system

Abstract

We provide the system. [Solution] A means for analyzing natural language instructions received from a user and generating a script for the corresponding task, A means for executing the generated script on digital computing software, A means of converting user instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on those instructions, A means for presenting the execution result of the script to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] It is difficult for non-experts to easily perform complex operations and settings of digital spreadsheet software, resulting in a problem of reduced work efficiency. In addition, users often do not have the technical skills to generate and manage scripts, and in such a script-dependent working environment, there is a lack of flexibility in operations that require quick responses.

Means for Solving the Problems

[0005] This invention solves these problems by providing a system that allows users to instruct spreadsheet software operations using natural language. Specifically, it provides a system comprising means for analyzing the user's natural language instructions and generating a script, means for executing the generated script on the spreadsheet software, and means for providing feedback of the execution results to the user. As a result, even users without technical skills can intuitively operate the spreadsheet software, thereby improving work efficiency.

[0006] A "user" is an individual or group that operates a system and gives instructions in natural language.

[0007] "Natural language instructions" refer to commands that use everyday language to express a user's intentions or requests.

[0008] "Analysis" refers to information processing that involves interpreting instructions in natural language, understanding their content, and converting them into an executable format.

[0009] A "script" is a predefined program or code used to perform specific actions within digital spreadsheet software.

[0010] "Digital spreadsheet software" refers to software applications used to input, edit, and calculate numerical and text data in a tabular format.

[0011] "API" stands for Application Programming Interface, and it is a defined method for software to share functions and data with each other.

[0012] "Feedback" refers to the process of providing information to the user regarding the processes and results performed by a system. [Brief explanation of the drawing]

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

[0014] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

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

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

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

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

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0034] This invention relates to a system that enables users to provide instructions for operating spreadsheet software in their everyday language. Users input instructions in natural language through an interface on a terminal. These instructions include, but are not limited to, manipulating spreadsheet cells, filtering data, and summarizing data.

[0035] The server analyzes the natural language instructions received from the terminal. Natural language processing techniques are used for the analysis to clearly understand the meaning of the instructions. Specifically, the server extracts the target of the operation, the operation content, and the data range from the instructions, and based on this, generates a specific script for manipulating the spreadsheet.

[0036] The generated script is executed on existing digital spreadsheet software such as Google® Apps Script. The server automatically uses the online service's API as a communication channel to instruct the software to perform the corresponding operations. This process then translates the user's instructions into action on the spreadsheet.

[0037] The results of the execution are fed back to the user via the terminal. This feedback includes confirmation of whether the operation was completed successfully and a report of specific changes in the spreadsheet based on the instructions.

[0038] For example, if a user enters the instruction, "Filter the data in column B to 50 or greater, and copy the results to a new sheet," the server analyzes the instruction, generates a script to extract the relevant data from column B, and copy it to the new sheet. A message indicating successful filtering and copying is displayed on the terminal, allowing the user to proceed smoothly.

[0039] Thus, the present invention provides an environment in which users can intuitively perform complex spreadsheet operations using natural language, even without technical skills. This makes it possible to create a more efficient work environment.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user accesses the interface on their device and enters the operation they want to perform in natural language. For example, they might enter the instruction, "Sort the data in column A in ascending order."

[0043] Step 2:

[0044] The terminal receives instructions from the user in natural language and sends that data to the server. The data format is converted to a standard format that the system can parse.

[0045] Step 3:

[0046] The server analyzes the received natural language instructions. Here, natural language processing techniques are used to understand the content of the instructions and extract the details of the requested operation. Specifically, it identifies the target data range and the type of operation (e.g., sorting or filtering).

[0047] Step 4:

[0048] Based on the analysis results, the server automatically generates scripts for digital spreadsheet software such as Google Apps Script. These scripts are then assembled into the necessary code to perform specific spreadsheet operations.

[0049] Step 5:

[0050] The server executes the generated script via the spreadsheet API. The script is sent through the API call, and the operations are performed on the specified spreadsheet.

[0051] Step 6:

[0052] Once the operation is complete, the server sends a summary of the results back to the terminal. This includes information on whether the operation completed successfully or if any errors occurred.

[0053] Step 7:

[0054] The terminal receives results from the server and provides feedback to the user. For example, by displaying a confirmation message such as "Data has been sorted in ascending order," the user can confirm that the expected action was performed.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Operating digital computing software often requires users to possess complex technical skills, and there is a particular problem with using natural language instructions for operation. Therefore, many users find it difficult to use computing software intuitively and efficiently.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes means for a user to input operation instructions to a computing system in natural language, means using a generative AI model to analyze the input natural language instructions and extract information including the target of operation, the content of the operation, and the data range, and means for generating a script based on the extracted information and executing it on digital computing software. This makes it possible for users to intuitively operate complex digital computing software using natural language, even without technical skills.

[0060] A "user" refers to a person or organization that operates a digital computing system and gives instructions in natural language.

[0061] "Natural language" refers to the language that humans use in everyday life and is used to describe operations in spreadsheets and other digital computing systems.

[0062] A "generative AI model" is a computer program or system that uses natural language processing technology to analyze necessary information from input instructions and understand their meaning.

[0063] A "script" refers to a set of instructions written in digital computing software to perform a specific operation.

[0064] "Digital computing software" refers to digital applications for handling numerical data, providing functions such as data calculation, filtering, and aggregation.

[0065] A "program interface" refers to an interface that allows data and commands to be exchanged between different software or components, and to execute functions.

[0066] This invention is a system that enables users to directly operate digital computing software using natural language. The system consists of a user, a terminal, and a server.

[0067] On the terminal, users use an interface that allows them to operate digital calculation software such as spreadsheets using natural language. Users input instructions such as, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." This input is sent to the server via the internet.

[0068] When the server receives this natural language instruction, it performs analysis using a generative AI model. Specifically, it extracts information such as the target of the operation, the operation content, and the data range from the analysis of the instruction. This analysis utilizes natural language processing technology and uses prompt statements to accurately understand the intent of the user's instruction. An example of a prompt statement is, "Analyze the given instruction and generate a script to perform operations on the spreadsheet."

[0069] Based on the extracted information, the server generates a script for execution on digital computing software. Script generation utilizes scripting languages ​​and programming interfaces, one example being the scripting protocol provided by Google.

[0070] The generated script is sent to digital computing software via a program interface, and the specified operations are executed. The execution results are returned to the terminal as feedback and displayed to the user. This allows the user to check the progress and results of the work and continue working.

[0071] This system provides an environment where users can operate digital computing software using natural language without requiring specialized technical knowledge. As a result, operational efficiency and usability are improved, and the work environment is optimized.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user accesses the interface through their device and inputs instructions for manipulating the spreadsheet in natural language. For example, the input might be, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." These instructions are then sent from the device to the server.

[0075] Step 2:

[0076] The server analyzes natural language instructions received from the terminal using a generative AI model. Based on the analysis of the instructions, the server extracts elements such as the target of the operation (column B), the operation content (filtering and copying), and the data range (more than 50 data points). To improve the accuracy of the analysis, prompt sentences are provided to the AI ​​model to obtain the analysis results.

[0077] Step 3:

[0078] Based on the analysis results, the server generates a script to perform the necessary operations on the spreadsheet. A specific scripting language and programming interface are used for script generation. The generated script includes a series of steps for specific filtering and copying operations.

[0079] Step 4:

[0080] The server executes the generated script through the programming interface of the digital computing software. In this step, the script is actually executed using an online platform, and the instructed operations are performed on the spreadsheet.

[0081] Step 5:

[0082] Once the operation is complete, the server collects the results and sends them to the terminal. The terminal then provides feedback to the user, including a message indicating that the operation was successful and the changes made to the spreadsheet as a result of the operation. This allows the user to confirm that the operation yielded the intended results.

[0083] (Application Example 1)

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

[0085] Modern household management presents challenges such as inefficiency due to the large number of manual tasks and the difficulty for users to intuitively perform complex operations. In particular, there is a need for systems that can easily handle household management tasks such as meal planning, grocery management, and shopping list creation.

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

[0087] In this invention, the server includes means for analyzing natural language instructions received from a user and generating a script for the corresponding task; means for executing the generated script on digital computing software; and means for converting the user's instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on the instructions. This makes it possible to perform management tasks within the home efficiently and intuitively.

[0088] "User instructions" are requests or suggestions that users communicate to the system using natural language.

[0089] "Natural language processing" is the process by which computers understand human language and interpret its meaning.

[0090] "Script generation" is the process of automatically creating a set of instructions based on specific tasks or directives.

[0091] "Digital computing software" refers to programs used on computers to process and manage numerical data.

[0092] "Speech recognition technology" is a technology that converts speech into text, and it is the foundation for computers to understand human speech.

[0093] "Environmental information" refers to data concerning the physical or logical conditions under which a system operates.

[0094] "Automatic information generation" refers to the act of a program automatically creating necessary information based on specific rules or data.

[0095] "Household management" refers to the process of organizing and adjusting various resources, tasks, and schedules within a household.

[0096] To implement this invention, a system is needed in which the user gives instructions in natural language, which are then analyzed to perform household management tasks. The server uses speech recognition technology to convert the user's instructions into text. This technology includes a speech recognition system and uses natural language processing technology to analyze the instructions. The specific information generated by the analysis is automatically reflected by computational management software.

[0097] In this embodiment, a "speech recognition system" is used for speech recognition, a "natural language processing engine" for natural language processing, and a "computation management system" for operating digital computing software. This allows users to intuitively and efficiently manage various household tasks (e.g., creating shopping lists, managing groceries, etc.).

[0098] For example, if a user instructs the server to "create a list of ingredients needed for this week's dinners," the server will analyze the information, calculate the necessary ingredients based on past data and recipes, and reflect them in a spreadsheet. The prompt for such a generative AI model could be something like, "List the ingredients needed for dinner and tell me what else I need to buy."

[0099] This system allows users to perform complex management tasks in their living environment using natural language, even without specific knowledge, and to instantly see the results.

[0100] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0101] Step 1:

[0102] The user inputs instructions to the terminal using natural language voice. This voice data is digitized as a preprocessing step before being sent to the server by the terminal. This voice data then becomes the system's input.

[0103] Step 2:

[0104] The server uses speech recognition technology to convert the received audio data into text data. In this process, the speech recognition system identifies the audio pattern and outputs the corresponding string. The resulting text becomes the input for the next processing step.

[0105] Step 3:

[0106] The server uses a natural language processing engine to analyze text data. This analysis clarifies the instructions and their intent, and identifies the necessary tasks and operations. The analysis results are output as work content and target data based on the user's instructions.

[0107] Step 4:

[0108] Based on the analysis results, the server activates an automated script generation module to create a script for the computation management software. This script contains specific instructions for performing the identified tasks and defines the operations to be performed on the spreadsheet. The generated script is passed to the next execution step as system output.

[0109] Step 5:

[0110] The server executes the generated script on digital computing software and performs the specified data manipulation. This process automatically organizes the information according to the user's request and reflects it in a spreadsheet. The results of the operation are updated internally by the system and output as feedback to the user.

[0111] Step 6:

[0112] The terminal displays the execution results to the user, reporting whether it was successful or not, and any changes in the spreadsheet. The user can then review the feedback and take necessary actions. This completes the information and lists the user needs, allowing them to easily proceed to the next step.

