system

Abstract

We provide the system. [Solution] A means for receiving and integrating audio, image, and text data, A means of analyzing data in real time using a generative AI model and generating information that meets user requirements, Means for providing the user with analysis results visually or audibly, A means of integrating with external services to obtain necessary data, A means of personalizing information based on the user's history and preferences, A system that includes this.

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, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The abundance of information in the digital environment, the accompanying burden on users, and the complexity of cooperation between multiple applications and services are factors that hinder users' efficient information acquisition and operation. As a result, there is a problem that users cannot quickly obtain the necessary information and cause digital fatigue.

Means for Solving the Problems

[0005] This invention comprehensively handles diverse user requests by providing means capable of integrating and analyzing voice, image, and text data. This system analyzes data in real time using a generative AI model and generates information tailored to user requests. Furthermore, it seamlessly integrates with external services to acquire necessary data and personalizes information based on user history and preferences, thereby achieving efficient information delivery.

[0006] "Sound" refers to human voices and other sounds, which are signals processed as digital data.

[0007] An "image" is visual data that represents visual information and is converted into a digital format.

[0008] "Text data" refers to linguistic information expressed as characters and recorded in digital format.

[0009] "Integrated analysis" refers to the process of processing multiple data formats in a unified manner and analyzing them in order to understand their interrelationships.

[0010] A "generative AI model" is an artificial intelligence algorithm or model used for data analysis or information generation.

[0011] "Real-time analysis" refers to a process that performs analysis almost instantly with virtually no delay the moment data is received.

[0012] "User requests" refer to the desired information or operations based on the information entered by the user into the system.

[0013] "Generating information" refers to creating new information as a result of data analysis.

[0014] "External services" refer to third-party services that exist outside the system and provide specific functions or information.

[0015] "History" refers to the records of a user's past actions and operations.

[0016] "Preference" refers to the characteristics and tendencies that a user particularly prefers and has a tendency to habitually select.

[0017] "Personalizing information" refers to individually adapting information and services based on the preferences and history of an individual user.

Brief Explanation of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It 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 Example 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.

Embodiment for Implementing the Invention

[0019] 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.

[0020] First, the language used in the following description will be explained.

[0021] 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), and the like.

[0022] 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.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] This invention is a system designed to enhance the user's digital experience through multimodal data processing capabilities. This system enables the integrated analysis of voice, image, and text data to generate information tailored to the user's needs. The following describes embodiments for carrying out this invention.

[0040] The server receives audio, image, and text data provided by the user. For audio data, the terminal converts the audio to text and sends it to the server. The server analyzes the received audio, text, and image data, and uses generative AI models to understand the user's requests. Through this analysis, the server determines what the user wants and retrieves relevant data from external services.

[0041] For example, suppose a user speaks into their device saying, "Show me the coffee maker reviews." The device converts this speech into text and sends it to the server. The server analyzes this text, retrieves relevant coffee maker reviews from an external review service, and generates the most relevant and useful information.

[0042] The generated information is displayed visually to the user via the device. In some cases, the information can be read aloud, making it easily accessible to the user. Furthermore, if the user provides feedback or asks additional questions about specific information, the server re-analyzes the content and provides even more detailed information. The server also manages the user's history and preferences, and the information provided is customized for each user.

[0043] In this way, the system of the present invention enables the rapid understanding of the user's complex requirements and the provision of personalized, practical information.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] When a device receives voice input from a user, it converts that voice into text data. This conversion is usually performed in real time by the device's built-in speech recognition system.

[0047] Step 2:

[0048] The device sends the converted text data to the server. Images and existing text data are also sent in the same manner.

[0049] Step 3:

[0050] The server receives text data sent from the terminal, and simultaneously captures images and other data. It then uses a generative AI model to analyze this data in a unified manner.

[0051] Step 4:

[0052] The server uses a generative AI model to analyze the content of incoming data. It identifies the information and actions the user is seeking and generates analysis results based on those requests.

[0053] Step 5:

[0054] The server will, as needed, interact with external information services and applications to obtain data relevant to the analysis results. For example, if a user is requesting product reviews, it will retrieve the latest reviews of that product from an external service.

[0055] Step 6:

[0056] The server integrates the collected information to generate results that are most relevant to the user. These results are then personalized as needed, based on the user's history and preferences.

[0057] Step 7:

[0058] The server sends the generated results to the terminal. The terminal receives this information and either displays it visually to the user or provides it as audio feedback.

[0059] Step 8:

[0060] The user reviews the provided information and enters any additional requests or feedback into the terminal. Based on this input, the processing loop may be restarted.

[0061] (Example 1)

[0062] 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."

[0063] Despite the need for systems that can respond to diverse user requests in real time and provide personalized information, current technologies are insufficient to meet these demands. Furthermore, integrating and effectively utilizing data across multiple media formats (audio, images, text) remains a challenge. Additionally, personalization based on users' past actions and preferences, while effectively collaborating with external information sources, is still incomplete.

[0064] 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.

[0065] In this invention, the server includes means for receiving input data in the form of audio, images, and text and for integratively analyzing it; means for processing the analyzed data in real time using a generative AI model and generating information tailored to the user's requests; and means for presenting the generated information to the user visually or audibly. This enables a rapid and accurate response to user requests and the provision of personalized information.

[0066] "Audio data" refers to information obtained by converting audio into a digital format, which is represented in a form that can be processed by a computer.

[0067] "Image data" refers to a digital representation of visual information, and is data used to analyze two-dimensional visual information using a computer.

[0068] "Text data" refers to information composed of characters and symbols, represented in a digital format, and is in a format that can be analyzed using natural language processing.

[0069] "Integrated analysis" refers to the process of combining and analyzing data in different formats (audio, images, text) to arrive at a comprehensive understanding.

[0070] A "generative AI model" is a model that uses artificial intelligence technology to generate and interpret data, and primarily uses neural networks to generate information.

[0071] "Real-time processing" refers to a process where data is analyzed immediately after it is received, and results are generated with virtually no delay.

[0072] "User requests" refer to the information and services that users ask the system to provide.

[0073] "External information supply services" refer to information and data services provided by other organizations via the internet, and are accessible through APIs, etc.

[0074] "Personalizing" refers to the process of adjusting the content of information and services according to each user's individual preferences and history, thereby providing a personalized experience.

[0075] This invention is a multimodal data processing system designed to enhance the user's digital experience, integrating and analyzing audio, image, and text data to generate information tailored to the user's needs. Specifically, it is configured as follows:

[0076] The server receives audio, image, and text data via the user's input device. For audio data, the device converts the speech to text and sends that data to the server. This conversion can utilize speech recognition software, such as a general-purpose API service.

[0077] The server analyzes the received text and image data in real time using a generative AI model. This AI model, for example, is based on neural network technology and performs analysis that integrates natural language processing and image recognition. As a result, it understands the user's requests and extracts and organizes relevant information.

[0078] When generating information, the server accesses external information supply services to obtain the necessary data. This includes collecting information through application programming interfaces. The acquired information is then personalized based on each user's history and preferences.

[0079] For example, if a user requests by voice, "Tell me the latest camera reviews," the device converts this voice into text, and the server retrieves relevant review information from external services based on that instruction, providing the most useful information.

[0080] The generated information is presented to the user via the terminal, either visually or through audio output. This allows the user to easily access the necessary information. Furthermore, if the user provides feedback or asks additional questions, the server re-analyzes the information based on that feedback, enabling the provision of more precise information.

[0081] Examples of prompt statements include the following:

[0082] "Please analyze the user request: 'Tell me reviews of the latest cameras.' Retrieve information from the data source and generate relevant information."

[0083] In this way, the system of the present invention is able to respond quickly to the diverse and complex needs of users and provide personalized and useful information.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user inputs voice data using a device. This voice data requests information about the latest camera reviews. The device captures the voice data through its microphone and passes it to voice recognition software in real time.

[0087] Step 2:

[0088] The device converts the audio data into text data. The speech recognition software analyzes the audio waveform to identify phonemes and converts them into strings to output the text data. The converted text data is "Tell me a review of the latest camera."

[0089] Step 3:

[0090] The terminal sends the converted text data to the server. The server, receiving the text data as input, uses a generative AI model to analyze the data and understand the user's request. In this analysis process, the text is tokenized and the AI ​​model understands the context.

[0091] Step 4:

[0092] The server initiates access to external information supply services based on the user's request. For example, it connects to the application programming interface (API) of a service that provides camera review information and retrieves the relevant data. The input for this step is the request, and the output is the collected review information.

[0093] Step 5:

[0094] The server generates information based on the acquired data. Using a generative AI model, it identifies highly relevant reviews and summarizes information valuable to the user. At this stage, the information is personalized based on the user's history and preferences.

[0095] Step 6:

[0096] The server sends the generated information back to the terminal. The terminal then builds an interface to visually display this information to the user. In some cases, it can also use speech synthesis software to play the information as audio for the user to hear.

[0097] Step 7:

[0098] The user provides feedback on the information received or enters additional questions. The device transcribes this feedback back into text and sends it to the server as new input. The server then re-analyzes this feedback to provide more detailed information.

[0099] (Application Example 1)

[0100] 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."

[0101] In today's retail environment, it is difficult for consumers to obtain timely detailed information and reviews of products they are looking for. Especially in physical stores, there are limitations to the quantity and quality of information that store staff can provide, and there is a need to efficiently support consumers' purchasing decisions. Furthermore, there is a lack of means to improve customer satisfaction by providing information tailored to each consumer's preferences.

[0102] 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.

[0103] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text data; means for analyzing the data in real time using a generative AI model and generating information in response to user requests; and means for presenting the information using the user's visual device to realize an interactive sales experience. This makes it possible to quickly and accurately provide consumers with the product information they desire and to realize a personalized purchasing experience.

[0104] "Receiving and integrating audio, image, and text data" means simultaneously receiving different types of data, determining the characteristics and relationships of each data, and deriving an overall result.

[0105] "Using a generative AI model to analyze data in real time and generate information that meets user requests" refers to a process that utilizes artificial intelligence technology to instantly analyze provided data and generate the information most relevant to the user's request.

[0106] "Providing analysis results to the user visually or audibly" means presenting the results of data analysis in a way that the user can see or hear.

[0107] "Collaborating with external services to obtain necessary data" refers to activities that involve communicating with other information provision systems via the internet or other means to acquire necessary information.

[0108] "Personalizing information based on user history and personal preferences" means adjusting the information to be most suitable for each user based on data about their past behavior and unique preferences.

[0109] "Presenting information using the user's visual devices and realizing an interactive sales experience" means displaying information using a display device worn by the user, enabling a purchasing process in which the user and the system mutually influence each other.

[0110] "Analyzing product information using imaging devices in visual devices" refers to a method of photographing products using a camera built into a display device and extracting product-related information from that image data.

[0111] The system realizing this invention functions as an interactive shopping assistant using smart glasses. The server integrates and receives and analyzes voice, image, and text data. This process includes speech recognition software to convert speech to text, image recognition algorithms to process image data, and a text analysis engine that leverages a generative AI model.

[0112] Smart glasses capture the user's voice input through a microphone and convert the audio to text in real time. The user's spoken content is sent to a server, which performs data analysis using a generative AI model. This analysis retrieves the most relevant information to the user's request from external information services and generates results in real time. The generated information is presented visually via a display built into the smart glasses, and in some cases, can be read aloud.

