is sent to the server.

[0987] Step 8:

[0988] The server performs the analysis again, generates a new interpretation, and sends it back.

[0989] Input: Text data of the additional questions received by the server in Step 7.

[0990] Operation: The server receives additional questions, structures them again through the natural language processing module, and inputs them into the generative AI model. The generative AI model generates a new interpretation and sends it to the user's terminal as an HTTP response.

[0991] Output: A new interpretation (e.g., "In the future, you may have a higher chance of forming strong bonds with new people") reaches the user's terminal.

[0992] (Application Example 1)

[0993] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0994] Traditional conversational systems primarily provided static interpretations of user input, which limited their ability to deliver personalized services. Furthermore, they lacked the means to reflect customers' psychological states and emotions in real time and provide useful information to store staff. Therefore, there was a growing need for a system that could provide information more tailored to individual customer needs in real time, thereby improving the customer experience.

[0995] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0996] In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means. This enables the analysis of customers' dreams and emotions, the presentation of the analysis results to store staff in real time, and more personalized customer service and product suggestions.

[0997] A "user input device" is a device or interface for a user to input the content and emotions of their dreams in text format.

[0998] "Input data transmission means" refers to a means for sending data entered by a user to a server.

[0999] A "natural language processing system" is a mechanism that analyzes text data received by a server and converts it into structured data.

[1000] The "generative AI model analysis method" is a means of supplying naturally language processed data to a deep learning model to generate dream interpretations.

[1001] The "interpretation result reply method" is a means of sending the generated dream interpretation results from the server to the user's terminal.

[1002] The "interpretation result display means" is a mechanism that displays the dream interpretation results received from the server on the user's terminal.

[1003] An "additional questioning mechanism" is a means for users to input and submit additional questions to seek further detailed interpretations.

[1004] A "customer input method" refers to a device or interface that allows customers to provide the content and emotions of their dreams through voice or text input.

[1005] "Customer data transmission means" refers to a means of sending data entered by a customer to a server.

[1006] A "customer analysis tool" is a system that analyzes data entered by customers and converts it into structured data.

[1007] "Staff presentation tools" refer to devices or interfaces that display information to enable store staff to make appropriate suggestions to customers based on analyzed data.

[1008] The system for realizing this invention consists of the following means: a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means.

[1009] System Configuration

[1010] 1. User input means

[1011] Users input the content of their dreams and related emotions using smart glasses or a smartphone. This is done via voice recognition or text input.

[1012] 2. Input data transmission means

[1013] The data entered by the user is sent from smart glasses or a smartphone to a backend server via the internet. This transmission is primarily done using HTTP POST requests.

[1014] 3. Natural Language Processing Means

[1015] The server analyzes the received text data using natural language processing technologies (e.g., Google Cloud Natural Language, Microsoft Azure Cognitive Services) and converts it into structured data.

[1016] 4. Generative AI Model Analysis Method

[1017] The naturally processed data is fed into a generative AI model (e.g., OpenAI GPT-4) to generate dream interpretation results.

[1018] 5. Means of responding to interpretation results

[1019] The dream interpretation results generated by the generative AI model are sent back to the user's terminal from the server as an HTTP response.

[1020] 6. Means for displaying interpretation results

[1021] The user's device displays the interpretation results received from the server on the screen of smart glasses or a smartphone. This allows the user to check the interpretation of their dream.

[1022] 7. Additional questioning methods

[1023] If the user requests a more detailed interpretation, they can enter additional questions via voice or text. These questions are sent back to the server, and a new interpretation is generated using the same procedure.

[1024] 8. Customer Input Methods

[1025] Customers input the content and emotions of their dreams through smart glasses within the store, using either voice recognition or text input.

[1026] 9. Means for transmitting customer data

[1027] The data entered by the customer is sent from the smart glasses to the server via the internet. It is sent using an HTTP POST request.

[1028] 10. Customer analysis methods

[1029] The server analyzes the data entered by the customer using natural language processing technology and converts it into structured data.

[1030] 11. Staff presentation methods

[1031] The analyzed data is displayed on smart glasses worn by store staff, allowing them to suggest suitable products and services to customers in real time.

[1032] Specific example

[1033] When a customer inputs, "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it was happiness. What does this mean?", this data is analyzed through a series of steps. The generating AI model analysis method produces the interpretation that "Dreaming of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life."

[1034] This interpretation is displayed on the store staff's smart glasses, allowing them to suggest to customers, "It seems you are looking for freedom and adventure. We can recommend relevant ocean-related products and adventure tours."

[1035] This allows customers to receive personalized service tailored to their mental state, leading to increased satisfaction. Additionally, staff can respond to customers more effectively.

[1036] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1037] Step 1:

[1038] The user inputs the content and emotions of their dream using smart glasses or a smartphone. The user input method collects data through voice recognition or text input and converts the entered data into text format. For example, the input received is: "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it is happiness."

[1039] Step 2:

[1040] The input data transmission method sends the text data entered by the user to the server via the internet. An HTTP POST request is used to send the converted text data to the server. The input is the data collected in the previous step, and the output is the data sent to the server.

[1041] Step 3:

[1042] The server analyzes the received text data using natural language processing tools and converts it into structured data. This process utilizes natural language processing technologies such as Google Cloud Natural Language and Microsoft Azure Cognitive Services. The input is text data, and the output is structured data.

[1043] Step 4:

[1044] The generative AI model analysis method generates dream interpretation results using structured data. It uses OpenAI's GPT-4 as the generative AI model to generate interpretations based on the data. The input is naturally language processed structured data, and the output is the dream interpretation result.

[1045] Step 5:

[1046] The interpretation result return mechanism sends the generated dream interpretation result back to the user terminal from the server as an HTTP response. The input is the generated dream interpretation result, and the output is the data sent to the user terminal.

[1047] Step 6:

[1048] The user's terminal receives dream interpretation results from the server and displays them on smart glasses or a smartphone screen via an interpretation result display device. The input is the interpretation result data from the server, and the output is the screen display that the user can check.

[1049] Step 7:

[1050] If the user requests further interpretation, they can enter additional questions through an additional questioning mechanism. These additional questions are accepted via voice or text and sent back to the server. The input is the user's additional question, and the output is the additional question data sent to the server.

[1051] Step 8:

[1052] Customers input the content and emotions of their dreams using smart glasses, employing either voice recognition or text input. Data is collected via the customer's input method and converted into text format. Input is the customer's voice or text, and output is the converted text data.

[1053] Step 9:

[1054] The customer data transmission method sends the entered data to the server. Similar to the input data transmission method, it uses an HTTP POST request to send the data. The input is the converted text data, and the output is the data sent to the server.

[1055] Step 10:

[1056] The server analyzes the data received from the customer using natural language processing and converts it into structured data. This step is the same as in step 3. The input is the customer's text data, and the output is structured data.

[1057] Step 11:

[1058] The customer analysis system generates dream interpretation results based on an AI model and displays them on the smart glasses of store staff via a staff presentation system. This information allows staff to suggest suitable products and services to customers. The input is the analyzed data, and the output is the display data for staff.

[1059] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1060] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. Furthermore, it incorporates an emotion engine that automatically recognizes the user's emotions, improving the accuracy and personalization of the interpretation. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion engine means, an interpretation result reply means, an interpretation result display means, and an additional question means.

[1061] 1. System Overview

[1062] User input means

[1063] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided.

[1064] Emotional Engine Means

[1065] The system automatically detects emotions based on text data entered by the user, voice input, and facial recognition data. For example, text analysis uses natural language processing technology to infer emotions from the tone and content of the entered words. Voice analysis uses voice tone and pitch to detect emotions, and facial recognition determines emotions from facial expressions.

[1066] Input data transmission means

[1067] The system sends information such as the content of the dream entered by the user and the detected emotion data to the server. This transmission typically uses an HTTP POST request.

[1068] Natural language processing means

[1069] The server analyzes the received text data. During the analysis, the text data is converted into structured data, which is then combined with sentiment data from the sentiment engine for a more detailed analysis.

[1070] Generative AI Model Analysis Method

[1071] Natural language processing data and emotion engine data are input into a generative AI model. Specifically, the generative AI model uses a deep learning model to generate dream interpretations by combining complex text analysis with emotion data.

[1072] Means of responding to interpretation results

[1073] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response.

[1074] Means for displaying interpretation results

[1075] The user's terminal receives an HTTP response from the server and analyzes the dream interpretation results. The analysis results are displayed on the user interface. The interpretation results include a detailed analysis based on the dream's content and emotions.

