System

Abstract

A system is provided.SOLUTION: A system comprising: input means for a user to input a search query into a terminal; transmitting means for the terminal to transmit the search query to a server; generating means for the server to receive the search query and collect related information from the Internet; filtering and summarizing means for the server to filter the collected information and create a summary; voice synthesizing means for the server to convert the summary into voice data; transmitting means for the server to transmit the voice data to the terminal; and playing means for the terminal to play the received voice data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In today's world, users have an increasing need to quickly and efficiently gather various information in their daily lives. However, using a smartphone to obtain information while walking or traveling can be dangerous. Furthermore, there is often no time to sit down and gather information in a calm environment. In these situations, there is a need for a method that allows users to obtain information efficiently and safely. [Means for solving the problem]

[0005] The present invention provides a system in which a user inputs a search query into a terminal, the terminal transmits the search query to a server, and the server collects related information from the Internet based on the search query. The system also includes means for filtering the collected information, creating a summary, converting the summary into voice data, and transmitting the speech data to the terminal. This allows users to efficiently obtain necessary information by voice while walking or on the move.

[0006] "User" refers to the entity that utilizes the system to search for and receive information via voice.

[0007] "Terminal" refers to a device operated by a user, which inputs search queries, transmits them to a server, and plays back audio data.

[0008] A "search query" refers to a request to search for information that a user enters into a terminal.

[0009] "Transmission means" refers to a function that enables a terminal to transmit a search query to a server.

[0010] "Server" refers to a computer system that receives search queries and collects and processes related information from the Internet.

[0011] "Generating means" refers to the function of the server to collect relevant information based on a search query.

[0012] "Filtering and organization means" refers to the function of sorting the information collected by the server and organizing it in a format that is useful to the user.

[0013] "Speech synthesis means" refers to the function by which the server converts organized information into voice data.

[0014] "Playback means" refers to the function of the terminal to play back audio data.

[0015] "Means for identifying" refers to the functionality by which the server identifies relevant web pages based on a search query.

[0016] "Format" refers to the function by which the server arranges the filtered and organized information in a form appropriate for the user. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a 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.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0031] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention provides a system for users to efficiently and securely gather information. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts the information into voice data, and transmits it back to the terminal. A practical implementation of this system is described below.

[0039] Parts operated by the user

[0040] First, the user installs a dedicated application on their smartphone or other device. They launch the application and enter the required information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0041] Device behavior

[0042] The device receives the search query entered by the user and sends it to the server. When sending, the search query is sent to the server in the form of an HTTP request using the POST method. This ensures that the user's search query reaches the server safely and quickly.

[0043] Server Operation

[0044] The server receives the search query and begins collecting information based on the query. Specifically, the server's internal AI generation module analyzes the query and collects information from related web pages and APIs. For example, if the query contains weather forecast information, it will retrieve data from a reliable weather forecast site.

[0045] Filtering and organizing information

[0046] The server then runs the collected information through a filtering algorithm, which evaluates the data based on factors such as reliability, recency, and relevance. The most relevant information is then summarized and presented to the user in text form. This summary is then formatted in a user-friendly format.

[0047] Speech synthesis and transmission

[0048] The server passes the summarized text data to a speech synthesis engine to generate voice data. The generated voice data is then sent to the terminal in the form of an HTTP response. The server specifies the type of voice data and transmits it in the appropriate format.

[0049] Playing audio on your device

[0050] The device decodes the voice data received from the server and plays it back in the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided to the user as voice.

[0051] As a concrete example, let us consider the series of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, converts it into audio data, and returns it to the device. The device then plays the audio data, allowing the user to hear "the weather in Tokyo this weekend."

[0052] This allows users to safely use their smartphones while walking or on the move and efficiently collect information.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data.

[0056] Step 2:

[0057] The device sends the acquired search query to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0058] Step 3:

[0059] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[0060] Step 4:

[0061] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[0062] Step 5:

[0063] The server evaluates the collected data through a filtering algorithm, filtering the data based on its reliability and recency, and selecting the most appropriate information.

[0064] Step 6:

[0065] The server summarizes the selected information and generates text data to be presented to the user. The server uses a summarization process to organize the collected data into a concise and easy-to-understand format.

[0066] Step 7:

[0067] The server passes the summarized text data to a speech synthesis engine to generate audio data. The server then inputs the text into a speech synthesis API and obtains the generated audio file.

[0068] Step 8:

[0069] The server sends the generated audio data to the device, which then encodes the audio data as an HTTP response and sends it back to the device.

[0070] Step 9:

[0071] The device decodes the audio data received from the server and inputs it into the audio player. The device then plays the audio data, allowing the user to hear "This weekend's weather in Tokyo" aloud.

[0072] These steps allow the user to efficiently gather information while walking.

[0073] Example 1

[0074] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0075] In conventional information gathering systems, users often only obtain information text-based, making it difficult to access information hands-free, especially while on the move or at work. Furthermore, the reliability and relevance of the collected information may not be adequately evaluated, preventing users from efficiently obtaining the information they need. Furthermore, information is often disorganized and not provided in a format that is easy for users to understand.

[0076] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0077] In this invention, the server includes a collection means for collecting relevant information using a generative model, a filtering and organizing means for evaluating the information using a filtering algorithm and creating a summary, and a speech synthesis means for converting the summary into speech data, thereby enabling a user to efficiently obtain reliable information by voice without using their hands and providing it in an easy-to-understand format.

[0078] An "input means" is a device or interface that allows a user to input a search query into a terminal.

[0079] "Transmission means" refers to the functions and protocols that allow a terminal to transmit a search query to a server.

[0080] A "collection means" is a mechanism by which the server uses the generative model to collect relevant information.

[0081] "Filtering and Consolidation Methods" are the algorithms and processes used by the server to evaluate and summarize the information collected.

[0082] "Speech synthesis means" refers to the technology or engine that the server uses to convert summarized text data into speech data.

[0083] "Playback means" refers to a device or software for playing back audio data received by a terminal.

[0084] "Means for identification" refers to the functionality that allows the server to retrieve information from relevant web pages or APIs based on the search query.

[0085] The "shaping means" is a method by which the server shapes the information evaluated by the filtering and organizing means into a form that is most appropriate for the user.

[0086] The present invention is an information processing system that allows a user to collect information efficiently and safely. Specific embodiments of this system will be described below.

[0087] 1. User operations

[0088] First, the user installs a dedicated application on their smartphone or personal computer. When the application is launched, a search bar appears. The user enters a search query, such as "Tokyo weather this weekend." The entered query is processed as text data by the device.

[0089] 2. Device Operation

[0090] The device retrieves the search query entered by the user and sends it to the server in the form of an HTTP POST request. Specifically, the device sends a request including query parameters to the https: / / example.com / search endpoint. The communication is encrypted to ensure security and data integrity.

[0091] 3. Server Operation

[0092] The server analyzes the received HTTP request and creates and inputs a prompt to a generative AI model (for example, a natural language processing module). The prompt might be something like, "Please provide information about the weather in Tokyo this weekend." This prompt is then used to collect the required information in real time from related web pages and APIs.

[0093] 4. Filtering and organizing information

[0094] The server runs the information obtained from the generative AI model through a filtering algorithm and evaluates it based on its reliability, recency, and relevance. Based on the evaluation results, the server selects the most appropriate information and summarizes it in text format. The organized information is then formatted in a way that is easy for users to understand.

[0095] 5. Speech synthesis and transmission

[0096] The server inputs the summarized text data into a speech synthesis engine such as the Google® Text-to-Speech API to generate audio data. The generated audio data is encoded in MP3 format and sent back to the device as an HTTP response. At this time, the server adds appropriate header information to specify the type of data.

[0097] 6. Audio playback on device

[0098] The device decodes the audio data received from the server and plays it in a dedicated application. The device's audio playback module (such as Android Media Player or iOS AVPlayer) captures the audio data and begins playing it for the user. For example, it might provide audio information such as, "The weather in Tokyo this weekend will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees."

[0099] Examples and prompts

[0100] For example, if a user wants to know "the weather in Tokyo this weekend," the query would look like this:

[0101] A user starts a smartphone application and enters "Weather in Tokyo this weekend."

[0102] The terminal sends this input to the server.

[0103] The server collects, organizes, and filters information using generative AI models.

[0104] The organized information is converted into audio data and sent to the terminal.

[0105] The terminal plays the audio data, allowing the user to obtain information through audio.

[0106] Example prompt sentence:

[0107] "Please provide information about the weather in Tokyo this weekend."

[0108] In this way, users can efficiently obtain up-to-date and reliable information through voice without using their hands.

[0109] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0110] Step 1:

[0111] A user enters a search query into a device. Specifically, the user launches an application on a smartphone or PC and enters "Tokyo weather this weekend" into the search bar. The entered query is processed as text data.

[0112] Input: The search query entered by the user (e.g., "Weather in Tokyo this weekend")

[0113] Output: Search query data in text format

[0114] Step 2:

[0115] The device sends the search query to the server. The device sends the search query for the acquired text data to the server as an HTTP POST request. For example, a request including query parameters is sent to the endpoint https: / / example.com / search. The communication may be encrypted during transmission.

[0116] Input: Search query data in text format

[0117] Output: HTTP POST request sent to the server

[0118] Step 3:

[0119] The server receives the search query and collects information. Using a generative AI model, it generates the prompt "Please provide information about the weather in Tokyo this weekend" and collects information in real time from relevant web pages and APIs.

[0120] Input: The search query in the received HTTP POST request

[0121] Output: Relevant information collected

[0122] Step 4:

[0123] The server filters and organizes the collected information. Filtering algorithms are used to evaluate the information based on reliability, currency, and relevance. The selected information is summarized and organized in text format.

[0124] Input: Collected relevant information

[0125] Output: Summarized text data

[0126] Step 5:

[0127] The server converts the summarized text data into audio data. Using a speech synthesis engine such as the Google Text-to-Speech API, the text data is converted into audio data (e.g., MP3 format), and the appropriate header information is added before sending the data to the device as an HTTP response.

[0128] Input: Summarized text data

[0129] Output: Generated audio data (e.g. MP3 file)

[0130] Step 6:

[0131] The device plays the audio data received from the server. The device's audio playback module (e.g., MediaPlayer on Android or AVPlayer on iOS) plays the audio data and provides information to the user.

[0132] Input: Audio data received from the server

[0133] Output: Information provided by audio playback

[0134] Through the above steps, the user can efficiently and safely obtain the latest information by voice.

[0135] (Application example 1)

[0136] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0137] To improve work efficiency and safety in factories, there is a need for a system that allows workers to efficiently collect the necessary information via robots. However, with existing systems, workers must manually search for information and perform their tasks based on that information, which takes time and reduces work efficiency. Furthermore, manually collecting information carries the risk of generating incorrect information. This leads to issues such as reduced factory productivity and difficulty in improving the working environment.

[0138] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0139] In this invention, the server includes an input means for a user to input a search query to a terminal, a transmission means for the terminal to transmit the search query to the server, a generation means for the server to receive the search query and collect related information from the Internet, a filtering and organizing means for filtering the collected information and creating a summary, a voice synthesis means for the server to convert the summary into voice data, a transmission means for the server to transmit the voice data to the terminal, a playback means for playing the voice data received by the terminal, a robot control means for providing a search result to a factory robot by voice based on the user query, a voice input means for inputting the user query by voice, and a voice playback means for the robot to play the voice data. This enables workers to efficiently obtain necessary information and reflect it in their work simply by inputting a voice query.

[0140] A "terminal" is a device through which a user inputs a search query and communicates with a server.

[0141] A "search query" is text data that a user enters to find out the information they want to know.

[0142] A "server" is a device that receives search queries, collects, filters, organizes, converts related information into audio data, and transmits it to a terminal.

[0143] The "generation means" is a function that collects information based on a search query within the server.

[0144] "Filtering and organization" refers to the ability to evaluate collected information and select the information that is most relevant to the user.

[0145] The "voice synthesis means" is a function that converts text data into voice data.

[0146] "Transmission means" is a function by which the terminal and the server transmit and receive data.

[0147] The "playback means" is a function for playing back audio data received by the terminal.

[0148] The "robot control means" is a function that enables a factory robot to provide search results by voice based on a user query.

[0149] The "voice input means" is a function that allows the user to input a query by voice.

[0150] "Audio playback means" is a function that enables the robot to play back audio data.

[0151] This invention is a system that allows users to efficiently and safely collect information. The user inputs a search query using a voice input means on a terminal, and the terminal sends the query to a server. The server collects information based on the received search query, filters and organizes it, converts it into voice data, and sends it back to the terminal. The terminal plays the received voice data and provides the information to the user. Furthermore, this system is compatible with factory robots, obtaining information in real time via the robots and providing work instructions via voice.

[0152] Hardware used

[0153] Terminals: Mobile devices and fixed equipment used within the factory

[0154] Server: A computer system that collects, filters, and organizes information from the Internet.

[0155] Factory robots: Mechanical devices for automating work

[0156] Software used

[0157] HTTP request library (e.g., requests): Sends data from the device to the server

[0158] Speech synthesis library (e.g., pyttsx3): converts text data generated on the server into speech data.

[0159] Generative AI model: Used to collect and summarize information within the server

[0160] Speech input and playback libraries (e.g., SpeechRecognition, playsound): Used to process and play audio data on devices and robots

[0161] Data processing and calculation flow

[0162] 1. Voice input: The user inputs a search query to the factory robot by voice. For example, the user might say, "Tell me the details of the next process."

[0163] 2. Transmission means: The terminal sends this query to the server using the HTTP POST method.

[0164] 3. Generating means: The server uses the generative AI model to collect information corresponding to the query from the Internet.

[0165] 4. Filtering and organization: The server filters the collected information and summarizes it in a form suitable for the user.

[0166] 5. Speech synthesis means: The server converts the summarized text information into speech data.

[0167] 6. Retransmission means: The server retransmits the generated voice data to the terminal.

[0168] 7. Audio playback means: The terminal and the robot play back the received audio data to provide information to the user.

[0169] Specific examples

[0170] For example, consider a scenario where a worker in a factory sends a voice query to a robot saying, "Tell me the details of the next process." The robot sends this query to a server, which uses a generative AI model to collect information about the next process from reliable data sources. It also filters and organizes the collected information, summarizing only the parts that are important to the user and generating voice data. This voice data is then sent to a terminal, and the robot plays it back, allowing the worker to obtain the details of the next process by voice in real time.

[0171] Prompt Sentence Examples

[0172] Could you please give me more details about the next step?

[0173] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0174] Step 1:

[0175] A user enters a search query by voice into a factory robot.

[0176] Input: User's voice query (e.g., "Please tell me the details of the next step")

[0177] Output: Audio data

[0178] How it works: When a user speaks a voice query to the robot, the robot's internal voice recognition system captures the speech and converts it into text data.

[0179] Step 2:

[0180] The terminal transmits the converted text data to the server.

[0181] Input: Text data converted from audio

[0182] Output: HTTP request sent to the server

[0183] Specific operation: The robot's control system converts voice data into text and sends it to the server using the HTTP POST method. At this time, the text data is included in the request payload.

[0184] Step 3:

[0185] The server uses a generative AI model to collect information based on the search query received.

[0186] Input: Search query as an HTTP request

[0187] Output: Collected raw information data

[0188] How it works: The server analyzes the received search query and triggers a generative AI model, which gathers relevant information from the internet, for example, by retrieving detailed information about the next step from multiple data sources.

[0189] Step 4:

[0190] The server filters and organizes the collected information to create a summary.

[0191] Input: Collected raw information data

[0192] Output: Summarized text data

[0193] How it works: The server uses a filtering algorithm to select reliable and relevant information from the collected data, then summarizes only the necessary information and formats it as text data.

[0194] Step 5:

[0195] The server converts the summarized text data into audio data.

[0196] Input: Summarized text data

[0197] Output: Audio data

[0198] Specific operation: The server's speech synthesis engine receives the summarized text data and converts it into natural-sounding speech data, for example, creating a voice message to inform the user of the details of the next step.

[0199] Step 6:

[0200] The server transmits the generated voice data to the terminal.

[0201] Input: Audio data

[0202] Output: HTTP response sent to the device

[0203] Specific operation: The server packages the generated audio data as an HTTP response and sends it to the terminal. In this case, the audio data is included in the body of the response.

[0204] Step 7:

[0205] The terminal plays back the received audio data.

[0206] Input: Audio data received from the server

[0207] Output: Audio information presented to the user

[0208] Specific operation: The robot's control system decodes the received voice data and plays it back to the user through the built-in speaker. For example, the user is told, "The next step is to attach part A to part B."

[0209] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0210] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a device, and the device transmits the query to a server. The server collects, filters, and organizes the information, converts it into emotion-adjusted voice data, and transmits it back to the device.

[0211] Parts operated by the user

[0212] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0213] The emotion engine, which is also used by users, analyzes their emotions during and after a search. The emotion engine analyzes the user's tone of voice and facial expressions in real time and reflects the results throughout the system.