[0113] For example, if a user says, "I want to see reviews for this bag," the smart glasses' camera takes a picture of the bag and sends the image data to a server. This data is analyzed using a generative AI model to retrieve appropriate review information, which is then displayed to the user. Furthermore, recommended products in the same category are also presented. This allows users to enjoy an efficient and personalized shopping experience in the store.

[0114] Examples of prompt messages include inquiries such as, "Show me the reviews for this product," "Do you have any recommended accessories?", and "What items are on sale?".

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The device (smart glasses) captures the user's voice input via a microphone. The input voice is converted into text data in real time by speech recognition software. The voice waveform is output as text data and sent to the server.

[0118] Step 2:

[0119] The server analyzes the text data received from the terminal. This analysis uses a generative AI model to understand the user's request. The data processing performed here involves extracting the intent behind the request using natural language processing, resulting in the generation of data that reflects the user's request.

[0120] Step 3:

[0121] Simultaneously, the terminal captures image data taken by the user through the camera and sends it to the server. The server uses an image recognition algorithm to identify the products shown in the video. Image data is taken as input, and product identification information is obtained as output.

[0122] Step 4:

[0123] The server integrates the text data and product identification information obtained in the previous step and connects to relevant external information services. Based on the generated data, it sends database queries to the external services to retrieve the necessary review information and product details.

[0124] Step 5:

[0125] The acquired information is analyzed using a generative AI model to generate information best suited to the user's needs. This analysis includes data correlation and importance evaluation, and relevant information is selected. The final generated result is a set of information to be presented visually or audibly.

[0126] Step 6:

[0127] The server sends the generated information set to the terminal, which then displays it on the smart glasses' screen. Additionally, audio information is provided via the speaker as needed. This allows the user to receive information both visually and aurally.

[0128] 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.

[0129] The present invention is a multimodal data processing system incorporating an emotion engine that recognizes user emotions, enabling it to optimize responses to user requests based on those emotions. This system comprehensively receives and analyzes voice, image, and text data and provides corresponding information to the user. The following describes specific embodiments for carrying out the present invention.

[0130] First, the user provides voice or text input to the device. Upon receiving this input, the device converts the voice into text data and, if necessary, also collects image data and sends it to the server. The server uses a generative AI model and an emotion engine to process the received data comprehensively. The emotion engine recognizes emotions from the user's input and incorporates them into the analysis results.

[0131] The server utilizes a generative AI model to analyze user requests, taking their emotions into account, and generates information as a result. For example, if a user requests via voice, "I've been busy and tired lately, please recommend some relaxing music," the emotion engine recognizes "tired" and "relaxed" as emotional elements. Based on this information, the server collects appropriate relaxing music playlists and sends the generated results to the device.

[0132] The device either visually displays results to the user or provides suggestions via voice. This process customizes the information to best suit the user's emotional state and delivers it accordingly. Furthermore, the system considers the user's past interactions and feedback to further personalize the information it provides.

[0133] In this way, a system incorporating the emotion engine of the present invention can accurately grasp the user's emotions and, based on that, provide information and services to enrich the digital experience.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user interacts with the device by speaking or typing text. Let's say the user types, "I'm feeling stressed, so I'd like to know how to relax."

[0137] Step 2:

[0138] The device converts voice input into text data and retrieves related images if necessary. It then sends the converted text and image data to the server.

[0139] Step 3:

[0140] The server analyzes the data received from the terminal. Here, it uses an emotion engine to identify the emotion "stress" contained in the user's input.

[0141] Step 4:

[0142] The server uses a generative AI model to understand the user's request and combine it with the results of the emotion engine. For example, it combines the request to relax with the emotion of stress to determine the direction of suggesting an appropriate solution.

[0143] Step 5:

[0144] The server accesses external information services to obtain information on activities and music that can help with relaxation. This includes music streaming services and wellness information platforms.

[0145] Step 6:

[0146] The server creates personalized options that match the user's preferences based on the information it has gathered, taking into account the user's past history and preferences.

[0147] Step 7:

[0148] The server sends the generated results to the terminal. This may include links to relaxing music playlists or stretching videos.

[0149] Step 8:

[0150] The device visually displays the transmitted information to the user and provides audio feedback if necessary. The user can then review this information, utilize the available options, and make additional requests.

[0151] (Example 2)

[0152] 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".

[0153] In recent years, with the increasing diversity and volume of information, there is a growing demand for information tailored to the emotions and needs of individual users. However, conventional systems fail to adequately integrate and provide information while considering user emotions. Furthermore, personalized information provision based on user history and preferences is insufficient, making it difficult to optimize the user experience.

[0154] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0155] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using generative artificial intelligence and generating information that meets the user's requests; and means for incorporating the user's emotions into the analysis results using an emotion recognition engine. This makes it possible to provide information based on the user's emotions and needs, thereby realizing more personalized information delivery.

[0156] "Audio, image, and text information" refers to the types of information input by users, and includes data expressed in the form of audio, images, and text.

[0157] "Integrated analysis" refers to the process of analyzing audio, image, and text data together to comprehensively understand the correlations and meanings between them.

[0158] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate new information and content from data using machine learning.

[0159] An "emotion recognition engine" refers to a technology that detects and analyzes a user's emotions and sensibilities from the input information.

[0160] "Providing visually or audibly" refers to means of informing the user of the analysis results through screen display or audio output.

[0161] "External information services" refer to other information-providing systems or platforms on the internet that are used to obtain necessary data and services.

[0162] "Personalization" refers to the process of optimizing information and services for specific users by taking into account their history and preferences.

[0163] An "application program interface" refers to an interface function that allows information and services to be exchanged between different software programs.

[0164] This invention is a personalized information delivery system that takes into account the user's emotions. The system consists of a terminal, a server, and software components including an emotion recognition engine and generative artificial intelligence.

[0165] The device receives voice, image, and text information from the user. Specifically, it uses a microphone for voice input and a camera to acquire image information. It then uses speech recognition software to convert the voice into text.

[0166] The converted and collected information is sent from the terminal to the server. The server uses an application program interface to obtain the necessary information in order to interact with external information services.

[0167] The server analyzes the received data using an emotion recognition engine. This includes specific software modules, such as algorithms for identifying the user's emotions. The server also uses generative artificial intelligence to generate information based on prompts from the user.

[0168] For example, if a user requests, "I've been busy and tired lately, please recommend some relaxing music," the system will assess emotions such as "tired" and "relaxed" and generate a suitable playlist using an external music streaming service. This analysis result is provided to the user via the device using a visual display or audio output.

[0169] Specific examples of prompt sentences include, "Can you recommend some lighthearted articles about recent weather?" and "Can you recommend a list of relaxing movies?"

[0170] This system allows users to quickly obtain information that matches their emotions, improving the user experience. The system also takes into account user history and preferences, ensuring that the most relevant information is always provided.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The user inputs information to the terminal via voice or text. In the case of voice input, a microphone is used, and the input is converted to text by speech recognition software. The input in this step is either the user's voice or directly entered text, and the output is text data.

[0174] Step 2:

[0175] The terminal sends the converted text data to the server along with image data as needed. Specifically, the terminal converts audio data into text and sends it to the server over the network. The input for this step is text data (and image data as needed), and the output is the transmission of data to the server.

[0176] Step 3:

[0177] The server analyzes the received text data using an emotion recognition engine to identify the user's emotions. In this case, for example, it analyzes the words and context contained in the text and extracts emotional elements such as "tired" or "relaxed." The input for this step is the text data sent from the terminal, and the output is the emotion recognition result.

[0178] Step 4:

[0179] The server generates information using a generative AI model based on the emotion recognition results. Here, it generates information best suited to the user based on specific prompt statements. The inputs to this step are the emotion recognition results and prompts for the generative AI model, and the output is information corresponding to the user's emotions.

[0180] Step 5:

[0181] The server sends the generated information to the terminal. The terminal either displays the received information visually to the user or outputs it as speech using speech synthesis. In this step, the input is the information sent from the server, and the output is the presentation of the results to the user.

[0182] Step 6:

[0183] The user enters feedback on the provided information into the terminal. The terminal sends this feedback data back to the server. The server collects this data and uses it to improve future information generation. In this step, the input is the user's feedback, and the output is the transmission of feedback data to the server.

[0184] (Application Example 2)

[0185] 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".

[0186] There is a need to develop information delivery systems that can respond quickly and appropriately to the diverse emotions and needs of users. In particular, in physical stores, providing customer service methods that enable personalized product suggestions based on customer emotions is a challenge. Currently, conventional information delivery systems have difficulty adequately considering user emotions, and there is a need to achieve more effective personalization.

[0187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0188] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using a generation AI algorithm and generating relevant information that corresponds to the user's emotions and requests; and means for displaying product suggestions that correspond to the user's emotions via a visual terminal. This makes it possible to quickly provide personalized information and product suggestions that take into account the emotional state of each individual user.

[0189] "Audio, image, and text information" refers to various forms of information received from users, including audio data, visual data, and linguistic data.

[0190] "Integrated analysis methods" refer to techniques that process audio, image, and text information in a complex manner and combine the features obtained from them for analysis.

[0191] A "generative AI algorithm" is a computational method that uses AI technology to generate information based on user input data.

[0192] "Real-time analysis" refers to the process of receiving user input, immediately processing the data, and generating results.

[0193] "User emotions" refers to the psychological state of individual users as interpreted from their voice, facial expressions, and text.

[0194] "Generating relevant information" means creating contextual information and suggestions based on the user's needs and emotions.

[0195] A "visual terminal" is a device used to present information to a user visually, and includes display devices and eyeglass-type terminals.

[0196] "Personalized information" refers to information provided that is customized to the specific needs and preferences of individual users.

[0197] The system for realizing this invention comprises hardware and software for acquiring and integrating user voice, image, and text information. The system consists of a visual terminal such as smart glasses and a server, and uses a generative AI model and emotion engine to analyze the user's emotions.

[0198] The server receives audio and image data provided by the user through smart glasses and converts the audio to text using a speech recognition API (e.g., Google® Speech-to-Text). It also analyzes the user's facial expressions using an image processing library (e.g., OpenCV) and identifies their emotional state with an emotion engine. The analyzed data is processed by a generative AI algorithm (e.g., TENSORFLOW®) to create appropriate suggestions based on the user's emotions.

[0199] The generated suggestions are then displayed on the visual terminal's screen. This allows users to receive personalized product and service suggestions tailored to their emotions.

[0200] As a concrete example, a user might say to the glasses, "I'm stressed out from work and want to refresh myself." In this case, the system analyzes the user's request and suggests a "relaxing product." An example of the system's prompt message is as follows:

[0201] "User says: 'I'm feeling stressed from work.' System processes the voice input and facial expression. Generate a personalized product suggestion focused on relaxation."

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The user provides voice input through smart glasses. This voice data is captured by the device. The input is voice data, and the output is a digital audio file. The device acquires this audio file and prepares it for further processing.

[0205] Step 2:

[0206] The device sends audio data to a cloud server. The server uses a speech recognition API to convert this audio into text. The input is a digital audio file, and the output is text data obtained through speech recognition. The server uses this text as the basis for analysis.

[0207] Step 3:

[0208] The smart glasses capture the user's face. The image data is stored on the device and then sent to a cloud server. The input is image data, and the output is formatted image data for analysis. The server uses an image processing library to analyze the facial expression.

[0209] Step 4:

[0210] The server uses a generative AI model to integrate text data and image data from speech to infer the user's emotions. The input is text data and analyzed image data, and the output is identified emotion data. Based on this emotion data, the server identifies the user's needs.