[1076] Additional questioning methods

[1077] If a user requests a more detailed interpretation, they can enter additional questions. These additional questions are also analyzed by the sentiment engine and sent to the server.

[1078] 2. Specific Examples

[1079] Consider an example where a user inputs information about a dream they had last night. The user inputs the dream's content as text: "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also used, with the user speaking in a quiet tone.

[1080] When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is then processed through a generative AI model to generate an interpretation of the dream, such as "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1081] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[1082] The following describes the processing flow.

[1083] Step 1:

[1084] User: The user enters the content of their dream and the associated feelings into the application's input form in text format. For example, they might enter, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1085] Step 2:

[1086] Terminal: While waiting for the user to press the button to send the dream content and emotions, it collects additional emotion data such as voice input and facial recognition data.

[1087] Step 3:

[1088] Terminal: When the user presses the send button, the entered dream content and emotions, along with collected voice input and facial recognition data, are converted into JSON format data and sent to the server as an HTTP POST request.

[1089] Step 4:

[1090] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes dream content, emotions, voice input, and facial recognition data.

[1091] Step 5:

[1092] Server: Passes received dream content and emotion data, voice input, and facial recognition data to natural language processing and emotion engines, which then analyze the text data. In this analysis, the text data is converted into structured data, and emotions are inferred from the voice and facial expression data.

[1093] Step 6:

[1094] Server: Inputs analysis data obtained from natural language processing and emotion engines into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform detailed analysis combining text and emotion data.

[1095] Step 7:

[1096] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[1097] Step 8:

[1098] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[1099] Step 9:

[1100] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1101] Step 10:

[1102] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[1103] Step 11:

[1104] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[1105] Step 12:

[1106] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[1107] Step 13:

[1108] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[1109] Step 14:

[1110] Terminal: Displays the new interpretation results in the user interface.

[1111] Step 15:

[1112] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[1113] (Example 2)

[1114] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1115] While systems currently exist that analyze dream content and associated emotions to provide detailed, individualized interpretations, their accuracy and personalization capabilities are limited. Furthermore, they do not adequately address users' desires for further details based on dream analysis results. This invention aims to solve these problems.

[1116] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the content and emotions of the user's dream, means for transmitting the input data to the server, and means for analyzing the data received by the server using natural language processing technology. This makes it possible to automatically generate and send back a highly accurate dream interpretation based on the dream content and emotion data provided by the user.

[1117] "Means for inputting the content and emotions of a user's dreams" refers to a device or application for a user to input information about their dreams as text, voice, or facial recognition data.

[1118] "Means of sending input data to the server" refers to a communication protocol (e.g., HTTP POST request) used to send data entered by a user to a server via the internet.

[1119] "Means for analyzing data received by a server using natural language processing techniques" refers to the techniques and tools (e.g., natural language processing tools) used by a server to analyze text data received and convert it into structured data.

[1120] "Means for inputting naturally language processed data and sentiment data into a generative AI model" refers to a processing method for inputting structured text data and sentiment data into a generative AI model (e.g., a deep learning model) for analysis.

[1121] "Means for sending the generated dream interpretation results back to the user's terminal" refers to a communication protocol (e.g., HTTP response) for converting the dream interpretation results generated by the generation AI model into JSON format and sending them to the user's terminal via the internet.

[1122] "Means for a user terminal to display interpretation results" refers to software and hardware for a user's terminal (e.g., smartphone, personal computer) to display the interpretation results it has received on a user interface.

[1123] "Means for receiving additional user questions" refers to a device or application that allows a user to input additional questions seeking further details regarding an interpretation result and to send them to the server.

[1124] This system allows users to input the content and emotions of their dreams, which are then analyzed to obtain a dream interpretation. The system includes the following methods:

[1125] User input means

[1126] Users input the content of their dreams and the emotions associated with them in text format. This input is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided. For example, a user might input, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1127] Emotional Engine Means

[1128] The system automatically detects emotions based on user-entered text data, voice input, and facial recognition data. The emotion engine uses natural language processing techniques (e.g., Google Cloud Natural Language API) for text analysis, voice tone and pitch for voice analysis, and facial expressions for facial recognition to determine emotions. For example, it can detect the emotion "happiness" from entered text.

[1129] Input data transmission means

[1130] The user enters dream content and emotional data, which is then sent to the server. This transmission typically uses an HTTP POST request. When the user presses the submit button, this data is sent to the server.

[1131] Natural language processing means

[1132] The server analyzes the received text data. This analysis uses natural language processing tools (e.g., Google Cloud Natural Language API) to convert the text data into structured data. Furthermore, sentiment data from the sentiment engine is also used for a more detailed analysis.

[1133] Generative AI Model Analysis Method

[1134] The server inputs naturally processed data and emotion engine data into a generative AI model (e.g., OpenAI GPT-3). This generative AI model uses deep learning to generate dream interpretations by combining complex text analysis with emotion data.

[1135] Means of responding to interpretation results

[1136] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response. The dream interpretation results generated by the server include statements such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1137] Means for displaying interpretation results

[1138] The user's device analyzes the HTTP response received from the server and displays the dream interpretation results on the user interface. Users can check the interpretation results on the screen of a smartphone or computer application.

[1139] Additional questioning methods

[1140] If the user wants a more detailed interpretation, they can enter an additional question in text. For example, they might type, "I want to know how this dream will affect my future," and submit it again. The server receives this additional question and generates a new interpretation through its generative AI model. The result of this re-analysis might be, "In the future, you may have a higher chance of forming strong bonds with new people."

[1141] Specific example

[1142] Let's say a user types the text, "Last night I dreamt I was swimming with dolphins in the ocean. I felt very happy," and selects "happy" as the emotion. They also use voice input, speaking in a quiet tone. When the user presses the send button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is processed by a generative AI model, which generates an interpretation of the dream: "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The added feeling of happiness suggests that you are satisfied with your current life." The interpretation result is sent back to the user's device, and the user checks the result on the screen. If the user then types an additional question, "I want to know how this dream will affect my future," and sends it again, the generative AI model analyzer generates a new interpretation result, which is sent back to the user in the form of, "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[1143] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1144] Step 1:

[1145] The user enters the content and emotions of their dream.

[1146] Input: The user enters the content and feelings of their dream using text, voice, or facial recognition data. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1147] Output: Content and emotional data of the entered dream.

[1148] Specific operation: Users use smartphone or computer applications to input details and emotions about their dreams using various input methods.

[1149] Step 2:

[1150] Send the input data to the server.

[1151] Input: Text, voice, and facial recognition data entered by the user through an input method.

[1152] Output: Dream content and emotional data sent to the server.

[1153] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[1154] Step 3:

[1155] The server receives the data and performs natural language processing.

[1156] Input: Dream content and emotional data received by the server.

[1157] Output: Natural language processed structured data.

[1158] Specific operation: The server uses a natural language processing tool (e.g., Google Cloud Natural Language API) to analyze the received text data and convert it into structured data.

[1159] Step 4:

[1160] The server analyzes the emotional data.

[1161] Input: Received data and naturally language processed structured data.

[1162] Output: Data on which emotions were detected.

[1163] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to automatically detect emotions based on text, voice, and facial recognition data.

[1164] Step 5:

[1165] Natural language processing data and sentiment data are input into a generating AI model.

[1166] Input: Natural language processed text data and sentiment data.

[1167] Output: Analysis data input to the generating AI model.

[1168] Specific operation: The server inputs structured text data and sentiment data into a generating AI model (e.g., OpenAI GPT-3).

[1169] Step 6:

[1170] The generative AI model generates interpretations of dreams.

[1171] Input: Data entered into the generative AI model.

[1172] Output: Dream interpretation result.

[1173] Specific operation: The generative AI model combines complex text analysis and emotional data to generate dream interpretations. For example, it might output an analysis result such as, "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection."

[1174] Step 7:

[1175] The server returns the interpretation result to the user's terminal.

[1176] Input: Dream interpretation results generated by a generative AI model.

[1177] Output: Interpretation result returned to the user terminal.

[1178] Specific operation: The server converts the generated dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[1179] Step 8:

[1180] The terminal displays the interpretation result.

[1181] Input: Interpretation result received from the server.

[1182] Output: The dream interpretation results displayed in the user interface.

[1183] Specific operation: The system analyzes the HTTP response received by the user's device and displays the dream interpretation results on a smartphone or PC application.