[0214] Device behavior

[0215] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0216] Server Operation

[0217] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[0218] The generative AI module analyzes the query and gathers data from relevant web pages and APIs, for example, weather forecast information is pulled from trusted weather sites.

[0219] Filtering and organizing information

[0220] The server evaluates the collected information through a filtering algorithm, filtering the information based on its reliability and recency, and selects the most appropriate information.

[0221] The selected information is then summarised and generated as text data for the user. The summarised text data is then adjusted by an emotion engine, taking into account the user's emotions.

[0222] Emotion-based speech synthesis and transmission

[0223] The server then passes the summarized text data to a speech synthesis engine to generate speech data, which then adjusts the tone of the speech or modifies the content based on the user's emotions.

[0224] The generated audio data is sent to the terminal again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[0225] Emotion-based audio playback on the device

[0226] The device decodes the voice data received from the server and plays it back within the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a voice tone that includes warmth and encouragement according to the user's emotions.

[0227] As a concrete example, we will explain the sequence of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, uses an emotion engine to generate voice data appropriate to the user's emotions, and returns it to the device. The device then plays the voice data, allowing the user to hear "the weather in Tokyo this weekend" by voice.

[0228] This allows users to use their smartphones safely while walking or on the move, efficiently collect information, and enjoy a better user experience by taking their emotions into consideration.

[0229] The processing flow will be explained below.

[0230] Step 1:

[0231] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data. The device's built-in emotion engine analyzes the user's voice and facial expressions to recognize their current emotional state.

[0232] Step 2:

[0233] The device sends the acquired search query and emotion data to the server as an HTTP request. The device then encodes the input search query and emotion data into JSON format and sends it to the server's API endpoint using the POST method.

[0234] Step 3:

[0235] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" and emotion data from the request body. The server passes the extracted query to the generation AI module and the emotion data to the emotion engine.

[0236] Step 4:

[0237] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[0238] Step 5:

[0239] The server evaluates the collected data through a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information then undergoes a summary process, and is generated as text data to be provided to the user.

[0240] Step 6:

[0241] The server's emotion engine adjusts the collected information based on the user's emotional state. Specifically, the tone and content of the information provided are adjusted to match the user's emotions. For example, if the user is feeling anxious, the information provided will be adjusted to a tone that gives a sense of security.

[0242] Step 7:

[0243] The server passes the summarized text data to a speech synthesis engine to generate speech data, which adjusts the tone of the speech based on the user's emotions.

[0244] Step 8:

[0245] The server sends the generated audio data to the device. The server encodes the audio data as an HTTP response and sends it back to the device. The device receives the audio data.

[0246] Step 9:

[0247] The device decodes the voice data received from the server and plays it back to the user. The device then inputs the voice data into an audio player and provides the user with a voice report of "Tokyo's weather this weekend." Based on the analysis results of the emotion engine, the tone and content of the voice are also adjusted appropriately according to the emotion.

[0248] This allows users to efficiently collect information while walking and receive information that takes into account their emotions at the time.

[0249] Example 2

[0250] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0251] Conventional information gathering systems require users to look directly at the screen, which makes them unsafe when used while walking or moving. In addition, because they do not take into account the user's emotions, the user experience is uniform, making it difficult to provide information tailored to the needs of each individual user.

[0252] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means that receives a search query and collects related information from a network, a filtering and organization means that filters the collected information and creates a summary, an emotion analysis means that analyzes the user's emotion, and a voice synthesis means that converts the adjusted summary into voice data. This allows the user to safely collect information while walking or on the move, and obtain information in a form that takes into consideration the user's emotions.

[0253] The "input means" refers to a means by which a user inputs a search query into a terminal.

[0254] The "transmission means" is a means by which the terminal transmits the search query to the server.

[0255] The "generating means" is a means by which the server receives the search query and collects related information from a network.

[0256] "Filtering and organizing means" refers to means for filtering and summarizing the information collected by the server.

[0257] The "emotion analysis means" is a means by which the server analyzes the user's emotions.

[0258] The "adjustment means" is a means by which the server adjusts the summary based on the user's feelings.

[0259] The "voice synthesis means" is a means by which the server converts the adjusted summary into voice data.

[0260] The "reproducing means" is a means for reproducing the audio data received by the terminal.

[0261] The "identification means" is a means by which the server identifies relevant information sources based on a search query.

[0262] The "shaping means" is a means by which the server shapes the information evaluated by the filtering and organizing means into the most appropriate form.

[0263] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts it into speech data adjusted based on emotions, and transmits it back to the terminal. The specific configuration and processing are described below.

[0264] composition

[0265] User operation method

[0266] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0267] Terminal transmission means

[0268] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0269] Server generation and filtering means

[0270] The server receives an HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server passes this extracted query to the generation AI module, which analyzes the query and collects data from relevant web pages and APIs. For example, if the weather forecast information is needed, it retrieves data from a reliable weather forecast site.

[0271] Server emotion analysis and adjustment means

[0272] The server evaluates the collected information using a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information goes through a summary process and is generated as text data to be provided to the user. This text data is adjusted by an emotion engine. The emotion engine analyzes the user's emotions and adjusts the information to suit the user's emotions.

[0273] Server's voice synthesis and transmission methods

[0274] The server passes the summarized text data to a speech synthesis engine to generate audio data. The speech synthesis engine adjusts the tone of the voice based on the user's emotions or modifies the content. The generated audio data is then sent to the device again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format (e.g., MP3, WAV).

[0275] Device playback method

[0276] The device decodes the voice data received from the server and plays it back within a specific application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a tone of warmth and encouragement that corresponds to the user's emotions.

[0277] Specific examples

[0278] The user launches the dedicated application and enters "This weekend's weather in Tokyo." The device encodes this information into JSON format and sends a POST request to the server. The server analyzes the query and collects weather data from weather forecast sites. It filters the information and summarizes it as "Saturday and Sunday will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees." The emotion engine analyzes this summary, and if it determines that the user is a little tired, the speech synthesis engine generates voice data in a warm tone saying, "The weekend will be sunny so you can refresh yourself!" The server sends this voice data to the device in MP3 format, and the device plays the audio within the app.

[0279] Prompt Sentence Examples

[0280] "What's the weather like in Tokyo this weekend?" Please generate voice data that conveys weather information in a cheerful and encouraging tone, taking into account the user's emotions.

[0281] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0282] Step 1:

[0283] The user launches a dedicated application and enters a search query.

[0284] Input: A natural language search query typed by a user (e.g., "What's the weather like in Tokyo this weekend?")

[0285] Output: Text data of the search query

[0286] How it works: A user opens a dedicated application on their smartphone and enters "Tokyo weather this weekend" in the search bar. This text data is stored internally and passed to the next processing step.

[0287] Step 2:

[0288] The device sends the search query to the server as an HTTP request.

[0289] Input: Text data of the search query

[0290] Output: HTTP request in JSON format sent to the server

[0291] Specific operation: The device encodes the search query entered by the user into JSON format and sends it to the server using the POST method, to the server's API endpoint.

[0292] Step 3:

[0293] The server receives the HTTP request and extracts the search query.

[0294] Input: HTTP request sent from the terminal

[0295] Output: Extracted search query text data

[0296] Specific operation: The server receives an HTTP request and extracts a search query such as "Weather in Tokyo this weekend" from the request body.

[0297] Step 4:

[0298] The server passes the search query to a generation AI module for analysis.

[0299] Input: Extracted search query

[0300] Output: Information related to the analysis results (e.g., weather information)

[0301] How it works: The server passes the search query to the AI ​​generation module, which then analyzes the query and collects relevant information from the network, such as data from a weather forecast website.

[0302] Step 5:

[0303] The server filters the collected information and creates a summary.

[0304] Input: relevant information obtained from the generative AI module

[0305] Output: filtered and summarized text data

[0306] How it works: The server filters the collected information using an evaluation algorithm and summarizes the information selected based on reliability and recency, for example, "Saturday and Sunday will be sunny, with a maximum temperature of 25°C and a minimum temperature of 18°C."

[0307] Step 6:

[0308] The server analyzes the summarized information using an emotion engine and makes adjustments.

[0309] Input: Summarized text data

[0310] Output: Text data adjusted based on user sentiment

[0311] How it works: The server uses an emotion engine to tailor information based on the user's emotional data (e.g., past search history and real-time voice tone). For example, if the server determines that the user is tired, it will tailor the information to something like, "We hope the weekend will be sunny so you can feel refreshed!"

[0312] Step 7:

[0313] The server passes the adjusted text data to a speech synthesis engine to generate speech data.

[0314] Input: Adjusted text data

[0315] Output: Synthesized voice data

[0316] Specific operation: The server passes the adjusted text data to a speech synthesis engine to generate audio data (e.g., MP3 format). The speech synthesis engine generates audio with a tone that matches the user's emotions.

[0317] Step 8:

[0318] The server sends the generated audio data to the terminal as an HTTP response.

[0319] Input: Generated audio data

[0320] Output: HTTP response sent to the device

[0321] Specific operation: The generated audio data is sent to the terminal in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[0322] Step 9:

[0323] The terminal plays back the received audio data.

[0324] Input: Audio data received from the server

[0325] Output: Audio playback that the user can hear

[0326] Specific operation: The device decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" will be heard in a voice tone that corresponds to the user's emotions.

[0327] These steps allow users to safely gather information while walking or on the move, and to receive that information in an emotionally sensitive way.

[0328] (Application example 2)

[0329] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] Conventional systems simply provide information when users input search queries to obtain information, without taking into account the user's emotions or circumstances. As a result, when receiving information in stressful or rushed situations in factories or production lines, the information delivery method may be inappropriate, resulting in reduced production efficiency and management capabilities. Furthermore, if information is not properly filtered and organized, the information provided to users may be excessive or inaccurate. To solve these issues, it is necessary to analyze the user's emotional state in real time and provide information appropriate to that emotion.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0332] In this invention, the server includes an input means for a user to input a search query into a terminal, a transmission means for the terminal to transmit the search query to the server, an emotion analysis means for the terminal to analyze the user's emotion, and an adjustment means for adjusting the voice tone based on the emotion analysis means. This makes it possible to provide information by voice in an appropriate tone according to the user's emotion. This allows managers, particularly in factories and production lines, to obtain the information they need quickly and with little stress, improving production efficiency and management capabilities.

[0333] A "user" is a person who uses the system and is the entity that inputs a search query and obtains information.

[0334] A "terminal" is a computing device through which a user inputs a search query and communicates with a server.

[0335] A "search query" is text data that a user enters to identify the information they are looking for.

[0336] "Server" means a central control system for receiving search queries, collecting relevant information, and providing it to users.

[0337] The "transmission means" is a function for transmitting a search query from a terminal to a server, and for transmitting voice data from the server to a terminal.

[0338] A "generator" is a processing mechanism by which the server collects relevant information based on a search query.

[0339] "Filtering and organization" refers to the mechanism by which the server evaluates the information it collects and summarizes it in a form that is most relevant to the user.

[0340] The "voice synthesis means" is a mechanism for converting summarized information into voice data.

[0341] The "playback means" is a function for allowing the user to listen to the audio data received on the terminal.

[0342] The "emotion analysis means" is a mechanism for analyzing the user's emotional state in real time.

[0343] The "adjustment means" is a mechanism for adjusting the tone of the voice based on the emotion analysis means.

[0344] A "network" is an infrastructure for information communication such as the Internet.

[0345] A "data page" is a web page or database that contains information that exists on a network.

[0346] The "shaping means" is a mechanism for optimizing the information evaluated by the filtering and organizing means in a form that is presented to the user.

[0347] The present invention provides a system that allows a user to input a search query, collects information based on the query, analyzes the user's emotions, and provides the information in an appropriate voice tone. This system is composed of a terminal, a server, a transmission means, an input means, an emotion analysis means, a voice synthesis means, and a playback means.

[0348] Parts operated by the user

[0349] First, the user installs a dedicated application on their smart device (e.g., smartphone or tablet). They launch the application and enter the required information into the search bar. For example, they enter "current production efficiency." This input is processed as text data. The user then uses an emotion analysis tool, which analyzes the user's emotions during and after the search in real time. The emotion analysis tool analyzes the user's tone of voice and facial expressions, and reflects the results in the system.

[0350] Device behavior

[0351] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0352] Server Operation

[0353] The server receives an HTTP request and extracts the search query from the request body. The server passes this extracted query to the generation AI module. The generation AI module analyzes the query and collects the necessary information from related data pages and APIs. The server evaluates the collected information using a filtering algorithm and selects the most appropriate information based on its reliability and recency. The selected information undergoes a summarization process, generating text data to be provided to the user. The summarized text data is then adjusted by a sentiment analysis means to take into account the user's emotions.

[0354] Emotion-based speech synthesis and transmission

[0355] The server passes the summarized text data to a speech synthesis engine to generate voice data. The speech synthesis engine adjusts the voice tone according to the user's emotions based on the emotion analysis means described above. For example, if it determines that the user is in an emergency, it uses a quick and easy-to-understand voice tone. The generated voice data is again sent to the terminal in the form of an HTTP response.

[0356] Emotion-based audio playback on the device

[0357] The terminal decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an urgent tone to reflect the user's sense of urgency.

[0358] Specific examples

[0359] For example, if a line manager on a factory production line asks a robot assistant, "What is the current production efficiency?", the query is sent to a server, which collects and organizes the latest production data. If the emotion analysis tool determines that the user is under stress, the robot responds in a calm voice, "Current production efficiency is 95%. There are delays on some lines."

[0360] Prompt Sentence Examples

[0361] What is the current production efficiency?

[0362] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0363] Step 1:

[0364] A user enters a search query into a device.

[0365] (input)

[0366] The user enters specific information into the search bar of the dedicated application on the device, for example, "current production efficiency."

[0367] (output)

[0368] The search query is saved as text data on the device.

[0369] (Specific actions)

[0370] When a user uses a smartphone or tablet interface to enter text into the application's search bar, the emotion analysis means simultaneously analyzes the user's tone of voice and facial expressions.

[0371] Step 2:

[0372] The device sends a search query to the server.

[0373] (input)

[0374] User-entered search queries and real-time analyzed sentiment data.

[0375] (output)

[0376] The search query and sentiment data are sent to the server as an HTTP request.

[0377] (Specific actions)

[0378] The device creates an HTTP request, encodes the search query in JSON format, includes the emotion data in the request, and sends it to the server's API endpoint using the POST method.

[0379] Step 3:

[0380] The server receives the HTTP request and passes the search query to the generative AI model.

[0381] (input)

[0382] The search query and sentiment data sent to the server.

[0383] (output)

[0384] A search query is input into the generative AI model.

[0385] (Specific actions)

[0386] The server extracts search queries and sentiment data from the body of the received HTTP request, inputs the extracted search queries into a generative AI model, and collects information from related data pages and APIs.

[0387] Step 4:

[0388] Filtering and organizing the information collected by the server.

[0389] (input)

[0390] Relevant information collected by generative AI models.

[0391] (output)

[0392] A filtered and organized summary of information.

[0393] (Specific actions)

[0394] The server runs a filtering algorithm on the collected information to select the most relevant data based on its reliability and recency, and then the selected information is summarised and generated as concise text data.

[0395] Step 5:

[0396] The server passes the summarized text data to the speech synthesis engine.

[0397] (input)

[0398] Summarized text and sentiment data.

[0399] (output)

[0400] Audio data adjusted according to the user's emotions.

[0401] (Specific actions)

[0402] The server inputs the summarized text data into a speech synthesis engine, which adjusts the tone of the voice based on the emotion analysis means and generates speech data.

[0403] Step 6:

[0404] The server sends the audio data to the terminal.

[0405] (input)

[0406] The generated audio data.

[0407] (output)

[0408] The audio data is sent to the device as an HTTP response.

[0409] (Specific actions)

[0410] The server encodes the generated audio data in an appropriate format and sends it to the terminal as an HTTP response.

[0411] Step 7:

[0412] The terminal receives and plays the audio data.

[0413] (input)

[0414] Audio data sent from the server.

[0415] (output)

[0416] The user receives audio information in a tone that corresponds to the user's emotion.

[0417] (Specific actions)

[0418] The device decodes the received voice data and plays it back using a dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an appropriate tone of voice, reflecting the user's real-time emotions.

[0419] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0420] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0421] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0422] [Second embodiment]

[0423] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0424] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0425] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0426] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0427] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0428] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0429] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0430] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0431] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0432] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0433] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0434] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0435] The present invention provides a system for users to efficiently and securely gather information. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts the information into voice data, and transmits it back to the terminal. A practical implementation of this system is described below.

[0436] Parts operated by the user

[0437] First, the user installs a dedicated application on their smartphone or other device. They launch the application and enter the required information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0438] Device behavior

[0439] The device receives the search query entered by the user and sends it to the server. When sending, the search query is sent to the server in the form of an HTTP request using the POST method. This ensures that the user's search query reaches the server safely and quickly.