[0211] Step 5:

[0212] The server generates product and service suggestions using a generative AI algorithm based on the user's emotions and requests. The input is emotion data, and the output is personalized suggestion data. The server references historical data and existing databases to generate the best possible suggestions.

[0213] Step 6:

[0214] The suggested data is displayed on the smart glasses' screen and presented to the user visually. The input is the suggested data, and the output is the visually presented information. The user reviews the information on the display and takes the next action.

[0215] Each step is seamlessly connected, allowing users to automatically receive personalized information in real time.

[0216] 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.

[0217] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0218] 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.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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".

[0232] This invention is a system designed to enhance the user's digital experience through multimodal data processing capabilities. This system enables the integrated analysis of voice, image, and text data to generate information tailored to the user's needs. The following describes embodiments for carrying out this invention.

[0233] The server receives audio, image, and text data provided by the user. For audio data, the terminal converts the audio to text and sends it to the server. The server analyzes the received audio, text, and image data, and uses generative AI models to understand the user's requests. Through this analysis, the server determines what the user wants and retrieves relevant data from external services.

[0234] For example, suppose a user speaks into their device saying, "Show me the coffee maker reviews." The device converts this speech into text and sends it to the server. The server analyzes this text, retrieves relevant coffee maker reviews from an external review service, and generates the most relevant and useful information.

[0235] The generated information is displayed visually to the user via the device. In some cases, the information can be read aloud, making it easily accessible to the user. Furthermore, if the user provides feedback or asks additional questions about specific information, the server re-analyzes the content and provides even more detailed information. The server also manages the user's history and preferences, and the information provided is customized for each user.

[0236] In this way, the system of the present invention enables the rapid understanding of the user's complex requirements and the provision of personalized, practical information.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] When a device receives voice input from a user, it converts that voice into text data. This conversion is usually performed in real time by the device's built-in speech recognition system.

[0240] Step 2:

[0241] The device sends the converted text data to the server. Images and existing text data are also sent in the same manner.

[0242] Step 3:

[0243] The server receives text data sent from the terminal, and simultaneously captures images and other data. It then uses a generative AI model to analyze this data in a unified manner.

[0244] Step 4:

[0245] The server uses a generative AI model to analyze the content of incoming data. It identifies the information and actions the user is seeking and generates analysis results based on those requests.

[0246] Step 5:

[0247] The server will, as needed, interact with external information services and applications to obtain data relevant to the analysis results. For example, if a user is requesting product reviews, it will retrieve the latest reviews of that product from an external service.

[0248] Step 6:

[0249] The server integrates the collected information to generate results that are most relevant to the user. These results are then personalized as needed, based on the user's history and preferences.

[0250] Step 7:

[0251] The server sends the generated results to the terminal. The terminal receives this information and either displays it visually to the user or provides it as audio feedback.

[0252] Step 8:

[0253] The user reviews the provided information and enters any additional requests or feedback into the terminal. Based on this input, the processing loop may be restarted.

[0254] (Example 1)

[0255] 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."

[0256] Despite the need for systems that can respond to diverse user requests in real time and provide personalized information, current technologies are insufficient to meet these demands. Furthermore, integrating and effectively utilizing data across multiple media formats (audio, images, text) remains a challenge. Additionally, personalization based on users' past actions and preferences, while effectively collaborating with external information sources, is still incomplete.

[0257] 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.

[0258] In this invention, the server includes means for receiving input data in the form of audio, images, and text and for integratively analyzing it; means for processing the analyzed data in real time using a generative AI model and generating information tailored to the user's requests; and means for presenting the generated information to the user visually or audibly. This enables a rapid and accurate response to user requests and the provision of personalized information.

[0259] "Audio data" refers to information obtained by converting audio into a digital format, which is represented in a form that can be processed by a computer.

[0260] "Image data" refers to a digital representation of visual information, and is data used to analyze two-dimensional visual information using a computer.

[0261] "Text data" refers to information composed of characters and symbols, represented in a digital format, and is in a format that can be analyzed using natural language processing.

[0262] "Integrated analysis" refers to the process of combining and analyzing data in different formats (audio, images, text) to arrive at a comprehensive understanding.

[0263] A "generative AI model" is a model that uses artificial intelligence technology to generate and interpret data, and primarily uses neural networks to generate information.

[0264] "Real-time processing" refers to a process where data is analyzed immediately after it is received, and results are generated with virtually no delay.

[0265] "User requests" refer to the information and services that users ask the system to provide.

[0266] "External information supply services" refer to information and data services provided by other organizations via the internet, and are accessible through APIs, etc.

[0267] "Personalizing" refers to the process of adjusting the content of information and services according to each user's individual preferences and history, thereby providing a personalized experience.

[0268] This invention is a multimodal data processing system designed to enhance the user's digital experience, integrating and analyzing audio, image, and text data to generate information tailored to the user's needs. Specifically, it is configured as follows:

[0269] The server receives audio, image, and text data via the user's input device. For audio data, the device converts the speech to text and sends that data to the server. This conversion can utilize speech recognition software, such as a general-purpose API service.

[0270] The server analyzes the received text and image data in real time using a generative AI model. This AI model, for example, is based on neural network technology and performs analysis that integrates natural language processing and image recognition. As a result, it understands the user's requests and extracts and organizes relevant information.

[0271] When generating information, the server accesses external information supply services to obtain the necessary data. This includes collecting information through application programming interfaces. The acquired information is then personalized based on each user's history and preferences.

[0272] For example, if a user requests by voice, "Tell me the latest camera reviews," the device converts this voice into text, and the server retrieves relevant review information from external services based on that instruction, providing the most useful information.

[0273] The generated information is presented to the user via the terminal, either visually or through audio output. This allows the user to easily access the necessary information. Furthermore, if the user provides feedback or asks additional questions, the server re-analyzes the information based on that feedback, enabling the provision of more precise information.

[0274] Examples of prompt statements include the following:

[0275] "Please analyze the user request: 'Tell me reviews of the latest cameras.' Retrieve information from the data source and generate relevant information."

[0276] In this way, the system of the present invention is able to respond quickly to the diverse and complex needs of users and provide personalized and useful information.

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The user inputs voice data using a terminal. This voice data requests information regarding the latest camera reviews. The terminal captures the voice data through a microphone and passes it to voice recognition software in real-time.

[0280] Step 2:

[0281] The terminal converts the voice data into text data. The voice recognition software analyzes the voice waveform to identify phonemes and converts this into a character string to output the text data. The converted text data is "Tell me about the latest camera reviews".

[0282] Step 3:

[0283] The terminal transmits the converted text data to the server. The server that receives the text data as input analyzes the data using a generative AI model and understands the user's request. In this analysis process, the text is tokenized and the context is understood by the AI model.

[0284] Step 4:

[0285] The server starts accessing an external information supply service based on the user's request. For example, it connects to the application programming interface (API) of a service that provides camera review information and obtains relevant data. The input for this step is the request content, and the output is the collected review information.

[0286] Step 5:

[0287] The server generates information based on the acquired data. Using a generative AI model, it identifies relevant reviews and summarizes information valuable to the user. At this time, the information is personalized based on the user's history and preferences.

[0288] Step 6:

[0289] The server sends the generated information back to the terminal. The terminal then builds an interface to visually display this information to the user. In some cases, it can also use speech synthesis software to play the information as audio for the user to hear.

[0290] Step 7:

[0291] The user provides feedback on the information received or enters additional questions. The device transcribes this feedback back into text and sends it to the server as new input. The server then re-analyzes this feedback to provide more detailed information.

[0292] (Application Example 1)

[0293] 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."

[0294] In today's retail environment, it is difficult for consumers to obtain timely detailed information and reviews of products they are looking for. Especially in physical stores, there are limitations to the quantity and quality of information that store staff can provide, and there is a need to efficiently support consumers' purchasing decisions. Furthermore, there is a lack of means to improve customer satisfaction by providing information tailored to each consumer's preferences.

[0295] 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.

[0296] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text data; means for analyzing the data in real time using a generative AI model and generating information in response to user requests; and means for presenting the information using the user's visual device to realize an interactive sales experience. This makes it possible to quickly and accurately provide consumers with the product information they desire and to realize a personalized purchasing experience.

[0297] "Receiving and integrating audio, image, and text data" means simultaneously receiving different types of data, determining the characteristics and relationships of each data, and deriving an overall result.

[0298] "Using a generative AI model to analyze data in real time and generate information that meets user requests" refers to a process that utilizes artificial intelligence technology to instantly analyze provided data and generate the information most relevant to the user's request.

[0299] "Providing analysis results to the user visually or audibly" means presenting the results of data analysis in a way that the user can see or hear.

[0300] "Collaborating with external services to obtain necessary data" refers to activities that involve communicating with other information provision systems via the internet or other means to acquire necessary information.

[0301] "Personalizing information based on user history and personal preferences" means adjusting the information to be most suitable for each user based on data about their past behavior and unique preferences.

[0302] "Presenting information using the user's visual devices and realizing an interactive sales experience" means displaying information using a display device worn by the user, enabling a purchasing process in which the user and the system mutually influence each other.

[0303] "Analyzing product information by leveraging the imaging device of a visual device" refers to a method of photographing a product using a camera equipped in a display device and extracting information about the product from the image data.

[0304] The system that realizes this invention functions as an interactive shopping assistant using smart glasses. The server integrally receives voice, image, and text data and performs analysis. This process includes voice recognition software for converting voice to text, an image recognition algorithm for processing image data, and a text analysis engine leveraging a generative AI model.

[0305] The smart glasses capture the user's voice input through a microphone and convert the voice to text in real time. The content spoken by the user through the device is sent to the server, and the server performs data analysis using the generative AI model. In this analysis, the information most relevant to the user's request is obtained from an external information providing service, and the result is generated in real time. The generated information is visually presented via the display built into the smart glasses and can also be read aloud by voice in some cases.

[0306] For example, when the user says, "I want to see the reviews of this bag," the camera of the smart glasses takes a picture of the bag and sends the image data to the server. This data is analyzed using the generative AI model, appropriate review information is obtained, and presented to the user. Additionally, recommended products in the same category are also presented. This enables the user to enjoy an efficient and personalized shopping experience in the store.

[0307] Examples of prompt sentences include inquiries such as "Show me the reviews of this product," "Are there any recommended accessories?" and "What items are on sale?"

[0308] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The device (smart glasses) captures the user's voice input via a microphone. The input voice is converted into text data in real time by speech recognition software. The voice waveform is output as text data and sent to the server.

[0311] Step 2:

[0312] The server analyzes the text data received from the terminal. This analysis uses a generative AI model to understand the user's request. The data processing performed here involves extracting the intent behind the request using natural language processing, resulting in the generation of data that reflects the user's request.

[0313] Step 3:

[0314] Simultaneously, the terminal captures image data taken by the user through the camera and sends it to the server. The server uses an image recognition algorithm to identify the products shown in the video. Image data is taken as input, and product identification information is obtained as output.

[0315] Step 4:

[0316] The server integrates the text data and product identification information obtained in the previous step and connects to relevant external information services. Based on the generated data, it sends database queries to the external services to retrieve the necessary review information and product details.

[0317] Step 5:

[0318] The acquired information is analyzed using a generative AI model to generate information best suited to the user's needs. This analysis includes data correlation and importance evaluation, and relevant information is selected. The final generated result is a set of information to be presented visually or audibly.

[0319] Step 6:

[0320] The server sends the generated information set to the terminal, which then displays it on the smart glasses' screen. Additionally, audio information is provided via the speaker as needed. This allows the user to receive information both visually and aurally.