[1184] Step 9:

[1185] The user enters additional questions.

[1186] Input: Enter questions based on the additional information the user wants to know.

[1187] Output: Additional question data.

[1188] Specific action: The user enters an additional question in text, for example, "I want to know how this dream will affect my future," and presses the submit button.

[1189] Step 10:

[1190] Send additional question data to the server.

[1191] Input: Additional questions entered by the user.

[1192] Output: Additional question data sent to the server.

[1193] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[1194] Step 11:

[1195] The server will analyze the additional questions.

[1196] Input: Additional question data received.

[1197] Output: Additional question data processed using natural language processing.

[1198] Specific operation: The server uses natural language processing tools to analyze the additional question data and convert it into structured data.

[1199] Step 12:

[1200] The generative AI model generates additional interpretation results.

[1201] Input: Additional question data processed using natural language.

[1202] Output: Additional interpretation results.

[1203] Specific operation: The generative AI model generates an interpretation of the additional question. For example, it might generate a result such as, "In the future, you may be more likely to form strong bonds with new people."

[1204] Step 13:

[1205] The server sends additional interpretation results back to the user's terminal.

[1206] Input: Additional interpretation results generated by the generative AI model.

[1207] Output: Additional interpretation results sent back to the user's terminal.

[1208] Specific operation: The server converts the generated additional dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[1209] Step 14:

[1210] The device displays additional interpretation results.

[1211] Input: Additional interpretation results received from the server.

[1212] Output: Additional interpretation results displayed in the user interface.

[1213] Specific operation: The system analyzes the HTTP response received by the user's device and displays additional dream interpretation results on the smartphone or PC application.

[1214] (Application Example 2)

[1215] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1216] Conventional dream analysis systems have low accuracy in generating interpretations based on the content and emotions of dreams entered by the user, and lack personalization. Furthermore, they have not made efforts to improve the user experience using head-mounted displays, smartphones, etc. This invention aims to solve these problems and provide users with accurate and personalized dream interpretations.

[1217] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion recognition means, an interpretation result reply means, an interpretation result display means, an additional question means, and a means for recognizing the user's emotions through a head-mounted display or smartphone. This makes it possible to accurately analyze the content and emotions of the user's dreams and provide personalized dream interpretation results in real time.

[1218] A "user input method" is an interface for users to input the content of their dreams and the emotions associated with them.

[1219] The "input data transmission means" is a means of sending the content and emotional data of the dream entered by the user to the server.

[1220] "Natural language processing means" refers to technical means that analyze text data received by a server and convert it into structured data.

[1221] The "generative AI model analysis method" is a method for interpreting dreams using a generative AI model based on naturally processed data and emotional data.

[1222] "Emotion recognition means" refers to a method that analyzes text data entered by the user, as well as voice and facial recognition data, to automatically detect the user's emotions.

[1223] The "interpretation result return means" is a means of returning the dream interpretation results generated by the generation AI model analysis means to the user's terminal.

[1224] The "interpretation result display means" is a means of analyzing the dream interpretation results received by the user terminal and displaying them on the interface.

[1225] An "additional questioning method" is a means by which a user enters additional questions to request a more detailed interpretation and sends those questions to the server.

[1226] A "head-mounted display" is a device that a user wears and uses as an interface for virtual reality or augmented reality.

[1227] A "smartphone" is a multi-functional mobile device capable of making calls, browsing the internet, and running applications.

[1228] This invention is an interactive system for analyzing the content of a user's dreams and the emotions experienced during those dreams, and providing a dream interpretation. The system includes a user input means, an emotion recognition means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. It also includes means for recognizing the user's emotions using a head-mounted display (HMD) or a smartphone.

[1229] Hardware and software configuration

[1230] User input means

[1231] User input means are interfaces for users to input the content and emotions of their dreams. This is provided via smartphones or head-mounted displays. Methods include text input, voice input, and facial recognition.

[1232] emotion recognition means

[1233] Emotion recognition is a method that automatically detects emotions by analyzing text data, voice, and facial recognition data entered by the user. This analysis utilizes natural language processing and speech analysis technologies. Specifically, it uses general natural language processing libraries (e.g., NLTK) and speech analysis libraries.

[1234] Input data transmission means

[1235] The input data transmission method is a means for sending the content and emotional data of dreams entered by the user to the server. The data is sent using an HTTP POST request.

[1236] Natural language processing means

[1237] Natural language processing (NLP) is a technique that analyzes text data received by a server and converts it into structured data. This analysis is performed using natural language processing libraries and APIs.

[1238] Generative AI Model Analysis Method

[1239] The generative AI model analysis method involves inputting naturally processed data and emotional data into a generative AI model to interpret dreams. This generative AI model utilizes deep learning models or large-scale language models (e.g., OpenAI APIs).

[1240] Means of responding to interpretation results

[1241] The interpretation result return method is a means of returning the dream interpretation result generated by the generation AI model analysis method to the user's terminal. This data is transmitted in JSON format.

[1242] Means for displaying interpretation results

[1243] The interpretation result display means analyzes the dream interpretation results received by the user terminal and displays them on the user interface. A smartphone screen or a head-mounted display visual interface is used for the display.

[1244] Additional questioning methods

[1245] The additional questioning feature allows users to request a more detailed interpretation of their dreams. Users enter additional questions and send them to the server. Based on this additional information, the AI ​​model is re-analyzed, and a new interpretation is generated.

[1246] Specific example

[1247] The user enters text describing their dream, such as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also available, spoken in a quiet tone. When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and emotion recognition tools. The analyzed data is then processed by a generative AI model to generate an interpretation of the dream, such as, "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life." This interpretation is then sent back from the server to the user's terminal, where the user can view the result on the screen.

[1248] Example of a prompt

[1249] The following are examples of input prompts for a generative AI model.

[1250] Here is the content of the dream: Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy.

[1251] The emotion associated with this dream is: happiness

[1252] Please interpret this dream.

[1253] This allows the system to analyze the content and emotions of the user's dreams and provide accurate and personalized dream interpretations.

[1254] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1255] Step 1:

[1256] The user inputs the content and emotions of their dream. Text input, voice input, and facial recognition data are acquired using a smartphone or head-mounted display. The input data includes dream details and associated emotions. The entered data is collected and passed on to the next processing step.

[1257] Step 2:

[1258] The device sends input data to the server using an HTTP POST request. This data includes the content of the dream entered by the user, audio data, facial recognition data, and emotional information. The server receives this data and prepares it for analysis.

[1259] Step 3:

[1260] The server analyzes the received text data using natural language processing tools. Specifically, it tokenizes the text data using a natural language processing library (e.g., NLTK) and converts it into structured data. This structured data is then generated, and the process proceeds to the next step.

[1261] Step 4:

[1262] The server uses emotion recognition capabilities to analyze the user's emotions from the input voice data and facial recognition data. This involves using a voice analysis library to estimate emotions based on tone and pitch. Additionally, a facial recognition algorithm is used to determine emotions from facial expressions. Detected emotion data is then generated.

[1263] Step 5:

[1264] The server inputs naturally processed data and emotional data into a generating AI model analysis system. A large-scale language model (e.g., OpenAI API) is used in the generating AI model to interpret the user's dreams. As a result of the analysis, dream interpretation data is generated.

[1265] Step 6:

[1266] The server converts the generated dream interpretation results into JSON format and sends them back to the terminal using the interpretation result reply method. The dream interpretation results are sent as an HTTP response. The user terminal receives this data.

[1267] Step 7:

[1268] The system analyzes the dream interpretation received by the user's device and displays it on the interface. The interpretation includes a detailed analysis based on the dream's content and emotions. The user reviews the interpretation on the screen and enters any additional questions.

[1269] Step 8:

[1270] The user enters an additional question, and the device sends that data to the server again. Similarly, the question data is sent using an HTTP POST request, and the server receives it.

[1271] Step 9:

[1272] The server uses an additional questioning mechanism to analyze the additional questions and generates new interpretation results through the AI ​​model analysis mechanism. This new data is then sent back to the terminal through the interpretation result reply mechanism.

[1273] Step 10:

[1274] The user's terminal receives the new interpretation results and displays them again on the interface. This allows the user to gain deeper insights.

[1275] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1276] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1277] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1278] [Fourth Embodiment]

[1279] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1280] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1281] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1282] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1283] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1284] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1285] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1286] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1287] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1288] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1289] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1290] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1291] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1292] The present invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. This system includes user input means, input data transmission means, natural language processing means, generation AI model analysis means, interpretation result reply means, interpretation result display means, and additional question means.