[0113] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0114] This invention relates to a system that recognizes emotions and optimizes the entire system when a user gives instructions in natural language to manipulate a spreadsheet. The user inputs instructions in natural language that reflect their emotions through the terminal interface. For example, a user who feels uneasy about setting up a complex formula can give instructions such as, "I want this formula to be set up correctly, but I feel a little uneasy."

[0115] The server analyzes natural language instructions received from the terminal. This analysis utilizes natural language processing techniques as well as an emotion engine. The emotion engine analyzes the emotions contained within the user's instructions and responds adaptively based on that analysis. For example, if an emotion indicating anxiety is detected, the server can simplify the operation and generate a script with detailed guidance.

[0116] Subsequently, the server automatically generates scripts, such as Google Apps Script, that take the user's emotional state into account, and executes them on digital spreadsheet software. During this process, the server accesses the spreadsheet via an API and performs predetermined operations. For example, it flexibly adjusts the operations to provide progress feedback based on the user's emotions.

[0117] The execution results are returned to the device as feedback. This feedback includes messages that are considerate of the user's feelings, so for example, a message such as "The work is progressing smoothly. If you have any further questions or concerns, we will provide support" may be displayed.

[0118] For example, if a user inputs a message such as, "I want to analyze data, but I'm nervous because I don't know how to start," the system recognizes this emotion and generates and executes a script that provides step-by-step guidance. This allows the user to experience an intuitive and reassuring interaction.

[0119] Thus, in this embodiment of the present invention, the system understands the user's emotions and automatically positions and adjusts accordingly, making it possible to provide a more user-friendly and intuitive operating environment.

[0120] The following describes the processing flow.

[0121] Step 1:

[0122] Users input instructions for operating the spreadsheet using natural language via their device. It's also possible to include emotions in these instructions. For example, they might input an instruction such as, "I want to see the sales data trends, but I'm a little worried."

[0123] Step 2:

[0124] The terminal receives input from the user and sends that data to the server. Here, natural language input is delivered to the server in its original format.

[0125] Step 3:

[0126] The server analyzes the received instructions. First, it interprets the instructions using natural language processing techniques, and then it recognizes the user's emotional state using an emotion engine. This process extracts both the analyzed information and the emotional data.

[0127] Step 4:

[0128] Based on the analysis results, the server automatically generates application scripts that take emotional states into consideration. When performing complex processing, it can also add explanatory text and assistance based on the emotional state.

[0129] Step 5:

[0130] The server executes the generated script on digital spreadsheet software. It accesses the spreadsheet via an API and performs specified operations. For example, it generates a graph to visualize sales data trends.

[0131] Step 6:

[0132] The server aggregates the results of the script execution, generates an emotion-based feedback message, and sends it to the terminal. This feedback is tailored to align with the user's emotions and is designed to provide a sense of reassurance.

[0133] Step 7:

[0134] The device receives feedback from the server and displays the results to the user. For example, a message such as, "Sales trends were analyzed successfully. Please contact us if you have any further questions." This provides the user with an interaction that takes both results and emotions into consideration.

[0135] (Example 2)

[0136] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0137] When users provide information processing instructions using natural language, a problem exists in that it can be difficult to obtain the intended result if the instructions are complex or if the user's emotional state is not adequately considered. This invention aims to solve this problem and realize natural interaction that responds to the user's emotions and efficient information processing.

[0138] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0139] In this invention, the server includes means for analyzing natural language instructions received from a user, performing sentiment analysis, and generating automated procedures for corresponding tasks based on the analysis; means for executing the generated automated procedures on information processing software; and means for providing feedback on the execution results of the automated procedures in a manner that takes the user's emotions into consideration. This makes it possible to perform information processing efficiently while taking the user's emotions into consideration.

[0140] A "user" is an entity that uses a system to give instructions and receives the results.

[0141] "Natural language" refers to the language system that humans use on a daily basis, and which requires analysis by a computer.

[0142] "Instructions" are pieces of information that represent requests or commands regarding operations or processes that a user performs on a system.

[0143] "Analysis" is the process of interpretation and analysis that a system performs in order to understand and process information received from a user.

[0144] "Emotion analysis" is the process of detecting the emotions contained in a user's instructions and evaluating their state.

[0145] An "automated procedure" is a series of processing steps generated based on instructions to perform a specific task on information processing software.

[0146] "Information processing software" is a collection of programs used to manipulate, analyze, and display digital data.

[0147] "Feedback" refers to information provided to the user regarding the results and progress of a process.

[0148] An "interface" is a point of contact or method for an information processing system to interact with a user or another system.

[0149] This invention provides a system that optimizes user interaction with information processing software by considering the user's emotions when the user operates the software using natural language. The user inputs instructions in natural language via a terminal, and the system analyzes these instructions and performs emotion analysis.

[0150] The server analyzes user instructions using natural language processing technology. An emotion engine is used for the analysis, evaluating the emotions within the instructions. Based on the evaluated emotions, the server generates adaptive automated procedures. These automated procedures execute tasks on information processing software. Specific software such as Google Apps Script can be used. The server accesses data via APIs through the information processing software interface and performs the specified processing.

[0151] The processing results are returned to the device as feedback, displaying messages that take the user's emotional state into consideration. This feedback is designed to reduce the user's anxiety about the operation and allow them to proceed with confidence. For example, it may include a message such as, "The process is progressing smoothly. If you have any questions or concerns, we are here to help."

[0152] For example, if a user inputs a message such as, "I want to analyze data, but I don't know where to start," the server recognizes this sentiment and generates and executes an automated procedure that provides step-by-step guidance. This process allows the user to experience an intuitive and reassuring interaction.

[0153] An example of a prompt message for a generative AI model might be, "Generate a guide to help users easily configure spreadsheets, which they may find confusing."

[0154] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0155] Step 1:

[0156] The user inputs natural language instructions through their device. These instructions include the actions the user wants to perform on the spreadsheet and the emotions associated with them. The entered text data is sent to the server.

[0157] Step 2:

[0158] The server uses natural language processing techniques to analyze user input. The analysis engine extracts keywords from the input data and works to understand the intent. Next, the emotion engine evaluates the emotions within the instructions and adds the detected emotion information to generate processed data. Based on this data, the server identifies the user's emotional state.

[0159] Step 3:

[0160] The server generates automated procedures based on the analysis results and emotional information. Specifically, it creates a script for the generating AI model using the prompt, "The user is anxious, so guide them through the steps to smoothly add a column to the spreadsheet." This script is structured to include guidance that alleviates the user's anxiety.

[0161] Step 4:

[0162] The server uses information processing software such as Google Apps Script to execute the generated automation procedures. The server accesses the spreadsheet via an API, processes the data according to the analysis results, and performs the necessary operations. Here, the operations on the specified spreadsheet are performed automatically.

[0163] Step 5:

[0164] The execution results are returned from the server to the terminal. The server notifies the user of the results, including a message confirming the success of the operation and providing detailed feedback. For example, a message such as "Column addition complete. Please let us know if you have any questions" might appear on the user's terminal. This allows the user to confirm the system's execution results and gain confidence in proceeding with the next operation.

[0165] (Application Example 2)

[0166] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0167] When users operate digital spreadsheet applications, there is a need to reduce emotional burden and enable intuitive voice-based input. However, conventional systems often disregard user emotions, and their complexity can increase user burden. Furthermore, users may feel uneasy with mechanical interfaces, so it is necessary to build a system that can solve these problems.

[0168] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0169] In this invention, the server includes means for analyzing natural language instructions received from the user and generating a script for the corresponding task; means for executing the generated script on a digital spreadsheet application; means for recognizing the user's emotions using emotion analysis technology and optimizing the instructions; means for obtaining natural language instructions from the user using speech recognition technology; and means for providing feedback to the user on the results of the script execution. This enables the optimization of operations based on the user's voice instructions and emotions.

[0170] A "user" is someone who operates a digital device and provides instructions or information through natural language or voice.

[0171] "Natural language instructions" are instructions that are in the form of commands or inquiries made in the language that users use on a daily basis, and that contain information that can be interpreted by a machine.

[0172] A "script" is program code generated to automate specific operations within a digital spreadsheet application.

[0173] A "digital spreadsheet application" is software that runs on digital devices and is used for organizing and calculating data.

[0174] "Emotion analysis technology" is a technology that analyzes information and behavior from users to identify their emotional state.

[0175] "Voice recognition technology" is a technology that allows a digital device to interpret the voice spoken by a user as text information and use it as an operation command.

[0176] "Feedback" is a response from a system to a user, providing them with the results of their actions or supplementary information.

[0177] An "application programming interface" is an interface that allows other programs to access the functions and data of software.

[0178] The embodiments for carrying out the present invention are shown below.

[0179] The server receives instructions provided by the user via voice, combining speech recognition and natural language processing technologies. This involves a speech recognition module converting the speech into text data, and a natural language processing engine analyzing that text to understand its meaning. This technology is implemented using open-source speech recognition libraries and commercial natural language processing models.

[0180] Furthermore, the server generates scripts to automate related tasks based on the parsed natural language instructions. These scripts are executed via the API of a digital spreadsheet application, such as using Google Apps Script. The generated scripts are designed to perform the necessary data manipulations on the spreadsheet application and meet the user's requirements.

[0181] The server also uses sentiment analysis technology to detect emotions from the user's voice instructions. Sentiment analysis is a process that infers the user's emotional state from specific keywords and phrases and optimizes the response accordingly. For example, if the user shows anxiety, it provides feedback that explains the operation procedure in detail. This feedback is played aloud to help the user feel more at ease interacting with the system.

[0182] Users can operate a digital spreadsheet application using voice commands via a home smart speaker. By receiving feedback from the server, they can reduce anxiety about ongoing operations and manage data intuitively and effectively.

[0183] As a concrete example, consider a scenario where a user gives a voice command such as, "I need help managing this month's budget, but I'm unsure, so please explain in detail." In this case, the system recognizes the user's anxiety through sentiment analysis and executes a script while presenting detailed steps. Furthermore, when inputting prompt text into the generating AI model, it is recommended to use instructions that take into account the user's voice command and their emotions.

[0184] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0185] Step 1:

[0186] The user inputs voice commands into the smart speaker. The smart speaker uses a voice recognition module to convert the voice into text. This text is sent to a server as input data for analysis by a natural language processing engine.

[0187] Step 2:

[0188] The server analyzes the received text data using a natural language processing engine. Through this analysis, it identifies the meaning of the instructions and extracts information necessary to convert them into a script to be executed in a digital spreadsheet application. In this process, it obtains necessary formulas and cell location information, generating the basic data for script generation.

[0189] Step 3:

[0190] The server uses an emotion analysis engine to detect the user's emotional state from text data. The emotional information extracted through emotion analysis influences subsequent feedback and the steps taken during script execution. Based on these results, if the user is anxious, instructions are set to generate a script that includes detailed steps.

[0191] Step 4:

[0192] The server uses platforms such as Google Apps Script to automatically generate scripts that respond to user instructions and emotional states. These generated scripts are executed via the API of a digital spreadsheet application, performing specified calculations and data manipulations, and reflecting the results in the spreadsheet.

[0193] Step 5:

[0194] The server generates a feedback message for the user based on the results after the script execution. This message takes into account the user's emotional state and may include content such as, "The task is complete. Do you have any concerns?" The feedback message is delivered to the user as an audio message via a smart speaker.