[0321] 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.

[0322] The present invention is a multimodal data processing system incorporating an emotion engine that recognizes user emotions, enabling it to optimize responses to user requests based on those emotions. This system comprehensively receives and analyzes voice, image, and text data and provides corresponding information to the user. The following describes specific embodiments for carrying out the present invention.

[0323] First, the user provides voice or text input to the device. Upon receiving this input, the device converts the voice into text data and, if necessary, also collects image data and sends it to the server. The server uses a generative AI model and an emotion engine to process the received data comprehensively. The emotion engine recognizes emotions from the user's input and incorporates them into the analysis results.

[0324] The server utilizes a generative AI model to analyze user requests, taking their emotions into account, and generates information as a result. For example, if a user requests via voice, "I've been busy and tired lately, please recommend some relaxing music," the emotion engine recognizes "tired" and "relaxed" as emotional elements. Based on this information, the server collects appropriate relaxing music playlists and sends the generated results to the device.

[0325] The device either visually displays results to the user or provides suggestions via voice. This process customizes the information to best suit the user's emotional state and delivers it accordingly. Furthermore, the system considers the user's past interactions and feedback to further personalize the information it provides.

[0326] In this way, a system incorporating the emotion engine of the present invention can accurately grasp the user's emotions and, based on that, provide information and services to enrich the digital experience.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The user interacts with the device by speaking or typing text. Let's say the user types, "I'm feeling stressed, so I'd like to know how to relax."

[0330] Step 2:

[0331] The device converts voice input into text data and retrieves related images if necessary. It then sends the converted text and image data to the server.

[0332] Step 3:

[0333] The server analyzes the data received from the terminal. Here, it uses an emotion engine to identify the emotion "stress" contained in the user's input.

[0334] Step 4:

[0335] The server uses a generative AI model to understand the user's request and combine it with the results of the emotion engine. For example, it combines the request to relax with the emotion of stress to determine the direction of suggesting an appropriate solution.

[0336] Step 5:

[0337] The server accesses external information services to obtain information on activities and music that can help with relaxation. This includes music streaming services and wellness information platforms.

[0338] Step 6:

[0339] The server creates personalized options that match the user's preferences based on the information it has gathered, taking into account the user's past history and preferences.

[0340] Step 7:

[0341] The server sends the generated results to the terminal. This may include links to relaxing music playlists or stretching videos.

[0342] Step 8:

[0343] The device visually displays the transmitted information to the user and provides audio feedback if necessary. The user can then review this information, utilize the available options, and make additional requests.

[0344] (Example 2)

[0345] 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".

[0346] In recent years, with the increasing diversity and volume of information, there is a growing demand for information tailored to the emotions and needs of individual users. However, conventional systems fail to adequately integrate and provide information while considering user emotions. Furthermore, personalized information provision based on user history and preferences is insufficient, making it difficult to optimize the user experience.

[0347] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0348] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using generative artificial intelligence and generating information that meets the user's requests; and means for incorporating the user's emotions into the analysis results using an emotion recognition engine. This makes it possible to provide information based on the user's emotions and needs, thereby realizing more personalized information delivery.

[0349] "Audio, image, and text information" refers to the types of information input by users, and includes data expressed in the form of audio, images, and text.

[0350] "Integrated analysis" refers to the process of analyzing audio, image, and text data together to comprehensively understand the correlations and meanings between them.

[0351] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate new information and content from data using machine learning.

[0352] An "emotion recognition engine" refers to a technology that detects and analyzes a user's emotions and sensibilities from the input information.

[0353] "Providing visually or audibly" refers to means of informing the user of the analysis results through screen display or audio output.

[0354] "External information services" refer to other information-providing systems or platforms on the internet that are used to obtain necessary data and services.

[0355] "Personalization" refers to the process of optimizing information and services for specific users by taking into account their history and preferences.

[0356] An "application program interface" refers to an interface function that allows information and services to be exchanged between different software programs.

[0357] This invention is a personalized information delivery system that takes into account the user's emotions. The system consists of a terminal, a server, and software components including an emotion recognition engine and generative artificial intelligence.

[0358] The device receives voice, image, and text information from the user. Specifically, it uses a microphone for voice input and a camera to acquire image information. It then uses speech recognition software to convert the voice into text.

[0359] The converted and collected information is sent from the terminal to the server. The server uses an application program interface to obtain the necessary information in order to interact with external information services.

[0360] The server analyzes the received data using an emotion recognition engine. This includes specific software modules, such as algorithms for identifying the user's emotions. The server also uses generative artificial intelligence to generate information based on prompts from the user.

[0361] For example, if a user requests, "I've been busy and tired lately, please recommend some relaxing music," the system will assess emotions such as "tired" and "relaxed" and generate a suitable playlist using an external music streaming service. This analysis result is provided to the user via the device using a visual display or audio output.

[0362] Specific examples of prompt sentences include, "Can you recommend some lighthearted articles about recent weather?" and "Can you recommend a list of relaxing movies?"

[0363] This system allows users to quickly obtain information that matches their emotions, improving the user experience. The system also takes into account user history and preferences, ensuring that the most relevant information is always provided.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] The user inputs information to the terminal via voice or text. In the case of voice input, a microphone is used, and the input is converted to text by speech recognition software. The input in this step is either the user's voice or directly entered text, and the output is text data.

[0367] Step 2:

[0368] The terminal sends the converted text data to the server along with image data as needed. Specifically, the terminal converts audio data into text and sends it to the server over the network. The input for this step is text data (and image data as needed), and the output is the transmission of data to the server.

[0369] Step 3:

[0370] The server analyzes the received text data using an emotion recognition engine to identify the user's emotions. In this case, for example, it analyzes the words and context contained in the text and extracts emotional elements such as "tired" or "relaxed." The input for this step is the text data sent from the terminal, and the output is the emotion recognition result.

[0371] Step 4:

[0372] The server generates information using a generative AI model based on the emotion recognition results. Here, it generates information best suited to the user based on specific prompt statements. The inputs to this step are the emotion recognition results and prompts for the generative AI model, and the output is information corresponding to the user's emotions.

[0373] Step 5:

[0374] The server sends the generated information to the terminal. The terminal either displays the received information visually to the user or outputs it as speech using speech synthesis. In this step, the input is the information sent from the server, and the output is the presentation of the results to the user.

[0375] Step 6:

[0376] The user enters feedback on the provided information into the terminal. The terminal sends this feedback data back to the server. The server collects this data and uses it to improve future information generation. In this step, the input is the user's feedback, and the output is the transmission of feedback data to the server.

[0377] (Application Example 2)

[0378] 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."

[0379] There is a need to develop information delivery systems that can respond quickly and appropriately to the diverse emotions and needs of users. In particular, in physical stores, providing customer service methods that enable personalized product suggestions based on customer emotions is a challenge. Currently, conventional information delivery systems have difficulty adequately considering user emotions, and there is a need to achieve more effective personalization.

[0380] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0381] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using a generation AI algorithm and generating relevant information that corresponds to the user's emotions and requests; and means for displaying product suggestions that correspond to the user's emotions via a visual terminal. This makes it possible to quickly provide personalized information and product suggestions that take into account the emotional state of each individual user.

[0382] "Audio, image, and text information" refers to various forms of information received from users, including audio data, visual data, and linguistic data.

[0383] "Integrated analysis methods" refer to techniques that process audio, image, and text information in a complex manner and combine the features obtained from them for analysis.

[0384] A "generative AI algorithm" is a computational method that uses AI technology to generate information based on user input data.

[0385] "Real-time analysis" refers to the process of receiving user input, immediately processing the data, and generating results.

[0386] "User emotions" refers to the psychological state of individual users as interpreted from their voice, facial expressions, and text.

[0387] "Generating relevant information" means creating contextual information and suggestions based on the user's needs and emotions.

[0388] A "visual terminal" is a device used to present information to a user visually, and includes display devices and eyeglass-type terminals.

[0389] "Personalized information" refers to information provided that is customized to the specific needs and preferences of individual users.

[0390] The system for realizing this invention comprises hardware and software for acquiring and integrating user voice, image, and text information. The system consists of a visual terminal such as smart glasses and a server, and uses a generative AI model and emotion engine to analyze the user's emotions.

[0391] The server receives audio and image data provided by the user through smart glasses and converts the audio to text using a speech recognition API (e.g., Google Speech-to-Text). It also analyzes the user's facial expressions using an image processing library (e.g., OpenCV) and identifies their emotional state with an emotion engine. The analyzed data is processed by a generative AI algorithm (e.g., TensorFlow) to create appropriate suggestions based on the user's emotions.

[0392] The generated suggestions are then displayed on the visual terminal's screen. This allows users to receive personalized product and service suggestions tailored to their emotions.

[0393] As a concrete example, a user might say to the glasses, "I'm stressed out from work and want to refresh myself." In this case, the system analyzes the user's request and suggests a "relaxing product." An example of the system's prompt message is as follows:

[0394] "User says: 'I'm feeling stressed from work.' System processes the voice input and facial expression. Generate a personalized product suggestion focused on relaxation."

[0395] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0396] Step 1:

[0397] The user provides voice input through smart glasses. This voice data is captured by the device. The input is voice data, and the output is a digital audio file. The device acquires this audio file and prepares it for further processing.

[0398] Step 2:

[0399] The device sends audio data to a cloud server. The server uses a speech recognition API to convert this audio into text. The input is a digital audio file, and the output is text data obtained through speech recognition. The server uses this text as the basis for analysis.

[0400] Step 3:

[0401] The smart glasses capture the user's face. The image data is stored on the device and then sent to a cloud server. The input is image data, and the output is formatted image data for analysis. The server uses an image processing library to analyze the facial expression.

[0402] Step 4:

[0403] The server uses a generative AI model to integrate text data and image data from speech to infer the user's emotions. The input is text data and analyzed image data, and the output is identified emotion data. Based on this emotion data, the server identifies the user's needs.

[0404] Step 5:

[0405] The server generates product and service suggestions using a generative AI algorithm based on the user's emotions and requests. The input is emotion data, and the output is personalized suggestion data. The server references historical data and existing databases to generate the best possible suggestions.

[0406] Step 6:

[0407] The suggested data is displayed on the smart glasses' screen and presented to the user visually. The input is the suggested data, and the output is the visually presented information. The user reviews the information on the display and takes the next action.

[0408] Each step is seamlessly connected, allowing users to automatically receive personalized information in real time.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] [Third Embodiment]

[0413] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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".

[0425] This invention is a system designed to enhance the user's digital experience through multimodal data processing capabilities. This system enables the integrated analysis of voice, image, and text data to generate information tailored to the user's needs. The following describes embodiments for carrying out this invention.

[0426] The server receives audio, image, and text data provided by the user. For audio data, the terminal converts the audio to text and sends it to the server. The server analyzes the received audio, text, and image data, and uses generative AI models to understand the user's requests. Through this analysis, the server determines what the user wants and retrieves relevant data from external services.

[0427] For example, suppose a user speaks into their device saying, "Show me the coffee maker reviews." The device converts this speech into text and sends it to the server. The server analyzes this text, retrieves relevant coffee maker reviews from an external review service, and generates the most relevant and useful information.

[0428] The generated information is displayed visually to the user via the device. In some cases, the information can be read aloud, making it easily accessible to the user. Furthermore, if the user provides feedback or asks additional questions about specific information, the server re-analyzes the content and provides even more detailed information. The server also manages the user's history and preferences, and the information provided is customized for each user.