[1293] 1. System Overview

[1294] User input means

[1295] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications.

[1296] Input data transmission means

[1297] The data entered by the user (the content and emotions of the dream) is sent to the server via the internet. This transmission typically uses an HTTP POST request.

[1298] Natural language processing means

[1299] The text data received by the server is analyzed using natural language processing techniques. In this step, the text data is converted into structured data, and semantic analysis is performed.

[1300] Generative AI Model Analysis Method

[1301] The naturally processed data is fed into a generative AI model. Specifically, this generative AI model uses a deep learning model to generate dream interpretations based on this data.

[1302] Means of responding to interpretation results

[1303] The dream interpretation results generated by the generative AI model are sent back from the server to the user's terminal. This reply is usually sent as an HTTP response.

[1304] Means for displaying interpretation results

[1305] The user's terminal displays the dream interpretation results received from the server on the screen. This allows the user to confirm the dream interpretation.

[1306] Additional questioning methods

[1307] If the user requests a more detailed interpretation, they can enter additional questions. These additional questions are sent back to the server, and the process described above is repeated to generate a new interpretation, which is then sent back to the user.

[1308] 2. Specific Examples

[1309] Consider an example where a user enters information about a dream they had last night. The user enters the dream content as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. When the user presses the submit button, this data is sent to the server.

[1310] The server receives the input data and analyzes it using natural language processing. The analyzed data is then analyzed by a generative AI model, which generates the following interpretation of the dream: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1311] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[1312] The following describes the processing flow.

[1313] Step 1:

[1314] User: Enter the content of your dream and the emotions associated with it into the application's input form as text. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1315] Step 2:

[1316] Terminal: When the user presses the submit button, the entered dream content and emotions are converted into JSON data and sent to the server as an HTTP POST request.

[1317] Step 3:

[1318] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes the content and emotions of the dream.

[1319] Step 4:

[1320] Server: The received dream content and emotions are passed to a natural language processing system for text data analysis. This analysis converts the text data into structured data and then analyzes its meaning.

[1321] Step 5:

[1322] Server: Inputs naturally language processed data into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform complex text analysis and pattern recognition.

[1323] Step 6:

[1324] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[1325] Step 7:

[1326] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[1327] Step 8:

[1328] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1329] Step 9:

[1330] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[1331] Step 10:

[1332] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[1333] Step 11:

[1334] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[1335] Step 12:

[1336] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[1337] Step 13:

[1338] Terminal: Displays the new interpretation results in the user interface.

[1339] Step 14:

[1340] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[1341] (Example 1)

[1342] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1343] In modern society, users often seek to interpret the content and emotions of their dreams to deepen their self-understanding. However, traditional dream interpretation methods are subjective, making it difficult to obtain consistent interpretations. Furthermore, when users ask additional questions, they have to re-enter information, hindering quick responses. New technologies and systems are needed to solve these problems.

[1344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1345] In this invention, the server includes means for the user to input the content and emotions of their dream in text format, means for transmitting the input data to the server via the internet, natural language processing means for analyzing the text data received by the server, generative AI model analysis means for generating a dream interpretation based on the naturally language processed data, means for returning the generated dream interpretation result to the user terminal, means for the user terminal to display the dream interpretation result, and means for the user to input additional questions to request a more detailed interpretation. This enables the user to quickly obtain a consistent dream interpretation and to appropriately respond to additional questions.

[1346] "Input method" refers to the interface of a device or application that allows a user to input the content and emotions of their dreams in text format.

[1347] "Transmission means" refers to the mechanism for sending input data to a server via the internet.

[1348] "Natural language processing means" refers to the technologies and processes used by a server to analyze text data received and convert it into structured data.

[1349] "Generative AI model analysis means" refers to a system that uses a deep learning algorithm to generate dream interpretations based on data structured using natural language processing.

[1350] "Reply method" refers to the process of sending the generated dream interpretation results to the user's device.

[1351] "Display means" refers to devices or software that allow a user terminal to display the dream interpretation results received from the server on a screen.

[1352] "Additional questioning mechanism" refers to a mechanism for users to input additional questions to request further detailed interpretations and send those questions to the server.

[1353] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain a dream interpretation result. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. Specifically, the invention is implemented as follows.

[1354] User input means

[1355] Users input the content and feelings of their dreams in text format using a smartphone or computer application. For example, a user might type "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application's interface and select "happy" as their emotion.

[1356] Input data transmission means

[1357] The data entered by the user (the content and emotions of the dream) is sent to the server over the internet using an HTTP POST request. When the user presses the submit button, this data is sent to the server. For example, the payload of the HTTP request includes {"dream": "Last night I dreamt I was swimming with dolphins in a big ocean. I felt very happy", "emotion": "happy"}.

[1358] Natural language processing means

[1359] The server passes the received text data to a natural language processing module, which analyzes the text data and converts it into structured data. In this step, the text data is semantically analyzed, and keywords and emotions are extracted. For example, keywords such as "sea," "dolphin," and "swimming," and the emotion "happiness" are recognized.

[1360] Generative AI Model Analysis Method

[1361] The structured data, processed using natural language processing, is fed into a generative AI model. This model employs deep learning algorithms to generate dream interpretations based on the input data. For example, it might generate an interpretation such as, "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1362] Means of responding to interpretation results

[1363] The generated dream interpretation is sent from the server to the user's terminal as an HTTP response. The server compiles the analysis results and sends them to the user. For example, the server includes the interpretation {"interpretation": "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."} in the payload of the HTTP response.

[1364] Means for displaying interpretation results

[1365] The user terminal parses the dream interpretation received from the server and displays it on the user interface. For example, the screen might display an interpretation such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1366] Additional questioning methods

[1367] If the user requests a more detailed interpretation, they can enter additional questions through the interface. For example, if the user enters "I want to know how this dream will affect my future" and presses the submit button, an HTTP POST request containing the additional question will be sent back to the server.

[1368] The server receives the additional question, interprets it again through the natural language processing module, and generates a new interpretation using a generative AI model. The new interpretation is then sent back to the user. For example, the interpretation "In the future, you may have a higher chance of forming strong bonds with new people" is generated and sent back to the user.

[1369] Example of a prompt

[1370] Examples of prompts a user might enter into the system include questions like, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy. What does this dream mean?" or, "Please tell me how this dream will affect my future."

[1371] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1372] Step 1:

[1373] The user enters the content and emotions of their dream.

[1374] Input: Users use a smartphone or computer application to input the content and emotions of their dreams in text format.

[1375] Operation: The user enters "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy" into the application interface and selects "Happy" as the emotion.

[1376] Output: Text data entered in the input field.

[1377] Step 2:

[1378] The terminal sends the input data to the server.

[1379] Input: Text data of the dream content and emotions entered by the user in Step 1.

[1380] Action: The terminal creates an HTTP POST request and sends a payload containing the entered data to the server. This action is triggered when the user presses the submit button.

[1381] Output: The HTTP request payload ({"dream": "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy", "emotion": "happy"}) is sent to the server.

[1382] Step 3:

[1383] The server analyzes the received data using a natural language processing module.

[1384] Input: Text data received by the server in Step 2.

[1385] Operation: The server passes the received data to the natural language processing module. The natural language processing module analyzes the text data and converts it into structured data. This analysis includes semantic analysis and keyword extraction.

[1386] Output: Natural language processed structured data (e.g., keywords "sea", "dolphin", "swim", emotion "happy").

[1387] Step 4:

[1388] The server generates dream interpretations using a generative AI model.

[1389] Input: Structured data obtained in Step 3.

[1390] Operation: Natural language processed data is fed to a generative AI model. The generative AI model uses a deep learning algorithm to generate dream interpretations. This process outputs dream interpretations based on the analysis results.

[1391] Output: The generated dream interpretation (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[1392] Step 5:

[1393] The server returns the interpretation result to the user's terminal.

[1394] Input: The dream interpretation result generated in Step 4.

[1395] Operation: The server sends the generated interpretation results to the user's terminal in the form of an HTTP response.

[1396] Output: The HTTP response payload ({"interpretation": "Dreaming of swimming with dolphins in the sea symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that the user is satisfied with their current life."}) reaches the user's terminal.

[1397] Step 6:

[1398] The terminal displays the interpretation result.

[1399] Input: Interpretation result received from the server in Step 5.

[1400] Operation: The device parses the interpretation of the received dream and displays it in the user interface.