[0195] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0196] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0197] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0198] [Second Embodiment]

[0199] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0200] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0201] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0202] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0203] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0204] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0205] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0206] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0207] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0208] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0209] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0210] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0211] This invention relates to a system that enables users to provide instructions for operating spreadsheet software in their everyday language. Users input instructions in natural language through an interface on a terminal. These instructions include, but are not limited to, manipulating spreadsheet cells, filtering data, and summarizing data.

[0212] The server analyzes the natural language instructions received from the terminal. Natural language processing techniques are used for the analysis to clearly understand the meaning of the instructions. Specifically, the server extracts the target of the operation, the operation content, and the data range from the instructions, and based on this, generates a specific script for manipulating the spreadsheet.

[0213] The generated script is executed on existing digital spreadsheet software such as Google Apps Script. The server automatically uses the online service's API as a communication channel to instruct the software to perform the corresponding operations. This process then translates the user's instructions into action on the spreadsheet.

[0214] The results of the execution are fed back to the user via the terminal. This feedback includes confirmation of whether the operation was completed successfully and a report of specific changes in the spreadsheet based on the instructions.

[0215] For example, if a user enters the instruction, "Filter the data in column B to 50 or greater, and copy the results to a new sheet," the server analyzes the instruction, generates a script to extract the relevant data from column B, and copy it to the new sheet. A message indicating successful filtering and copying is displayed on the terminal, allowing the user to proceed smoothly.

[0216] Thus, the present invention provides an environment in which users can intuitively perform complex spreadsheet operations using natural language, even without technical skills. This makes it possible to create a more efficient work environment.

[0217] The following describes the processing flow.

[0218] Step 1:

[0219] The user accesses the interface on their device and enters the operation they want to perform in natural language. For example, they might enter the instruction, "Sort the data in column A in ascending order."

[0220] Step 2:

[0221] The terminal receives instructions from the user in natural language and sends that data to the server. The data format is converted to a standard format that the system can parse.

[0222] Step 3:

[0223] The server analyzes the received natural language instructions. Here, natural language processing techniques are used to understand the content of the instructions and extract the details of the requested operation. Specifically, it identifies the target data range and the type of operation (e.g., sorting or filtering).

[0224] Step 4:

[0225] Based on the analysis results, the server automatically generates scripts for digital spreadsheet software such as Google Apps Script. These scripts are then assembled into the necessary code to perform specific spreadsheet operations.

[0226] Step 5:

[0227] The server executes the generated script via the spreadsheet API. The script is sent through the API call, and the operations are performed on the specified spreadsheet.

[0228] Step 6:

[0229] Once the operation is complete, the server sends a summary of the results back to the terminal. This includes information on whether the operation completed successfully or if any errors occurred.

[0230] Step 7:

[0231] The terminal receives results from the server and provides feedback to the user. For example, by displaying a confirmation message such as "Data has been sorted in ascending order," the user can confirm that the expected action was performed.

[0232] (Example 1)

[0233] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0234] Operating digital computing software often requires users to possess complex technical skills, and there is a particular problem with using natural language instructions for operation. Therefore, many users find it difficult to use computing software intuitively and efficiently.

[0235] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0236] In this invention, the server includes means for a user to input operation instructions to a computing system in natural language, means using a generative AI model to analyze the input natural language instructions and extract information including the target of operation, the content of the operation, and the data range, and means for generating a script based on the extracted information and executing it on digital computing software. This makes it possible for users to intuitively operate complex digital computing software using natural language, even without technical skills.

[0237] A "user" refers to a person or organization that operates a digital computing system and gives instructions in natural language.

[0238] "Natural language" refers to the language that humans use in everyday life and is used to describe operations in spreadsheets and other digital computing systems.

[0239] A "generative AI model" is a computer program or system that uses natural language processing technology to analyze necessary information from input instructions and understand their meaning.

[0240] A "script" refers to a set of instructions written in digital computing software to perform a specific operation.

[0241] "Digital computing software" refers to digital applications for handling numerical data, providing functions such as data calculation, filtering, and aggregation.

[0242] A "program interface" refers to an interface that allows data and commands to be exchanged between different software or components, and to execute functions.

[0243] This invention is a system that enables users to directly operate digital computing software using natural language. The system consists of a user, a terminal, and a server.

[0244] On the terminal, users use an interface that allows them to operate digital calculation software such as spreadsheets using natural language. Users input instructions such as, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." This input is sent to the server via the internet.

[0245] When the server receives this natural language instruction, it performs analysis using a generative AI model. Specifically, it extracts information such as the target of the operation, the operation content, and the data range from the analysis of the instruction. This analysis utilizes natural language processing technology and uses prompt statements to accurately understand the intent of the user's instruction. An example of a prompt statement is, "Analyze the given instruction and generate a script to perform operations on the spreadsheet."

[0246] Based on the extracted information, the server generates a script for execution on digital computing software. Script generation utilizes scripting languages ​​and programming interfaces, one example being the scripting protocol provided by Google.

[0247] The generated script is sent to digital computing software via a program interface, and the specified operations are executed. The execution results are returned to the terminal as feedback and displayed to the user. This allows the user to check the progress and results of the work and continue working.

[0248] This system provides an environment where users can operate digital computing software using natural language without requiring specialized technical knowledge. As a result, operational efficiency and usability are improved, and the work environment is optimized.

[0249] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0250] Step 1:

[0251] The user accesses the interface through their device and inputs instructions for manipulating the spreadsheet in natural language. For example, the input might be, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." These instructions are then sent from the device to the server.

[0252] Step 2:

[0253] The server analyzes natural language instructions received from the terminal using a generative AI model. Based on the analysis of the instructions, the server extracts elements such as the target of the operation (column B), the operation content (filtering and copying), and the data range (more than 50 data points). To improve the accuracy of the analysis, prompt sentences are provided to the AI ​​model to obtain the analysis results.

[0254] Step 3:

[0255] Based on the analysis results, the server generates a script to perform the necessary operations on the spreadsheet. A specific scripting language and programming interface are used for script generation. The generated script includes a series of steps for specific filtering and copying operations.

[0256] Step 4:

[0257] The server executes the generated script through the programming interface of the digital computing software. In this step, the script is actually executed using an online platform, and the instructed operations are performed on the spreadsheet.

[0258] Step 5:

[0259] Once the operation is complete, the server collects the results and sends them to the terminal. The terminal then provides feedback to the user, including a message indicating that the operation was successful and the changes made to the spreadsheet as a result of the operation. This allows the user to confirm that the operation yielded the intended results.

[0260] (Application Example 1)

[0261] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0262] Modern household management presents challenges such as inefficiency due to the large number of manual tasks and the difficulty for users to intuitively perform complex operations. In particular, there is a need for systems that can easily handle household management tasks such as meal planning, grocery management, and shopping list creation.

[0263] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0264] In this invention, the server includes means for analyzing natural language instructions received from a user and generating a script for the corresponding task; means for executing the generated script on digital computing software; and means for converting the user's instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on the instructions. This makes it possible to perform management tasks within the home efficiently and intuitively.

[0265] "User instructions" are requests or suggestions that users communicate to the system using natural language.

[0266] "Natural language processing" is the process by which computers understand human language and interpret its meaning.

[0267] "Script generation" is the process of automatically creating a set of instructions based on specific tasks or directives.

[0268] "Digital computing software" refers to programs used on computers to process and manage numerical data.

[0269] "Speech recognition technology" is a technology that converts speech into text, and it is the foundation for computers to understand human speech.

[0270] "Environmental information" refers to data concerning the physical or logical conditions under which a system operates.

[0271] "Automatic information generation" refers to the act of a program automatically creating necessary information based on specific rules or data.

[0272] "Household management" refers to the process of organizing and adjusting various resources, tasks, and schedules within a household.

[0273] To implement this invention, a system is needed in which the user gives instructions in natural language, which are then analyzed to perform household management tasks. The server uses speech recognition technology to convert the user's instructions into text. This technology includes a speech recognition system and uses natural language processing technology to analyze the instructions. The specific information generated by the analysis is automatically reflected by computational management software.

[0274] In this embodiment, a "speech recognition system" is used for speech recognition, a "natural language processing engine" for natural language processing, and a "computation management system" for operating digital computing software. This allows users to intuitively and efficiently manage various household tasks (e.g., creating shopping lists, managing groceries, etc.).

[0275] For example, if a user instructs the server to "create a list of ingredients needed for this week's dinners," the server will analyze the information, calculate the necessary ingredients based on past data and recipes, and reflect them in a spreadsheet. The prompt for such a generative AI model could be something like, "List the ingredients needed for dinner and tell me what else I need to buy."

[0276] This system allows users to perform complex management tasks in their living environment using natural language, even without specific knowledge, and to instantly see the results.

[0277] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0278] Step 1:

[0279] The user inputs instructions to the terminal using natural language voice. This voice data is digitized as a preprocessing step before being sent to the server by the terminal. This voice data then becomes the system's input.

[0280] Step 2:

[0281] The server uses speech recognition technology to convert the received voice data into text data. In this process, the speech recognition system identifies the speech pattern and outputs the corresponding character string. The obtained text becomes the input for the next processing step.

[0282] Step 3:

[0283] The server uses a natural language processing engine to analyze the text data. Through this analysis, the instruction content and its intention are clarified, and the necessary tasks and operations are identified. The analysis results are output as the work content and target data based on the user's instructions.

[0284] Step 4:

[0285] Based on the analysis results, the server activates an automatic script generation module to create a script for calculation management software. This script contains specific instructions for executing the identified tasks and defines the operation content of the spreadsheet. The generated script is passed to the next execution step as the output of the system.

[0286] Step 5:

[0287] The server executes the generated script on digital calculation software to perform the specified data operations. Through this process, the information according to the user's requirements is automatically sorted and reflected in the spreadsheet. The operation results are updated within the system and output as feedback to the user.

[0288] Step 6:

[0289] The terminal displays the execution results to the user and reports the success or failure and the changes in the spreadsheet. The user can check the feedback and take necessary actions. As a result, the information and list required by the user are completed, and it becomes a situation where the next step can be easily advanced.

[0290] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0291] This invention relates to a system that recognizes emotions and optimizes the entire system when a user gives instructions in natural language to manipulate a spreadsheet. The user inputs instructions in natural language that reflect their emotions through the terminal interface. For example, a user who feels uneasy about setting up a complex formula can give instructions such as, "I want this formula to be set up correctly, but I feel a little uneasy."

[0292] The server analyzes natural language instructions received from the terminal. This analysis utilizes natural language processing techniques as well as an emotion engine. The emotion engine analyzes the emotions contained within the user's instructions and responds adaptively based on that analysis. For example, if an emotion indicating anxiety is detected, the server can simplify the operation and generate a script with detailed guidance.

[0293] Subsequently, the server automatically generates scripts, such as Google Apps Script, that take the user's emotional state into account, and executes them on digital spreadsheet software. During this process, the server accesses the spreadsheet via an API and performs predetermined operations. For example, it flexibly adjusts the operations to provide progress feedback based on the user's emotions.

[0294] The execution results are returned to the device as feedback. This feedback includes messages that are considerate of the user's feelings, so for example, a message such as "The work is progressing smoothly. If you have any further questions or concerns, we will provide support" may be displayed.

[0295] For example, if a user inputs a message such as, "I want to analyze data, but I'm nervous because I don't know how to start," the system recognizes this emotion and generates and executes a script that provides step-by-step guidance. This allows the user to experience an intuitive and reassuring interaction.