[0429] In this way, the system of the present invention enables the rapid understanding of the user's complex requirements and the provision of personalized, practical information.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] When a device receives voice input from a user, it converts that voice into text data. This conversion is usually performed in real time by the device's built-in speech recognition system.

[0433] Step 2:

[0434] The device sends the converted text data to the server. Images and existing text data are also sent in the same manner.

[0435] Step 3:

[0436] The server receives text data sent from the terminal, and simultaneously captures images and other data. It then uses a generative AI model to analyze this data in a unified manner.

[0437] Step 4:

[0438] The server uses a generative AI model to analyze the content of incoming data. It identifies the information and actions the user is seeking and generates analysis results based on those requests.

[0439] Step 5:

[0440] The server will, as needed, interact with external information services and applications to obtain data relevant to the analysis results. For example, if a user is requesting product reviews, it will retrieve the latest reviews of that product from an external service.

[0441] Step 6:

[0442] The server integrates the collected information to generate results that are most relevant to the user. These results are then personalized as needed, based on the user's history and preferences.

[0443] Step 7:

[0444] The server sends the generated results to the terminal. The terminal receives this information and either displays it visually to the user or provides it as audio feedback.

[0445] Step 8:

[0446] The user reviews the provided information and enters any additional requests or feedback into the terminal. Based on this input, the processing loop may be restarted.

[0447] (Example 1)

[0448] 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."

[0449] Despite the need for systems that can respond to diverse user requests in real time and provide personalized information, current technologies are insufficient to meet these demands. Furthermore, integrating and effectively utilizing data across multiple media formats (audio, images, text) remains a challenge. Additionally, personalization based on users' past actions and preferences, while effectively collaborating with external information sources, is still incomplete.

[0450] 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.

[0451] In this invention, the server includes means for receiving input data in the form of audio, images, and text and for integratively analyzing it; means for processing the analyzed data in real time using a generative AI model and generating information tailored to the user's requests; and means for presenting the generated information to the user visually or audibly. This enables a rapid and accurate response to user requests and the provision of personalized information.

[0452] "Audio data" refers to information obtained by converting audio into a digital format, which is represented in a form that can be processed by a computer.

[0453] "Image data" refers to a digital representation of visual information, and is data used to analyze two-dimensional visual information using a computer.

[0454] "Text data" refers to information composed of characters and symbols, represented in a digital format, and is in a format that can be analyzed using natural language processing.

[0455] "Integrated analysis" refers to the process of combining and analyzing data in different formats (audio, images, text) to arrive at a comprehensive understanding.

[0456] A "generative AI model" is a model that uses artificial intelligence technology to generate and interpret data, and primarily uses neural networks to generate information.

[0457] "Real-time processing" refers to a process where data is analyzed immediately after it is received, and results are generated with virtually no delay.

[0458] "User requests" refer to the information and services that users ask the system to provide.

[0459] "External information supply services" refer to information and data services provided by other organizations via the internet, and are accessible through APIs, etc.

[0460] "Personalizing" refers to the process of adjusting the content of information and services according to each user's individual preferences and history, thereby providing a personalized experience.

[0461] This invention is a multimodal data processing system designed to enhance the user's digital experience, integrating and analyzing audio, image, and text data to generate information tailored to the user's needs. Specifically, it is configured as follows:

[0462] The server receives audio, image, and text data via the user's input device. For audio data, the device converts the speech to text and sends that data to the server. This conversion can utilize speech recognition software, such as a general-purpose API service.

[0463] The server analyzes the received text and image data in real time using a generative AI model. This AI model, for example, is based on neural network technology and performs analysis that integrates natural language processing and image recognition. As a result, it understands the user's requests and extracts and organizes relevant information.

[0464] When generating information, the server accesses external information supply services to obtain the necessary data. This includes collecting information through application programming interfaces. The acquired information is then personalized based on each user's history and preferences.

[0465] For example, if a user requests by voice, "Tell me the latest camera reviews," the device converts this voice into text, and the server retrieves relevant review information from external services based on that instruction, providing the most useful information.

[0466] The generated information is presented to the user via the terminal, either visually or through audio output. This allows the user to easily access the necessary information. Furthermore, if the user provides feedback or asks additional questions, the server re-analyzes the information based on that feedback, enabling the provision of more precise information.

[0467] Examples of prompt statements include the following:

[0468] "Please analyze the user request: 'Tell me reviews of the latest cameras.' Retrieve information from the data source and generate relevant information."

[0469] In this way, the system of the present invention is able to respond quickly to the diverse and complex needs of users and provide personalized and useful information.

[0470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0471] Step 1:

[0472] The user inputs voice data using a device. This voice data requests information about the latest camera reviews. The device captures the voice data through its microphone and passes it to voice recognition software in real time.

[0473] Step 2:

[0474] The device converts the audio data into text data. The speech recognition software analyzes the audio waveform to identify phonemes and converts them into strings to output the text data. The converted text data is "Tell me a review of the latest camera."

[0475] Step 3:

[0476] The terminal sends the converted text data to the server. The server, receiving the text data as input, uses a generative AI model to analyze the data and understand the user's request. In this analysis process, the text is tokenized and the AI ​​model understands the context.

[0477] Step 4:

[0478] The server initiates access to external information supply services based on the user's request. For example, it connects to the application programming interface (API) of a service that provides camera review information and retrieves the relevant data. The input for this step is the request, and the output is the collected review information.

[0479] Step 5:

[0480] The server generates information based on the acquired data. Using a generative AI model, it identifies highly relevant reviews and summarizes information valuable to the user. At this stage, the information is personalized based on the user's history and preferences.

[0481] Step 6:

[0482] The server sends the generated information back to the terminal. The terminal then builds an interface to visually display this information to the user. In some cases, it can also use speech synthesis software to play the information as audio for the user to hear.

[0483] Step 7:

[0484] The user provides feedback on the information received or enters additional questions. The device transcribes this feedback back into text and sends it to the server as new input. The server then re-analyzes this feedback to provide more detailed information.

[0485] (Application Example 1)

[0486] 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."

[0487] In today's retail environment, it is difficult for consumers to obtain timely detailed information and reviews of products they are looking for. Especially in physical stores, there are limitations to the quantity and quality of information that store staff can provide, and there is a need to efficiently support consumers' purchasing decisions. Furthermore, there is a lack of means to improve customer satisfaction by providing information tailored to each consumer's preferences.

[0488] 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.

[0489] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text data; means for analyzing the data in real time using a generative AI model and generating information in response to user requests; and means for presenting the information using the user's visual device to realize an interactive sales experience. This makes it possible to quickly and accurately provide consumers with the product information they desire and to realize a personalized purchasing experience.

[0490] "Receiving and integrating audio, image, and text data" means simultaneously receiving different types of data, determining the characteristics and relationships of each data, and deriving an overall result.

[0491] "Using a generative AI model to analyze data in real time and generate information that meets user requests" refers to a process that utilizes artificial intelligence technology to instantly analyze provided data and generate the information most relevant to the user's request.

[0492] "Providing analysis results to the user visually or audibly" means presenting the results of data analysis in a way that the user can see or hear.

[0493] "Collaborating with external services to obtain necessary data" refers to activities that involve communicating with other information provision systems via the internet or other means to acquire necessary information.

[0494] "Personalizing information based on user history and personal preferences" means adjusting the information to be most suitable for each user based on data about their past behavior and unique preferences.

[0495] "Presenting information using the user's visual devices and realizing an interactive sales experience" means displaying information using a display device worn by the user, enabling a purchasing process in which the user and the system mutually influence each other.

[0496] "Analyzing product information using imaging devices in visual devices" refers to a method of photographing products using a camera built into a display device and extracting product-related information from that image data.

[0497] The system realizing this invention functions as an interactive shopping assistant using smart glasses. The server integrates and receives and analyzes voice, image, and text data. This process includes speech recognition software to convert speech to text, image recognition algorithms to process image data, and a text analysis engine that leverages a generative AI model.

[0498] Smart glasses capture the user's voice input through a microphone and convert the audio to text in real time. The user's spoken content is sent to a server, which performs data analysis using a generative AI model. This analysis retrieves the most relevant information to the user's request from external information services and generates results in real time. The generated information is presented visually via a display built into the smart glasses, and in some cases, can be read aloud.

[0499] For example, if a user says, "I want to see reviews for this bag," the smart glasses' camera takes a picture of the bag and sends the image data to a server. This data is analyzed using a generative AI model to retrieve appropriate review information, which is then displayed to the user. Furthermore, recommended products in the same category are also presented. This allows users to enjoy an efficient and personalized shopping experience in the store.

[0500] Examples of prompt messages include inquiries such as, "Show me the reviews for this product," "Do you have any recommended accessories?", and "What items are on sale?".

[0501] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0502] Step 1:

[0503] The device (smart glasses) captures the user's voice input via a microphone. The input voice is converted into text data in real time by speech recognition software. The voice waveform is output as text data and sent to the server.

[0504] Step 2:

[0505] The server analyzes the text data received from the terminal. This analysis uses a generative AI model to understand the user's request. The data processing performed here involves extracting the intent behind the request using natural language processing, resulting in the generation of data that reflects the user's request.

[0506] Step 3:

[0507] Simultaneously, the terminal captures image data taken by the user through the camera and sends it to the server. The server uses an image recognition algorithm to identify the products shown in the video. Image data is taken as input, and product identification information is obtained as output.

[0508] Step 4:

[0509] The server integrates the text data and product identification information obtained in the previous step and connects to relevant external information services. Based on the generated data, it sends database queries to the external services to retrieve the necessary review information and product details.

[0510] Step 5:

[0511] The acquired information is analyzed using a generative AI model to generate information best suited to the user's needs. This analysis includes data correlation and importance evaluation, and relevant information is selected. The final generated result is a set of information to be presented visually or audibly.

[0512] Step 6:

[0513] The server sends the generated information set to the terminal, which then displays it on the smart glasses' screen. Additionally, audio information is provided via the speaker as needed. This allows the user to receive information both visually and aurally.

[0514] 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.

[0515] The present invention is a multimodal data processing system incorporating an emotion engine that recognizes user emotions, enabling it to optimize responses to user requests based on those emotions. This system comprehensively receives and analyzes voice, image, and text data and provides corresponding information to the user. The following describes specific embodiments for carrying out the present invention.

[0516] First, the user provides voice or text input to the device. Upon receiving this input, the device converts the voice into text data and, if necessary, also collects image data and sends it to the server. The server uses a generative AI model and an emotion engine to process the received data comprehensively. The emotion engine recognizes emotions from the user's input and incorporates them into the analysis results.

[0517] The server utilizes a generative AI model to analyze user requests, taking their emotions into account, and generates information as a result. For example, if a user requests via voice, "I've been busy and tired lately, please recommend some relaxing music," the emotion engine recognizes "tired" and "relaxed" as emotional elements. Based on this information, the server collects appropriate relaxing music playlists and sends the generated results to the device.

[0518] The device either visually displays results to the user or provides suggestions via voice. This process customizes the information to best suit the user's emotional state and delivers it accordingly. Furthermore, the system considers the user's past interactions and feedback to further personalize the information it provides.

[0519] In this way, a system incorporating the emotion engine of the present invention can accurately grasp the user's emotions and, based on that, provide information and services to enrich the digital experience.

[0520] The following describes the processing flow.

[0521] Step 1:

[0522] The user interacts with the device by speaking or typing text. Let's say the user types, "I'm feeling stressed, so I'd like to know how to relax."