[0440] Server Operation

[0441] The server receives the search query and begins collecting information based on the query. Specifically, the server's internal AI generation module analyzes the query and collects information from related web pages and APIs. For example, if the query contains weather forecast information, it will retrieve data from a reliable weather forecast site.

[0442] Filtering and organizing information

[0443] The server then runs the collected information through a filtering algorithm, which evaluates the data based on factors such as reliability, recency, and relevance. The most relevant information is then summarized and presented to the user in text form. This summary is then formatted in a user-friendly format.

[0444] Speech synthesis and transmission

[0445] The server passes the summarized text data to a speech synthesis engine to generate voice data. The generated voice data is then sent to the terminal in the form of an HTTP response. The server specifies the type of voice data and transmits it in the appropriate format.

[0446] Playing audio on your device

[0447] The device decodes the voice data received from the server and plays it back in the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided to the user as voice.

[0448] As a concrete example, let us consider the series of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, converts it into audio data, and returns it to the device. The device then plays the audio data, allowing the user to hear "the weather in Tokyo this weekend."

[0449] This allows users to safely use their smartphones while walking or on the move and efficiently collect information.

[0450] The processing flow will be explained below.

[0451] Step 1:

[0452] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data.

[0453] Step 2:

[0454] The device sends the acquired search query to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0455] Step 3:

[0456] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[0457] Step 4:

[0458] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[0459] Step 5:

[0460] The server evaluates the collected data through a filtering algorithm, filtering the data based on its reliability and recency, and selecting the most appropriate information.

[0461] Step 6:

[0462] The server summarizes the selected information and generates text data to be presented to the user. The server uses a summarization process to organize the collected data into a concise and easy-to-understand format.

[0463] Step 7:

[0464] The server passes the summarized text data to a speech synthesis engine to generate audio data. The server then inputs the text into a speech synthesis API and obtains the generated audio file.

[0465] Step 8:

[0466] The server sends the generated audio data to the device, which then encodes the audio data as an HTTP response and sends it back to the device.

[0467] Step 9:

[0468] The device decodes the audio data received from the server and inputs it into the audio player. The device then plays the audio data, allowing the user to hear "This weekend's weather in Tokyo" aloud.

[0469] These steps allow the user to efficiently gather information while walking.

[0470] Example 1

[0471] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0472] In conventional information gathering systems, users often only obtain information text-based, making it difficult to access information hands-free, especially while on the move or at work. Furthermore, the reliability and relevance of the collected information may not be adequately evaluated, preventing users from efficiently obtaining the information they need. Furthermore, information is often disorganized and not provided in a format that is easy for users to understand.

[0473] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0474] In this invention, the server includes a collection means for collecting relevant information using a generative model, a filtering and organizing means for evaluating the information using a filtering algorithm and creating a summary, and a speech synthesis means for converting the summary into speech data, thereby enabling a user to efficiently obtain reliable information by voice without using their hands and providing it in an easy-to-understand format.

[0475] An "input means" is a device or interface that allows a user to input a search query into a terminal.

[0476] "Transmission means" refers to the functions and protocols that allow a terminal to transmit a search query to a server.

[0477] A "collection means" is a mechanism by which the server uses the generative model to collect relevant information.

[0478] "Filtering and Consolidation Methods" are the algorithms and processes used by the server to evaluate and summarize the information collected.

[0479] "Speech synthesis means" refers to the technology or engine that the server uses to convert summarized text data into speech data.

[0480] "Playback means" refers to a device or software for playing back audio data received by a terminal.

[0481] "Means for identification" refers to the functionality that allows the server to retrieve information from relevant web pages or APIs based on the search query.

[0482] The "shaping means" is a method by which the server shapes the information evaluated by the filtering and organizing means into a form that is most appropriate for the user.

[0483] The present invention is an information processing system that allows a user to collect information efficiently and safely. Specific embodiments of this system will be described below.

[0484] 1. User operations

[0485] First, the user installs a dedicated application on their smartphone or personal computer. When the application is launched, a search bar appears. The user enters a search query, such as "Tokyo weather this weekend." The entered query is processed as text data by the device.

[0486] 2. Device Operation

[0487] The device retrieves the search query entered by the user and sends it to the server in the form of an HTTP POST request. Specifically, the device sends a request including query parameters to the https: / / example.com / search endpoint. The communication is encrypted to ensure security and data integrity.

[0488] 3. Server Operation

[0489] The server analyzes the received HTTP request and creates and inputs a prompt to a generative AI model (for example, a natural language processing module). The prompt might be something like, "Please provide information about the weather in Tokyo this weekend." This prompt is then used to collect the required information in real time from related web pages and APIs.

[0490] 4. Filtering and organizing information

[0491] The server runs the information obtained from the generative AI model through a filtering algorithm and evaluates it based on its reliability, recency, and relevance. Based on the evaluation results, the server selects the most appropriate information and summarizes it in text format. The organized information is then formatted in a way that is easy for users to understand.

[0492] 5. Speech synthesis and transmission

[0493] The server inputs the summarized text data into a speech synthesis engine such as the Google Text-to-Speech API to generate audio data. The generated audio data is encoded in MP3 format and sent back to the device as an HTTP response. At this time, the server adds appropriate header information to specify the data type.

[0494] 6. Audio playback on device

[0495] The device decodes the audio data received from the server and plays it in a dedicated application. The device's audio playback module (such as Android's MediaPlayer or iOS's AVPlayer) captures the audio data and begins playing it for the user. For example, it might provide audio information such as, "The weather in Tokyo this weekend will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees."

[0496] Examples and prompts

[0497] For example, if a user wants to know "the weather in Tokyo this weekend," the query would look like this:

[0498] A user starts a smartphone application and enters "Weather in Tokyo this weekend."

[0499] The terminal sends this input to the server.

[0500] The server collects, organizes, and filters information using generative AI models.

[0501] The organized information is converted into audio data and sent to the terminal.

[0502] The terminal plays the audio data, allowing the user to obtain information through audio.

[0503] Example prompt sentence:

[0504] "Please provide information about the weather in Tokyo this weekend."

[0505] In this way, users can efficiently obtain up-to-date and reliable information through voice without using their hands.

[0506] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0507] Step 1:

[0508] A user enters a search query into a device. Specifically, the user launches an application on a smartphone or PC and enters "Tokyo weather this weekend" into the search bar. The entered query is processed as text data.

[0509] Input: The search query entered by the user (e.g., "Weather in Tokyo this weekend")

[0510] Output: Search query data in text format

[0511] Step 2:

[0512] The device sends the search query to the server. The device sends the search query for the acquired text data to the server as an HTTP POST request. For example, a request including query parameters is sent to the endpoint https: / / example.com / search. The communication may be encrypted during transmission.

[0513] Input: Search query data in text format

[0514] Output: HTTP POST request sent to the server

[0515] Step 3:

[0516] The server receives the search query and collects information. Using a generative AI model, it generates the prompt "Please provide information about the weather in Tokyo this weekend" and collects information in real time from relevant web pages and APIs.

[0517] Input: The search query in the received HTTP POST request

[0518] Output: Relevant information collected

[0519] Step 4:

[0520] The server filters and organizes the collected information. Filtering algorithms are used to evaluate the information based on reliability, currency, and relevance. The selected information is summarized and organized in text format.

[0521] Input: Collected relevant information

[0522] Output: Summarized text data

[0523] Step 5:

[0524] The server converts the summarized text data into audio data. Using a speech synthesis engine such as the Google Text-to-Speech API, the text data is converted into audio data (e.g., MP3 format), and the appropriate header information is added before sending the data to the device as an HTTP response.

[0525] Input: Summarized text data

[0526] Output: Generated audio data (e.g. MP3 file)

[0527] Step 6:

[0528] The device plays the audio data received from the server. The device's audio playback module (e.g., MediaPlayer on Android or AVPlayer on iOS) plays the audio data and provides information to the user.

[0529] Input: Audio data received from the server

[0530] Output: Information provided by audio playback

[0531] Through the above steps, the user can efficiently and safely obtain the latest information by voice.

[0532] (Application example 1)

[0533] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0534] To improve work efficiency and safety in factories, there is a need for a system that allows workers to efficiently collect the necessary information via robots. However, with existing systems, workers must manually search for information and perform their tasks based on that information, which takes time and reduces work efficiency. Furthermore, manually collecting information carries the risk of generating incorrect information. This leads to issues such as reduced factory productivity and difficulty in improving the working environment.

[0535] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0536] In this invention, the server includes an input means for a user to input a search query to a terminal, a transmission means for the terminal to transmit the search query to the server, a generation means for the server to receive the search query and collect related information from the Internet, a filtering and organizing means for filtering the collected information and creating a summary, a voice synthesis means for the server to convert the summary into voice data, a transmission means for the server to transmit the voice data to the terminal, a playback means for playing the voice data received by the terminal, a robot control means for providing a search result to a factory robot by voice based on the user query, a voice input means for inputting the user query by voice, and a voice playback means for the robot to play the voice data. This enables workers to efficiently obtain necessary information and reflect it in their work simply by inputting a voice query.

[0537] A "terminal" is a device through which a user inputs a search query and communicates with a server.

[0538] A "search query" is text data that a user enters to find out the information they want to know.

[0539] A "server" is a device that receives search queries, collects, filters, organizes, converts related information into audio data, and transmits it to a terminal.

[0540] The "generation means" is a function that collects information based on a search query within the server.

[0541] "Filtering and organization" refers to the ability to evaluate collected information and select the information that is most relevant to the user.

[0542] The "voice synthesis means" is a function that converts text data into voice data.

[0543] "Transmission means" is a function by which the terminal and the server transmit and receive data.

[0544] The "playback means" is a function for playing back audio data received by the terminal.

[0545] The "robot control means" is a function that enables a factory robot to provide search results by voice based on a user query.

[0546] The "voice input means" is a function that allows the user to input a query by voice.

[0547] "Audio playback means" is a function that enables the robot to play back audio data.

[0548] This invention is a system that allows users to efficiently and safely collect information. The user inputs a search query using a voice input means on a terminal, and the terminal sends the query to a server. The server collects information based on the received search query, filters and organizes it, converts it into voice data, and sends it back to the terminal. The terminal plays the received voice data and provides the information to the user. Furthermore, this system is compatible with factory robots, obtaining information in real time via the robots and providing work instructions via voice.

[0549] Hardware used

[0550] Terminals: Mobile devices and fixed equipment used within the factory

[0551] Server: A computer system that collects, filters, and organizes information from the Internet.

[0552] Factory robots: Mechanical devices for automating work

[0553] Software used

[0554] HTTP request library (e.g., requests): Sends data from the device to the server

[0555] Speech synthesis library (e.g., pyttsx3): converts text data generated on the server into speech data.

[0556] Generative AI model: Used to collect and summarize information within the server

[0557] Speech input and playback libraries (e.g., SpeechRecognition, playsound): Used to process and play audio data on devices and robots

[0558] Data processing and calculation flow

[0559] 1. Voice input: The user inputs a search query to the factory robot by voice. For example, the user might say, "Tell me the details of the next process."

[0560] 2. Transmission means: The terminal sends this query to the server using the HTTP POST method.

[0561] 3. Generating means: The server uses the generative AI model to collect information corresponding to the query from the Internet.

[0562] 4. Filtering and organization: The server filters the collected information and summarizes it in a form suitable for the user.

[0563] 5. Speech synthesis means: The server converts the summarized text information into speech data.

[0564] 6. Retransmission means: The server retransmits the generated voice data to the terminal.

[0565] 7. Audio playback means: The terminal and the robot play back the received audio data to provide information to the user.

[0566] Specific examples

[0567] For example, consider a scenario where a worker in a factory sends a voice query to a robot saying, "Tell me the details of the next process." The robot sends this query to a server, which uses a generative AI model to collect information about the next process from reliable data sources. It also filters and organizes the collected information, summarizing only the parts that are important to the user and generating voice data. This voice data is then sent to a terminal, and the robot plays it back, allowing the worker to obtain the details of the next process by voice in real time.

[0568] Prompt Sentence Examples

[0569] Could you please give me more details about the next step?

[0570] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0571] Step 1:

[0572] A user enters a search query by voice into a factory robot.

[0573] Input: User's voice query (e.g., "Please tell me the details of the next step")

[0574] Output: Audio data

[0575] How it works: When a user speaks a voice query to the robot, the robot's internal voice recognition system captures the speech and converts it into text data.

[0576] Step 2:

[0577] The terminal transmits the converted text data to the server.

[0578] Input: Text data converted from audio

[0579] Output: HTTP request sent to the server

[0580] Specific operation: The robot's control system converts voice data into text and sends it to the server using the HTTP POST method. At this time, the text data is included in the request payload.

[0581] Step 3:

[0582] The server uses a generative AI model to collect information based on the search query received.

[0583] Input: Search query as an HTTP request

[0584] Output: Collected raw information data

[0585] How it works: The server analyzes the received search query and triggers a generative AI model, which gathers relevant information from the internet, for example, by retrieving detailed information about the next step from multiple data sources.

[0586] Step 4:

[0587] The server filters and organizes the collected information to create a summary.

[0588] Input: Collected raw information data

[0589] Output: Summarized text data

[0590] How it works: The server uses a filtering algorithm to select reliable and relevant information from the collected data, then summarizes only the necessary information and formats it as text data.

[0591] Step 5:

[0592] The server converts the summarized text data into audio data.

[0593] Input: Summarized text data

[0594] Output: Audio data

[0595] Specific operation: The server's speech synthesis engine receives the summarized text data and converts it into natural-sounding speech data, for example, creating a voice message to inform the user of the details of the next step.

[0596] Step 6:

[0597] The server transmits the generated voice data to the terminal.

[0598] Input: Audio data

[0599] Output: HTTP response sent to the device

[0600] Specific operation: The server packages the generated audio data as an HTTP response and sends it to the terminal. In this case, the audio data is included in the body of the response.

[0601] Step 7:

[0602] The terminal plays back the received audio data.

[0603] Input: Audio data received from the server

[0604] Output: Audio information presented to the user

[0605] Specific operation: The robot's control system decodes the received voice data and plays it back to the user through the built-in speaker. For example, the user is told, "The next step is to attach part A to part B."

[0606] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0607] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a device, and the device transmits the query to a server. The server collects, filters, and organizes the information, converts it into emotion-adjusted voice data, and transmits it back to the device.

[0608] Parts operated by the user

[0609] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0610] The emotion engine, which is also used by users, analyzes their emotions during and after a search. The emotion engine analyzes the user's tone of voice and facial expressions in real time and reflects the results throughout the system.

[0611] Device behavior

[0612] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0613] Server Operation

[0614] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[0615] The generative AI module analyzes the query and gathers data from relevant web pages and APIs, for example, weather forecast information is pulled from trusted weather sites.

[0616] Filtering and organizing information

[0617] The server evaluates the collected information through a filtering algorithm, filtering the information based on its reliability and recency, and selects the most appropriate information.

[0618] The selected information is then summarised and generated as text data for the user. The summarised text data is then adjusted by an emotion engine, taking into account the user's emotions.

[0619] Emotion-based speech synthesis and transmission

[0620] The server then passes the summarized text data to a speech synthesis engine to generate speech data, which then adjusts the tone of the speech or modifies the content based on the user's emotions.

[0621] The generated audio data is sent to the terminal again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[0622] Emotion-based audio playback on the device

[0623] The device decodes the voice data received from the server and plays it back within the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a voice tone that includes warmth and encouragement according to the user's emotions.

[0624] As a concrete example, we will explain the sequence of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, uses an emotion engine to generate voice data appropriate to the user's emotions, and returns it to the device. The device then plays the voice data, allowing the user to hear "the weather in Tokyo this weekend" by voice.

[0625] This allows users to use their smartphones safely while walking or on the move, efficiently collect information, and enjoy a better user experience by taking their emotions into consideration.

[0626] The processing flow will be explained below.

[0627] Step 1:

[0628] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data. The device's built-in emotion engine analyzes the user's voice and facial expressions to recognize their current emotional state.

[0629] Step 2:

[0630] The device sends the acquired search query and emotion data to the server as an HTTP request. The device then encodes the input search query and emotion data into JSON format and sends it to the server's API endpoint using the POST method.

[0631] Step 3:

[0632] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" and emotion data from the request body. The server passes the extracted query to the generation AI module and the emotion data to the emotion engine.

[0633] Step 4:

[0634] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[0635] Step 5:

[0636] The server evaluates the collected data through a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information then undergoes a summary process, and is generated as text data to be provided to the user.

[0637] Step 6:

[0638] The server's emotion engine adjusts the collected information based on the user's emotional state. Specifically, the tone and content of the information provided are adjusted to match the user's emotions. For example, if the user is feeling anxious, the information provided will be adjusted to a tone that gives a sense of security.