[0296] Thus, in this embodiment of the present invention, the system understands the user's emotions and automatically positions and adjusts accordingly, making it possible to provide a more user-friendly and intuitive operating environment.

[0297] The following describes the processing flow.

[0298] Step 1:

[0299] Users input instructions for operating the spreadsheet using natural language via their device. It's also possible to include emotions in these instructions. For example, they might input an instruction such as, "I want to see the sales data trends, but I'm a little worried."

[0300] Step 2:

[0301] The terminal receives input from the user and sends that data to the server. Here, natural language input is delivered to the server in its original format.

[0302] Step 3:

[0303] The server analyzes the received instructions. First, it interprets the instructions using natural language processing techniques, and then it recognizes the user's emotional state using an emotion engine. This process extracts both the analyzed information and the emotional data.

[0304] Step 4:

[0305] Based on the analysis results, the server automatically generates application scripts that take emotional states into consideration. When performing complex processing, it can also add explanatory text and assistance based on the emotional state.

[0306] Step 5:

[0307] The server executes the generated script on digital spreadsheet software. It accesses the spreadsheet via the API and performs the specified operations. For example, it generates a graph to visualize the trend of sales data.

[0308] Step 6:

[0309] The server summarizes the execution results of the script, generates a feedback message according to the emotion, and sends it to the terminal. This feedback is along the lines of the user's emotion and is adjusted to give a sense of reassurance.

[0310] Step 7:

[0311] The terminal receives the feedback from the server and displays the results to the user. For example, a message like "The sales trend has been analyzed normally. If you have any additional questions, please feel free to consult." The user is thus provided with an interaction that takes into account the results and emotions.

[0312] (Example 2)

[0313] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0314] When the user gives an information processing instruction in natural language, there is a problem that it is difficult to obtain the intended result if the instruction is complex or the user's emotional state is not appropriately considered. The present invention aims to solve such problems and realize natural interaction and efficient information processing according to the user's emotion.

[0315] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0316] In this invention, the server includes means for analyzing natural language instructions received from a user, performing sentiment analysis, and generating automated procedures for corresponding tasks based on the analysis; means for executing the generated automated procedures on information processing software; and means for providing feedback on the execution results of the automated procedures in a manner that takes the user's emotions into consideration. This makes it possible to perform information processing efficiently while taking the user's emotions into consideration.

[0317] A "user" is an entity that uses a system to give instructions and receives the results.

[0318] "Natural language" refers to the language system that humans use on a daily basis, and which requires analysis by a computer.

[0319] "Instructions" are pieces of information that represent requests or commands regarding operations or processes that a user performs on a system.

[0320] "Analysis" is the process of interpretation and analysis that a system performs in order to understand and process information received from a user.

[0321] "Emotion analysis" is the process of detecting the emotions contained in a user's instructions and evaluating their state.

[0322] An "automated procedure" is a series of processing steps generated based on instructions to perform a specific task on information processing software.

[0323] "Information processing software" is a collection of programs used to manipulate, analyze, and display digital data.

[0324] "Feedback" refers to information provided to the user regarding the results and progress of a process.

[0325] An "interface" is a point of contact or method for an information processing system to interact with a user or another system.

[0326] This invention provides a system that optimizes user interaction with information processing software by considering the user's emotions when the user operates the software using natural language. The user inputs instructions in natural language via a terminal, and the system analyzes these instructions and performs emotion analysis.

[0327] The server analyzes user instructions using natural language processing technology. An emotion engine is used for the analysis, evaluating the emotions within the instructions. Based on the evaluated emotions, the server generates adaptive automated procedures. These automated procedures execute tasks on information processing software. Specific software such as Google Apps Script can be used. The server accesses data via APIs through the information processing software interface and performs the specified processing.

[0328] The processing results are returned to the device as feedback, displaying messages that take the user's emotional state into consideration. This feedback is designed to reduce the user's anxiety about the operation and allow them to proceed with confidence. For example, it may include a message such as, "The process is progressing smoothly. If you have any questions or concerns, we are here to help."

[0329] For example, if a user inputs a message such as, "I want to analyze data, but I don't know where to start," the server recognizes this sentiment and generates and executes an automated procedure that provides step-by-step guidance. This process allows the user to experience an intuitive and reassuring interaction.

[0330] An example of a prompt message for a generative AI model might be, "Generate a guide to help users easily configure spreadsheets, which they may find confusing."

[0331] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0332] Step 1:

[0333] The user inputs natural language instructions through their device. These instructions include the actions the user wants to perform on the spreadsheet and the emotions associated with them. The entered text data is sent to the server.

[0334] Step 2:

[0335] The server uses natural language processing techniques to analyze user input. The analysis engine extracts keywords from the input data and works to understand the intent. Next, the emotion engine evaluates the emotions within the instructions and adds the detected emotion information to generate processed data. Based on this data, the server identifies the user's emotional state.

[0336] Step 3:

[0337] The server generates automated procedures based on the analysis results and emotional information. Specifically, it creates a script for the generating AI model using the prompt, "The user is anxious, so guide them through the steps to smoothly add a column to the spreadsheet." This script is structured to include guidance that alleviates the user's anxiety.

[0338] Step 4:

[0339] The server uses information processing software such as Google Apps Script to execute the generated automation procedures. The server accesses the spreadsheet via an API, processes the data according to the analysis results, and performs the necessary operations. Here, the operations on the specified spreadsheet are performed automatically.

[0340] Step 5:

[0341] The execution results are returned from the server to the terminal. The server notifies the user of the results, including a message confirming the success of the operation and providing detailed feedback. For example, a message such as "Column addition complete. Please let us know if you have any questions" might appear on the user's terminal. This allows the user to confirm the system's execution results and gain confidence in proceeding with the next operation.

[0342] (Application Example 2)

[0343] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0344] When users operate digital spreadsheet applications, there is a need to reduce emotional burden and enable intuitive voice-based input. However, conventional systems often disregard user emotions, and their complexity can increase user burden. Furthermore, users may feel uneasy with mechanical interfaces, so it is necessary to build a system that can solve these problems.

[0345] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0346] In this invention, the server includes means for analyzing natural language instructions received from the user and generating a script for the corresponding task; means for executing the generated script on a digital spreadsheet application; means for recognizing the user's emotions using emotion analysis technology and optimizing the instructions; means for obtaining natural language instructions from the user using speech recognition technology; and means for providing feedback to the user on the results of the script execution. This enables the optimization of operations based on the user's voice instructions and emotions.

[0347] A "user" is someone who operates a digital device and provides instructions or information through natural language or voice.

[0348] "Natural language instructions" are instructions that are in the form of commands or inquiries made in the language that users use on a daily basis, and that contain information that can be interpreted by a machine.

[0349] A "script" is program code generated to automate specific operations within a digital spreadsheet application.

[0350] A "digital spreadsheet application" is software that runs on digital devices and is used for organizing and calculating data.

[0351] "Emotion analysis technology" is a technology that analyzes information and behavior from users to identify their emotional state.

[0352] "Voice recognition technology" is a technology that allows a digital device to interpret the voice spoken by a user as text information and use it as an operation command.

[0353] "Feedback" is a response from a system to a user, providing them with the results of their actions or supplementary information.

[0354] An "application programming interface" is an interface that allows other programs to access the functions and data of software.

[0355] The embodiments for carrying out the present invention are shown below.

[0356] The server receives instructions provided by the user via voice, combining speech recognition and natural language processing technologies. This involves a speech recognition module converting the speech into text data, and a natural language processing engine analyzing that text to understand its meaning. This technology is implemented using open-source speech recognition libraries and commercial natural language processing models.

[0357] Furthermore, the server generates scripts to automate related tasks based on the parsed natural language instructions. These scripts are executed via the API of a digital spreadsheet application, such as using Google Apps Script. The generated scripts are designed to perform the necessary data manipulations on the spreadsheet application and meet the user's requirements.

[0358] The server also uses sentiment analysis technology to detect emotions from the user's voice instructions. Sentiment analysis is a process that infers the user's emotional state from specific keywords and phrases and optimizes the response accordingly. For example, if the user shows anxiety, it provides feedback that explains the operation procedure in detail. This feedback is played aloud to help the user feel more at ease interacting with the system.

[0359] Users can operate a digital spreadsheet application using voice commands via a home smart speaker. By receiving feedback from the server, they can reduce anxiety about ongoing operations and manage data intuitively and effectively.

[0360] As a concrete example, consider a scenario where a user gives a voice command such as, "I need help managing this month's budget, but I'm unsure, so please explain in detail." In this case, the system recognizes the user's anxiety through sentiment analysis and executes a script while presenting detailed steps. Furthermore, when inputting prompt text into the generating AI model, it is recommended to use instructions that take into account the user's voice command and their emotions.

[0361] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0362] Step 1:

[0363] The user inputs voice commands into the smart speaker. The smart speaker uses a voice recognition module to convert the voice into text. This text is sent to a server as input data for analysis by a natural language processing engine.

[0364] Step 2:

[0365] The server analyzes the received text data using a natural language processing engine. Through this analysis, it identifies the meaning of the instructions and extracts information necessary to convert them into a script to be executed in a digital spreadsheet application. In this process, it obtains necessary formulas and cell location information, generating the basic data for script generation.

[0366] Step 3:

[0367] The server uses an emotion analysis engine to detect the user's emotional state from text data. The emotional information extracted through emotion analysis influences subsequent feedback and the steps taken during script execution. Based on these results, if the user is anxious, instructions are set to generate a script that includes detailed steps.

[0368] Step 4:

[0369] The server uses platforms such as Google Apps Script to automatically generate scripts that respond to user instructions and emotional states. These generated scripts are executed via the API of a digital spreadsheet application, performing specified calculations and data manipulations, and reflecting the results in the spreadsheet.

[0370] Step 5:

[0371] The server generates a feedback message for the user based on the results after the script execution. This message takes into account the user's emotional state and may include content such as, "The task is complete. Do you have any concerns?" The feedback message is delivered to the user as an audio message via a smart speaker.

[0372] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0373] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0374] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0375] [Third Embodiment]

[0376] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0377] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0378] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0379] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0380] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0381] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0382] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0383] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0384] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0385] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0386] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0387] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0388] This invention relates to a system that enables users to provide instructions for operating spreadsheet software in their everyday language. Users input instructions in natural language through an interface on a terminal. These instructions include, but are not limited to, manipulating spreadsheet cells, filtering data, and summarizing data.

[0389] The server analyzes the natural language instructions received from the terminal. Natural language processing techniques are used for the analysis to clearly understand the meaning of the instructions. Specifically, the server extracts the target of the operation, the operation content, and the data range from the instructions, and based on this, generates a specific script for manipulating the spreadsheet.

[0390] The generated script is executed on existing digital spreadsheet software such as Google Apps Script. The server automatically uses the online service's API as a communication channel to instruct the software to perform the corresponding operations. This process then translates the user's instructions into action on the spreadsheet.

[0391] The results of the execution are fed back to the user via the terminal. This feedback includes confirmation of whether the operation was completed successfully and a report of specific changes in the spreadsheet based on the instructions.

[0392] For example, if a user enters the instruction, "Filter the data in column B to 50 or greater, and copy the results to a new sheet," the server analyzes the instruction, generates a script to extract the relevant data from column B, and copy it to the new sheet. A message indicating successful filtering and copying is displayed on the terminal, allowing the user to proceed smoothly.