[1401] Output: The dream interpretation results displayed on the screen (Example: "A dream of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life.")

[1402] Step 7:

[1403] The user enters and submits additional questions.

[1404] Input: Data entered by the user in the input field for additional questions.

[1405] Operation: The user enters an additional question, such as "I want to know how this dream will affect my future," and presses the submit button. The device then sends an HTTP POST request to the server containing this additional data.

[1406] Output: The HTTP request payload ({"question": "I want to know how this dream will affect my future"}) is sent to the server.

[1407] Step 8:

[1408] The server performs the analysis again, generates a new interpretation, and sends it back.

[1409] Input: Text data of the additional questions received by the server in Step 7.

[1410] Operation: The server receives additional questions, structures them again through the natural language processing module, and inputs them into the generative AI model. The generative AI model generates a new interpretation and sends it to the user's terminal as an HTTP response.

[1411] Output: A new interpretation (e.g., "In the future, you may have a higher chance of forming strong bonds with new people") reaches the user's terminal.

[1412] (Application Example 1)

[1413] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1414] Traditional conversational systems primarily provided static interpretations of user input, which limited their ability to deliver personalized services. Furthermore, they lacked the means to reflect customers' psychological states and emotions in real time and provide useful information to store staff. Therefore, there was a growing need for a system that could provide information more tailored to individual customer needs in real time, thereby improving the customer experience.

[1415] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1416] In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means. This enables the analysis of customers' dreams and emotions, the presentation of the analysis results to store staff in real time, and more personalized customer service and product suggestions.

[1417] A "user input device" is a device or interface for a user to input the content and emotions of their dreams in text format.

[1418] "Input data transmission means" refers to a means for sending data entered by a user to a server.

[1419] A "natural language processing system" is a mechanism that analyzes text data received by a server and converts it into structured data.

[1420] The "generative AI model analysis method" is a means of supplying naturally language processed data to a deep learning model to generate dream interpretations.

[1421] The "interpretation result reply method" is a means of sending the generated dream interpretation results from the server to the user's terminal.

[1422] The "interpretation result display means" is a mechanism that displays the dream interpretation results received from the server on the user's terminal.

[1423] An "additional questioning mechanism" is a means for users to input and submit additional questions to seek further detailed interpretations.

[1424] A "customer input method" refers to a device or interface that allows customers to provide the content and emotions of their dreams through voice or text input.

[1425] "Customer data transmission means" refers to a means of sending data entered by a customer to a server.

[1426] A "customer analysis tool" is a system that analyzes data entered by customers and converts it into structured data.

[1427] "Staff presentation tools" refer to devices or interfaces that display information to enable store staff to make appropriate suggestions to customers based on analyzed data.

[1428] The system for realizing this invention consists of the following means: a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, an additional question means, a customer input means, a customer data transmission means, a customer analysis means, and a staff presentation means.

[1429] System Configuration

[1430] 1. User input means

[1431] Users input the content of their dreams and related emotions using smart glasses or a smartphone. This is done via voice recognition or text input.

[1432] 2. Input data transmission means

[1433] The data entered by the user is sent from smart glasses or a smartphone to a backend server via the internet. This transmission is primarily done using HTTP POST requests.

[1434] 3. Natural Language Processing Means

[1435] The server analyzes the received text data using natural language processing technologies (e.g., Google Cloud Natural Language, Microsoft Azure Cognitive Services) and converts it into structured data.

[1436] 4. Generative AI Model Analysis Method

[1437] The naturally processed data is fed into a generative AI model (e.g., OpenAI GPT-4) to generate dream interpretation results.

[1438] 5. Means of responding to interpretation results

[1439] The dream interpretation results generated by the generative AI model are sent back to the user's terminal from the server as an HTTP response.

[1440] 6. Means for displaying interpretation results

[1441] The user's device displays the interpretation results received from the server on the screen of smart glasses or a smartphone. This allows the user to check the interpretation of their dream.

[1442] 7. Additional questioning methods

[1443] If the user requests a more detailed interpretation, they can enter additional questions via voice or text. These questions are sent back to the server, and a new interpretation is generated using the same procedure.

[1444] 8. Customer Input Methods

[1445] Customers input the content and emotions of their dreams through smart glasses within the store, using either voice recognition or text input.

[1446] 9. Means for transmitting customer data

[1447] The data entered by the customer is sent from the smart glasses to the server via the internet. It is sent using an HTTP POST request.

[1448] 10. Customer analysis methods

[1449] The server analyzes the data entered by the customer using natural language processing technology and converts it into structured data.

[1450] 11. Staff presentation methods

[1451] The analyzed data is displayed on smart glasses worn by store staff, allowing them to suggest suitable products and services to customers in real time.

[1452] Specific example

[1453] When a customer inputs, "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it was happiness. What does this mean?", this data is analyzed through a series of steps. The generating AI model analysis method produces the interpretation that "Dreaming of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life."

[1454] This interpretation is displayed on the store staff's smart glasses, allowing them to suggest to customers, "It seems you are looking for freedom and adventure. We can recommend relevant ocean-related products and adventure tours."

[1455] This allows customers to receive personalized service tailored to their mental state, leading to increased satisfaction. Additionally, staff can respond to customers more effectively.

[1456] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1457] Step 1:

[1458] The user inputs the content and emotions of their dream using smart glasses or a smartphone. The user input method collects data through voice recognition or text input and converts the entered data into text format. For example, the input received is: "Last night I dreamt I was swimming with dolphins in a vast ocean. The emotion associated with it is happiness."

[1459] Step 2:

[1460] The input data transmission method sends the text data entered by the user to the server via the internet. An HTTP POST request is used to send the converted text data to the server. The input is the data collected in the previous step, and the output is the data sent to the server.

[1461] Step 3:

[1462] The server analyzes the received text data using natural language processing tools and converts it into structured data. This process utilizes natural language processing technologies such as Google Cloud Natural Language and Microsoft Azure Cognitive Services. The input is text data, and the output is structured data.

[1463] Step 4:

[1464] The generative AI model analysis method generates dream interpretation results using structured data. It uses OpenAI's GPT-4 as the generative AI model to generate interpretations based on the data. The input is naturally language processed structured data, and the output is the dream interpretation result.

[1465] Step 5:

[1466] The interpretation result return mechanism sends the generated dream interpretation result back to the user terminal from the server as an HTTP response. The input is the generated dream interpretation result, and the output is the data sent to the user terminal.

[1467] Step 6:

[1468] The user's terminal receives dream interpretation results from the server and displays them on smart glasses or a smartphone screen via an interpretation result display device. The input is the interpretation result data from the server, and the output is the screen display that the user can check.

[1469] Step 7:

[1470] If the user requests further interpretation, they can enter additional questions through an additional questioning mechanism. These additional questions are accepted via voice or text and sent back to the server. The input is the user's additional question, and the output is the additional question data sent to the server.

[1471] Step 8:

[1472] Customers input the content and emotions of their dreams using smart glasses, employing either voice recognition or text input. Data is collected via the customer's input method and converted into text format. Input is the customer's voice or text, and output is the converted text data.

[1473] Step 9:

[1474] The customer data transmission method sends the entered data to the server. Similar to the input data transmission method, it uses an HTTP POST request to send the data. The input is the converted text data, and the output is the data sent to the server.

[1475] Step 10:

[1476] The server analyzes the data received from the customer using natural language processing and converts it into structured data. This step is the same as in step 3. The input is the customer's text data, and the output is structured data.

[1477] Step 11:

[1478] The customer analysis system generates dream interpretation results based on an AI model and displays them on the smart glasses of store staff via a staff presentation system. This information allows staff to suggest suitable products and services to customers. The input is the analyzed data, and the output is the display data for staff.

[1479] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1480] This invention is an interactive system for users to input the content and emotions of their dreams, analyze them, and obtain dream interpretation results. Furthermore, it incorporates an emotion engine that automatically recognizes the user's emotions, improving the accuracy and personalization of the interpretation. The system includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion engine means, an interpretation result reply means, an interpretation result display means, and an additional question means.

[1481] 1. System Overview

[1482] User input means

[1483] Users input the content of their dreams and the emotions associated with them in text format. This is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided.

[1484] Emotional Engine Means

[1485] The system automatically detects emotions based on text data entered by the user, voice input, and facial recognition data. For example, text analysis uses natural language processing technology to infer emotions from the tone and content of the entered words. Voice analysis uses voice tone and pitch to detect emotions, and facial recognition determines emotions from facial expressions.