[0639] Step 7:

[0640] The server passes the summarized text data to a speech synthesis engine to generate speech data, which adjusts the tone of the speech based on the user's emotions.

[0641] Step 8:

[0642] The server sends the generated audio data to the device. The server encodes the audio data as an HTTP response and sends it back to the device. The device receives the audio data.

[0643] Step 9:

[0644] The device decodes the voice data received from the server and plays it back to the user. The device then inputs the voice data into an audio player and provides the user with a voice report of "Tokyo's weather this weekend." Based on the analysis results of the emotion engine, the tone and content of the voice are also adjusted appropriately according to the emotion.

[0645] This allows users to efficiently collect information while walking and receive information that takes into account their emotions at the time.

[0646] Example 2

[0647] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0648] Conventional information gathering systems require users to look directly at the screen, which makes them unsafe when used while walking or moving. In addition, because they do not take into account the user's emotions, the user experience is uniform, making it difficult to provide information tailored to the needs of each individual user.

[0649] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means that receives a search query and collects related information from a network, a filtering and organization means that filters the collected information and creates a summary, an emotion analysis means that analyzes the user's emotion, and a voice synthesis means that converts the adjusted summary into voice data. This allows the user to safely collect information while walking or on the move, and obtain information in a form that takes into consideration the user's emotions.

[0650] The "input means" refers to a means by which a user inputs a search query into a terminal.

[0651] The "transmission means" is a means by which the terminal transmits the search query to the server.

[0652] The "generating means" is a means by which the server receives the search query and collects related information from a network.

[0653] "Filtering and organizing means" refers to means for filtering and summarizing the information collected by the server.

[0654] The "emotion analysis means" is a means by which the server analyzes the user's emotions.

[0655] The "adjustment means" is a means by which the server adjusts the summary based on the user's feelings.

[0656] The "voice synthesis means" is a means by which the server converts the adjusted summary into voice data.

[0657] The "reproducing means" is a means for reproducing the audio data received by the terminal.

[0658] The "identification means" is a means by which the server identifies relevant information sources based on a search query.

[0659] The "shaping means" is a means by which the server shapes the information evaluated by the filtering and organizing means into the most appropriate form.

[0660] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts it into speech data adjusted based on emotions, and transmits it back to the terminal. The specific configuration and processing are described below.

[0661] composition

[0662] User operation method

[0663] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0664] Terminal transmission means

[0665] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0666] Server generation and filtering means

[0667] The server receives an HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server passes this extracted query to the generation AI module, which analyzes the query and collects data from relevant web pages and APIs. For example, if the weather forecast information is needed, it retrieves data from a reliable weather forecast site.

[0668] Server emotion analysis and adjustment means

[0669] The server evaluates the collected information using a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information goes through a summary process and is generated as text data to be provided to the user. This text data is adjusted by an emotion engine. The emotion engine analyzes the user's emotions and adjusts the information to suit the user's emotions.

[0670] Server's voice synthesis and transmission methods

[0671] The server passes the summarized text data to a speech synthesis engine to generate audio data. The speech synthesis engine adjusts the tone of the voice based on the user's emotions or modifies the content. The generated audio data is then sent to the device again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format (e.g., MP3, WAV).

[0672] Device playback method

[0673] The device decodes the voice data received from the server and plays it back within a specific application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a tone of warmth and encouragement that corresponds to the user's emotions.

[0674] Specific examples

[0675] The user launches the dedicated application and enters "This weekend's weather in Tokyo." The device encodes this information into JSON format and sends a POST request to the server. The server analyzes the query and collects weather data from weather forecast sites. It filters the information and summarizes it as "Saturday and Sunday will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees." The emotion engine analyzes this summary, and if it determines that the user is a little tired, the speech synthesis engine generates voice data in a warm tone saying, "The weekend will be sunny so you can refresh yourself!" The server sends this voice data to the device in MP3 format, and the device plays the audio within the app.

[0676] Prompt Sentence Examples

[0677] "What's the weather like in Tokyo this weekend?" Please generate voice data that conveys weather information in a cheerful and encouraging tone, taking into account the user's emotions.

[0678] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0679] Step 1:

[0680] The user launches a dedicated application and enters a search query.

[0681] Input: A natural language search query typed by a user (e.g., "What's the weather like in Tokyo this weekend?")

[0682] Output: Text data of the search query

[0683] How it works: A user opens a dedicated application on their smartphone and enters "Tokyo weather this weekend" in the search bar. This text data is stored internally and passed to the next processing step.

[0684] Step 2:

[0685] The device sends the search query to the server as an HTTP request.

[0686] Input: Text data of the search query

[0687] Output: HTTP request in JSON format sent to the server

[0688] Specific operation: The device encodes the search query entered by the user into JSON format and sends it to the server using the POST method, to the server's API endpoint.

[0689] Step 3:

[0690] The server receives the HTTP request and extracts the search query.

[0691] Input: HTTP request sent from the terminal

[0692] Output: Extracted search query text data

[0693] Specific operation: The server receives an HTTP request and extracts a search query such as "Weather in Tokyo this weekend" from the request body.

[0694] Step 4:

[0695] The server passes the search query to a generation AI module for analysis.

[0696] Input: Extracted search query

[0697] Output: Information related to the analysis results (e.g., weather information)

[0698] How it works: The server passes the search query to the AI ​​generation module, which then analyzes the query and collects relevant information from the network, such as data from a weather forecast website.

[0699] Step 5:

[0700] The server filters the collected information and creates a summary.

[0701] Input: relevant information obtained from the generative AI module

[0702] Output: filtered and summarized text data

[0703] How it works: The server filters the collected information using an evaluation algorithm and summarizes the information selected based on reliability and recency, for example, "Saturday and Sunday will be sunny, with a maximum temperature of 25°C and a minimum temperature of 18°C."

[0704] Step 6:

[0705] The server analyzes the summarized information using an emotion engine and makes adjustments.

[0706] Input: Summarized text data

[0707] Output: Text data adjusted based on user sentiment

[0708] How it works: The server uses an emotion engine to tailor information based on the user's emotional data (e.g., past search history and real-time voice tone). For example, if the server determines that the user is tired, it will tailor the information to something like, "We hope the weekend will be sunny so you can feel refreshed!"

[0709] Step 7:

[0710] The server passes the adjusted text data to a speech synthesis engine to generate speech data.

[0711] Input: Adjusted text data

[0712] Output: Synthesized voice data

[0713] Specific operation: The server passes the adjusted text data to a speech synthesis engine to generate audio data (e.g., MP3 format). The speech synthesis engine generates audio with a tone that matches the user's emotions.

[0714] Step 8:

[0715] The server sends the generated audio data to the terminal as an HTTP response.

[0716] Input: Generated audio data

[0717] Output: HTTP response sent to the device

[0718] Specific operation: The generated audio data is sent to the terminal in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[0719] Step 9:

[0720] The terminal plays back the received audio data.

[0721] Input: Audio data received from the server

[0722] Output: Audio playback that the user can hear

[0723] Specific operation: The device decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" will be heard in a voice tone that corresponds to the user's emotions.

[0724] These steps allow users to safely gather information while walking or on the move, and to receive that information in an emotionally sensitive way.

[0725] (Application example 2)

[0726] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0727] Conventional systems simply provide information when users input search queries to obtain information, without taking into account the user's emotions or circumstances. As a result, when receiving information in stressful or rushed situations in factories or production lines, the information delivery method may be inappropriate, resulting in reduced production efficiency and management capabilities. Furthermore, if information is not properly filtered and organized, the information provided to users may be excessive or inaccurate. To solve these issues, it is necessary to analyze the user's emotional state in real time and provide information appropriate to that emotion.

[0728] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0729] In this invention, the server includes an input means for a user to input a search query into a terminal, a transmission means for the terminal to transmit the search query to the server, an emotion analysis means for the terminal to analyze the user's emotion, and an adjustment means for adjusting the voice tone based on the emotion analysis means. This makes it possible to provide information by voice in an appropriate tone according to the user's emotion. This allows managers, particularly in factories and production lines, to obtain the information they need quickly and with little stress, improving production efficiency and management capabilities.

[0730] A "user" is a person who uses the system and is the entity that inputs a search query and obtains information.

[0731] A "terminal" is a computing device through which a user inputs a search query and communicates with a server.

[0732] A "search query" is text data that a user enters to identify the information they are looking for.

[0733] "Server" means a central control system for receiving search queries, collecting relevant information, and providing it to users.

[0734] The "transmission means" is a function for transmitting a search query from a terminal to a server, and for transmitting voice data from the server to a terminal.

[0735] A "generator" is a processing mechanism by which the server collects relevant information based on a search query.

[0736] "Filtering and organization" refers to the mechanism by which the server evaluates the information it collects and summarizes it in a form that is most relevant to the user.

[0737] The "voice synthesis means" is a mechanism for converting summarized information into voice data.

[0738] The "playback means" is a function for allowing the user to listen to the audio data received on the terminal.

[0739] The "emotion analysis means" is a mechanism for analyzing the user's emotional state in real time.

[0740] The "adjustment means" is a mechanism for adjusting the tone of the voice based on the emotion analysis means.

[0741] A "network" is an infrastructure for information communication such as the Internet.

[0742] A "data page" is a web page or database that contains information that exists on a network.

[0743] The "shaping means" is a mechanism for optimizing the information evaluated by the filtering and organizing means in a form that is presented to the user.

[0744] The present invention provides a system that allows a user to input a search query, collects information based on the query, analyzes the user's emotions, and provides the information in an appropriate voice tone. This system is composed of a terminal, a server, a transmission means, an input means, an emotion analysis means, a voice synthesis means, and a playback means.

[0745] Parts operated by the user

[0746] First, the user installs a dedicated application on their smart device (e.g., smartphone or tablet). They launch the application and enter the required information into the search bar. For example, they enter "current production efficiency." This input is processed as text data. The user then uses an emotion analysis tool, which analyzes the user's emotions during and after the search in real time. The emotion analysis tool analyzes the user's tone of voice and facial expressions, and reflects the results in the system.

[0747] Device behavior

[0748] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0749] Server Operation

[0750] The server receives an HTTP request and extracts the search query from the request body. The server passes this extracted query to the generation AI module. The generation AI module analyzes the query and collects the necessary information from related data pages and APIs. The server evaluates the collected information using a filtering algorithm and selects the most appropriate information based on its reliability and recency. The selected information undergoes a summarization process, generating text data to be provided to the user. The summarized text data is then adjusted by a sentiment analysis means to take into account the user's emotions.

[0751] Emotion-based speech synthesis and transmission

[0752] The server passes the summarized text data to a speech synthesis engine to generate voice data. The speech synthesis engine adjusts the voice tone according to the user's emotions based on the emotion analysis means described above. For example, if it determines that the user is in an emergency, it uses a quick and easy-to-understand voice tone. The generated voice data is again sent to the terminal in the form of an HTTP response.

[0753] Emotion-based audio playback on the device

[0754] The terminal decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an urgent tone to reflect the user's sense of urgency.

[0755] Specific examples

[0756] For example, if a line manager on a factory production line asks a robot assistant, "What is the current production efficiency?", the query is sent to a server, which collects and organizes the latest production data. If the emotion analysis tool determines that the user is under stress, the robot responds in a calm voice, "Current production efficiency is 95%. There are delays on some lines."

[0757] Prompt Sentence Examples

[0758] What is the current production efficiency?

[0759] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0760] Step 1:

[0761] A user enters a search query into a device.

[0762] (input)

[0763] The user enters specific information into the search bar of the dedicated application on the device, for example, "current production efficiency."

[0764] (output)

[0765] The search query is saved as text data on the device.

[0766] (Specific actions)

[0767] When a user uses a smartphone or tablet interface to enter text into the application's search bar, the emotion analysis means simultaneously analyzes the user's tone of voice and facial expressions.

[0768] Step 2:

[0769] The device sends a search query to the server.

[0770] (input)

[0771] User-entered search queries and real-time analyzed sentiment data.

[0772] (output)

[0773] The search query and sentiment data are sent to the server as an HTTP request.

[0774] (Specific actions)

[0775] The device creates an HTTP request, encodes the search query in JSON format, includes the emotion data in the request, and sends it to the server's API endpoint using the POST method.

[0776] Step 3:

[0777] The server receives the HTTP request and passes the search query to the generative AI model.

[0778] (input)

[0779] The search query and sentiment data sent to the server.

[0780] (output)

[0781] A search query is input into the generative AI model.

[0782] (Specific actions)

[0783] The server extracts search queries and sentiment data from the body of the received HTTP request, inputs the extracted search queries into a generative AI model, and collects information from related data pages and APIs.

[0784] Step 4:

[0785] Filtering and organizing the information collected by the server.

[0786] (input)

[0787] Relevant information collected by generative AI models.

[0788] (output)

[0789] A filtered and organized summary of information.

[0790] (Specific actions)

[0791] The server runs a filtering algorithm on the collected information to select the most relevant data based on its reliability and recency, and then the selected information is summarised and generated as concise text data.

[0792] Step 5:

[0793] The server passes the summarized text data to the speech synthesis engine.

[0794] (input)

[0795] Summarized text and sentiment data.

[0796] (output)

[0797] Audio data adjusted according to the user's emotions.

[0798] (Specific actions)

[0799] The server inputs the summarized text data into a speech synthesis engine, which adjusts the tone of the voice based on the emotion analysis means and generates speech data.

[0800] Step 6:

[0801] The server sends the audio data to the terminal.

[0802] (input)

[0803] The generated audio data.

[0804] (output)

[0805] The audio data is sent to the device as an HTTP response.

[0806] (Specific actions)

[0807] The server encodes the generated audio data in an appropriate format and sends it to the terminal as an HTTP response.

[0808] Step 7:

[0809] The terminal receives and plays the audio data.

[0810] (input)

[0811] Audio data sent from the server.

[0812] (output)

[0813] The user receives audio information in a tone that corresponds to the user's emotion.

[0814] (Specific actions)

[0815] The device decodes the received voice data and plays it back using a dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an appropriate tone of voice, reflecting the user's real-time emotions.

[0816] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0817] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0818] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0819] [Third embodiment]

[0820] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0821] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0822] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0823] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0824] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0825] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0826] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0827] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0828] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0829] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0830] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0831] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0832] The present invention provides a system for users to efficiently and securely gather information. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts the information into voice data, and transmits it back to the terminal. A practical implementation of this system is described below.

[0833] Parts operated by the user

[0834] First, the user installs a dedicated application on their smartphone or other device. They launch the application and enter the required information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[0835] Device behavior

[0836] The device receives the search query entered by the user and sends it to the server. When sending, the search query is sent to the server in the form of an HTTP request using the POST method. This ensures that the user's search query reaches the server safely and quickly.

[0837] Server Operation

[0838] The server receives the search query and begins collecting information based on the query. Specifically, the server's internal AI generation module analyzes the query and collects information from related web pages and APIs. For example, if the query contains weather forecast information, it will retrieve data from a reliable weather forecast site.

[0839] Filtering and organizing information

[0840] The server then runs the collected information through a filtering algorithm, which evaluates the data based on factors such as reliability, recency, and relevance. The most relevant information is then summarized and presented to the user in text form. This summary is then formatted in a user-friendly format.

[0841] Speech synthesis and transmission

[0842] The server passes the summarized text data to a speech synthesis engine to generate voice data. The generated voice data is then sent to the terminal in the form of an HTTP response. The server specifies the type of voice data and transmits it in the appropriate format.

[0843] Playing audio on your device

[0844] The device decodes the voice data received from the server and plays it back in the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided to the user as voice.

[0845] As a concrete example, let us consider the series of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, converts it into audio data, and returns it to the device. The device then plays the audio data, allowing the user to hear "the weather in Tokyo this weekend."

[0846] This allows users to safely use their smartphones while walking or on the move and efficiently collect information.

[0847] The processing flow will be explained below.

[0848] Step 1:

[0849] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data.

[0850] Step 2:

[0851] The device sends the acquired search query to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[0852] Step 3:

[0853] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[0854] Step 4:

[0855] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[0856] Step 5:

[0857] The server evaluates the collected data through a filtering algorithm, filtering the data based on its reliability and recency, and selecting the most appropriate information.

[0858] Step 6:

[0859] The server summarizes the selected information and generates text data to be presented to the user. The server uses a summarization process to organize the collected data into a concise and easy-to-understand format.

[0860] Step 7:

[0861] The server passes the summarized text data to a speech synthesis engine to generate audio data. The server then inputs the text into a speech synthesis API and obtains the generated audio file.

[0862] Step 8:

[0863] The server sends the generated audio data to the device, which then encodes the audio data as an HTTP response and sends it back to the device.

[0864] Step 9:

[0865] The device decodes the audio data received from the server and inputs it into the audio player. The device then plays the audio data, allowing the user to hear "This weekend's weather in Tokyo" aloud.