[0393] Thus, the present invention provides an environment in which users can intuitively perform complex spreadsheet operations using natural language, even without technical skills. This makes it possible to create a more efficient work environment.

[0394] The following describes the processing flow.

[0395] Step 1:

[0396] The user accesses the interface on their device and enters the operation they want to perform in natural language. For example, they might enter the instruction, "Sort the data in column A in ascending order."

[0397] Step 2:

[0398] The terminal receives instructions from the user in natural language and sends that data to the server. The data format is converted to a standard format that the system can parse.

[0399] Step 3:

[0400] The server analyzes the received natural language instructions. Here, natural language processing techniques are used to understand the content of the instructions and extract the details of the requested operation. Specifically, it identifies the target data range and the type of operation (e.g., sorting or filtering).

[0401] Step 4:

[0402] Based on the analysis results, the server automatically generates scripts for digital spreadsheet software such as Google Apps Script. These scripts are then assembled into the necessary code to perform specific spreadsheet operations.

[0403] Step 5:

[0404] The server executes the generated script via the spreadsheet API. The script is sent through the API call, and the operations are performed on the specified spreadsheet.

[0405] Step 6:

[0406] Once the operation is complete, the server sends a summary of the results back to the terminal. This includes information on whether the operation completed successfully or if any errors occurred.

[0407] Step 7:

[0408] The terminal receives results from the server and provides feedback to the user. For example, by displaying a confirmation message such as "Data has been sorted in ascending order," the user can confirm that the expected action was performed.

[0409] (Example 1)

[0410] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0411] Operating digital computing software often requires users to possess complex technical skills, and there is a particular problem with using natural language instructions for operation. Therefore, many users find it difficult to use computing software intuitively and efficiently.

[0412] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0413] In this invention, the server includes means for a user to input operation instructions to a computing system in natural language, means using a generative AI model to analyze the input natural language instructions and extract information including the target of operation, the content of the operation, and the data range, and means for generating a script based on the extracted information and executing it on digital computing software. This makes it possible for users to intuitively operate complex digital computing software using natural language, even without technical skills.

[0414] A "user" refers to a person or organization that operates a digital computing system and gives instructions in natural language.

[0415] "Natural language" refers to the language that humans use in everyday life and is used to describe operations in spreadsheets and other digital computing systems.

[0416] A "generative AI model" is a computer program or system that uses natural language processing technology to analyze necessary information from input instructions and understand their meaning.

[0417] A "script" refers to a set of instructions written in digital computing software to perform a specific operation.

[0418] "Digital computing software" refers to digital applications for handling numerical data, providing functions such as data calculation, filtering, and aggregation.

[0419] A "program interface" refers to an interface that allows data and commands to be exchanged between different software or components, and to execute functions.

[0420] This invention is a system that enables users to directly operate digital computing software using natural language. The system consists of a user, a terminal, and a server.

[0421] On the terminal, users use an interface that allows them to operate digital calculation software such as spreadsheets using natural language. Users input instructions such as, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." This input is sent to the server via the internet.

[0422] When the server receives this natural language instruction, it performs analysis using a generative AI model. Specifically, it extracts information such as the target of the operation, the operation content, and the data range from the analysis of the instruction. This analysis utilizes natural language processing technology and uses prompt statements to accurately understand the intent of the user's instruction. An example of a prompt statement is, "Analyze the given instruction and generate a script to perform operations on the spreadsheet."

[0423] Based on the extracted information, the server generates a script for execution on digital computing software. Script generation utilizes scripting languages ​​and programming interfaces, one example being the scripting protocol provided by Google.

[0424] The generated script is sent to digital computing software via a program interface, and the specified operations are executed. The execution results are returned to the terminal as feedback and displayed to the user. This allows the user to check the progress and results of the work and continue working.

[0425] This system provides an environment where users can operate digital computing software using natural language without requiring specialized technical knowledge. As a result, operational efficiency and usability are improved, and the work environment is optimized.

[0426] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0427] Step 1:

[0428] The user accesses the interface through their device and inputs instructions for manipulating the spreadsheet in natural language. For example, the input might be, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." These instructions are then sent from the device to the server.

[0429] Step 2:

[0430] The server analyzes natural language instructions received from the terminal using a generative AI model. Based on the analysis of the instructions, the server extracts elements such as the target of the operation (column B), the operation content (filtering and copying), and the data range (more than 50 data points). To improve the accuracy of the analysis, prompt sentences are provided to the AI ​​model to obtain the analysis results.

[0431] Step 3:

[0432] Based on the analysis results, the server generates a script to perform the necessary operations on the spreadsheet. A specific scripting language and programming interface are used for script generation. The generated script includes a series of steps for specific filtering and copying operations.

[0433] Step 4:

[0434] The server executes the generated script through the programming interface of the digital computing software. In this step, the script is actually executed using an online platform, and the instructed operations are performed on the spreadsheet.

[0435] Step 5:

[0436] Once the operation is complete, the server collects the results and sends them to the terminal. The terminal then provides feedback to the user, including a message indicating that the operation was successful and the changes made to the spreadsheet as a result of the operation. This allows the user to confirm that the operation yielded the intended results.

[0437] (Application Example 1)

[0438] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0439] Modern household management presents challenges such as inefficiency due to the large number of manual tasks and the difficulty for users to intuitively perform complex operations. In particular, there is a need for systems that can easily handle household management tasks such as meal planning, grocery management, and shopping list creation.

[0440] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0441] In this invention, the server includes means for analyzing natural language instructions received from a user and generating a script for the corresponding task; means for executing the generated script on digital computing software; and means for converting the user's instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on the instructions. This makes it possible to perform management tasks within the home efficiently and intuitively.

[0442] "User instructions" are requests or suggestions that users communicate to the system using natural language.

[0443] "Natural language processing" is the process by which computers understand human language and interpret its meaning.

[0444] "Script generation" is the process of automatically creating a set of instructions based on specific tasks or directives.

[0445] "Digital computing software" refers to programs used on computers to process and manage numerical data.

[0446] "Speech recognition technology" is a technology that converts speech into text, and it is the foundation for computers to understand human speech.

[0447] "Environmental information" refers to data concerning the physical or logical conditions under which a system operates.

[0448] "Automatic information generation" refers to the act of a program automatically creating necessary information based on specific rules or data.

[0449] "Household management" refers to the process of organizing and adjusting various resources, tasks, and schedules within a household.

[0450] To implement this invention, a system is needed in which the user gives instructions in natural language, which are then analyzed to perform household management tasks. The server uses speech recognition technology to convert the user's instructions into text. This technology includes a speech recognition system and uses natural language processing technology to analyze the instructions. The specific information generated by the analysis is automatically reflected by computational management software.

[0451] In this embodiment, a "speech recognition system" is used for speech recognition, a "natural language processing engine" for natural language processing, and a "computation management system" for operating digital computing software. This allows users to intuitively and efficiently manage various household tasks (e.g., creating shopping lists, managing groceries, etc.).

[0452] For example, if a user instructs the server to "create a list of ingredients needed for this week's dinners," the server will analyze the information, calculate the necessary ingredients based on past data and recipes, and reflect them in a spreadsheet. The prompt for such a generative AI model could be something like, "List the ingredients needed for dinner and tell me what else I need to buy."

[0453] This system allows users to perform complex management tasks in their living environment using natural language, even without specific knowledge, and to instantly see the results.

[0454] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0455] Step 1:

[0456] The user inputs instructions to the terminal using natural language voice. This voice data is digitized as a preprocessing step before being sent to the server by the terminal. This voice data then becomes the system's input.

[0457] Step 2:

[0458] The server uses speech recognition technology to convert the received audio data into text data. In this process, the speech recognition system identifies the audio pattern and outputs the corresponding string. The resulting text becomes the input for the next processing step.

[0459] Step 3:

[0460] The server uses a natural language processing engine to analyze text data. This analysis clarifies the instructions and their intent, and identifies the necessary tasks and operations. The analysis results are output as work content and target data based on the user's instructions.

[0461] Step 4:

[0462] Based on the analysis results, the server activates an automated script generation module to create a script for the computation management software. This script contains specific instructions for performing the identified tasks and defines the operations to be performed on the spreadsheet. The generated script is passed to the next execution step as system output.

[0463] Step 5:

[0464] The server executes the generated script on digital computing software and performs the specified data manipulation. This process automatically organizes the information according to the user's request and reflects it in a spreadsheet. The results of the operation are updated internally by the system and output as feedback to the user.

[0465] Step 6:

[0466] The terminal displays the execution results to the user, reporting whether it was successful or not, and any changes in the spreadsheet. The user can then review the feedback and take necessary actions. This completes the information and lists the user needs, allowing them to easily proceed to the next step.

[0467] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0468] This invention relates to a system that recognizes emotions and optimizes the entire system when a user gives instructions in natural language to manipulate a spreadsheet. The user inputs instructions in natural language that reflect their emotions through the terminal interface. For example, a user who feels uneasy about setting up a complex formula can give instructions such as, "I want this formula to be set up correctly, but I feel a little uneasy."

[0469] The server analyzes natural language instructions received from the terminal. This analysis utilizes natural language processing techniques as well as an emotion engine. The emotion engine analyzes the emotions contained within the user's instructions and responds adaptively based on that analysis. For example, if an emotion indicating anxiety is detected, the server can simplify the operation and generate a script with detailed guidance.

[0470] Subsequently, the server automatically generates scripts, such as Google Apps Script, that take the user's emotional state into account, and executes them on digital spreadsheet software. During this process, the server accesses the spreadsheet via an API and performs predetermined operations. For example, it flexibly adjusts the operations to provide progress feedback based on the user's emotions.

[0471] The execution results are returned to the device as feedback. This feedback includes messages that are considerate of the user's feelings, so for example, a message such as "The work is progressing smoothly. If you have any further questions or concerns, we will provide support" may be displayed.

[0472] For example, if a user inputs a message such as, "I want to analyze data, but I'm nervous because I don't know how to start," the system recognizes this emotion and generates and executes a script that provides step-by-step guidance. This allows the user to experience an intuitive and reassuring interaction.

[0473] Thus, in this embodiment of the present invention, the system understands the user's emotions and automatically positions and adjusts accordingly, making it possible to provide a more user-friendly and intuitive operating environment.

[0474] The following describes the processing flow.

[0475] Step 1:

[0476] Users input instructions for operating the spreadsheet using natural language via their device. It's also possible to include emotions in these instructions. For example, they might input an instruction such as, "I want to see the sales data trends, but I'm a little worried."

[0477] Step 2:

[0478] The terminal receives input from the user and sends that data to the server. Here, natural language input is delivered to the server in its original format.

[0479] Step 3:

[0480] The server analyzes the received instructions. First, it interprets the instructions using natural language processing techniques, and then it recognizes the user's emotional state using an emotion engine. This process extracts both the analyzed information and the emotional data.

[0481] Step 4:

[0482] Based on the analysis results, the server automatically generates application scripts that take emotional states into consideration. When performing complex processing, it can also add explanatory text and assistance based on the emotional state.

[0483] Step 5:

[0484] The server executes the generated script on digital spreadsheet software. It accesses the spreadsheet via an API and performs specified operations. For example, it generates a graph to visualize sales data trends.

[0485] Step 6:

[0486] The server aggregates the results of the script execution, generates an emotion-based feedback message, and sends it to the terminal. This feedback is tailored to align with the user's emotions and is designed to provide a sense of reassurance.