[1486] Input data transmission means

[1487] The system sends information such as the content of the dream entered by the user and the detected emotion data to the server. This transmission typically uses an HTTP POST request.

[1488] Natural language processing means

[1489] The server analyzes the received text data. During the analysis, the text data is converted into structured data, which is then combined with sentiment data from the sentiment engine for a more detailed analysis.

[1490] Generative AI Model Analysis Method

[1491] Natural language processing data and emotion engine data are input into a generative AI model. Specifically, the generative AI model uses a deep learning model to generate dream interpretations by combining complex text analysis with emotion data.

[1492] Means of responding to interpretation results

[1493] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response.

[1494] Means for displaying interpretation results

[1495] The user's terminal receives an HTTP response from the server and analyzes the dream interpretation results. The analysis results are displayed on the user interface. The interpretation results include a detailed analysis based on the dream's content and emotions.

[1496] Additional questioning methods

[1497] If a user requests a more detailed interpretation, they can enter additional questions. These additional questions are also analyzed by the sentiment engine and sent to the server.

[1498] 2. Specific Examples

[1499] Consider an example where a user inputs information about a dream they had last night. The user inputs the dream's content as text: "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also used, with the user speaking in a quiet tone.

[1500] When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is then processed through a generative AI model to generate an interpretation of the dream, such as "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1501] The interpretation result is sent back from the server to the user's terminal, where the user can view the result on the screen. If the user enters an additional question, such as "I want to know how this dream will affect my future," and submits it again, a new interpretation result is generated by the generative AI model analysis method and sent back to the user in the form of "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[1502] The following describes the processing flow.

[1503] Step 1:

[1504] User: The user enters the content of their dream and the associated feelings into the application's input form in text format. For example, they might enter, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1505] Step 2:

[1506] Terminal: While waiting for the user to press the button to send the dream content and emotions, it collects additional emotion data such as voice input and facial recognition data.

[1507] Step 3:

[1508] Terminal: When the user presses the send button, the entered dream content and emotions, along with collected voice input and facial recognition data, are converted into JSON format data and sent to the server as an HTTP POST request.

[1509] Step 4:

[1510] Server: The server receives the incoming HTTP POST request and parses the sent JSON data. The data includes dream content, emotions, voice input, and facial recognition data.

[1511] Step 5:

[1512] Server: Passes received dream content and emotion data, voice input, and facial recognition data to natural language processing and emotion engines, which then analyze the text data. In this analysis, the text data is converted into structured data, and emotions are inferred from the voice and facial expression data.

[1513] Step 6:

[1514] Server: Inputs analysis data obtained from natural language processing and emotion engines into a generative AI model to generate dream interpretations. The generative AI model utilizes deep learning to perform detailed analysis combining text and emotion data.

[1515] Step 7:

[1516] Server: The server converts the dream interpretation results generated by the generative AI model back into JSON format and sends them back to the user's terminal as an HTTP response.

[1517] Step 8:

[1518] Terminal: The user terminal receives HTTP responses from the server and parses the results. The parsing results are displayed on the user interface.

[1519] Step 9:

[1520] User: View the dream interpretation results returned from the server. For example, the user checks the interpretation result: "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1521] Step 10:

[1522] User: If you would like a more detailed interpretation, enter an additional question. For example, enter "I would like to know how this dream will affect my future" and press the submit button again.

[1523] Step 11:

[1524] Terminal: Converts the data, including the additional questions, back into JSON format and sends it to the server.

[1525] Step 12:

[1526] Server: The server analyzes the received data again and generates new interpretation results using natural language processing tools and generative AI models.

[1527] Step 13:

[1528] Server: Converts the new interpretation result into JSON format and sends it back to the user's terminal as an HTTP response.

[1529] Step 14:

[1530] Terminal: Displays the new interpretation results in the user interface.

[1531] Step 15:

[1532] User: Check the interpretation of the additional question. In the specific example, the interpretation is "In the future, you may be more likely to form strong bonds with new people."

[1533] (Example 2)

[1534] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1535] While systems currently exist that analyze dream content and associated emotions to provide detailed, individualized interpretations, their accuracy and personalization capabilities are limited. Furthermore, they do not adequately address users' desires for further details based on dream analysis results. This invention aims to solve these problems.

[1536] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the content and emotions of the user's dream, means for transmitting the input data to the server, and means for analyzing the data received by the server using natural language processing technology. This makes it possible to automatically generate and send back a highly accurate dream interpretation based on the dream content and emotion data provided by the user.

[1537] "Means for inputting the content and emotions of a user's dreams" refers to a device or application for a user to input information about their dreams as text, voice, or facial recognition data.

[1538] "Means of sending input data to the server" refers to a communication protocol (e.g., HTTP POST request) used to send data entered by a user to a server via the internet.

[1539] "Means for analyzing data received by a server using natural language processing techniques" refers to the techniques and tools (e.g., natural language processing tools) used by a server to analyze text data received and convert it into structured data.

[1540] "Means for inputting naturally language processed data and sentiment data into a generative AI model" refers to a processing method for inputting structured text data and sentiment data into a generative AI model (e.g., a deep learning model) for analysis.

[1541] "Means for sending the generated dream interpretation results back to the user's terminal" refers to a communication protocol (e.g., HTTP response) for converting the dream interpretation results generated by the generation AI model into JSON format and sending them to the user's terminal via the internet.

[1542] "Means for a user terminal to display interpretation results" refers to software and hardware for a user's terminal (e.g., smartphone, personal computer) to display the interpretation results it has received on a user interface.

[1543] "Means for receiving additional user questions" refers to a device or application that allows a user to input additional questions seeking further details regarding an interpretation result and to send them to the server.

[1544] This system allows users to input the content and emotions of their dreams, which are then analyzed to obtain a dream interpretation. The system includes the following methods:

[1545] User input means

[1546] Users input the content of their dreams and the emotions associated with them in text format. This input is primarily done through smartphone or computer applications. Additional input methods such as voice input and facial recognition are also provided. For example, a user might input, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1547] Emotional Engine Means

[1548] The system automatically detects emotions based on user-entered text data, voice input, and facial recognition data. The emotion engine uses natural language processing techniques (e.g., Google Cloud Natural Language API) for text analysis, voice tone and pitch for voice analysis, and facial expressions for facial recognition to determine emotions. For example, it can detect the emotion "happiness" from entered text.

[1549] Input data transmission means

[1550] The user enters dream content and emotional data, which is then sent to the server. This transmission typically uses an HTTP POST request. When the user presses the submit button, this data is sent to the server.

[1551] Natural language processing means

[1552] The server analyzes the received text data. This analysis uses natural language processing tools (e.g., Google Cloud Natural Language API) to convert the text data into structured data. Furthermore, sentiment data from the sentiment engine is also used for a more detailed analysis.

[1553] Generative AI Model Analysis Method

[1554] The server inputs naturally processed data and emotion engine data into a generative AI model (e.g., OpenAI GPT-3). This generative AI model uses deep learning to generate dream interpretations by combining complex text analysis with emotion data.

[1555] Means of responding to interpretation results

[1556] The dream interpretation results generated by the generative AI model are converted back into JSON format and sent back to the user's terminal as an HTTP response. The dream interpretation results generated by the server include statements such as, "A dream of swimming with dolphins in the sea signifies freedom, adventure, and protection. The addition of happy feelings suggests that you are satisfied with your current life."

[1557] Means for displaying interpretation results

[1558] The user's device analyzes the HTTP response received from the server and displays the dream interpretation results on the user interface. Users can check the interpretation results on the screen of a smartphone or computer application.

[1559] Additional questioning methods

[1560] If the user wants a more detailed interpretation, they can enter an additional question in text. For example, they might type, "I want to know how this dream will affect my future," and submit it again. The server receives this additional question and generates a new interpretation through its generative AI model. The result of this re-analysis might be, "In the future, you may have a higher chance of forming strong bonds with new people."

[1561] Specific example

[1562] Let's say a user types the text, "Last night I dreamt I was swimming with dolphins in the ocean. I felt very happy," and selects "happy" as the emotion. They also use voice input, speaking in a quiet tone. When the user presses the send button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and an emotion engine. The analyzed data is processed by a generative AI model, which generates an interpretation of the dream: "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The added feeling of happiness suggests that you are satisfied with your current life." The interpretation result is sent back to the user's device, and the user checks the result on the screen. If the user then types an additional question, "I want to know how this dream will affect my future," and sends it again, the generative AI model analyzer generates a new interpretation result, which is sent back to the user in the form of, "In the future, you may have a higher chance of forming strong bonds with new people." This allows the user to gain deeper insights.