[0866] These steps allow the user to efficiently gather information while walking.

[0867] Example 1

[0868] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0869] In conventional information gathering systems, users often only obtain information text-based, making it difficult to access information hands-free, especially while on the move or at work. Furthermore, the reliability and relevance of the collected information may not be adequately evaluated, preventing users from efficiently obtaining the information they need. Furthermore, information is often disorganized and not provided in a format that is easy for users to understand.

[0870] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0871] In this invention, the server includes a collection means for collecting relevant information using a generative model, a filtering and organizing means for evaluating the information using a filtering algorithm and creating a summary, and a speech synthesis means for converting the summary into speech data, thereby enabling a user to efficiently obtain reliable information by voice without using their hands and providing it in an easy-to-understand format.

[0872] An "input means" is a device or interface that allows a user to input a search query into a terminal.

[0873] "Transmission means" refers to the functions and protocols that allow a terminal to transmit a search query to a server.

[0874] A "collection means" is a mechanism by which the server uses the generative model to collect relevant information.

[0875] "Filtering and Consolidation Methods" are the algorithms and processes used by the server to evaluate and summarize the information collected.

[0876] "Speech synthesis means" refers to the technology or engine that the server uses to convert summarized text data into speech data.

[0877] "Playback means" refers to a device or software for playing back audio data received by a terminal.

[0878] "Means for identification" refers to the functionality that allows the server to retrieve information from relevant web pages or APIs based on the search query.

[0879] The "shaping means" is a method by which the server shapes the information evaluated by the filtering and organizing means into a form that is most appropriate for the user.

[0880] The present invention is an information processing system that allows a user to collect information efficiently and safely. Specific embodiments of this system will be described below.

[0881] 1. User operations

[0882] First, the user installs a dedicated application on their smartphone or personal computer. When the application is launched, a search bar appears. The user enters a search query, such as "Tokyo weather this weekend." The entered query is processed as text data by the device.

[0883] 2. Device Operation

[0884] The device retrieves the search query entered by the user and sends it to the server in the form of an HTTP POST request. Specifically, the device sends a request including query parameters to the https: / / example.com / search endpoint. The communication is encrypted to ensure security and data integrity.

[0885] 3. Server Operation

[0886] The server analyzes the received HTTP request and creates and inputs a prompt to a generative AI model (for example, a natural language processing module). The prompt might be something like, "Please provide information about the weather in Tokyo this weekend." This prompt is then used to collect the required information in real time from related web pages and APIs.

[0887] 4. Filtering and organizing information

[0888] The server runs the information obtained from the generative AI model through a filtering algorithm and evaluates it based on its reliability, recency, and relevance. Based on the evaluation results, the server selects the most appropriate information and summarizes it in text format. The organized information is then formatted in a way that is easy for users to understand.

[0889] 5. Speech synthesis and transmission

[0890] The server inputs the summarized text data into a speech synthesis engine such as the Google Text-to-Speech API to generate audio data. The generated audio data is encoded in MP3 format and sent back to the device as an HTTP response. At this time, the server adds appropriate header information to specify the data type.

[0891] 6. Audio playback on device

[0892] The device decodes the audio data received from the server and plays it in a dedicated application. The device's audio playback module (such as Android's MediaPlayer or iOS's AVPlayer) captures the audio data and begins playing it for the user. For example, it might provide audio information such as, "The weather in Tokyo this weekend will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees."

[0893] Examples and prompts

[0894] For example, if a user wants to know "the weather in Tokyo this weekend," the query would look like this:

[0895] A user starts a smartphone application and enters "Weather in Tokyo this weekend."

[0896] The terminal sends this input to the server.

[0897] The server collects, organizes, and filters information using generative AI models.

[0898] The organized information is converted into audio data and sent to the terminal.

[0899] The terminal plays the audio data, allowing the user to obtain information through audio.

[0900] Example prompt sentence:

[0901] "Please provide information about the weather in Tokyo this weekend."

[0902] In this way, users can efficiently obtain up-to-date and reliable information through voice without using their hands.

[0903] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0904] Step 1:

[0905] A user enters a search query into a device. Specifically, the user launches an application on a smartphone or PC and enters "Tokyo weather this weekend" into the search bar. The entered query is processed as text data.

[0906] Input: The search query entered by the user (e.g., "Weather in Tokyo this weekend")

[0907] Output: Search query data in text format

[0908] Step 2:

[0909] The device sends the search query to the server. The device sends the search query for the acquired text data to the server as an HTTP POST request. For example, a request including query parameters is sent to the endpoint https: / / example.com / search. The communication may be encrypted during transmission.

[0910] Input: Search query data in text format

[0911] Output: HTTP POST request sent to the server

[0912] Step 3:

[0913] The server receives the search query and collects information. Using a generative AI model, it generates the prompt "Please provide information about the weather in Tokyo this weekend" and collects information in real time from relevant web pages and APIs.

[0914] Input: The search query in the received HTTP POST request

[0915] Output: Relevant information collected

[0916] Step 4:

[0917] The server filters and organizes the collected information. Filtering algorithms are used to evaluate the information based on reliability, currency, and relevance. The selected information is summarized and organized in text format.

[0918] Input: Collected relevant information

[0919] Output: Summarized text data

[0920] Step 5:

[0921] The server converts the summarized text data into audio data. Using a speech synthesis engine such as the Google Text-to-Speech API, the text data is converted into audio data (e.g., MP3 format), and the appropriate header information is added before sending the data to the device as an HTTP response.

[0922] Input: Summarized text data

[0923] Output: Generated audio data (e.g. MP3 file)

[0924] Step 6:

[0925] The device plays the audio data received from the server. The device's audio playback module (e.g., MediaPlayer on Android or AVPlayer on iOS) plays the audio data and provides information to the user.

[0926] Input: Audio data received from the server

[0927] Output: Information provided by audio playback

[0928] Through the above steps, the user can efficiently and safely obtain the latest information by voice.

[0929] (Application example 1)

[0930] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0931] To improve work efficiency and safety in factories, there is a need for a system that allows workers to efficiently collect the necessary information via robots. However, with existing systems, workers must manually search for information and perform their tasks based on that information, which takes time and reduces work efficiency. Furthermore, manually collecting information carries the risk of generating incorrect information. This leads to issues such as reduced factory productivity and difficulty in improving the working environment.

[0932] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0933] In this invention, the server includes an input means for a user to input a search query to a terminal, a transmission means for the terminal to transmit the search query to the server, a generation means for the server to receive the search query and collect related information from the Internet, a filtering and organizing means for filtering the collected information and creating a summary, a voice synthesis means for the server to convert the summary into voice data, a transmission means for the server to transmit the voice data to the terminal, a playback means for playing the voice data received by the terminal, a robot control means for providing a search result to a factory robot by voice based on the user query, a voice input means for inputting the user query by voice, and a voice playback means for the robot to play the voice data. This enables workers to efficiently obtain necessary information and reflect it in their work simply by inputting a voice query.

[0934] A "terminal" is a device through which a user inputs a search query and communicates with a server.

[0935] A "search query" is text data that a user enters to find out the information they want to know.

[0936] A "server" is a device that receives search queries, collects, filters, organizes, converts related information into audio data, and transmits it to a terminal.

[0937] The "generation means" is a function that collects information based on a search query within the server.

[0938] "Filtering and organization" refers to the ability to evaluate collected information and select the information that is most relevant to the user.

[0939] The "voice synthesis means" is a function that converts text data into voice data.

[0940] "Transmission means" is a function by which the terminal and the server transmit and receive data.

[0941] The "playback means" is a function for playing back audio data received by the terminal.

[0942] The "robot control means" is a function that enables a factory robot to provide search results by voice based on a user query.

[0943] The "voice input means" is a function that allows the user to input a query by voice.

[0944] "Audio playback means" is a function that enables the robot to play back audio data.

[0945] This invention is a system that allows users to efficiently and safely collect information. The user inputs a search query using a voice input means on a terminal, and the terminal sends the query to a server. The server collects information based on the received search query, filters and organizes it, converts it into voice data, and sends it back to the terminal. The terminal plays the received voice data and provides the information to the user. Furthermore, this system is compatible with factory robots, obtaining information in real time via the robots and providing work instructions via voice.

[0946] Hardware used

[0947] Terminals: Mobile devices and fixed equipment used within the factory

[0948] Server: A computer system that collects, filters, and organizes information from the Internet.

[0949] Factory robots: Mechanical devices for automating work

[0950] Software used

[0951] HTTP request library (e.g., requests): Sends data from the device to the server

[0952] Speech synthesis library (e.g., pyttsx3): converts text data generated on the server into speech data.

[0953] Generative AI model: Used to collect and summarize information within the server

[0954] Speech input and playback libraries (e.g., SpeechRecognition, playsound): Used to process and play audio data on devices and robots

[0955] Data processing and calculation flow

[0956] 1. Voice input: The user inputs a search query to the factory robot by voice. For example, the user might say, "Tell me the details of the next process."

[0957] 2. Transmission means: The terminal sends this query to the server using the HTTP POST method.

[0958] 3. Generating means: The server uses the generative AI model to collect information corresponding to the query from the Internet.

[0959] 4. Filtering and organization: The server filters the collected information and summarizes it in a form suitable for the user.

[0960] 5. Speech synthesis means: The server converts the summarized text information into speech data.

[0961] 6. Retransmission means: The server retransmits the generated voice data to the terminal.

[0962] 7. Audio playback means: The terminal and the robot play back the received audio data to provide information to the user.

[0963] Specific examples

[0964] For example, consider a scenario where a worker in a factory sends a voice query to a robot saying, "Tell me the details of the next process." The robot sends this query to a server, which uses a generative AI model to collect information about the next process from reliable data sources. It also filters and organizes the collected information, summarizing only the parts that are important to the user and generating voice data. This voice data is then sent to a terminal, and the robot plays it back, allowing the worker to obtain the details of the next process by voice in real time.

[0965] Prompt Sentence Examples

[0966] Could you please give me more details about the next step?

[0967] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0968] Step 1:

[0969] A user enters a search query by voice into a factory robot.

[0970] Input: User's voice query (e.g., "Please tell me the details of the next step")

[0971] Output: Audio data

[0972] How it works: When a user speaks a voice query to the robot, the robot's internal voice recognition system captures the speech and converts it into text data.

[0973] Step 2:

[0974] The terminal transmits the converted text data to the server.

[0975] Input: Text data converted from audio

[0976] Output: HTTP request sent to the server

[0977] Specific operation: The robot's control system converts voice data into text and sends it to the server using the HTTP POST method. At this time, the text data is included in the request payload.

[0978] Step 3:

[0979] The server uses a generative AI model to collect information based on the search query received.

[0980] Input: Search query as an HTTP request

[0981] Output: Collected raw information data

[0982] How it works: The server analyzes the received search query and triggers a generative AI model, which gathers relevant information from the internet, for example, by retrieving detailed information about the next step from multiple data sources.

[0983] Step 4:

[0984] The server filters and organizes the collected information to create a summary.

[0985] Input: Collected raw information data

[0986] Output: Summarized text data

[0987] How it works: The server uses a filtering algorithm to select reliable and relevant information from the collected data, then summarizes only the necessary information and formats it as text data.

[0988] Step 5:

[0989] The server converts the summarized text data into audio data.

[0990] Input: Summarized text data

[0991] Output: Audio data

[0992] Specific operation: The server's speech synthesis engine receives the summarized text data and converts it into natural-sounding speech data, for example, creating a voice message to inform the user of the details of the next step.

[0993] Step 6:

[0994] The server transmits the generated voice data to the terminal.

[0995] Input: Audio data

[0996] Output: HTTP response sent to the device

[0997] Specific operation: The server packages the generated audio data as an HTTP response and sends it to the terminal. In this case, the audio data is included in the body of the response.

[0998] Step 7:

[0999] The terminal plays back the received audio data.

[1000] Input: Audio data received from the server

[1001] Output: Audio information presented to the user

[1002] Specific operation: The robot's control system decodes the received voice data and plays it back to the user through the built-in speaker. For example, the user is told, "The next step is to attach part A to part B."

[1003] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1004] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a device, and the device transmits the query to a server. The server collects, filters, and organizes the information, converts it into emotion-adjusted voice data, and transmits it back to the device.

[1005] Parts operated by the user

[1006] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[1007] The emotion engine, which is also used by users, analyzes their emotions during and after a search. The emotion engine analyzes the user's tone of voice and facial expressions in real time and reflects the results throughout the system.

[1008] Device behavior

[1009] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1010] Server Operation

[1011] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[1012] The generative AI module analyzes the query and gathers data from relevant web pages and APIs, for example, weather forecast information is pulled from trusted weather sites.

[1013] Filtering and organizing information

[1014] The server evaluates the collected information through a filtering algorithm, filtering the information based on its reliability and recency, and selects the most appropriate information.

[1015] The selected information is then summarised and generated as text data for the user. The summarised text data is then adjusted by an emotion engine, taking into account the user's emotions.

[1016] Emotion-based speech synthesis and transmission

[1017] The server then passes the summarized text data to a speech synthesis engine to generate speech data, which then adjusts the tone of the speech or modifies the content based on the user's emotions.

[1018] The generated audio data is sent to the terminal again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[1019] Emotion-based audio playback on the device

[1020] The device decodes the voice data received from the server and plays it back within the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a voice tone that includes warmth and encouragement according to the user's emotions.

[1021] As a concrete example, we will explain the sequence of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, uses an emotion engine to generate voice data appropriate to the user's emotions, and returns it to the device. The device then plays the voice data, allowing the user to hear "the weather in Tokyo this weekend" by voice.

[1022] This allows users to use their smartphones safely while walking or on the move, efficiently collect information, and enjoy a better user experience by taking their emotions into consideration.

[1023] The processing flow will be explained below.

[1024] Step 1:

[1025] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data. The device's built-in emotion engine analyzes the user's voice and facial expressions to recognize their current emotional state.

[1026] Step 2:

[1027] The device sends the acquired search query and emotion data to the server as an HTTP request. The device then encodes the input search query and emotion data into JSON format and sends it to the server's API endpoint using the POST method.

[1028] Step 3:

[1029] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" and emotion data from the request body. The server passes the extracted query to the generation AI module and the emotion data to the emotion engine.

[1030] Step 4:

[1031] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[1032] Step 5:

[1033] The server evaluates the collected data through a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information then undergoes a summary process, and is generated as text data to be provided to the user.

[1034] Step 6:

[1035] The server's emotion engine adjusts the collected information based on the user's emotional state. Specifically, the tone and content of the information provided are adjusted to match the user's emotions. For example, if the user is feeling anxious, the information provided will be adjusted to a tone that gives a sense of security.

[1036] Step 7:

[1037] The server passes the summarized text data to a speech synthesis engine to generate speech data, which adjusts the tone of the speech based on the user's emotions.

[1038] Step 8:

[1039] The server sends the generated audio data to the device. The server encodes the audio data as an HTTP response and sends it back to the device. The device receives the audio data.

[1040] Step 9:

[1041] The device decodes the voice data received from the server and plays it back to the user. The device then inputs the voice data into an audio player and provides the user with a voice report of "Tokyo's weather this weekend." Based on the analysis results of the emotion engine, the tone and content of the voice are also adjusted appropriately according to the emotion.

[1042] This allows users to efficiently collect information while walking and receive information that takes into account their emotions at the time.

[1043] Example 2

[1044] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1045] Conventional information gathering systems require users to look directly at the screen, which makes them unsafe when used while walking or moving. In addition, because they do not take into account the user's emotions, the user experience is uniform, making it difficult to provide information tailored to the needs of each individual user.

[1046] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means that receives a search query and collects related information from a network, a filtering and organization means that filters the collected information and creates a summary, an emotion analysis means that analyzes the user's emotion, and a voice synthesis means that converts the adjusted summary into voice data. This allows the user to safely collect information while walking or on the move, and obtain information in a form that takes into consideration the user's emotions.

[1047] The "input means" refers to a means by which a user inputs a search query into a terminal.

[1048] The "transmission means" is a means by which the terminal transmits the search query to the server.

[1049] The "generating means" is a means by which the server receives the search query and collects related information from a network.

[1050] "Filtering and organizing means" refers to means for filtering and summarizing the information collected by the server.

[1051] The "emotion analysis means" is a means by which the server analyzes the user's emotions.

[1052] The "adjustment means" is a means by which the server adjusts the summary based on the user's feelings.

[1053] The "voice synthesis means" is a means by which the server converts the adjusted summary into voice data.

[1054] The "reproducing means" is a means for reproducing the audio data received by the terminal.

[1055] The "identification means" is a means by which the server identifies relevant information sources based on a search query.

[1056] The "shaping means" is a means by which the server shapes the information evaluated by the filtering and organizing means into the most appropriate form.

[1057] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts it into speech data adjusted based on emotions, and transmits it back to the terminal. The specific configuration and processing are described below.