[0487] Step 7:

[0488] The device receives feedback from the server and displays the results to the user. For example, a message such as, "Sales trends were analyzed successfully. Please contact us if you have any further questions." This provides the user with an interaction that takes both results and emotions into consideration.

[0489] (Example 2)

[0490] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0491] When users provide information processing instructions using natural language, a problem exists in that it can be difficult to obtain the intended result if the instructions are complex or if the user's emotional state is not adequately considered. This invention aims to solve this problem and realize natural interaction that responds to the user's emotions and efficient information processing.

[0492] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0493] In this invention, the server includes means for analyzing natural language instructions received from a user, performing sentiment analysis, and generating automated procedures for corresponding tasks based on the analysis; means for executing the generated automated procedures on information processing software; and means for providing feedback on the execution results of the automated procedures in a manner that takes the user's emotions into consideration. This makes it possible to perform information processing efficiently while taking the user's emotions into consideration.

[0494] A "user" is an entity that uses a system to give instructions and receives the results.

[0495] "Natural language" refers to the language system that humans use on a daily basis, and which requires analysis by a computer.

[0496] "Instructions" are pieces of information that represent requests or commands regarding operations or processes that a user performs on a system.

[0497] "Analysis" is the process of interpretation and analysis that a system performs in order to understand and process information received from a user.

[0498] "Emotion analysis" is the process of detecting the emotions contained in a user's instructions and evaluating their state.

[0499] An "automated procedure" is a series of processing steps generated based on instructions to perform a specific task on information processing software.

[0500] "Information processing software" is a collection of programs used to manipulate, analyze, and display digital data.

[0501] "Feedback" refers to information provided to the user regarding the results and progress of a process.

[0502] An "interface" is a point of contact or method for an information processing system to interact with a user or another system.

[0503] This invention provides a system that optimizes user interaction with information processing software by considering the user's emotions when the user operates the software using natural language. The user inputs instructions in natural language via a terminal, and the system analyzes these instructions and performs emotion analysis.

[0504] The server analyzes user instructions using natural language processing technology. An emotion engine is used for the analysis, evaluating the emotions within the instructions. Based on the evaluated emotions, the server generates adaptive automated procedures. These automated procedures execute tasks on information processing software. Specific software such as Google Apps Script can be used. The server accesses data via APIs through the information processing software interface and performs the specified processing.

[0505] The processing results are returned to the device as feedback, displaying messages that take the user's emotional state into consideration. This feedback is designed to reduce the user's anxiety about the operation and allow them to proceed with confidence. For example, it may include a message such as, "The process is progressing smoothly. If you have any questions or concerns, we are here to help."

[0506] For example, if a user inputs a message such as, "I want to analyze data, but I don't know where to start," the server recognizes this sentiment and generates and executes an automated procedure that provides step-by-step guidance. This process allows the user to experience an intuitive and reassuring interaction.

[0507] An example of a prompt message for a generative AI model might be, "Generate a guide to help users easily configure spreadsheets, which they may find confusing."

[0508] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0509] Step 1:

[0510] The user inputs natural language instructions through their device. These instructions include the actions the user wants to perform on the spreadsheet and the emotions associated with them. The entered text data is sent to the server.

[0511] Step 2:

[0512] The server uses natural language processing techniques to analyze user input. The analysis engine extracts keywords from the input data and works to understand the intent. Next, the emotion engine evaluates the emotions within the instructions and adds the detected emotion information to generate processed data. Based on this data, the server identifies the user's emotional state.

[0513] Step 3:

[0514] The server generates automated procedures based on the analysis results and emotional information. Specifically, it creates a script for the generating AI model using the prompt, "The user is anxious, so guide them through the steps to smoothly add a column to the spreadsheet." This script is structured to include guidance that alleviates the user's anxiety.

[0515] Step 4:

[0516] The server uses information processing software such as Google Apps Script to execute the generated automation procedures. The server accesses the spreadsheet via an API, processes the data according to the analysis results, and performs the necessary operations. Here, the operations on the specified spreadsheet are performed automatically.

[0517] Step 5:

[0518] The execution results are returned from the server to the terminal. The server notifies the user of the results, including a message confirming the success of the operation and providing detailed feedback. For example, a message such as "Column addition complete. Please let us know if you have any questions" might appear on the user's terminal. This allows the user to confirm the system's execution results and gain confidence in proceeding with the next operation.

[0519] (Application Example 2)

[0520] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0521] When users operate digital spreadsheet applications, there is a need to reduce emotional burden and enable intuitive voice-based input. However, conventional systems often disregard user emotions, and their complexity can increase user burden. Furthermore, users may feel uneasy with mechanical interfaces, so it is necessary to build a system that can solve these problems.

[0522] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0523] In this invention, the server includes means for analyzing natural language instructions received from the user and generating a script for the corresponding task; means for executing the generated script on a digital spreadsheet application; means for recognizing the user's emotions using emotion analysis technology and optimizing the instructions; means for obtaining natural language instructions from the user using speech recognition technology; and means for providing feedback to the user on the results of the script execution. This enables the optimization of operations based on the user's voice instructions and emotions.

[0524] A "user" is someone who operates a digital device and provides instructions or information through natural language or voice.

[0525] "Natural language instructions" are instructions that are in the form of commands or inquiries made in the language that users use on a daily basis, and that contain information that can be interpreted by a machine.

[0526] A "script" is program code generated to automate specific operations within a digital spreadsheet application.

[0527] A "digital spreadsheet application" is software that runs on digital devices and is used for organizing and calculating data.

[0528] "Emotion analysis technology" is a technology that analyzes information and behavior from users to identify their emotional state.

[0529] "Voice recognition technology" is a technology that allows a digital device to interpret the voice spoken by a user as text information and use it as an operation command.

[0530] "Feedback" is a response from a system to a user, providing them with the results of their actions or supplementary information.

[0531] An "application programming interface" is an interface that allows other programs to access the functions and data of software.

[0532] The embodiments for carrying out the present invention are shown below.

[0533] The server receives instructions provided by the user via voice, combining speech recognition and natural language processing technologies. This involves a speech recognition module converting the speech into text data, and a natural language processing engine analyzing that text to understand its meaning. This technology is implemented using open-source speech recognition libraries and commercial natural language processing models.

[0534] Furthermore, the server generates scripts to automate related tasks based on the parsed natural language instructions. These scripts are executed via the API of a digital spreadsheet application, such as using Google Apps Script. The generated scripts are designed to perform the necessary data manipulations on the spreadsheet application and meet the user's requirements.

[0535] The server also uses sentiment analysis technology to detect emotions from the user's voice instructions. Sentiment analysis is a process that infers the user's emotional state from specific keywords and phrases and optimizes the response accordingly. For example, if the user shows anxiety, it provides feedback that explains the operation procedure in detail. This feedback is played aloud to help the user feel more at ease interacting with the system.

[0536] Users can operate a digital spreadsheet application using voice commands via a home smart speaker. By receiving feedback from the server, they can reduce anxiety about ongoing operations and manage data intuitively and effectively.

[0537] As a concrete example, consider a scenario where a user gives a voice command such as, "I need help managing this month's budget, but I'm unsure, so please explain in detail." In this case, the system recognizes the user's anxiety through sentiment analysis and executes a script while presenting detailed steps. Furthermore, when inputting prompt text into the generating AI model, it is recommended to use instructions that take into account the user's voice command and their emotions.

[0538] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0539] Step 1:

[0540] The user inputs voice commands into the smart speaker. The smart speaker uses a voice recognition module to convert the voice into text. This text is sent to a server as input data for analysis by a natural language processing engine.

[0541] Step 2:

[0542] The server analyzes the received text data using a natural language processing engine. Through this analysis, it identifies the meaning of the instructions and extracts information necessary to convert them into a script to be executed in a digital spreadsheet application. In this process, it obtains necessary formulas and cell location information, generating the basic data for script generation.

[0543] Step 3:

[0544] The server uses an emotion analysis engine to detect the user's emotional state from text data. The emotional information extracted through emotion analysis influences subsequent feedback and the steps taken during script execution. Based on these results, if the user is anxious, instructions are set to generate a script that includes detailed steps.

[0545] Step 4:

[0546] The server uses platforms such as Google Apps Script to automatically generate scripts that respond to user instructions and emotional states. These generated scripts are executed via the API of a digital spreadsheet application, performing specified calculations and data manipulations, and reflecting the results in the spreadsheet.

[0547] Step 5:

[0548] The server generates a feedback message for the user based on the results after the script execution. This message takes into account the user's emotional state and may include content such as, "The task is complete. Do you have any concerns?" The feedback message is delivered to the user as an audio message via a smart speaker.

[0549] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0550] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0551] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0552] [Fourth Embodiment]

[0553] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0554] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0555] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0556] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0557] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0558] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0559] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0560] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0561] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0562] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0563] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0564] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0565] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0566] This invention relates to a system that enables users to provide instructions for operating spreadsheet software in their everyday language. Users input instructions in natural language through an interface on a terminal. These instructions include, but are not limited to, manipulating spreadsheet cells, filtering data, and summarizing data.

[0567] The server analyzes the natural language instructions received from the terminal. Natural language processing techniques are used for the analysis to clearly understand the meaning of the instructions. Specifically, the server extracts the target of the operation, the operation content, and the data range from the instructions, and based on this, generates a specific script for manipulating the spreadsheet.

[0568] The generated script is executed on existing digital spreadsheet software such as Google Apps Script. The server automatically uses the online service's API as a communication channel to instruct the software to perform the corresponding operations. This process then translates the user's instructions into action on the spreadsheet.

[0569] The results of the execution are fed back to the user via the terminal. This feedback includes confirmation of whether the operation was completed successfully and a report of specific changes in the spreadsheet based on the instructions.

[0570] For example, if a user enters the instruction, "Filter the data in column B to 50 or greater, and copy the results to a new sheet," the server analyzes the instruction, generates a script to extract the relevant data from column B, and copy it to the new sheet. A message indicating successful filtering and copying is displayed on the terminal, allowing the user to proceed smoothly.

[0571] Thus, the present invention provides an environment in which users can intuitively perform complex spreadsheet operations using natural language, even without technical skills. This makes it possible to create a more efficient work environment.

[0572] The following describes the processing flow.

[0573] Step 1:

[0574] The user accesses the interface on their device and enters the operation they want to perform in natural language. For example, they might enter the instruction, "Sort the data in column A in ascending order."

[0575] Step 2:

[0576] The terminal receives instructions from the user in natural language and sends that data to the server. The data format is converted to a standard format that the system can parse.

[0577] Step 3:

[0578] The server analyzes the received natural language instructions. Here, natural language processing techniques are used to understand the content of the instructions and extract the details of the requested operation. Specifically, it identifies the target data range and the type of operation (e.g., sorting or filtering).

[0579] Step 4:

[0580] Based on the analysis results, the server automatically generates scripts for digital spreadsheet software such as Google Apps Script. These scripts are then assembled into the necessary code to perform specific spreadsheet operations.

[0581] Step 5:

[0582] The server executes the generated script via the spreadsheet API. The script is sent through the API call, and the operations are performed on the specified spreadsheet.

[0583] Step 6:

[0584] Once the operation is complete, the server sends a summary of the results back to the terminal. This includes information on whether the operation completed successfully or if any errors occurred.

[0585] Step 7:

[0586] The terminal receives results from the server and provides feedback to the user. For example, by displaying a confirmation message such as "Data has been sorted in ascending order," the user can confirm that the expected action was performed.