[0523] Step 2:

[0524] The device converts voice input into text data and retrieves related images if necessary. It then sends the converted text and image data to the server.

[0525] Step 3:

[0526] The server analyzes the data received from the terminal. Here, it uses an emotion engine to identify the emotion "stress" contained in the user's input.

[0527] Step 4:

[0528] The server uses a generative AI model to understand the user's request and combine it with the results of the emotion engine. For example, it combines the request to relax with the emotion of stress to determine the direction of suggesting an appropriate solution.

[0529] Step 5:

[0530] The server accesses external information services to obtain information on activities and music that can help with relaxation. This includes music streaming services and wellness information platforms.

[0531] Step 6:

[0532] The server creates personalized options that match the user's preferences based on the information it has gathered, taking into account the user's past history and preferences.

[0533] Step 7:

[0534] The server sends the generated results to the terminal. This may include links to relaxing music playlists or stretching videos.

[0535] Step 8:

[0536] The device visually displays the transmitted information to the user and provides audio feedback if necessary. The user can then review this information, utilize the available options, and make additional requests.

[0537] (Example 2)

[0538] 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."

[0539] In recent years, with the increasing diversity and volume of information, there is a growing demand for information tailored to the emotions and needs of individual users. However, conventional systems fail to adequately integrate and provide information while considering user emotions. Furthermore, personalized information provision based on user history and preferences is insufficient, making it difficult to optimize the user experience.

[0540] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0541] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using generative artificial intelligence and generating information that meets the user's requests; and means for incorporating the user's emotions into the analysis results using an emotion recognition engine. This makes it possible to provide information based on the user's emotions and needs, thereby realizing more personalized information delivery.

[0542] "Audio, image, and text information" refers to the types of information input by users, and includes data expressed in the form of audio, images, and text.

[0543] "Integrated analysis" refers to the process of analyzing audio, image, and text data together to comprehensively understand the correlations and meanings between them.

[0544] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate new information and content from data using machine learning.

[0545] An "emotion recognition engine" refers to a technology that detects and analyzes a user's emotions and sensibilities from the input information.

[0546] "Providing visually or audibly" refers to means of informing the user of the analysis results through screen display or audio output.

[0547] "External information services" refer to other information-providing systems or platforms on the internet that are used to obtain necessary data and services.

[0548] "Personalization" refers to the process of optimizing information and services for specific users by taking into account their history and preferences.

[0549] An "application program interface" refers to an interface function that allows information and services to be exchanged between different software programs.

[0550] This invention is a personalized information delivery system that takes into account the user's emotions. The system consists of a terminal, a server, and software components including an emotion recognition engine and generative artificial intelligence.

[0551] The device receives voice, image, and text information from the user. Specifically, it uses a microphone for voice input and a camera to acquire image information. It then uses speech recognition software to convert the voice into text.

[0552] The converted and collected information is sent from the terminal to the server. The server uses an application program interface to obtain the necessary information in order to interact with external information services.

[0553] The server analyzes the received data using an emotion recognition engine. This includes specific software modules, such as algorithms for identifying the user's emotions. The server also uses generative artificial intelligence to generate information based on prompts from the user.

[0554] For example, if a user requests, "I've been busy and tired lately, please recommend some relaxing music," the system will assess emotions such as "tired" and "relaxed" and generate a suitable playlist using an external music streaming service. This analysis result is provided to the user via the device using a visual display or audio output.

[0555] Specific examples of prompt sentences include, "Can you recommend some lighthearted articles about recent weather?" and "Can you recommend a list of relaxing movies?"

[0556] This system allows users to quickly obtain information that matches their emotions, improving the user experience. The system also takes into account user history and preferences, ensuring that the most relevant information is always provided.

[0557] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0558] Step 1:

[0559] The user inputs information to the terminal via voice or text. In the case of voice input, a microphone is used, and the input is converted to text by speech recognition software. The input in this step is either the user's voice or directly entered text, and the output is text data.

[0560] Step 2:

[0561] The terminal sends the converted text data to the server along with image data as needed. Specifically, the terminal converts audio data into text and sends it to the server over the network. The input for this step is text data (and image data as needed), and the output is the transmission of data to the server.

[0562] Step 3:

[0563] The server analyzes the received text data using an emotion recognition engine to identify the user's emotions. In this case, for example, it analyzes the words and context contained in the text and extracts emotional elements such as "tired" or "relaxed." The input for this step is the text data sent from the terminal, and the output is the emotion recognition result.

[0564] Step 4:

[0565] The server generates information using a generative AI model based on the emotion recognition results. Here, it generates information best suited to the user based on specific prompt statements. The inputs to this step are the emotion recognition results and prompts for the generative AI model, and the output is information corresponding to the user's emotions.

[0566] Step 5:

[0567] The server sends the generated information to the terminal. The terminal either displays the received information visually to the user or outputs it as speech using speech synthesis. In this step, the input is the information sent from the server, and the output is the presentation of the results to the user.

[0568] Step 6:

[0569] The user enters feedback on the provided information into the terminal. The terminal sends this feedback data back to the server. The server collects this data and uses it to improve future information generation. In this step, the input is the user's feedback, and the output is the transmission of feedback data to the server.

[0570] (Application Example 2)

[0571] 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."

[0572] There is a need to develop information delivery systems that can respond quickly and appropriately to the diverse emotions and needs of users. In particular, in physical stores, providing customer service methods that enable personalized product suggestions based on customer emotions is a challenge. Currently, conventional information delivery systems have difficulty adequately considering user emotions, and there is a need to achieve more effective personalization.

[0573] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0574] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using a generation AI algorithm and generating relevant information that corresponds to the user's emotions and requests; and means for displaying product suggestions that correspond to the user's emotions via a visual terminal. This makes it possible to quickly provide personalized information and product suggestions that take into account the emotional state of each individual user.

[0575] "Audio, image, and text information" refers to various forms of information received from users, including audio data, visual data, and linguistic data.

[0576] "Integrated analysis methods" refer to techniques that process audio, image, and text information in a complex manner and combine the features obtained from them for analysis.

[0577] A "generative AI algorithm" is a computational method that uses AI technology to generate information based on user input data.

[0578] "Real-time analysis" refers to the process of receiving user input, immediately processing the data, and generating results.

[0579] "User emotions" refers to the psychological state of individual users as interpreted from their voice, facial expressions, and text.

[0580] "Generating relevant information" means creating contextual information and suggestions based on the user's needs and emotions.

[0581] A "visual terminal" is a device used to present information to a user visually, and includes display devices and eyeglass-type terminals.

[0582] "Personalized information" refers to information provided that is customized to the specific needs and preferences of individual users.

[0583] The system for realizing this invention comprises hardware and software for acquiring and integrating user voice, image, and text information. The system consists of a visual terminal such as smart glasses and a server, and uses a generative AI model and emotion engine to analyze the user's emotions.

[0584] The server receives audio and image data provided by the user through smart glasses and converts the audio to text using a speech recognition API (e.g., Google Speech-to-Text). It also analyzes the user's facial expressions using an image processing library (e.g., OpenCV) and identifies their emotional state with an emotion engine. The analyzed data is processed by a generative AI algorithm (e.g., TensorFlow) to create appropriate suggestions based on the user's emotions.

[0585] The generated suggestions are then displayed on the visual terminal's screen. This allows users to receive personalized product and service suggestions tailored to their emotions.

[0586] As a concrete example, a user might say to the glasses, "I'm stressed out from work and want to refresh myself." In this case, the system analyzes the user's request and suggests a "relaxing product." An example of the system's prompt message is as follows:

[0587] "User says: 'I'm feeling stressed from work.' System processes the voice input and facial expression. Generate a personalized product suggestion focused on relaxation."

[0588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0589] Step 1:

[0590] The user provides voice input through smart glasses. This voice data is captured by the device. The input is voice data, and the output is a digital audio file. The device acquires this audio file and prepares it for further processing.

[0591] Step 2:

[0592] The device sends audio data to a cloud server. The server uses a speech recognition API to convert this audio into text. The input is a digital audio file, and the output is text data obtained through speech recognition. The server uses this text as the basis for analysis.

[0593] Step 3:

[0594] The smart glasses capture the user's face. The image data is stored on the device and then sent to a cloud server. The input is image data, and the output is formatted image data for analysis. The server uses an image processing library to analyze the facial expression.

[0595] Step 4:

[0596] The server uses a generative AI model to integrate text data and image data from speech to infer the user's emotions. The input is text data and analyzed image data, and the output is identified emotion data. Based on this emotion data, the server identifies the user's needs.

[0597] Step 5:

[0598] The server generates product and service suggestions using a generative AI algorithm based on the user's emotions and requests. The input is emotion data, and the output is personalized suggestion data. The server references historical data and existing databases to generate the best possible suggestions.

[0599] Step 6:

[0600] The suggested data is displayed on the smart glasses' screen and presented to the user visually. The input is the suggested data, and the output is the visually presented information. The user reviews the information on the display and takes the next action.

[0601] Each step is seamlessly connected, allowing users to automatically receive personalized information in real time.

[0602] 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.

[0603] 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.

[0604] 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.

[0605] [Fourth Embodiment]

[0606] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0607] 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.

[0608] 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).

[0609] 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.

[0610] 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.

[0611] 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).

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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".

[0619] This invention is a system designed to enhance the user's digital experience through multimodal data processing capabilities. This system enables the integrated analysis of voice, image, and text data to generate information tailored to the user's needs. The following describes embodiments for carrying out this invention.

[0620] The server receives audio, image, and text data provided by the user. For audio data, the terminal converts the audio to text and sends it to the server. The server analyzes the received audio, text, and image data, and uses generative AI models to understand the user's requests. Through this analysis, the server determines what the user wants and retrieves relevant data from external services.

[0621] For example, suppose a user speaks into their device saying, "Show me the coffee maker reviews." The device converts this speech into text and sends it to the server. The server analyzes this text, retrieves relevant coffee maker reviews from an external review service, and generates the most relevant and useful information.

[0622] The generated information is displayed visually to the user via the device. In some cases, the information can be read aloud, making it easily accessible to the user. Furthermore, if the user provides feedback or asks additional questions about specific information, the server re-analyzes the content and provides even more detailed information. The server also manages the user's history and preferences, and the information provided is customized for each user.

[0623] In this way, the system of the present invention enables the rapid understanding of the user's complex requirements and the provision of personalized, practical information.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] When a device receives voice input from a user, it converts that voice into text data. This conversion is usually performed in real time by the device's built-in speech recognition system.

[0627] Step 2:

[0628] The device sends the converted text data to the server. Images and existing text data are also sent in the same manner.

[0629] Step 3:

[0630] The server receives text data sent from the terminal, and simultaneously captures images and other data. It then uses a generative AI model to analyze this data in a unified manner.

[0631] Step 4:

[0632] The server uses a generative AI model to analyze the content of incoming data. It identifies the information and actions the user is seeking and generates analysis results based on those requests.

[0633] Step 5:

[0634] The server will, as needed, interact with external information services and applications to obtain data relevant to the analysis results. For example, if a user is requesting product reviews, it will retrieve the latest reviews of that product from an external service.

[0635] Step 6:

[0636] The server integrates the collected information to generate results that are most relevant to the user. These results are then personalized as needed, based on the user's history and preferences.

[0637] Step 7:

[0638] The server sends the generated results to the terminal. The terminal receives this information and either displays it visually to the user or provides it as audio feedback.