[1058] composition

[1059] User operation method

[1060] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[1061] Terminal transmission means

[1062] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1063] Server generation and filtering means

[1064] The server receives an HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server passes this extracted query to the generation AI module, which analyzes the query and collects data from relevant web pages and APIs. For example, if the weather forecast information is needed, it retrieves data from a reliable weather forecast site.

[1065] Server emotion analysis and adjustment means

[1066] The server evaluates the collected information using a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information goes through a summary process and is generated as text data to be provided to the user. This text data is adjusted by an emotion engine. The emotion engine analyzes the user's emotions and adjusts the information to suit the user's emotions.

[1067] Server's voice synthesis and transmission methods

[1068] The server passes the summarized text data to a speech synthesis engine to generate audio data. The speech synthesis engine adjusts the tone of the voice based on the user's emotions or modifies the content. The generated audio data is then sent to the device again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format (e.g., MP3, WAV).

[1069] Device playback method

[1070] The device decodes the voice data received from the server and plays it back within a specific application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a tone of warmth and encouragement that corresponds to the user's emotions.

[1071] Specific examples

[1072] The user launches the dedicated application and enters "This weekend's weather in Tokyo." The device encodes this information into JSON format and sends a POST request to the server. The server analyzes the query and collects weather data from weather forecast sites. It filters the information and summarizes it as "Saturday and Sunday will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees." The emotion engine analyzes this summary, and if it determines that the user is a little tired, the speech synthesis engine generates voice data in a warm tone saying, "The weekend will be sunny so you can refresh yourself!" The server sends this voice data to the device in MP3 format, and the device plays the audio within the app.

[1073] Prompt Sentence Examples

[1074] "What's the weather like in Tokyo this weekend?" Please generate voice data that conveys weather information in a cheerful and encouraging tone, taking into account the user's emotions.

[1075] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1076] Step 1:

[1077] The user launches a dedicated application and enters a search query.

[1078] Input: A natural language search query typed by a user (e.g., "What's the weather like in Tokyo this weekend?")

[1079] Output: Text data of the search query

[1080] How it works: A user opens a dedicated application on their smartphone and enters "Tokyo weather this weekend" in the search bar. This text data is stored internally and passed to the next processing step.

[1081] Step 2:

[1082] The device sends the search query to the server as an HTTP request.

[1083] Input: Text data of the search query

[1084] Output: HTTP request in JSON format sent to the server

[1085] Specific operation: The device encodes the search query entered by the user into JSON format and sends it to the server using the POST method, to the server's API endpoint.

[1086] Step 3:

[1087] The server receives the HTTP request and extracts the search query.

[1088] Input: HTTP request sent from the terminal

[1089] Output: Extracted search query text data

[1090] Specific operation: The server receives an HTTP request and extracts a search query such as "Weather in Tokyo this weekend" from the request body.

[1091] Step 4:

[1092] The server passes the search query to a generation AI module for analysis.

[1093] Input: Extracted search query

[1094] Output: Information related to the analysis results (e.g., weather information)

[1095] How it works: The server passes the search query to the AI ​​generation module, which then analyzes the query and collects relevant information from the network, such as data from a weather forecast website.

[1096] Step 5:

[1097] The server filters the collected information and creates a summary.

[1098] Input: relevant information obtained from the generative AI module

[1099] Output: filtered and summarized text data

[1100] How it works: The server filters the collected information using an evaluation algorithm and summarizes the information selected based on reliability and recency, for example, "Saturday and Sunday will be sunny, with a maximum temperature of 25°C and a minimum temperature of 18°C."

[1101] Step 6:

[1102] The server analyzes the summarized information using an emotion engine and makes adjustments.

[1103] Input: Summarized text data

[1104] Output: Text data adjusted based on user sentiment

[1105] How it works: The server uses an emotion engine to tailor information based on the user's emotional data (e.g., past search history and real-time voice tone). For example, if the server determines that the user is tired, it will tailor the information to something like, "We hope the weekend will be sunny so you can feel refreshed!"

[1106] Step 7:

[1107] The server passes the adjusted text data to a speech synthesis engine to generate speech data.

[1108] Input: Adjusted text data

[1109] Output: Synthesized voice data

[1110] Specific operation: The server passes the adjusted text data to a speech synthesis engine to generate audio data (e.g., MP3 format). The speech synthesis engine generates audio with a tone that matches the user's emotions.

[1111] Step 8:

[1112] The server sends the generated audio data to the terminal as an HTTP response.

[1113] Input: Generated audio data

[1114] Output: HTTP response sent to the device

[1115] Specific operation: The generated audio data is sent to the terminal in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[1116] Step 9:

[1117] The terminal plays back the received audio data.

[1118] Input: Audio data received from the server

[1119] Output: Audio playback that the user can hear

[1120] Specific operation: The device decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" will be heard in a voice tone that corresponds to the user's emotions.

[1121] These steps allow users to safely gather information while walking or on the move, and to receive that information in an emotionally sensitive way.

[1122] (Application example 2)

[1123] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1124] Conventional systems simply provide information when users input search queries to obtain information, without taking into account the user's emotions or circumstances. As a result, when receiving information in stressful or rushed situations in factories or production lines, the information delivery method may be inappropriate, resulting in reduced production efficiency and management capabilities. Furthermore, if information is not properly filtered and organized, the information provided to users may be excessive or inaccurate. To solve these issues, it is necessary to analyze the user's emotional state in real time and provide information appropriate to that emotion.

[1125] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1126] In this invention, the server includes an input means for a user to input a search query into a terminal, a transmission means for the terminal to transmit the search query to the server, an emotion analysis means for the terminal to analyze the user's emotion, and an adjustment means for adjusting the voice tone based on the emotion analysis means. This makes it possible to provide information by voice in an appropriate tone according to the user's emotion. This allows managers, particularly in factories and production lines, to obtain the information they need quickly and with little stress, improving production efficiency and management capabilities.

[1127] A "user" is a person who uses the system and is the entity that inputs a search query and obtains information.

[1128] A "terminal" is a computing device through which a user inputs a search query and communicates with a server.

[1129] A "search query" is text data that a user enters to identify the information they are looking for.

[1130] "Server" means a central control system for receiving search queries, collecting relevant information, and providing it to users.

[1131] The "transmission means" is a function for transmitting a search query from a terminal to a server, and for transmitting voice data from the server to a terminal.

[1132] A "generator" is a processing mechanism by which the server collects relevant information based on a search query.

[1133] "Filtering and organization" refers to the mechanism by which the server evaluates the information it collects and summarizes it in a form that is most relevant to the user.

[1134] The "voice synthesis means" is a mechanism for converting summarized information into voice data.

[1135] The "playback means" is a function for allowing the user to listen to the audio data received on the terminal.

[1136] The "emotion analysis means" is a mechanism for analyzing the user's emotional state in real time.

[1137] The "adjustment means" is a mechanism for adjusting the tone of the voice based on the emotion analysis means.

[1138] A "network" is an infrastructure for information communication such as the Internet.

[1139] A "data page" is a web page or database that contains information that exists on a network.

[1140] The "shaping means" is a mechanism for optimizing the information evaluated by the filtering and organizing means in a form that is presented to the user.

[1141] The present invention provides a system that allows a user to input a search query, collects information based on the query, analyzes the user's emotions, and provides the information in an appropriate voice tone. This system is composed of a terminal, a server, a transmission means, an input means, an emotion analysis means, a voice synthesis means, and a playback means.

[1142] Parts operated by the user

[1143] First, the user installs a dedicated application on their smart device (e.g., smartphone or tablet). They launch the application and enter the required information into the search bar. For example, they enter "current production efficiency." This input is processed as text data. The user then uses an emotion analysis tool, which analyzes the user's emotions during and after the search in real time. The emotion analysis tool analyzes the user's tone of voice and facial expressions, and reflects the results in the system.

[1144] Device behavior

[1145] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1146] Server Operation

[1147] The server receives an HTTP request and extracts the search query from the request body. The server passes this extracted query to the generation AI module. The generation AI module analyzes the query and collects the necessary information from related data pages and APIs. The server evaluates the collected information using a filtering algorithm and selects the most appropriate information based on its reliability and recency. The selected information undergoes a summarization process, generating text data to be provided to the user. The summarized text data is then adjusted by a sentiment analysis means to take into account the user's emotions.

[1148] Emotion-based speech synthesis and transmission

[1149] The server passes the summarized text data to a speech synthesis engine to generate voice data. The speech synthesis engine adjusts the voice tone according to the user's emotions based on the emotion analysis means described above. For example, if it determines that the user is in an emergency, it uses a quick and easy-to-understand voice tone. The generated voice data is again sent to the terminal in the form of an HTTP response.

[1150] Emotion-based audio playback on the device

[1151] The terminal decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an urgent tone to reflect the user's sense of urgency.

[1152] Specific examples

[1153] For example, if a line manager on a factory production line asks a robot assistant, "What is the current production efficiency?", the query is sent to a server, which collects and organizes the latest production data. If the emotion analysis tool determines that the user is under stress, the robot responds in a calm voice, "Current production efficiency is 95%. There are delays on some lines."

[1154] Prompt Sentence Examples

[1155] What is the current production efficiency?

[1156] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1157] Step 1:

[1158] A user enters a search query into a device.

[1159] (input)

[1160] The user enters specific information into the search bar of the dedicated application on the device, for example, "current production efficiency."

[1161] (output)

[1162] The search query is saved as text data on the device.

[1163] (Specific actions)

[1164] When a user uses a smartphone or tablet interface to enter text into the application's search bar, the emotion analysis means simultaneously analyzes the user's tone of voice and facial expressions.

[1165] Step 2:

[1166] The device sends a search query to the server.

[1167] (input)

[1168] User-entered search queries and real-time analyzed sentiment data.

[1169] (output)

[1170] The search query and sentiment data are sent to the server as an HTTP request.

[1171] (Specific actions)

[1172] The device creates an HTTP request, encodes the search query in JSON format, includes the emotion data in the request, and sends it to the server's API endpoint using the POST method.

[1173] Step 3:

[1174] The server receives the HTTP request and passes the search query to the generative AI model.

[1175] (input)

[1176] The search query and sentiment data sent to the server.

[1177] (output)

[1178] A search query is input into the generative AI model.

[1179] (Specific actions)

[1180] The server extracts search queries and sentiment data from the body of the received HTTP request, inputs the extracted search queries into a generative AI model, and collects information from related data pages and APIs.

[1181] Step 4:

[1182] Filtering and organizing the information collected by the server.

[1183] (input)

[1184] Relevant information collected by generative AI models.

[1185] (output)

[1186] A filtered and organized summary of information.

[1187] (Specific actions)

[1188] The server runs a filtering algorithm on the collected information to select the most relevant data based on its reliability and recency, and then the selected information is summarised and generated as concise text data.

[1189] Step 5:

[1190] The server passes the summarized text data to the speech synthesis engine.

[1191] (input)

[1192] Summarized text and sentiment data.

[1193] (output)

[1194] Audio data adjusted according to the user's emotions.

[1195] (Specific actions)

[1196] The server inputs the summarized text data into a speech synthesis engine, which adjusts the tone of the voice based on the emotion analysis means and generates speech data.

[1197] Step 6:

[1198] The server sends the audio data to the terminal.

[1199] (input)

[1200] The generated audio data.

[1201] (output)

[1202] The audio data is sent to the device as an HTTP response.

[1203] (Specific actions)

[1204] The server encodes the generated audio data in an appropriate format and sends it to the terminal as an HTTP response.

[1205] Step 7:

[1206] The terminal receives and plays the audio data.

[1207] (input)

[1208] Audio data sent from the server.

[1209] (output)

[1210] The user receives audio information in a tone that corresponds to the user's emotion.

[1211] (Specific actions)

[1212] The device decodes the received voice data and plays it back using a dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an appropriate tone of voice, reflecting the user's real-time emotions.

[1213] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1214] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1215] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1216] [Fourth embodiment]

[1217] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1218] 7, a 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.

[1219] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1220] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1221] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1223] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1224] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1225] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1226] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1227] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1228] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1229] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1230] The present invention provides a system for users to efficiently and securely gather information. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts the information into voice data, and transmits it back to the terminal. A practical implementation of this system is described below.

[1231] Parts operated by the user

[1232] First, the user installs a dedicated application on their smartphone or other device. They launch the application and enter the required information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[1233] Device behavior

[1234] The device receives the search query entered by the user and sends it to the server. When sending, the search query is sent to the server in the form of an HTTP request using the POST method. This ensures that the user's search query reaches the server safely and quickly.

[1235] Server Operation

[1236] The server receives the search query and begins collecting information based on the query. Specifically, the server's internal AI generation module analyzes the query and collects information from related web pages and APIs. For example, if the query contains weather forecast information, it will retrieve data from a reliable weather forecast site.

[1237] Filtering and organizing information

[1238] The server then runs the collected information through a filtering algorithm, which evaluates the data based on factors such as reliability, recency, and relevance. The most relevant information is then summarized and presented to the user in text form. This summary is then formatted in a user-friendly format.

[1239] Speech synthesis and transmission

[1240] The server passes the summarized text data to a speech synthesis engine to generate voice data. The generated voice data is then sent to the terminal in the form of an HTTP response. The server specifies the type of voice data and transmits it in the appropriate format.

[1241] Playing audio on your device

[1242] The device decodes the voice data received from the server and plays it back in the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided to the user as voice.

[1243] As a concrete example, let us consider the series of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, converts it into audio data, and returns it to the device. The device then plays the audio data, allowing the user to hear "the weather in Tokyo this weekend."

[1244] This allows users to safely use their smartphones while walking or on the move and efficiently collect information.

[1245] The processing flow will be explained below.

[1246] Step 1:

[1247] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data.

[1248] Step 2:

[1249] The device sends the acquired search query to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1250] Step 3:

[1251] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[1252] Step 4:

[1253] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[1254] Step 5:

[1255] The server evaluates the collected data through a filtering algorithm, filtering the data based on its reliability and recency, and selecting the most appropriate information.

[1256] Step 6:

[1257] The server summarizes the selected information and generates text data to be presented to the user. The server uses a summarization process to organize the collected data into a concise and easy-to-understand format.

[1258] Step 7:

[1259] The server passes the summarized text data to a speech synthesis engine to generate audio data. The server then inputs the text into a speech synthesis API and obtains the generated audio file.

[1260] Step 8:

[1261] The server sends the generated audio data to the device, which then encodes the audio data as an HTTP response and sends it back to the device.

[1262] Step 9:

[1263] The device decodes the audio data received from the server and inputs it into the audio player. The device then plays the audio data, allowing the user to hear "This weekend's weather in Tokyo" aloud.

[1264] These steps allow the user to efficiently gather information while walking.

[1265] Example 1

[1266] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1267] In conventional information gathering systems, users often only obtain information text-based, making it difficult to access information hands-free, especially while on the move or at work. Furthermore, the reliability and relevance of the collected information may not be adequately evaluated, preventing users from efficiently obtaining the information they need. Furthermore, information is often disorganized and not provided in a format that is easy for users to understand.

[1268] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1269] In this invention, the server includes a collection means for collecting relevant information using a generative model, a filtering and organizing means for evaluating the information using a filtering algorithm and creating a summary, and a speech synthesis means for converting the summary into speech data, thereby enabling a user to efficiently obtain reliable information by voice without using their hands and providing it in an easy-to-understand format.

[1270] An "input means" is a device or interface that allows a user to input a search query into a terminal.

[1271] "Transmission means" refers to the functions and protocols that allow a terminal to transmit a search query to a server.

[1272] A "collection means" is a mechanism by which the server uses the generative model to collect relevant information.

[1273] "Filtering and Consolidation Methods" are the algorithms and processes used by the server to evaluate and summarize the information collected.

[1274] "Speech synthesis means" refers to the technology or engine that the server uses to convert summarized text data into speech data.

[1275] "Playback means" refers to a device or software for playing back audio data received by a terminal.

[1276] "Means for identification" refers to the functionality that allows the server to retrieve information from relevant web pages or APIs based on the search query.

[1277] The "shaping means" is a method by which the server shapes the information evaluated by the filtering and organizing means into a form that is most appropriate for the user.

[1278] The present invention is an information processing system that allows a user to collect information efficiently and safely. Specific embodiments of this system will be described below.

[1279] 1. User operations

[1280] First, the user installs a dedicated application on their smartphone or personal computer. When the application is launched, a search bar appears. The user enters a search query, such as "Tokyo weather this weekend." The entered query is processed as text data by the device.

[1281] 2. Device Operation

[1282] The device retrieves the search query entered by the user and sends it to the server in the form of an HTTP POST request. Specifically, the device sends a request including query parameters to the https: / / example.com / search endpoint. The communication is encrypted to ensure security and data integrity.