[0587] (Example 1)

[0588] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0589] Operating digital computing software often requires users to possess complex technical skills, and there is a particular problem with using natural language instructions for operation. Therefore, many users find it difficult to use computing software intuitively and efficiently.

[0590] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0591] In this invention, the server includes means for a user to input operation instructions to a computing system in natural language, means using a generative AI model to analyze the input natural language instructions and extract information including the target of operation, the content of the operation, and the data range, and means for generating a script based on the extracted information and executing it on digital computing software. This makes it possible for users to intuitively operate complex digital computing software using natural language, even without technical skills.

[0592] A "user" refers to a person or organization that operates a digital computing system and gives instructions in natural language.

[0593] "Natural language" refers to the language that humans use in everyday life and is used to describe operations in spreadsheets and other digital computing systems.

[0594] A "generative AI model" is a computer program or system that uses natural language processing technology to analyze necessary information from input instructions and understand their meaning.

[0595] A "script" refers to a set of instructions written in digital computing software to perform a specific operation.

[0596] "Digital computing software" refers to digital applications for handling numerical data, providing functions such as data calculation, filtering, and aggregation.

[0597] A "program interface" refers to an interface that allows data and commands to be exchanged between different software or components, and to execute functions.

[0598] This invention is a system that enables users to directly operate digital computing software using natural language. The system consists of a user, a terminal, and a server.

[0599] On the terminal, users use an interface that allows them to operate digital calculation software such as spreadsheets using natural language. Users input instructions such as, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." This input is sent to the server via the internet.

[0600] When the server receives this natural language instruction, it performs analysis using a generative AI model. Specifically, it extracts information such as the target of the operation, the operation content, and the data range from the analysis of the instruction. This analysis utilizes natural language processing technology and uses prompt statements to accurately understand the intent of the user's instruction. An example of a prompt statement is, "Analyze the given instruction and generate a script to perform operations on the spreadsheet."

[0601] Based on the extracted information, the server generates a script for execution on digital computing software. Script generation utilizes scripting languages ​​and programming interfaces, one example being the scripting protocol provided by Google.

[0602] The generated script is sent to digital computing software via a program interface, and the specified operations are executed. The execution results are returned to the terminal as feedback and displayed to the user. This allows the user to check the progress and results of the work and continue working.

[0603] This system provides an environment where users can operate digital computing software using natural language without requiring specialized technical knowledge. As a result, operational efficiency and usability are improved, and the work environment is optimized.

[0604] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0605] Step 1:

[0606] The user accesses the interface through their device and inputs instructions for manipulating the spreadsheet in natural language. For example, the input might be, "Filter the data in column B to 50 or greater, and copy the results to a new sheet." These instructions are then sent from the device to the server.

[0607] Step 2:

[0608] The server analyzes natural language instructions received from the terminal using a generative AI model. Based on the analysis of the instructions, the server extracts elements such as the target of the operation (column B), the operation content (filtering and copying), and the data range (more than 50 data points). To improve the accuracy of the analysis, prompt sentences are provided to the AI ​​model to obtain the analysis results.

[0609] Step 3:

[0610] Based on the analysis results, the server generates a script to perform the necessary operations on the spreadsheet. A specific scripting language and programming interface are used for script generation. The generated script includes a series of steps for specific filtering and copying operations.

[0611] Step 4:

[0612] The server executes the generated script through the programming interface of the digital computing software. In this step, the script is actually executed using an online platform, and the instructed operations are performed on the spreadsheet.

[0613] Step 5:

[0614] Once the operation is complete, the server collects the results and sends them to the terminal. The terminal then provides feedback to the user, including a message indicating that the operation was successful and the changes made to the spreadsheet as a result of the operation. This allows the user to confirm that the operation yielded the intended results.

[0615] (Application Example 1)

[0616] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0617] Modern household management presents challenges such as inefficiency due to the large number of manual tasks and the difficulty for users to intuitively perform complex operations. In particular, there is a need for systems that can easily handle household management tasks such as meal planning, grocery management, and shopping list creation.

[0618] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0619] In this invention, the server includes means for analyzing natural language instructions received from a user and generating a script for the corresponding task; means for executing the generated script on digital computing software; and means for converting the user's instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on the instructions. This makes it possible to perform management tasks within the home efficiently and intuitively.

[0620] "User instructions" are requests or suggestions that users communicate to the system using natural language.

[0621] "Natural language processing" is the process by which computers understand human language and interpret its meaning.

[0622] "Script generation" is the process of automatically creating a set of instructions based on specific tasks or directives.

[0623] "Digital computing software" refers to programs used on computers to process and manage numerical data.

[0624] "Speech recognition technology" is a technology that converts speech into text, and it is the foundation for computers to understand human speech.

[0625] "Environmental information" refers to data concerning the physical or logical conditions under which a system operates.

[0626] "Automatic information generation" refers to the act of a program automatically creating necessary information based on specific rules or data.

[0627] "Household management" refers to the process of organizing and adjusting various resources, tasks, and schedules within a household.

[0628] To implement this invention, a system is needed in which the user gives instructions in natural language, which are then analyzed to perform household management tasks. The server uses speech recognition technology to convert the user's instructions into text. This technology includes a speech recognition system and uses natural language processing technology to analyze the instructions. The specific information generated by the analysis is automatically reflected by computational management software.

[0629] In this embodiment, a "speech recognition system" is used for speech recognition, a "natural language processing engine" for natural language processing, and a "computation management system" for operating digital computing software. This allows users to intuitively and efficiently manage various household tasks (e.g., creating shopping lists, managing groceries, etc.).

[0630] For example, if a user instructs the server to "create a list of ingredients needed for this week's dinners," the server will analyze the information, calculate the necessary ingredients based on past data and recipes, and reflect them in a spreadsheet. The prompt for such a generative AI model could be something like, "List the ingredients needed for dinner and tell me what else I need to buy."

[0631] This system allows users to perform complex management tasks in their living environment using natural language, even without specific knowledge, and to instantly see the results.

[0632] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0633] Step 1:

[0634] The user inputs instructions to the terminal using natural language voice. This voice data is digitized as a preprocessing step before being sent to the server by the terminal. This voice data then becomes the system's input.

[0635] Step 2:

[0636] The server uses speech recognition technology to convert the received audio data into text data. In this process, the speech recognition system identifies the audio pattern and outputs the corresponding string. The resulting text becomes the input for the next processing step.

[0637] Step 3:

[0638] The server uses a natural language processing engine to analyze text data. This analysis clarifies the instructions and their intent, and identifies the necessary tasks and operations. The analysis results are output as work content and target data based on the user's instructions.

[0639] Step 4:

[0640] Based on the analysis results, the server activates an automated script generation module to create a script for the computation management software. This script contains specific instructions for performing the identified tasks and defines the operations to be performed on the spreadsheet. The generated script is passed to the next execution step as system output.

[0641] Step 5:

[0642] The server executes the generated script on digital computing software and performs the specified data manipulation. This process automatically organizes the information according to the user's request and reflects it in a spreadsheet. The results of the operation are updated internally by the system and output as feedback to the user.

[0643] Step 6:

[0644] The terminal displays the execution results to the user, reporting whether it was successful or not, and any changes in the spreadsheet. The user can then review the feedback and take necessary actions. This completes the information and lists the user needs, allowing them to easily proceed to the next step.

[0645] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0646] This invention relates to a system that recognizes emotions and optimizes the entire system when a user gives instructions in natural language to manipulate a spreadsheet. The user inputs instructions in natural language that reflect their emotions through the terminal interface. For example, a user who feels uneasy about setting up a complex formula can give instructions such as, "I want this formula to be set up correctly, but I feel a little uneasy."

[0647] The server analyzes natural language instructions received from the terminal. This analysis utilizes natural language processing techniques as well as an emotion engine. The emotion engine analyzes the emotions contained within the user's instructions and responds adaptively based on that analysis. For example, if an emotion indicating anxiety is detected, the server can simplify the operation and generate a script with detailed guidance.

[0648] Subsequently, the server automatically generates scripts, such as Google Apps Script, that take the user's emotional state into account, and executes them on digital spreadsheet software. During this process, the server accesses the spreadsheet via an API and performs predetermined operations. For example, it flexibly adjusts the operations to provide progress feedback based on the user's emotions.

[0649] The execution results are returned to the device as feedback. This feedback includes messages that are considerate of the user's feelings, so for example, a message such as "The work is progressing smoothly. If you have any further questions or concerns, we will provide support" may be displayed.

[0650] For example, if a user inputs a message such as, "I want to analyze data, but I'm nervous because I don't know how to start," the system recognizes this emotion and generates and executes a script that provides step-by-step guidance. This allows the user to experience an intuitive and reassuring interaction.

[0651] Thus, in this embodiment of the present invention, the system understands the user's emotions and automatically positions and adjusts accordingly, making it possible to provide a more user-friendly and intuitive operating environment.

[0652] The following describes the processing flow.

[0653] Step 1:

[0654] Users input instructions for operating the spreadsheet using natural language via their device. It's also possible to include emotions in these instructions. For example, they might input an instruction such as, "I want to see the sales data trends, but I'm a little worried."

[0655] Step 2:

[0656] The terminal receives input from the user and sends that data to the server. Here, natural language input is delivered to the server in its original format.

[0657] Step 3:

[0658] The server analyzes the received instructions. First, it interprets the instructions using natural language processing techniques, and then it recognizes the user's emotional state using an emotion engine. This process extracts both the analyzed information and the emotional data.

[0659] Step 4:

[0660] Based on the analysis results, the server automatically generates application scripts that take emotional states into consideration. When performing complex processing, it can also add explanatory text and assistance based on the emotional state.

[0661] Step 5:

[0662] The server executes the generated script on digital spreadsheet software. It accesses the spreadsheet via an API and performs specified operations. For example, it generates a graph to visualize sales data trends.

[0663] Step 6:

[0664] The server aggregates the results of the script execution, generates an emotion-based feedback message, and sends it to the terminal. This feedback is tailored to align with the user's emotions and is designed to provide a sense of reassurance.

[0665] Step 7:

[0666] The device receives feedback from the server and displays the results to the user. For example, a message such as, "Sales trends were analyzed successfully. Please contact us if you have any further questions." This provides the user with an interaction that takes both results and emotions into consideration.

[0667] (Example 2)

[0668] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0669] When users provide information processing instructions using natural language, a problem exists in that it can be difficult to obtain the intended result if the instructions are complex or if the user's emotional state is not adequately considered. This invention aims to solve this problem and realize natural interaction that responds to the user's emotions and efficient information processing.

[0670] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0671] In this invention, the server includes means for analyzing natural language instructions received from a user, performing sentiment analysis, and generating automated procedures for corresponding tasks based on the analysis; means for executing the generated automated procedures on information processing software; and means for providing feedback on the execution results of the automated procedures in a manner that takes the user's emotions into consideration. This makes it possible to perform information processing efficiently while taking the user's emotions into consideration.

[0672] A "user" is an entity that uses a system to give instructions and receives the results.

[0673] "Natural language" refers to the language system that humans use on a daily basis, and which requires analysis by a computer.

[0674] "Instructions" are pieces of information that represent requests or commands regarding operations or processes that a user performs on a system.

[0675] "Analysis" is the process of interpretation and analysis that a system performs in order to understand and process information received from a user.

[0676] "Emotion analysis" is the process of detecting the emotions contained in a user's instructions and evaluating their state.