[0639] Step 8:

[0640] The user reviews the provided information and enters any additional requests or feedback into the terminal. Based on this input, the processing loop may be restarted.

[0641] (Example 1)

[0642] 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".

[0643] Despite the need for systems that can respond to diverse user requests in real time and provide personalized information, current technologies are insufficient to meet these demands. Furthermore, integrating and effectively utilizing data across multiple media formats (audio, images, text) remains a challenge. Additionally, personalization based on users' past actions and preferences, while effectively collaborating with external information sources, is still incomplete.

[0644] 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.

[0645] In this invention, the server includes means for receiving input data in the form of audio, images, and text and for integratively analyzing it; means for processing the analyzed data in real time using a generative AI model and generating information tailored to the user's requests; and means for presenting the generated information to the user visually or audibly. This enables a rapid and accurate response to user requests and the provision of personalized information.

[0646] "Audio data" refers to information obtained by converting audio into a digital format, which is represented in a form that can be processed by a computer.

[0647] "Image data" refers to a digital representation of visual information, and is data used to analyze two-dimensional visual information using a computer.

[0648] "Text data" refers to information composed of characters and symbols, represented in a digital format, and is in a format that can be analyzed using natural language processing.

[0649] "Integrated analysis" refers to the process of combining and analyzing data in different formats (audio, images, text) to arrive at a comprehensive understanding.

[0650] A "generative AI model" is a model that uses artificial intelligence technology to generate and interpret data, and primarily uses neural networks to generate information.

[0651] "Real-time processing" refers to a process where data is analyzed immediately after it is received, and results are generated with virtually no delay.

[0652] "User requests" refer to the information and services that users ask the system to provide.

[0653] "External information supply services" refer to information and data services provided by other organizations via the internet, and are accessible through APIs, etc.

[0654] "Personalizing" refers to the process of adjusting the content of information and services according to each user's individual preferences and history, thereby providing a personalized experience.

[0655] This invention is a multimodal data processing system designed to enhance the user's digital experience, integrating and analyzing audio, image, and text data to generate information tailored to the user's needs. Specifically, it is configured as follows:

[0656] The server receives audio, image, and text data via the user's input device. For audio data, the device converts the speech to text and sends that data to the server. This conversion can utilize speech recognition software, such as a general-purpose API service.

[0657] The server analyzes the received text and image data in real time using a generative AI model. This AI model, for example, is based on neural network technology and performs analysis that integrates natural language processing and image recognition. As a result, it understands the user's requests and extracts and organizes relevant information.

[0658] When generating information, the server accesses external information supply services to obtain the necessary data. This includes collecting information through application programming interfaces. The acquired information is then personalized based on each user's history and preferences.

[0659] For example, if a user requests by voice, "Tell me the latest camera reviews," the device converts this voice into text, and the server retrieves relevant review information from external services based on that instruction, providing the most useful information.

[0660] The generated information is presented to the user via the terminal, either visually or through audio output. This allows the user to easily access the necessary information. Furthermore, if the user provides feedback or asks additional questions, the server re-analyzes the information based on that feedback, enabling the provision of more precise information.

[0661] Examples of prompt statements include the following:

[0662] "Please analyze the user request: 'Tell me reviews of the latest cameras.' Retrieve information from the data source and generate relevant information."

[0663] In this way, the system of the present invention is able to respond quickly to the diverse and complex needs of users and provide personalized and useful information.

[0664] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0665] Step 1:

[0666] The user inputs voice data using a device. This voice data requests information about the latest camera reviews. The device captures the voice data through its microphone and passes it to voice recognition software in real time.

[0667] Step 2:

[0668] The device converts the audio data into text data. The speech recognition software analyzes the audio waveform to identify phonemes and converts them into strings to output the text data. The converted text data is "Tell me a review of the latest camera."

[0669] Step 3:

[0670] The terminal sends the converted text data to the server. The server, receiving the text data as input, uses a generative AI model to analyze the data and understand the user's request. In this analysis process, the text is tokenized and the AI ​​model understands the context.

[0671] Step 4:

[0672] The server initiates access to external information supply services based on the user's request. For example, it connects to the application programming interface (API) of a service that provides camera review information and retrieves the relevant data. The input for this step is the request, and the output is the collected review information.

[0673] Step 5:

[0674] The server generates information based on the acquired data. Using a generative AI model, it identifies highly relevant reviews and summarizes information valuable to the user. At this stage, the information is personalized based on the user's history and preferences.

[0675] Step 6:

[0676] The server sends the generated information back to the terminal. The terminal then builds an interface to visually display this information to the user. In some cases, it can also use speech synthesis software to play the information as audio for the user to hear.

[0677] Step 7:

[0678] The user provides feedback on the information received or enters additional questions. The device transcribes this feedback back into text and sends it to the server as new input. The server then re-analyzes this feedback to provide more detailed information.

[0679] (Application Example 1)

[0680] 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".

[0681] In today's retail environment, it is difficult for consumers to obtain timely detailed information and reviews of products they are looking for. Especially in physical stores, there are limitations to the quantity and quality of information that store staff can provide, and there is a need to efficiently support consumers' purchasing decisions. Furthermore, there is a lack of means to improve customer satisfaction by providing information tailored to each consumer's preferences.

[0682] 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.

[0683] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text data; means for analyzing the data in real time using a generative AI model and generating information in response to user requests; and means for presenting the information using the user's visual device to realize an interactive sales experience. This makes it possible to quickly and accurately provide consumers with the product information they desire and to realize a personalized purchasing experience.

[0684] "Receiving and integrating audio, image, and text data" means simultaneously receiving different types of data, determining the characteristics and relationships of each data, and deriving an overall result.

[0685] "Using a generative AI model to analyze data in real time and generate information that meets user requests" refers to a process that utilizes artificial intelligence technology to instantly analyze provided data and generate the information most relevant to the user's request.

[0686] "Providing analysis results to the user visually or audibly" means presenting the results of data analysis in a way that the user can see or hear.

[0687] "Collaborating with external services to obtain necessary data" refers to activities that involve communicating with other information provision systems via the internet or other means to acquire necessary information.

[0688] "Personalizing information based on user history and personal preferences" means adjusting the information to be most suitable for each user based on data about their past behavior and unique preferences.

[0689] "Presenting information using the user's visual devices and realizing an interactive sales experience" means displaying information using a display device worn by the user, enabling a purchasing process in which the user and the system mutually influence each other.

[0690] "Analyzing product information using imaging devices in visual devices" refers to a method of photographing products using a camera built into a display device and extracting product-related information from that image data.

[0691] The system realizing this invention functions as an interactive shopping assistant using smart glasses. The server integrates and receives and analyzes voice, image, and text data. This process includes speech recognition software to convert speech to text, image recognition algorithms to process image data, and a text analysis engine that leverages a generative AI model.

[0692] Smart glasses capture the user's voice input through a microphone and convert the audio to text in real time. The user's spoken content is sent to a server, which performs data analysis using a generative AI model. This analysis retrieves the most relevant information to the user's request from external information services and generates results in real time. The generated information is presented visually via a display built into the smart glasses, and in some cases, can be read aloud.

[0693] For example, if a user says, "I want to see reviews for this bag," the smart glasses' camera takes a picture of the bag and sends the image data to a server. This data is analyzed using a generative AI model to retrieve appropriate review information, which is then displayed to the user. Furthermore, recommended products in the same category are also presented. This allows users to enjoy an efficient and personalized shopping experience in the store.

[0694] Examples of prompt messages include inquiries such as, "Show me the reviews for this product," "Do you have any recommended accessories?", and "What items are on sale?".

[0695] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0696] Step 1:

[0697] The device (smart glasses) captures the user's voice input via a microphone. The input voice is converted into text data in real time by speech recognition software. The voice waveform is output as text data and sent to the server.

[0698] Step 2:

[0699] The server analyzes the text data received from the terminal. This analysis uses a generative AI model to understand the user's request. The data processing performed here involves extracting the intent behind the request using natural language processing, resulting in the generation of data that reflects the user's request.

[0700] Step 3:

[0701] Simultaneously, the terminal captures image data taken by the user through the camera and sends it to the server. The server uses an image recognition algorithm to identify the products shown in the video. Image data is taken as input, and product identification information is obtained as output.

[0702] Step 4:

[0703] The server integrates the text data and product identification information obtained in the previous step and connects to relevant external information services. Based on the generated data, it sends database queries to the external services to retrieve the necessary review information and product details.

[0704] Step 5:

[0705] The acquired information is analyzed using a generative AI model to generate information best suited to the user's needs. This analysis includes data correlation and importance evaluation, and relevant information is selected. The final generated result is a set of information to be presented visually or audibly.

[0706] Step 6:

[0707] The server sends the generated information set to the terminal, which then displays it on the smart glasses' screen. Additionally, audio information is provided via the speaker as needed. This allows the user to receive information both visually and aurally.

[0708] 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.

[0709] The present invention is a multimodal data processing system incorporating an emotion engine that recognizes user emotions, enabling it to optimize responses to user requests based on those emotions. This system comprehensively receives and analyzes voice, image, and text data and provides corresponding information to the user. The following describes specific embodiments for carrying out the present invention.

[0710] First, the user provides voice or text input to the device. Upon receiving this input, the device converts the voice into text data and, if necessary, also collects image data and sends it to the server. The server uses a generative AI model and an emotion engine to process the received data comprehensively. The emotion engine recognizes emotions from the user's input and incorporates them into the analysis results.

[0711] The server utilizes a generative AI model to analyze user requests, taking their emotions into account, and generates information as a result. For example, if a user requests via voice, "I've been busy and tired lately, please recommend some relaxing music," the emotion engine recognizes "tired" and "relaxed" as emotional elements. Based on this information, the server collects appropriate relaxing music playlists and sends the generated results to the device.

[0712] The device either visually displays results to the user or provides suggestions via voice. This process customizes the information to best suit the user's emotional state and delivers it accordingly. Furthermore, the system considers the user's past interactions and feedback to further personalize the information it provides.

[0713] In this way, a system incorporating the emotion engine of the present invention can accurately grasp the user's emotions and, based on that, provide information and services to enrich the digital experience.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The user interacts with the device by speaking or typing text. Let's say the user types, "I'm feeling stressed, so I'd like to know how to relax."

[0717] Step 2:

[0718] The device converts voice input into text data and retrieves related images if necessary. It then sends the converted text and image data to the server.

[0719] Step 3:

[0720] The server analyzes the data received from the terminal. Here, it uses an emotion engine to identify the emotion "stress" contained in the user's input.

[0721] Step 4:

[0722] The server uses a generative AI model to understand the user's request and combine it with the results of the emotion engine. For example, it combines the request to relax with the emotion of stress to determine the direction of suggesting an appropriate solution.

[0723] Step 5:

[0724] The server accesses external information services to obtain information on activities and music that can help with relaxation. This includes music streaming services and wellness information platforms.

[0725] Step 6:

[0726] The server creates personalized options that match the user's preferences based on the information it has gathered, taking into account the user's past history and preferences.

[0727] Step 7:

[0728] The server sends the generated results to the terminal. This may include links to relaxing music playlists or stretching videos.

[0729] Step 8:

[0730] The device visually displays the transmitted information to the user and provides audio feedback if necessary. The user can then review this information, utilize the available options, and make additional requests.

[0731] (Example 2)

[0732] 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".

[0733] In recent years, with the increasing diversity and volume of information, there is a growing demand for information tailored to the emotions and needs of individual users. However, conventional systems fail to adequately integrate and provide information while considering user emotions. Furthermore, personalized information provision based on user history and preferences is insufficient, making it difficult to optimize the user experience.