[1283] 3. Server Operation

[1284] The server analyzes the received HTTP request and creates and inputs a prompt to a generative AI model (for example, a natural language processing module). The prompt might be something like, "Please provide information about the weather in Tokyo this weekend." This prompt is then used to collect the required information in real time from related web pages and APIs.

[1285] 4. Filtering and organizing information

[1286] The server runs the information obtained from the generative AI model through a filtering algorithm and evaluates it based on its reliability, recency, and relevance. Based on the evaluation results, the server selects the most appropriate information and summarizes it in text format. The organized information is then formatted in a way that is easy for users to understand.

[1287] 5. Speech synthesis and transmission

[1288] The server inputs the summarized text data into a speech synthesis engine such as the Google Text-to-Speech API to generate audio data. The generated audio data is encoded in MP3 format and sent back to the device as an HTTP response. At this time, the server adds appropriate header information to specify the data type.

[1289] 6. Audio playback on device

[1290] The device decodes the audio data received from the server and plays it in a dedicated application. The device's audio playback module (such as Android's MediaPlayer or iOS's AVPlayer) captures the audio data and begins playing it for the user. For example, it might provide audio information such as, "The weather in Tokyo this weekend will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees."

[1291] Examples and prompts

[1292] For example, if a user wants to know "the weather in Tokyo this weekend," the query would look like this:

[1293] A user starts a smartphone application and enters "Weather in Tokyo this weekend."

[1294] The terminal sends this input to the server.

[1295] The server collects, organizes, and filters information using generative AI models.

[1296] The organized information is converted into audio data and sent to the terminal.

[1297] The terminal plays the audio data, allowing the user to obtain information through audio.

[1298] Example prompt sentence:

[1299] "Please provide information about the weather in Tokyo this weekend."

[1300] In this way, users can efficiently obtain up-to-date and reliable information through voice without using their hands.

[1301] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1302] Step 1:

[1303] A user enters a search query into a device. Specifically, the user launches an application on a smartphone or PC and enters "Tokyo weather this weekend" into the search bar. The entered query is processed as text data.

[1304] Input: The search query entered by the user (e.g., "Weather in Tokyo this weekend")

[1305] Output: Search query data in text format

[1306] Step 2:

[1307] The device sends the search query to the server. The device sends the search query for the acquired text data to the server as an HTTP POST request. For example, a request including query parameters is sent to the endpoint https: / / example.com / search. The communication may be encrypted during transmission.

[1308] Input: Search query data in text format

[1309] Output: HTTP POST request sent to the server

[1310] Step 3:

[1311] The server receives the search query and collects information. Using a generative AI model, it generates the prompt "Please provide information about the weather in Tokyo this weekend" and collects information in real time from relevant web pages and APIs.

[1312] Input: The search query in the received HTTP POST request

[1313] Output: Relevant information collected

[1314] Step 4:

[1315] The server filters and organizes the collected information. Filtering algorithms are used to evaluate the information based on reliability, currency, and relevance. The selected information is summarized and organized in text format.

[1316] Input: Collected relevant information

[1317] Output: Summarized text data

[1318] Step 5:

[1319] The server converts the summarized text data into audio data. Using a speech synthesis engine such as the Google Text-to-Speech API, the text data is converted into audio data (e.g., MP3 format), and the appropriate header information is added before sending the data to the device as an HTTP response.

[1320] Input: Summarized text data

[1321] Output: Generated audio data (e.g. MP3 file)

[1322] Step 6:

[1323] The device plays the audio data received from the server. The device's audio playback module (e.g., MediaPlayer on Android or AVPlayer on iOS) plays the audio data and provides information to the user.

[1324] Input: Audio data received from the server

[1325] Output: Information provided by audio playback

[1326] Through the above steps, the user can efficiently and safely obtain the latest information by voice.

[1327] (Application example 1)

[1328] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1329] To improve work efficiency and safety in factories, there is a need for a system that allows workers to efficiently collect the necessary information via robots. However, with existing systems, workers must manually search for information and perform their tasks based on that information, which takes time and reduces work efficiency. Furthermore, manually collecting information carries the risk of generating incorrect information. This leads to issues such as reduced factory productivity and difficulty in improving the working environment.

[1330] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1331] In this invention, the server includes an input means for a user to input a search query to a terminal, a transmission means for the terminal to transmit the search query to the server, a generation means for the server to receive the search query and collect related information from the Internet, a filtering and organizing means for filtering the collected information and creating a summary, a voice synthesis means for the server to convert the summary into voice data, a transmission means for the server to transmit the voice data to the terminal, a playback means for playing the voice data received by the terminal, a robot control means for providing a search result to a factory robot by voice based on the user query, a voice input means for inputting the user query by voice, and a voice playback means for the robot to play the voice data. This enables workers to efficiently obtain necessary information and reflect it in their work simply by inputting a voice query.

[1332] A "terminal" is a device through which a user inputs a search query and communicates with a server.

[1333] A "search query" is text data that a user enters to find out the information they want to know.

[1334] A "server" is a device that receives search queries, collects, filters, organizes, converts related information into audio data, and transmits it to a terminal.

[1335] The "generation means" is a function that collects information based on a search query within the server.

[1336] "Filtering and organization" refers to the ability to evaluate collected information and select the information that is most relevant to the user.

[1337] The "voice synthesis means" is a function that converts text data into voice data.

[1338] "Transmission means" is a function by which the terminal and the server transmit and receive data.

[1339] The "playback means" is a function for playing back audio data received by the terminal.

[1340] The "robot control means" is a function that enables a factory robot to provide search results by voice based on a user query.

[1341] The "voice input means" is a function that allows the user to input a query by voice.

[1342] "Audio playback means" is a function that enables the robot to play back audio data.

[1343] This invention is a system that allows users to efficiently and safely collect information. The user inputs a search query using a voice input means on a terminal, and the terminal sends the query to a server. The server collects information based on the received search query, filters and organizes it, converts it into voice data, and sends it back to the terminal. The terminal plays the received voice data and provides the information to the user. Furthermore, this system is compatible with factory robots, obtaining information in real time via the robots and providing work instructions via voice.

[1344] Hardware used

[1345] Terminals: Mobile devices and fixed equipment used within the factory

[1346] Server: A computer system that collects, filters, and organizes information from the Internet.

[1347] Factory robots: Mechanical devices for automating work

[1348] Software used

[1349] HTTP request library (e.g., requests): Sends data from the device to the server

[1350] Speech synthesis library (e.g., pyttsx3): converts text data generated on the server into speech data.

[1351] Generative AI model: Used to collect and summarize information within the server

[1352] Speech input and playback libraries (e.g., SpeechRecognition, playsound): Used to process and play audio data on devices and robots

[1353] Data processing and calculation flow

[1354] 1. Voice input: The user inputs a search query to the factory robot by voice. For example, the user might say, "Tell me the details of the next process."

[1355] 2. Transmission means: The terminal sends this query to the server using the HTTP POST method.

[1356] 3. Generating means: The server uses the generative AI model to collect information corresponding to the query from the Internet.

[1357] 4. Filtering and organization: The server filters the collected information and summarizes it in a form suitable for the user.

[1358] 5. Speech synthesis means: The server converts the summarized text information into speech data.

[1359] 6. Retransmission means: The server retransmits the generated voice data to the terminal.

[1360] 7. Audio playback means: The terminal and the robot play back the received audio data to provide information to the user.

[1361] Specific examples

[1362] For example, consider a scenario where a worker in a factory sends a voice query to a robot saying, "Tell me the details of the next process." The robot sends this query to a server, which uses a generative AI model to collect information about the next process from reliable data sources. It also filters and organizes the collected information, summarizing only the parts that are important to the user and generating voice data. This voice data is then sent to a terminal, and the robot plays it back, allowing the worker to obtain the details of the next process by voice in real time.

[1363] Prompt Sentence Examples

[1364] Could you please give me more details about the next step?

[1365] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1366] Step 1:

[1367] A user enters a search query by voice into a factory robot.

[1368] Input: User's voice query (e.g., "Please tell me the details of the next step")

[1369] Output: Audio data

[1370] How it works: When a user speaks a voice query to the robot, the robot's internal voice recognition system captures the speech and converts it into text data.

[1371] Step 2:

[1372] The terminal transmits the converted text data to the server.

[1373] Input: Text data converted from audio

[1374] Output: HTTP request sent to the server

[1375] Specific operation: The robot's control system converts voice data into text and sends it to the server using the HTTP POST method. At this time, the text data is included in the request payload.

[1376] Step 3:

[1377] The server uses a generative AI model to collect information based on the search query received.

[1378] Input: Search query as an HTTP request

[1379] Output: Collected raw information data

[1380] How it works: The server analyzes the received search query and triggers a generative AI model, which gathers relevant information from the internet, for example, by retrieving detailed information about the next step from multiple data sources.

[1381] Step 4:

[1382] The server filters and organizes the collected information to create a summary.

[1383] Input: Collected raw information data

[1384] Output: Summarized text data

[1385] How it works: The server uses a filtering algorithm to select reliable and relevant information from the collected data, then summarizes only the necessary information and formats it as text data.

[1386] Step 5:

[1387] The server converts the summarized text data into audio data.

[1388] Input: Summarized text data

[1389] Output: Audio data

[1390] Specific operation: The server's speech synthesis engine receives the summarized text data and converts it into natural-sounding speech data, for example, creating a voice message to inform the user of the details of the next step.

[1391] Step 6:

[1392] The server transmits the generated voice data to the terminal.

[1393] Input: Audio data

[1394] Output: HTTP response sent to the device

[1395] Specific operation: The server packages the generated audio data as an HTTP response and sends it to the terminal. In this case, the audio data is included in the body of the response.

[1396] Step 7:

[1397] The terminal plays back the received audio data.

[1398] Input: Audio data received from the server

[1399] Output: Audio information presented to the user

[1400] Specific operation: The robot's control system decodes the received voice data and plays it back to the user through the built-in speaker. For example, the user is told, "The next step is to attach part A to part B."

[1401] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1402] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a device, and the device transmits the query to a server. The server collects, filters, and organizes the information, converts it into emotion-adjusted voice data, and transmits it back to the device.

[1403] Parts operated by the user

[1404] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[1405] The emotion engine, which is also used by users, analyzes their emotions during and after a search. The emotion engine analyzes the user's tone of voice and facial expressions in real time and reflects the results throughout the system.

[1406] Device behavior

[1407] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1408] Server Operation

[1409] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server then passes this extracted query to the generation AI module.

[1410] The generative AI module analyzes the query and gathers data from relevant web pages and APIs, for example, weather forecast information is pulled from trusted weather sites.

[1411] Filtering and organizing information

[1412] The server evaluates the collected information through a filtering algorithm, filtering the information based on its reliability and recency, and selects the most appropriate information.

[1413] The selected information is then summarised and generated as text data for the user. The summarised text data is then adjusted by an emotion engine, taking into account the user's emotions.

[1414] Emotion-based speech synthesis and transmission

[1415] The server then passes the summarized text data to a speech synthesis engine to generate speech data, which then adjusts the tone of the speech or modifies the content based on the user's emotions.

[1416] The generated audio data is sent to the terminal again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[1417] Emotion-based audio playback on the device

[1418] The device decodes the voice data received from the server and plays it back within the dedicated application the user is operating. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a voice tone that includes warmth and encouragement according to the user's emotions.

[1419] As a concrete example, we will explain the sequence of events that occur when a user searches for "the weather in Tokyo this weekend." In this case, the user enters a search query into a smartphone app, and the device sends that information to a server. The server collects and organizes weather information from the web based on the query, uses an emotion engine to generate voice data appropriate to the user's emotions, and returns it to the device. The device then plays the voice data, allowing the user to hear "the weather in Tokyo this weekend" by voice.

[1420] This allows users to use their smartphones safely while walking or on the move, efficiently collect information, and enjoy a better user experience by taking their emotions into consideration.

[1421] The processing flow will be explained below.

[1422] Step 1:

[1423] A user launches a smartphone app and types "Tokyo weather this weekend" into the search bar. The device captures this input as text data. The device's built-in emotion engine analyzes the user's voice and facial expressions to recognize their current emotional state.

[1424] Step 2:

[1425] The device sends the acquired search query and emotion data to the server as an HTTP request. The device then encodes the input search query and emotion data into JSON format and sends it to the server's API endpoint using the POST method.

[1426] Step 3:

[1427] The server receives the HTTP request and extracts the search query "Weather in Tokyo this weekend" and emotion data from the request body. The server passes the extracted query to the generation AI module and the emotion data to the emotion engine.

[1428] Step 4:

[1429] The server's generative AI module analyzes the received search query and identifies the most suitable sources of information, using web scraping tools and APIs to gather data from relevant weather forecast sites.

[1430] Step 5:

[1431] The server evaluates the collected data through a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information then undergoes a summary process, and is generated as text data to be provided to the user.

[1432] Step 6:

[1433] The server's emotion engine adjusts the collected information based on the user's emotional state. Specifically, the tone and content of the information provided are adjusted to match the user's emotions. For example, if the user is feeling anxious, the information provided will be adjusted to a tone that gives a sense of security.

[1434] Step 7:

[1435] The server passes the summarized text data to a speech synthesis engine to generate speech data, which adjusts the tone of the speech based on the user's emotions.

[1436] Step 8:

[1437] The server sends the generated audio data to the device. The server encodes the audio data as an HTTP response and sends it back to the device. The device receives the audio data.

[1438] Step 9:

[1439] The device decodes the voice data received from the server and plays it back to the user. The device then inputs the voice data into an audio player and provides the user with a voice report of "Tokyo's weather this weekend." Based on the analysis results of the emotion engine, the tone and content of the voice are also adjusted appropriately according to the emotion.

[1440] This allows users to efficiently collect information while walking and receive information that takes into account their emotions at the time.

[1441] Example 2

[1442] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1443] Conventional information gathering systems require users to look directly at the screen, which makes them unsafe when used while walking or moving. In addition, because they do not take into account the user's emotions, the user experience is uniform, making it difficult to provide information tailored to the needs of each individual user.

[1444] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means that receives a search query and collects related information from a network, a filtering and organization means that filters the collected information and creates a summary, an emotion analysis means that analyzes the user's emotion, and a voice synthesis means that converts the adjusted summary into voice data. This allows the user to safely collect information while walking or on the move, and obtain information in a form that takes into consideration the user's emotions.

[1445] The "input means" refers to a means by which a user inputs a search query into a terminal.

[1446] The "transmission means" is a means by which the terminal transmits the search query to the server.

[1447] The "generating means" is a means by which the server receives the search query and collects related information from a network.

[1448] "Filtering and organizing means" refers to means for filtering and summarizing the information collected by the server.

[1449] The "emotion analysis means" is a means by which the server analyzes the user's emotions.

[1450] The "adjustment means" is a means by which the server adjusts the summary based on the user's feelings.

[1451] The "voice synthesis means" is a means by which the server converts the adjusted summary into voice data.

[1452] The "reproducing means" is a means for reproducing the audio data received by the terminal.

[1453] The "identification means" is a means by which the server identifies relevant information sources based on a search query.

[1454] The "shaping means" is a means by which the server shapes the information evaluated by the filtering and organizing means into the most appropriate form.

[1455] The present invention provides a system that allows users to efficiently and safely collect information while taking into account the user's emotions. The user inputs a search query using a terminal, and the terminal transmits the query to a server. The server collects, filters, and organizes the information, converts it into speech data adjusted based on emotions, and transmits it back to the terminal. The specific configuration and processing are described below.

[1456] composition

[1457] User operation method

[1458] First, the user installs a dedicated application on a device such as a smartphone. Then, they launch the application and enter the necessary information into the search bar. For example, they might enter "Weather in Tokyo this weekend." This input is then processed as text data by the device.

[1459] Terminal transmission means

[1460] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1461] Server generation and filtering means

[1462] The server receives an HTTP request and extracts the search query "Weather in Tokyo this weekend" from the request body. The server passes this extracted query to the generation AI module, which analyzes the query and collects data from relevant web pages and APIs. For example, if the weather forecast information is needed, it retrieves data from a reliable weather forecast site.

[1463] Server emotion analysis and adjustment means

[1464] The server evaluates the collected information using a filtering algorithm. The server filters the information based on its reliability and recency, and selects the most appropriate information. The selected information goes through a summary process and is generated as text data to be provided to the user. This text data is adjusted by an emotion engine. The emotion engine analyzes the user's emotions and adjusts the information to suit the user's emotions.

[1465] Server's voice synthesis and transmission methods

[1466] The server passes the summarized text data to a speech synthesis engine to generate audio data. The speech synthesis engine adjusts the tone of the voice based on the user's emotions or modifies the content. The generated audio data is then sent to the device again in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format (e.g., MP3, WAV).

[1467] Device playback method

[1468] The device decodes the voice data received from the server and plays it back within a specific application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" is provided in a tone of warmth and encouragement that corresponds to the user's emotions.