[1563] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1564] Step 1:

[1565] The user enters the content and emotions of their dream.

[1566] Input: The user enters the content and feelings of their dream using text, voice, or facial recognition data. For example, "Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy."

[1567] Output: Content and emotional data of the entered dream.

[1568] Specific operation: Users use smartphone or computer applications to input details and emotions about their dreams using various input methods.

[1569] Step 2:

[1570] Send the input data to the server.

[1571] Input: Text, voice, and facial recognition data entered by the user through an input method.

[1572] Output: Dream content and emotional data sent to the server.

[1573] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[1574] Step 3:

[1575] The server receives the data and performs natural language processing.

[1576] Input: Dream content and emotional data received by the server.

[1577] Output: Natural language processed structured data.

[1578] Specific operation: The server uses a natural language processing tool (e.g., Google Cloud Natural Language API) to analyze the received text data and convert it into structured data.

[1579] Step 4:

[1580] The server analyzes the emotional data.

[1581] Input: Received data and naturally language processed structured data.

[1582] Output: Data on which emotions were detected.

[1583] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to automatically detect emotions based on text, voice, and facial recognition data.

[1584] Step 5:

[1585] Natural language processing data and sentiment data are input into a generating AI model.

[1586] Input: Natural language processed text data and sentiment data.

[1587] Output: Analysis data input to the generating AI model.

[1588] Specific operation: The server inputs structured text data and sentiment data into a generating AI model (e.g., OpenAI GPT-3).

[1589] Step 6:

[1590] The generative AI model generates interpretations of dreams.

[1591] Input: Data entered into the generative AI model.

[1592] Output: Dream interpretation result.

[1593] Specific operation: The generative AI model combines complex text analysis and emotional data to generate dream interpretations. For example, it might output an analysis result such as, "A dream of swimming with dolphins in the ocean signifies freedom, adventure, and protection."

[1594] Step 7:

[1595] The server returns the interpretation result to the user's terminal.

[1596] Input: Dream interpretation results generated by a generative AI model.

[1597] Output: Interpretation result returned to the user terminal.

[1598] Specific operation: The server converts the generated dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[1599] Step 8:

[1600] The terminal displays the interpretation result.

[1601] Input: Interpretation result received from the server.

[1602] Output: The dream interpretation results displayed in the user interface.

[1603] Specific operation: The system analyzes the HTTP response received by the user's device and displays the dream interpretation results on a smartphone or PC application.

[1604] Step 9:

[1605] The user enters additional questions.

[1606] Input: Enter questions based on the additional information the user wants to know.

[1607] Output: Additional question data.

[1608] Specific action: The user enters an additional question in text, for example, "I want to know how this dream will affect my future," and presses the submit button.

[1609] Step 10:

[1610] Send additional question data to the server.

[1611] Input: Additional questions entered by the user.

[1612] Output: Additional question data sent to the server.

[1613] Specific operation: The user presses the submit button, and the data is sent to the server via an HTTP POST request.

[1614] Step 11:

[1615] The server will analyze the additional questions.

[1616] Input: Additional question data received.

[1617] Output: Additional question data processed using natural language processing.

[1618] Specific operation: The server uses natural language processing tools to analyze the additional question data and convert it into structured data.

[1619] Step 12:

[1620] The generative AI model generates additional interpretation results.

[1621] Input: Additional question data processed using natural language.

[1622] Output: Additional interpretation results.

[1623] Specific operation: The generative AI model generates an interpretation of the additional question. For example, it might generate a result such as, "In the future, you may be more likely to form strong bonds with new people."

[1624] Step 13:

[1625] The server sends additional interpretation results back to the user's terminal.

[1626] Input: Additional interpretation results generated by the generative AI model.

[1627] Output: Additional interpretation results sent back to the user's terminal.

[1628] Specific operation: The server converts the generated additional dream interpretation results into JSON format and sends them to the user's terminal as an HTTP response.

[1629] Step 14:

[1630] The device displays additional interpretation results.

[1631] Input: Additional interpretation results received from the server.

[1632] Output: Additional interpretation results displayed in the user interface.

[1633] Specific operation: The system analyzes the HTTP response received by the user's device and displays additional dream interpretation results on the smartphone or PC application.

[1634] (Application Example 2)

[1635] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1636] Conventional dream analysis systems have low accuracy in generating interpretations based on the content and emotions of dreams entered by the user, and lack personalization. Furthermore, they have not made efforts to improve the user experience using head-mounted displays, smartphones, etc. This invention aims to solve these problems and provide users with accurate and personalized dream interpretations.

[1637] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an emotion recognition means, an interpretation result reply means, an interpretation result display means, an additional question means, and a means for recognizing the user's emotions through a head-mounted display or smartphone. This makes it possible to accurately analyze the content and emotions of the user's dreams and provide personalized dream interpretation results in real time.

[1638] A "user input method" is an interface for users to input the content of their dreams and the emotions associated with them.

[1639] The "input data transmission means" is a means of sending the content and emotional data of the dream entered by the user to the server.

[1640] "Natural language processing means" refers to technical means that analyze text data received by a server and convert it into structured data.

[1641] The "generative AI model analysis method" is a method for interpreting dreams using a generative AI model based on naturally processed data and emotional data.

[1642] "Emotion recognition means" refers to a method that analyzes text data entered by the user, as well as voice and facial recognition data, to automatically detect the user's emotions.

[1643] The "interpretation result return means" is a means of returning the dream interpretation results generated by the generation AI model analysis means to the user's terminal.

[1644] The "interpretation result display means" is a means of analyzing the dream interpretation results received by the user terminal and displaying them on the interface.

[1645] An "additional questioning method" is a means by which a user enters additional questions to request a more detailed interpretation and sends those questions to the server.

[1646] A "head-mounted display" is a device that a user wears and uses as an interface for virtual reality or augmented reality.

[1647] A "smartphone" is a multi-functional mobile device capable of making calls, browsing the internet, and running applications.

[1648] This invention is an interactive system for analyzing the content of a user's dreams and the emotions experienced during those dreams, and providing a dream interpretation. The system includes a user input means, an emotion recognition means, an input data transmission means, a natural language processing means, a generation AI model analysis means, an interpretation result reply means, an interpretation result display means, and an additional question means. It also includes means for recognizing the user's emotions using a head-mounted display (HMD) or a smartphone.

[1649] Hardware and software configuration

[1650] User input means

[1651] User input means are interfaces for users to input the content and emotions of their dreams. This is provided via smartphones or head-mounted displays. Methods include text input, voice input, and facial recognition.

[1652] emotion recognition means

[1653] Emotion recognition is a method that automatically detects emotions by analyzing text data, voice, and facial recognition data entered by the user. This analysis utilizes natural language processing and speech analysis technologies. Specifically, it uses general natural language processing libraries (e.g., NLTK) and speech analysis libraries.

[1654] Input data transmission means

[1655] The input data transmission method is a means for sending the content and emotional data of dreams entered by the user to the server. The data is sent using an HTTP POST request.

[1656] Natural language processing means

[1657] Natural language processing (NLP) is a technique that analyzes text data received by a server and converts it into structured data. This analysis is performed using natural language processing libraries and APIs.

[1658] Generative AI Model Analysis Method

[1659] The generative AI model analysis method involves inputting naturally processed data and emotional data into a generative AI model to interpret dreams. This generative AI model utilizes deep learning models or large-scale language models (e.g., OpenAI APIs).

[1660] Means of responding to interpretation results

[1661] The interpretation result return method is a means of returning the dream interpretation result generated by the generation AI model analysis method to the user's terminal. This data is transmitted in JSON format.

[1662] Means for displaying interpretation results

[1663] The interpretation result display means analyzes the dream interpretation results received by the user terminal and displays them on the user interface. A smartphone screen or a head-mounted display visual interface is used for the display.

[1664] Additional questioning methods

[1665] The additional questioning feature allows users to request a more detailed interpretation of their dreams. Users enter additional questions and send them to the server. Based on this additional information, the AI ​​model is re-analyzed, and a new interpretation is generated.