[0677] An "automated procedure" is a series of processing steps generated based on instructions to perform a specific task on information processing software.

[0678] "Information processing software" is a collection of programs used to manipulate, analyze, and display digital data.

[0679] "Feedback" refers to information provided to the user regarding the results and progress of a process.

[0680] An "interface" is a point of contact or method for an information processing system to interact with a user or another system.

[0681] This invention provides a system that optimizes user interaction with information processing software by considering the user's emotions when the user operates the software using natural language. The user inputs instructions in natural language via a terminal, and the system analyzes these instructions and performs emotion analysis.

[0682] The server analyzes user instructions using natural language processing technology. An emotion engine is used for the analysis, evaluating the emotions within the instructions. Based on the evaluated emotions, the server generates adaptive automated procedures. These automated procedures execute tasks on information processing software. Specific software such as Google Apps Script can be used. The server accesses data via APIs through the information processing software interface and performs the specified processing.

[0683] The processing results are returned to the device as feedback, displaying messages that take the user's emotional state into consideration. This feedback is designed to reduce the user's anxiety about the operation and allow them to proceed with confidence. For example, it may include a message such as, "The process is progressing smoothly. If you have any questions or concerns, we are here to help."

[0684] For example, if a user inputs a message such as, "I want to analyze data, but I don't know where to start," the server recognizes this sentiment and generates and executes an automated procedure that provides step-by-step guidance. This process allows the user to experience an intuitive and reassuring interaction.

[0685] An example of a prompt message for a generative AI model might be, "Generate a guide to help users easily configure spreadsheets, which they may find confusing."

[0686] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0687] Step 1:

[0688] The user inputs natural language instructions through their device. These instructions include the actions the user wants to perform on the spreadsheet and the emotions associated with them. The entered text data is sent to the server.

[0689] Step 2:

[0690] The server uses natural language processing techniques to analyze user input. The analysis engine extracts keywords from the input data and works to understand the intent. Next, the emotion engine evaluates the emotions within the instructions and adds the detected emotion information to generate processed data. Based on this data, the server identifies the user's emotional state.

[0691] Step 3:

[0692] The server generates automated procedures based on the analysis results and emotional information. Specifically, it creates a script for the generating AI model using the prompt, "The user is anxious, so guide them through the steps to smoothly add a column to the spreadsheet." This script is structured to include guidance that alleviates the user's anxiety.

[0693] Step 4:

[0694] The server uses information processing software such as Google Apps Script to execute the generated automation procedures. The server accesses the spreadsheet via an API, processes the data according to the analysis results, and performs the necessary operations. Here, the operations on the specified spreadsheet are performed automatically.

[0695] Step 5:

[0696] The execution results are returned from the server to the terminal. The server notifies the user of the results, including a message confirming the success of the operation and providing detailed feedback. For example, a message such as "Column addition complete. Please let us know if you have any questions" might appear on the user's terminal. This allows the user to confirm the system's execution results and gain confidence in proceeding with the next operation.

[0697] (Application Example 2)

[0698] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0699] When users operate digital spreadsheet applications, there is a need to reduce emotional burden and enable intuitive voice-based input. However, conventional systems often disregard user emotions, and their complexity can increase user burden. Furthermore, users may feel uneasy with mechanical interfaces, so it is necessary to build a system that can solve these problems.

[0700] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0701] In this invention, the server includes means for analyzing natural language instructions received from the user and generating a script for the corresponding task; means for executing the generated script on a digital spreadsheet application; means for recognizing the user's emotions using emotion analysis technology and optimizing the instructions; means for obtaining natural language instructions from the user using speech recognition technology; and means for providing feedback to the user on the results of the script execution. This enables the optimization of operations based on the user's voice instructions and emotions.

[0702] A "user" is someone who operates a digital device and provides instructions or information through natural language or voice.

[0703] "Natural language instructions" are instructions that are in the form of commands or inquiries made in the language that users use on a daily basis, and that contain information that can be interpreted by a machine.

[0704] A "script" is program code generated to automate specific operations within a digital spreadsheet application.

[0705] A "digital spreadsheet application" is software that runs on digital devices and is used for organizing and calculating data.

[0706] "Emotion analysis technology" is a technology that analyzes information and behavior from users to identify their emotional state.

[0707] "Voice recognition technology" is a technology that allows a digital device to interpret the voice spoken by a user as text information and use it as an operation command.

[0708] "Feedback" is a response from a system to a user, providing them with the results of their actions or supplementary information.

[0709] An "application programming interface" is an interface that allows other programs to access the functions and data of software.

[0710] The embodiments for carrying out the present invention are shown below.

[0711] The server receives instructions provided by the user via voice, combining speech recognition and natural language processing technologies. This involves a speech recognition module converting the speech into text data, and a natural language processing engine analyzing that text to understand its meaning. This technology is implemented using open-source speech recognition libraries and commercial natural language processing models.

[0712] Furthermore, the server generates scripts to automate related tasks based on the parsed natural language instructions. These scripts are executed via the API of a digital spreadsheet application, such as using Google Apps Script. The generated scripts are designed to perform the necessary data manipulations on the spreadsheet application and meet the user's requirements.

[0713] The server also uses sentiment analysis technology to detect emotions from the user's voice instructions. Sentiment analysis is a process that infers the user's emotional state from specific keywords and phrases and optimizes the response accordingly. For example, if the user shows anxiety, it provides feedback that explains the operation procedure in detail. This feedback is played aloud to help the user feel more at ease interacting with the system.

[0714] Users can operate a digital spreadsheet application using voice commands via a home smart speaker. By receiving feedback from the server, they can reduce anxiety about ongoing operations and manage data intuitively and effectively.

[0715] As a concrete example, consider a scenario where a user gives a voice command such as, "I need help managing this month's budget, but I'm unsure, so please explain in detail." In this case, the system recognizes the user's anxiety through sentiment analysis and executes a script while presenting detailed steps. Furthermore, when inputting prompt text into the generating AI model, it is recommended to use instructions that take into account the user's voice command and their emotions.

[0716] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0717] Step 1:

[0718] The user inputs voice commands into the smart speaker. The smart speaker uses a voice recognition module to convert the voice into text. This text is sent to a server as input data for analysis by a natural language processing engine.

[0719] Step 2:

[0720] The server analyzes the received text data using a natural language processing engine. Through this analysis, it identifies the meaning of the instructions and extracts information necessary to convert them into a script to be executed in a digital spreadsheet application. In this process, it obtains necessary formulas and cell location information, generating the basic data for script generation.

[0721] Step 3:

[0722] The server uses an emotion analysis engine to detect the user's emotional state from text data. The emotional information extracted through emotion analysis influences subsequent feedback and the steps taken during script execution. Based on these results, if the user is anxious, instructions are set to generate a script that includes detailed steps.

[0723] Step 4:

[0724] The server uses platforms such as Google Apps Script to automatically generate scripts that respond to user instructions and emotional states. These generated scripts are executed via the API of a digital spreadsheet application, performing specified calculations and data manipulations, and reflecting the results in the spreadsheet.

[0725] Step 5:

[0726] The server generates a feedback message for the user based on the results after the script execution. This message takes into account the user's emotional state and may include content such as, "The task is complete. Do you have any concerns?" The feedback message is delivered to the user as an audio message via a smart speaker.

[0727] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0728] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0729] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0730] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0731] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0732] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0733] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0734] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0735] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0736] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0737] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0738] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0739] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0740] 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.

[0741] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0742] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0743] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0744] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0745] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0746] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0747] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0748] The following is further disclosed regarding the embodiments described above.

[0749] (Claim 1)

[0750] A means for analyzing natural language instructions received from a user and generating a script for the corresponding task,

[0751] A means for executing the generated script on digital spreadsheet software,

[0752] A means for providing feedback to the user on the execution result of the aforementioned script,

[0753] A system that includes this.

[0754] (Claim 2)

[0755] The system according to claim 1, which utilizes natural language processing technology for analyzing natural language input.

[0756] (Claim 3)

[0757] The system according to claim 1, wherein the generated script is executed via the API of digital spreadsheet software.

[0758] "Example 1"

[0759] (Claim 1)

[0760] A means for users to input operational instructions to a computing system in natural language,

[0761] A method using a generative AI model to analyze input natural language instructions and extract information including the target of the operation, the operation content, and the data range,

[0762] A means for generating a script based on the extracted information and executing it on digital computing software,

[0763] A means of communicating with computing software using the generated script and performing operations as instructed,

[0764] A means of providing feedback to the user on the results of the operation,

[0765] A system that includes this.

[0766] (Claim 2)

[0767] The system according to claim 1, which analyzes user instructions using natural language processing technology.

[0768] (Claim 3)

[0769] The system according to claim 1, wherein the generated script is executed via the program interface of the computing software.

[0770] "Application Example 1"

[0771] (Claim 1)

[0772] A means for analyzing natural language instructions received from a user and generating a script for the corresponding task,

[0773] A means for executing the generated script on digital computing software,

[0774] A means of converting user instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on those instructions,

[0775] A means for presenting the execution result of the script to the user,

[0776] A system that includes this.

[0777] (Claim 2)

[0778] The system according to claim 1, which uses natural language processing technology to analyze natural language input and applies information processing to household management.

[0779] (Claim 3)

[0780] The system according to claim 1, wherein the generated script is executed via the interface of computation management software and applied to home information management.

[0781] "Example 2 of combining an emotion engine"

[0782] (Claim 1)

[0783] A means for analyzing natural language instructions received from a user, performing sentiment analysis, and generating automated procedures for corresponding tasks based on that analysis,

[0784] A means for executing the generated automation procedure on information processing software,

[0785] A means for providing feedback on the results of the aforementioned automated procedure in a manner that takes into consideration the user's feelings,

[0786] A system that includes this.

[0787] (Claim 2)

[0788] The system according to claim 1, which utilizes information processing technology for analyzing natural language input and sentiment analysis.

[0789] (Claim 3)

[0790] The system according to claim 1, wherein the generated automated procedure is executed via an interface of information processing software.

[0791] "Application example 2 when combining with an emotional engine"

[0792] (Claim 1)

[0793] A means for analyzing natural language instructions received from a user and generating a script for the corresponding task,

[0794] A means for executing the generated script on a digital spreadsheet application,

[0795] A means of recognizing user emotions using emotion analysis technology and optimizing instructions,

[0796] A means of obtaining natural language instructions from a user using speech recognition technology,

[0797] A means for providing feedback to the user on the execution result of the aforementioned script,

[0798] A system that includes this.

[0799] (Claim 2)

[0800] The system according to claim 1, which uses natural language processing technology to analyze natural language input and integrates sentiment analysis to adjust operations according to the user's emotional state.

[0801] (Claim 3)

[0802] The system according to claim 1, wherein the generated script is executed via the application programming interface of a digital spreadsheet application and includes feedback based on the user's emotional state. [Explanation of Symbols]

[0803] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for analyzing natural language instructions received from a user and generating a script for the corresponding task, A means for executing the generated script on digital computing software, A means of converting user instructions into text using speech recognition technology based on environmental information, and automatically generating and reflecting information based on those instructions, A means for presenting the execution result of the script to the user, A system that includes this.

2. The system according to claim 1, which uses natural language processing technology to analyze natural language input and applies information processing to household management.

3. The system according to claim 1, wherein the generated script is executed via the interface of computation management software and applied to home information management.

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