[1469] Specific examples

[1470] The user launches the dedicated application and enters "This weekend's weather in Tokyo." The device encodes this information into JSON format and sends a POST request to the server. The server analyzes the query and collects weather data from weather forecast sites. It filters the information and summarizes it as "Saturday and Sunday will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees." The emotion engine analyzes this summary, and if it determines that the user is a little tired, the speech synthesis engine generates voice data in a warm tone saying, "The weekend will be sunny so you can refresh yourself!" The server sends this voice data to the device in MP3 format, and the device plays the audio within the app.

[1471] Prompt Sentence Examples

[1472] "What's the weather like in Tokyo this weekend?" Please generate voice data that conveys weather information in a cheerful and encouraging tone, taking into account the user's emotions.

[1473] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1474] Step 1:

[1475] The user launches a dedicated application and enters a search query.

[1476] Input: A natural language search query typed by a user (e.g., "What's the weather like in Tokyo this weekend?")

[1477] Output: Text data of the search query

[1478] How it works: A user opens a dedicated application on their smartphone and enters "Tokyo weather this weekend" in the search bar. This text data is stored internally and passed to the next processing step.

[1479] Step 2:

[1480] The device sends the search query to the server as an HTTP request.

[1481] Input: Text data of the search query

[1482] Output: HTTP request in JSON format sent to the server

[1483] Specific operation: The device encodes the search query entered by the user into JSON format and sends it to the server using the POST method, to the server's API endpoint.

[1484] Step 3:

[1485] The server receives the HTTP request and extracts the search query.

[1486] Input: HTTP request sent from the terminal

[1487] Output: Extracted search query text data

[1488] Specific operation: The server receives an HTTP request and extracts a search query such as "Weather in Tokyo this weekend" from the request body.

[1489] Step 4:

[1490] The server passes the search query to a generation AI module for analysis.

[1491] Input: Extracted search query

[1492] Output: Information related to the analysis results (e.g., weather information)

[1493] How it works: The server passes the search query to the AI ​​generation module, which then analyzes the query and collects relevant information from the network, such as data from a weather forecast website.

[1494] Step 5:

[1495] The server filters the collected information and creates a summary.

[1496] Input: relevant information obtained from the generative AI module

[1497] Output: filtered and summarized text data

[1498] How it works: The server filters the collected information using an evaluation algorithm and summarizes the information selected based on reliability and recency, for example, "Saturday and Sunday will be sunny, with a maximum temperature of 25°C and a minimum temperature of 18°C."

[1499] Step 6:

[1500] The server analyzes the summarized information using an emotion engine and makes adjustments.

[1501] Input: Summarized text data

[1502] Output: Text data adjusted based on user sentiment

[1503] How it works: The server uses an emotion engine to tailor information based on the user's emotional data (e.g., past search history and real-time voice tone). For example, if the server determines that the user is tired, it will tailor the information to something like, "We hope the weekend will be sunny so you can feel refreshed!"

[1504] Step 7:

[1505] The server passes the adjusted text data to a speech synthesis engine to generate speech data.

[1506] Input: Adjusted text data

[1507] Output: Synthesized voice data

[1508] Specific operation: The server passes the adjusted text data to a speech synthesis engine to generate audio data (e.g., MP3 format). The speech synthesis engine generates audio with a tone that matches the user's emotions.

[1509] Step 8:

[1510] The server sends the generated audio data to the terminal as an HTTP response.

[1511] Input: Generated audio data

[1512] Output: HTTP response sent to the device

[1513] Specific operation: The generated audio data is sent to the terminal in the form of an HTTP response. The server specifies the type of audio data and transmits it in the appropriate format.

[1514] Step 9:

[1515] The terminal plays back the received audio data.

[1516] Input: Audio data received from the server

[1517] Output: Audio playback that the user can hear

[1518] Specific operation: The device decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Today and tomorrow's weather in Tokyo will be sunny, with a maximum temperature of 25 degrees and a minimum temperature of 18 degrees" will be heard in a voice tone that corresponds to the user's emotions.

[1519] These steps allow users to safely gather information while walking or on the move, and to receive that information in an emotionally sensitive way.

[1520] (Application example 2)

[1521] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1522] Conventional systems simply provide information when users input search queries to obtain information, without taking into account the user's emotions or circumstances. As a result, when receiving information in stressful or rushed situations in factories or production lines, the information delivery method may be inappropriate, resulting in reduced production efficiency and management capabilities. Furthermore, if information is not properly filtered and organized, the information provided to users may be excessive or inaccurate. To solve these issues, it is necessary to analyze the user's emotional state in real time and provide information appropriate to that emotion.

[1523] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1524] In this invention, the server includes an input means for a user to input a search query into a terminal, a transmission means for the terminal to transmit the search query to the server, an emotion analysis means for the terminal to analyze the user's emotion, and an adjustment means for adjusting the voice tone based on the emotion analysis means. This makes it possible to provide information by voice in an appropriate tone according to the user's emotion. This allows managers, particularly in factories and production lines, to obtain the information they need quickly and with little stress, improving production efficiency and management capabilities.

[1525] A "user" is a person who uses the system and is the entity that inputs a search query and obtains information.

[1526] A "terminal" is a computing device through which a user inputs a search query and communicates with a server.

[1527] A "search query" is text data that a user enters to identify the information they are looking for.

[1528] "Server" means a central control system for receiving search queries, collecting relevant information, and providing it to users.

[1529] The "transmission means" is a function for transmitting a search query from a terminal to a server, and for transmitting voice data from the server to a terminal.

[1530] A "generator" is a processing mechanism by which the server collects relevant information based on a search query.

[1531] "Filtering and organization" refers to the mechanism by which the server evaluates the information it collects and summarizes it in a form that is most relevant to the user.

[1532] The "voice synthesis means" is a mechanism for converting summarized information into voice data.

[1533] The "playback means" is a function for allowing the user to listen to the audio data received on the terminal.

[1534] The "emotion analysis means" is a mechanism for analyzing the user's emotional state in real time.

[1535] The "adjustment means" is a mechanism for adjusting the tone of the voice based on the emotion analysis means.

[1536] A "network" is an infrastructure for information communication such as the Internet.

[1537] A "data page" is a web page or database that contains information that exists on a network.

[1538] The "shaping means" is a mechanism for optimizing the information evaluated by the filtering and organizing means in a form that is presented to the user.

[1539] The present invention provides a system that allows a user to input a search query, collects information based on the query, analyzes the user's emotions, and provides the information in an appropriate voice tone. This system is composed of a terminal, a server, a transmission means, an input means, an emotion analysis means, a voice synthesis means, and a playback means.

[1540] Parts operated by the user

[1541] First, the user installs a dedicated application on their smart device (e.g., smartphone or tablet). They launch the application and enter the required information into the search bar. For example, they enter "current production efficiency." This input is processed as text data. The user then uses an emotion analysis tool, which analyzes the user's emotions during and after the search in real time. The emotion analysis tool analyzes the user's tone of voice and facial expressions, and reflects the results in the system.

[1542] Device behavior

[1543] The device sends the search query entered by the user to the server as an HTTP request. The device encodes the entered search query into JSON format and sends it to the server's API endpoint using the POST method.

[1544] Server Operation

[1545] The server receives an HTTP request and extracts the search query from the request body. The server passes this extracted query to the generation AI module. The generation AI module analyzes the query and collects the necessary information from related data pages and APIs. The server evaluates the collected information using a filtering algorithm and selects the most appropriate information based on its reliability and recency. The selected information undergoes a summarization process, generating text data to be provided to the user. The summarized text data is then adjusted by a sentiment analysis means to take into account the user's emotions.

[1546] Emotion-based speech synthesis and transmission

[1547] The server passes the summarized text data to a speech synthesis engine to generate voice data. The speech synthesis engine adjusts the voice tone according to the user's emotions based on the emotion analysis means described above. For example, if it determines that the user is in an emergency, it uses a quick and easy-to-understand voice tone. The generated voice data is again sent to the terminal in the form of an HTTP response.

[1548] Emotion-based audio playback on the device

[1549] The terminal decodes the voice data received from the server and plays it back within the dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an urgent tone to reflect the user's sense of urgency.

[1550] Specific examples

[1551] For example, if a line manager on a factory production line asks a robot assistant, "What is the current production efficiency?", the query is sent to a server, which collects and organizes the latest production data. If the emotion analysis tool determines that the user is under stress, the robot responds in a calm voice, "Current production efficiency is 95%. There are delays on some lines."

[1552] Prompt Sentence Examples

[1553] What is the current production efficiency?

[1554] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1555] Step 1:

[1556] A user enters a search query into a device.

[1557] (input)

[1558] The user enters specific information into the search bar of the dedicated application on the device, for example, "current production efficiency."

[1559] (output)

[1560] The search query is saved as text data on the device.

[1561] (Specific actions)

[1562] When a user uses a smartphone or tablet interface to enter text into the application's search bar, the emotion analysis means simultaneously analyzes the user's tone of voice and facial expressions.

[1563] Step 2:

[1564] The device sends a search query to the server.

[1565] (input)

[1566] User-entered search queries and real-time analyzed sentiment data.

[1567] (output)

[1568] The search query and sentiment data are sent to the server as an HTTP request.

[1569] (Specific actions)

[1570] The device creates an HTTP request, encodes the search query in JSON format, includes the emotion data in the request, and sends it to the server's API endpoint using the POST method.

[1571] Step 3:

[1572] The server receives the HTTP request and passes the search query to the generative AI model.

[1573] (input)

[1574] The search query and sentiment data sent to the server.

[1575] (output)

[1576] A search query is input into the generative AI model.

[1577] (Specific actions)

[1578] The server extracts search queries and sentiment data from the body of the received HTTP request, inputs the extracted search queries into a generative AI model, and collects information from related data pages and APIs.

[1579] Step 4:

[1580] Filtering and organizing the information collected by the server.

[1581] (input)

[1582] Relevant information collected by generative AI models.

[1583] (output)

[1584] A filtered and organized summary of information.

[1585] (Specific actions)

[1586] The server runs a filtering algorithm on the collected information to select the most relevant data based on its reliability and recency, and then the selected information is summarised and generated as concise text data.

[1587] Step 5:

[1588] The server passes the summarized text data to the speech synthesis engine.

[1589] (input)

[1590] Summarized text and sentiment data.

[1591] (output)

[1592] Audio data adjusted according to the user's emotions.

[1593] (Specific actions)

[1594] The server inputs the summarized text data into a speech synthesis engine, which adjusts the tone of the voice based on the emotion analysis means and generates speech data.

[1595] Step 6:

[1596] The server sends the audio data to the terminal.

[1597] (input)

[1598] The generated audio data.

[1599] (output)

[1600] The audio data is sent to the device as an HTTP response.

[1601] (Specific actions)

[1602] The server encodes the generated audio data in an appropriate format and sends it to the terminal as an HTTP response.

[1603] Step 7:

[1604] The terminal receives and plays the audio data.

[1605] (input)

[1606] Audio data sent from the server.

[1607] (output)

[1608] The user receives audio information in a tone that corresponds to the user's emotion.

[1609] (Specific actions)

[1610] The device decodes the received voice data and plays it back using a dedicated application. For example, information such as "Current production efficiency is 95%. Delays are occurring on some lines" is provided in an appropriate tone of voice, reflecting the user's real-time emotions.

[1611] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1612] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1613] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1614] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1615] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1616] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1617] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1618] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1619] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1620] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1621] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1622] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1623] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1624] 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.

[1625] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1626] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1627] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1628] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1629] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1630] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1631] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1632] The following is further disclosed regarding the above embodiment.

[1633] (Claim 1)

[1634] an input means for a user to input a search query into the terminal;

[1635] a transmitting means for transmitting the search query from the terminal to a server;

[1636] generating means for the server to receive the search query and collect related information from the Internet;

[1637] a filtering and organizing means for filtering and summarizing the information collected by the server;

[1638] a voice synthesis means for converting the summary into voice data;

[1639] a transmitting means for transmitting the voice data from the server to the terminal;

[1640] The system includes a playback means for playing back audio data received by said terminal.

[1641] (Claim 2)

[1642] 10. The system of claim 1, wherein the server further comprises identifying means for identifying relevant web pages based on a search query.

[1643] (Claim 3)

[1644] 2. The system of claim 1, wherein said server further comprises a formatting means for formatting the information evaluated by said filtering and organizing means into a form most appropriate for a user.

[1645] "Example 1"

[1646] (Claim 1)

[1647] an input means for a user to input a search query into the terminal;

[1648] a transmitting means for transmitting the search query from the terminal to a server;

[1649] a collection means for the server to receive the search query and gather related information using a generative model;

[1650] a filtering and organizing means for evaluating the information collected by the server using a filtering algorithm to generate a summary;

[1651] a voice synthesis means for converting the summary into voice data;

[1652] a transmitting means for transmitting the voice data from the server to the terminal;

[1653] The system includes a playback means for playing back audio data received by said terminal.

[1654] (Claim 2)

[1655] 10. The system of claim 1, wherein the server further comprises identifying means for retrieving information from relevant web pages or APIs based on the search query.

[1656] (Claim 3)

[1657] 2. The system of claim 1, wherein said server further comprises a formatting means for formatting the information evaluated by said filtering and organizing means into a form most appropriate for a user.

[1658] "Application Example 1"

[1659] (Claim 1)

[1660] an input means for a user to input a search query into the terminal;

[1661] a transmitting means for transmitting the search query from the terminal to a server;

[1662] generating means for the server to receive the search query and collect related information from the Internet;

[1663] a filtering and organizing means for filtering and summarizing the information collected by the server;

[1664] a voice synthesis means for converting the summary into voice data;

[1665] a transmitting means for transmitting the voice data from the server to the terminal;

[1666] a playback means for playing back the audio data received by the terminal;

[1667] robot control means for providing audible search results to a factory robot based on a user query;

[1668] a voice input means for inputting a user query by voice;

[1669] The system includes an audio playback means for the robot to play back the audio data.

[1670] (Claim 2)

[1671] 10. The system of claim 1, wherein the server further comprises identifying means for identifying relevant web pages based on a search query.

[1672] (Claim 3)

[1673] 2. The system of claim 1, wherein said server further comprises a formatting means for formatting the information evaluated by said filtering and organizing means into a form most appropriate for a user.

[1674] "Example 2: Combining Emotion Engines"

[1675] (Claim 1)

[1676] an input means for a user to input a search query into the terminal;

[1677] a transmitting means for transmitting the search query from the terminal to a server;

[1678] generating means for the server to receive the search query and collect related information from a network;

[1679] a filtering and organizing means for filtering and summarizing the information collected by the server;

[1680] emotion analysis means for analyzing the emotion of a user in the server;

[1681] an adjusting means for adjusting the summary based on the user's emotion;

[1682] a voice synthesis means for converting the adjusted summary into voice data by the server;

[1683] a transmitting means for transmitting the voice data from the server to the terminal;

[1684] The system includes a playback means for playing back audio data received by said terminal.

[1685] (Claim 2)

[1686] The system of claim 1 , wherein the server further comprises identifying means for identifying relevant sources of information based on the search query.

[1687] (Claim 3)

[1688] 2. The system of claim 1, wherein said server further comprises a formatting means for formatting the information evaluated by said filtering and organizing means into a form most appropriate for a user.

[1689] "Application example 2 when combining emotion engines"

[1690] (Claim 1)

[1691] an input means for a user to input a search query into the terminal;

[1692] a transmitting means for transmitting the search query from the terminal to a server;

[1693] generating means for the server to receive the search query and collect related information from a network;

[1694] a filtering and organizing means for filtering and summarizing the information collected by the server;

[1695] a voice synthesis means for converting the summary into voice data;

[1696] a transmitting means for transmitting the voice data from the server to the terminal;

[1697] a playback means for playing back the audio data received by the terminal;

[1698] emotion analysis means for the terminal to analyze the emotion of a user;

[1699] The system wherein the speech synthesis means includes adjustment means for adjusting speech tone based on the emotion analysis means.

[1700] (Claim 2)

[1701] The system of claim 1 , wherein the server further comprises identifying means for identifying relevant data pages based on a search query.

[1702] (Claim 3)

[1703] 2. The system of claim 1, wherein said server further comprises a formatting means for formatting the information evaluated by said filtering and organizing means into a form most appropriate for a user. [Explanation of symbols]

[1704] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an input means for a user to input a search query into the terminal; a transmitting means for transmitting the search query from the terminal to a server; generating means for the server to receive the search query and collect related information from the Internet; a filtering and organizing means for filtering and summarizing the information collected by the server; a voice synthesis means for converting the summary into voice data; a transmitting means for transmitting the voice data from the server to the terminal; The system includes a playback means for playing back audio data received by said terminal.

2. The system of claim 1 , wherein the server further comprises identifying means for identifying relevant web pages based on a search query.

3. 2. The system of claim 1, wherein said server further comprises a formatting means for formatting the information evaluated by said filtering and organizing means into a form most appropriate for a user.

Images