[1666] Specific example

[1667] The user enters text describing their dream, such as, "Last night, I dreamt I was swimming with dolphins in a vast ocean. I felt very happy," and specifies "happy" as the emotion. Voice input is also available, spoken in a quiet tone. When the user presses the submit button, this data is sent to the server. The server receives the input data and analyzes it using natural language processing and emotion recognition tools. The analyzed data is then processed by a generative AI model to generate an interpretation of the dream, such as, "Dreaming of swimming with dolphins in the ocean symbolizes freedom, adventure, and protection. The addition of a happy emotion suggests that you are satisfied with your current life." This interpretation is then sent back from the server to the user's terminal, where the user can view the result on the screen.

[1668] Example of a prompt

[1669] The following are examples of input prompts for a generative AI model.

[1670] Here is the content of the dream: Last night I dreamt I was swimming with dolphins in a vast ocean. I felt very happy.

[1671] The emotion associated with this dream is: happiness

[1672] Please interpret this dream.

[1673] This allows the system to analyze the content and emotions of the user's dreams and provide accurate and personalized dream interpretations.

[1674] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1675] Step 1:

[1676] The user inputs the content and emotions of their dream. Text input, voice input, and facial recognition data are acquired using a smartphone or head-mounted display. The input data includes dream details and associated emotions. The entered data is collected and passed on to the next processing step.

[1677] Step 2:

[1678] The device sends input data to the server using an HTTP POST request. This data includes the content of the dream entered by the user, audio data, facial recognition data, and emotional information. The server receives this data and prepares it for analysis.

[1679] Step 3:

[1680] The server analyzes the received text data using natural language processing tools. Specifically, it tokenizes the text data using a natural language processing library (e.g., NLTK) and converts it into structured data. This structured data is then generated, and the process proceeds to the next step.

[1681] Step 4:

[1682] The server uses emotion recognition capabilities to analyze the user's emotions from the input voice data and facial recognition data. This involves using a voice analysis library to estimate emotions based on tone and pitch. Additionally, a facial recognition algorithm is used to determine emotions from facial expressions. Detected emotion data is then generated.

[1683] Step 5:

[1684] The server inputs naturally processed data and emotional data into a generating AI model analysis system. A large-scale language model (e.g., OpenAI API) is used in the generating AI model to interpret the user's dreams. As a result of the analysis, dream interpretation data is generated.

[1685] Step 6:

[1686] The server converts the generated dream interpretation results into JSON format and sends them back to the terminal using the interpretation result reply method. The dream interpretation results are sent as an HTTP response. The user terminal receives this data.

[1687] Step 7:

[1688] The system analyzes the dream interpretation received by the user's device and displays it on the interface. The interpretation includes a detailed analysis based on the dream's content and emotions. The user reviews the interpretation on the screen and enters any additional questions.

[1689] Step 8:

[1690] The user enters an additional question, and the device sends that data to the server again. Similarly, the question data is sent using an HTTP POST request, and the server receives it.

[1691] Step 9:

[1692] The server uses an additional questioning mechanism to analyze the additional questions and generates new interpretation results through the AI ​​model analysis mechanism. This new data is then sent back to the terminal through the interpretation result reply mechanism.

[1693] Step 10:

[1694] The user's terminal receives the new interpretation results and displays them again on the interface. This allows the user to gain deeper insights.

[1695] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1696] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1697] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1698] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1699] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1700] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1701] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1702] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1703] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1704] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1705] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1706] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1707] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1708] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1709] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1710] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1711] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1712] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1713] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1714] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1715] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1716] The following is further disclosed regarding the embodiments described above.

[1717] (Claim 1)

[1718] User input means,

[1719] Input data transmission means,

[1720] Natural language processing means,

[1721] Generative AI model analysis means,

[1722] Means of responding to interpretation results,

[1723] Means for displaying interpretation results,

[1724] A system that includes means for asking additional questions.

[1725] (Claim 2)

[1726] The system according to claim 1, wherein the generating AI model analysis means analyzes the content and emotions of the user's dream and generates a dream interpretation result.

[1727] (Claim 3)

[1728] The system according to claim 1, wherein an additional questioning means receives additional questions from the user, generates additional interpretation results again through a regenerating AI model analysis means, and returns them to the user.

[1729] "Example 1"

[1730] (Claim 1)

[1731] An input method in which the user enters the content and emotions of their dream in text format,

[1732] A transmission means for sending input data to a server via the internet,

[1733] A natural language processing means that analyzes text data received by the server,

[1734] A generative AI model analysis means that generates dream interpretations based on naturally language processed data,

[1735] A means of sending the generated dream interpretation results back to the user's terminal,

[1736] A display means on the user's terminal that displays the results of dream interpretation,

[1737] A system that includes an additional questioning mechanism for users to enter additional questions to request further detailed interpretations.

[1738] (Claim 2)

[1739] The system according to claim 1, wherein the generating AI model analysis means analyzes the content and emotions of the user's dream and generates a dream interpretation result.

[1740] (Claim 3)

[1741] The system according to claim 1, wherein an additional questioning means receives additional questions from the user, generates additional interpretation results again through a regenerating AI model analysis means, and returns them to the user.

[1742] "Application Example 1"

[1743] (Claim 1)

[1744] User input means,

[1745] Input data transmission means,

[1746] Natural language processing means,

[1747] Generative AI model analysis means,

[1748] Means of responding to interpretation results,

[1749] Means for displaying interpretation results,

[1750] Additional questioning methods,

[1751] Customer input method,

[1752] Customer data transmission means and

[1753] Customer analysis methods,

[1754] A system that includes methods for staff to present information.

[1755] (Claim 2)

[1756] The system according to claim 1, wherein the generating AI model analysis means analyzes the content and emotions of the user's dream and generates a dream interpretation result.

[1757] (Claim 3)

[1758] The system according to claim 1, wherein an additional questioning means receives additional questions from the user, generates additional interpretation results again through a regenerating AI model analysis means, and returns them to the user.

[1759] (Claim 4)

[1760] The system according to claim 1, wherein the customer analysis means analyzes customer input data based on the generated AI model analysis means and displays the analysis results on the staff presentation means.

[1761] "Example 2 of combining an emotion engine"

[1762] (Claim 1)

[1763] A means for users to input the content and emotions of their dreams,

[1764] A means of sending input data to a server,

[1765] A means of analyzing data received by a server using natural language processing technology,

[1766] A method for generating dream interpretation results by inputting naturally processed data and emotional data into an AI model,

[1767] A means of returning the generated dream interpretation results to the user's terminal,

[1768] A means for the user terminal to display the interpretation result,

[1769] A system that includes a means of receiving additional questions from users.

[1770] (Claim 2)

[1771] The system according to claim 1, wherein the generating AI model analysis means generates dream interpretation results based on the user's dream content and emotional data.

[1772] (Claim 3)

[1773] The system according to claim 1, wherein an additional questioning means receives additional questions from the user, generates additional interpretation results again through a regenerating AI model analysis means, and returns them to the user.

[1774] "Application example 2 when combining with an emotional engine"

[1775] (Claim 1)

[1776] User input means,

[1777] Input data transmission means,

[1778] Natural language processing means,

[1779] Generative AI model analysis means,

[1780] Means of recognizing emotions,

[1781] Means of responding to interpretation results,

[1782] Means for displaying interpretation results,

[1783] Additional questioning methods,

[1784] A system that includes means of recognizing a user's emotions through a head-mounted display or smartphone.

[1785] (Claim 2)

[1786] The system according to claim 1, wherein the generating AI model analysis means analyzes the content and emotions of the user's dream and generates a dream interpretation result.

[1787] (Claim 3)

[1788] The system according to claim 1, wherein an additional questioning means receives additional questions from the user, generates additional interpretation results again through a regenerating AI model analysis means, and returns them to the user. [Explanation of Symbols]

[1789] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A user input method for users to enter the content and emotions of their dreams in text format, An input data transmission means that sends data entered by the user to a server, A natural language processing means that analyzes text data sent by a user and converts it into structured data, A generative AI model analysis means that generates dream interpretation results using generative AI based on naturally language processed data, A means for returning the interpretation results of the generated dream to the user's device, Interpretation result display means for displaying the interpretation results of dreams received on the user terminal, A system that includes a mechanism for users to input additional questions regarding the interpretation of their dreams, and then re-analyze those questions.

2. The system according to claim 1, wherein the generating AI model analysis means analyzes the content and emotions of the user's dream and generates a dream interpretation result.

3. The system according to claim 1, wherein an additional questioning means receives additional questions from the user, generates additional interpretation results again through the generation AI model analysis means, and returns them to the user.

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