[0734] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0735] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using generative artificial intelligence and generating information that meets the user's requests; and means for incorporating the user's emotions into the analysis results using an emotion recognition engine. This makes it possible to provide information based on the user's emotions and needs, thereby realizing more personalized information delivery.

[0736] "Audio, image, and text information" refers to the types of information input by users, and includes data expressed in the form of audio, images, and text.

[0737] "Integrated analysis" refers to the process of analyzing audio, image, and text data together to comprehensively understand the correlations and meanings between them.

[0738] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate new information and content from data using machine learning.

[0739] An "emotion recognition engine" refers to a technology that detects and analyzes a user's emotions and sensibilities from the input information.

[0740] "Providing visually or audibly" refers to means of informing the user of the analysis results through screen display or audio output.

[0741] "External information services" refer to other information-providing systems or platforms on the internet that are used to obtain necessary data and services.

[0742] "Personalization" refers to the process of optimizing information and services for specific users by taking into account their history and preferences.

[0743] An "application program interface" refers to an interface function that allows information and services to be exchanged between different software programs.

[0744] This invention is a personalized information delivery system that takes into account the user's emotions. The system consists of a terminal, a server, and software components including an emotion recognition engine and generative artificial intelligence.

[0745] The device receives voice, image, and text information from the user. Specifically, it uses a microphone for voice input and a camera to acquire image information. It then uses speech recognition software to convert the voice into text.

[0746] The converted and collected information is sent from the terminal to the server. The server uses an application program interface to obtain the necessary information in order to interact with external information services.

[0747] The server analyzes the received data using an emotion recognition engine. This includes specific software modules, such as algorithms for identifying the user's emotions. The server also uses generative artificial intelligence to generate information based on prompts from the user.

[0748] For example, if a user requests, "I've been busy and tired lately, please recommend some relaxing music," the system will assess emotions such as "tired" and "relaxed" and generate a suitable playlist using an external music streaming service. This analysis result is provided to the user via the device using a visual display or audio output.

[0749] Specific examples of prompt sentences include, "Can you recommend some lighthearted articles about recent weather?" and "Can you recommend a list of relaxing movies?"

[0750] This system allows users to quickly obtain information that matches their emotions, improving the user experience. The system also takes into account user history and preferences, ensuring that the most relevant information is always provided.

[0751] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0752] Step 1:

[0753] The user inputs information to the terminal via voice or text. In the case of voice input, a microphone is used, and the input is converted to text by speech recognition software. The input in this step is either the user's voice or directly entered text, and the output is text data.

[0754] Step 2:

[0755] The terminal sends the converted text data to the server along with image data as needed. Specifically, the terminal converts audio data into text and sends it to the server over the network. The input for this step is text data (and image data as needed), and the output is the transmission of data to the server.

[0756] Step 3:

[0757] The server analyzes the received text data using an emotion recognition engine to identify the user's emotions. In this case, for example, it analyzes the words and context contained in the text and extracts emotional elements such as "tired" or "relaxed." The input for this step is the text data sent from the terminal, and the output is the emotion recognition result.

[0758] Step 4:

[0759] The server generates information using a generative AI model based on the emotion recognition results. Here, it generates information best suited to the user based on specific prompt statements. The inputs to this step are the emotion recognition results and prompts for the generative AI model, and the output is information corresponding to the user's emotions.

[0760] Step 5:

[0761] The server sends the generated information to the terminal. The terminal either displays the received information visually to the user or outputs it as speech using speech synthesis. In this step, the input is the information sent from the server, and the output is the presentation of the results to the user.

[0762] Step 6:

[0763] The user enters feedback on the provided information into the terminal. The terminal sends this feedback data back to the server. The server collects this data and uses it to improve future information generation. In this step, the input is the user's feedback, and the output is the transmission of feedback data to the server.

[0764] (Application Example 2)

[0765] 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".

[0766] There is a need to develop information delivery systems that can respond quickly and appropriately to the diverse emotions and needs of users. In particular, in physical stores, providing customer service methods that enable personalized product suggestions based on customer emotions is a challenge. Currently, conventional information delivery systems have difficulty adequately considering user emotions, and there is a need to achieve more effective personalization.

[0767] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0768] In this invention, the server includes means for receiving and comprehensively analyzing voice, image, and text information; means for analyzing the information in real time using a generation AI algorithm and generating relevant information that corresponds to the user's emotions and requests; and means for displaying product suggestions that correspond to the user's emotions via a visual terminal. This makes it possible to quickly provide personalized information and product suggestions that take into account the emotional state of each individual user.

[0769] "Audio, image, and text information" refers to various forms of information received from users, including audio data, visual data, and linguistic data.

[0770] "Integrated analysis methods" refer to techniques that process audio, image, and text information in a complex manner and combine the features obtained from them for analysis.

[0771] A "generative AI algorithm" is a computational method that uses AI technology to generate information based on user input data.

[0772] "Real-time analysis" refers to the process of receiving user input, immediately processing the data, and generating results.

[0773] "User emotions" refers to the psychological state of individual users as interpreted from their voice, facial expressions, and text.

[0774] "Generating relevant information" means creating contextual information and suggestions based on the user's needs and emotions.

[0775] A "visual terminal" is a device used to present information to a user visually, and includes display devices and eyeglass-type terminals.

[0776] "Personalized information" refers to information provided that is customized to the specific needs and preferences of individual users.

[0777] The system for realizing this invention comprises hardware and software for acquiring and integrating user voice, image, and text information. The system consists of a visual terminal such as smart glasses and a server, and uses a generative AI model and emotion engine to analyze the user's emotions.

[0778] The server receives audio and image data provided by the user through smart glasses and converts the audio to text using a speech recognition API (e.g., Google Speech-to-Text). It also analyzes the user's facial expressions using an image processing library (e.g., OpenCV) and identifies their emotional state with an emotion engine. The analyzed data is processed by a generative AI algorithm (e.g., TensorFlow) to create appropriate suggestions based on the user's emotions.

[0779] The generated suggestions are then displayed on the visual terminal's screen. This allows users to receive personalized product and service suggestions tailored to their emotions.

[0780] As a concrete example, a user might say to the glasses, "I'm stressed out from work and want to refresh myself." In this case, the system analyzes the user's request and suggests a "relaxing product." An example of the system's prompt message is as follows:

[0781] "User says: 'I'm feeling stressed from work.' System processes the voice input and facial expression. Generate a personalized product suggestion focused on relaxation."

[0782] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0783] Step 1:

[0784] The user provides voice input through smart glasses. This voice data is captured by the device. The input is voice data, and the output is a digital audio file. The device acquires this audio file and prepares it for further processing.

[0785] Step 2:

[0786] The device sends audio data to a cloud server. The server uses a speech recognition API to convert this audio into text. The input is a digital audio file, and the output is text data obtained through speech recognition. The server uses this text as the basis for analysis.

[0787] Step 3:

[0788] The smart glasses capture the user's face. The image data is stored on the device and then sent to a cloud server. The input is image data, and the output is formatted image data for analysis. The server uses an image processing library to analyze the facial expression.

[0789] Step 4:

[0790] The server uses a generative AI model to integrate text data and image data from speech to infer the user's emotions. The input is text data and analyzed image data, and the output is identified emotion data. Based on this emotion data, the server identifies the user's needs.

[0791] Step 5:

[0792] The server generates product and service suggestions using a generative AI algorithm based on the user's emotions and requests. The input is emotion data, and the output is personalized suggestion data. The server references historical data and existing databases to generate the best possible suggestions.

[0793] Step 6:

[0794] The suggested data is displayed on the smart glasses' screen and presented to the user visually. The input is the suggested data, and the output is the visually presented information. The user reviews the information on the display and takes the next action.

[0795] Each step is seamlessly connected, allowing users to automatically receive personalized information in real time.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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."

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] The following is further disclosed regarding the embodiments described above.

[0818] (Claim 1)

[0819] A means for receiving and integrating audio, image, and text data,

[0820] A means of analyzing data in real time using a generative AI model and generating information that meets user requirements,

[0821] Means for providing the user with analysis results visually or audibly,

[0822] A means of integrating with external services to obtain necessary data,

[0823] A means of personalizing information based on the user's history and preferences,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1 for converting speech to text.

[0827] (Claim 3)

[0828] The system according to claim 1, wherein the server connects to an external information provision service API.

[0829] "Example 1"

[0830] (Claim 1)

[0831] A means for receiving input data in the form of audio, images, and text, and for integrating and analyzing it,

[0832] A means of using a generative AI model to process analyzed data in real time and generate information that matches the user's requirements,

[0833] A means of presenting the generated information to the user visually or audibly,

[0834] A means of interacting with external information supply services and obtaining necessary relevant data,

[0835] A means of personalizing the acquired information according to the user's behavioral history and preferences,

[0836] A system that includes this.

[0837] (Claim 2)

[0838] The system according to claim 1, which converts audio data into text format.

[0839] (Claim 3)

[0840] The system according to claim 1, wherein the server connects to an application program interface of an external data provision service.

[0841] "Application Example 1"

[0842] (Claim 1)

[0843] A means for receiving and integrating audio, image, and text data,

[0844] A means of analyzing data in real time using a generative AI model and generating information that meets user requirements,

[0845] Means for providing the user with analysis results visually or audibly,

[0846] A means of integrating with external services to obtain necessary data,

[0847] Means of personalizing information based on user history and personal preferences,

[0848] A means of presenting information using the user's visual devices and realizing an interactive sales experience,

[0849] A means of analyzing product information using imaging devices for visual devices,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1 for converting speech to text.

[0853] (Claim 3)

[0854] The system according to claim 1, wherein the server connects to an external information provision service API.

[0855] "Example 2 of combining an emotion engine"

[0856] (Claim 1)

[0857] A means for receiving and integrating audio, image, and text information,

[0858] A means of analyzing information in real time using generative artificial intelligence and generating information that meets the user's requirements,

[0859] A means of incorporating the user's emotions into the analysis results using an emotion recognition engine,

[0860] Means for providing the analysis results to the user visually or audibly,

[0861] A means of obtaining necessary information by linking with external information services,

[0862] A means of personalizing information based on the user's history and preferences,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1 for converting speech to text.

[0866] (Claim 3)

[0867] The system according to claim 1, wherein the server connects to an external information provision service application program interface.

[0868] "Application example 2 of combining emotional engines"

[0869] (Claim 1)

[0870] A means for receiving and integrating audio, image, and text information,

[0871] A means for analyzing information in real time using a generative AI algorithm and generating relevant information that responds to the user's emotions and requests,

[0872] Means for providing the analysis results to the user visually or audibly,

[0873] A means of obtaining necessary information by collaborating with external data supply services,

[0874] A means of personalizing information based on the user's history and preferences,

[0875] A means of displaying product suggestions tailored to the user's emotions via a visual terminal,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1 for converting speech into text.

[0879] (Claim 3)

[0880] The system according to claim 1, wherein the server connects to an interface for an external information supply service. [Explanation of symbols]

[0881] 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 means for receiving and integrating audio, image, and text data, A means of analyzing data in real time using a generative AI model and generating information that meets user requirements, Means for providing the user with analysis results visually or audibly, A means of integrating with external services to obtain necessary data, A means of personalizing information based on the user's history and preferences, A system that includes this.

2. The system according to claim 1 for converting speech to text.

3. The system according to claim 1, wherein the server connects to an external information provision service API.

Images