system

Abstract

We provide the system. [Solution] A system for controlling an information processing device that generates electronic communications, including a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the content of a conversation in real time and suggesting the most appropriate language to support communication in a purchasing conversation.

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, the method including steps of receiving a user utterance, adding the user utterance to a prompt including a directive related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] In communication via electronic communication, there is a problem that smooth information transmission is hindered due to emotional expressions, misspellings, or use of inappropriate styles. Such situations can create misunderstandings and discomfort, and may have an adverse impact on business and daily relationships. The purpose of this invention is to solve these problems and realize smoother and misunderstanding-free communication.

Means for Solving the Problems

[0005] This invention provides an information processing device for generating electronic communications, which offers multiple means for analyzing the input communication text, detecting and converting emotional expressions, correcting errors, and adjusting the writing style based on recipient information. Specifically, it uses natural language processing technology to reduce emotional expressions in the electronic communication text and corrects them to appropriate expressions by referring to a dictionary database for error detection. Furthermore, by adding a writing style adjustment function based on recipient information, it realizes a system that automatically creates an appropriate text structure according to the recipient. This system enables users to effectively convey their intended message to the recipient.

[0006] "Electronic communication" refers to messages and data sent and received via the internet or networks.

[0007] An "information processing device" refers to a device, such as a computer or server, used for inputting, processing, storing, and outputting data.

[0008] "Communication text" refers to the content of messages or documents included in electronic communications.

[0009] "Input means" refers to interfaces or devices that users use to transmit information to electronic devices, such as keyboards and touchscreens.

[0010] "Analysis means" refers to functions or algorithms used to analyze specific data or information.

[0011] "Emotional expression" refers to words or phrases included in a text that strongly express emotions or feelings.

[0012] "Conversion means" refers to a function for changing specific data or expressions into other formats or expressions.

[0013] "Misprint" refers to a description that contains errors or mistakes in character input.

[0014] "Correction measures" refer to functions that detect errors and correct them to the correct descriptions.

[0015] "Recipient information" refers to information regarding the recipient or addressee in electronic communication.

[0016] "Adjustment means" refers to a function or device for adjusting something to an appropriate state.

[0017] "Control means" refers to a function or technology for managing and controlling the state and operation of a system or device.

Brief Description of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0021] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

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

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

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

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] The system according to the present invention is implemented in which, when a user generates an electronic communication, the server receives the communication text sent from the user's terminal, analyzes it, corrects it appropriately, and then presents it to the user. This system integrates multiple functions to perform emotional expression conversion, correction of typographical errors, and adjustment of writing style according to the recipient information.

[0040] When a user types an email or message, its content is sent from the user's device to the server. The server first uses natural language processing technology to analyze the message body and detect emotional expressions. For example, if an email contains aggressive language, it is converted into more polite language. This function can mitigate the negative impact that emotional expressions may have on the recipient.

[0041] Next, the server detects typos and corrects them to the correct words and grammar. This process involves string manipulation and dictionary database lookups, and spell and grammar checks are performed automatically. For example, if the input is "おはようござまう", it will be corrected to "おはようございます".

[0042] Furthermore, the server has the ability to select an appropriate writing style based on the recipient information and adjust the entire document as needed. This allows you to change emails addressed to superiors or clients to be more respectful. For example, it can correct a document containing casual language with more formal language as necessary.

[0043] The corrected message body is sent from the server to the user's terminal, where the user performs a final check. After the check, if the user determines that there are no problems, the email is sent to the designated recipient.

[0044] By implementing this system, users can send messages exactly as intended, avoiding misunderstandings and inappropriate tones. As a result, smoother communication can be achieved.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user enters an email or message on their device. The user enters text and specifies the recipient as usual.

[0048] Step 2:

[0049] The terminal sends the entered message body and recipient information to the server. At this time, the email is transferred to the server in data format.

[0050] Step 3:

[0051] The server analyzes the text of the communication it receives. Natural language processing techniques are used to identify emotional expressions within the text.

[0052] Step 4:

[0053] The server converts emotionally charged expressions it identifies into more polite language. For example, the expression "It's taking too long!" would be changed to "It seems to be taking a little longer than expected, could you please provide an update on the progress?"

[0054] Step 5:

[0055] The server detects errors in the text. It performs spell checks and grammar checks, and corrects them by referring to a dictionary database.

[0056] Step 6:

[0057] The server analyzes the recipient information to determine and adjust the appropriate writing style. For example, it might rewrite an email addressed to a superior to be more formal.

[0058] Step 7:

[0059] The server sends the corrected message to the terminal. The corrections are presented to the user, and they are asked to confirm them.

[0060] Step 8:

[0061] The user can review the correction results. They can also make manual fine adjustments as needed.

[0062] Step 9:

[0063] The user confirms the message content and then formally sends it. The process is completed when the device sends the email to the designated recipient.

[0064] (Example 1)

[0065] 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."

[0066] In modern electronic communications, misleading emotional expressions, inaccurate descriptions, and stylistic inconsistencies hinder smooth communication. This can create unnecessary tension between senders and receivers, leading to inefficiencies in business and personal interactions. Therefore, there is a need for a system that appropriately translates emotional expressions, automatically corrects inaccurate descriptions, and quickly and accurately adjusts writing style to suit the recipient.

[0067] 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.

[0068] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and identifying emotional expressions, and a conversion means for converting the identified emotional expressions into more appropriate expressions. This makes it possible to efficiently perform appropriate conversion of emotional expressions in electronic communications, correction of inaccurate descriptions, and consistency of writing style.

[0069] An "information processing system" refers to the entire apparatus or network used to generate or process electronic communications. This system integrates multiple means to effectively and efficiently manage information.

[0070] "Input means" refers to the interface or method by which a user provides the content of electronic communications to a system. This allows the user to input text messages or data.

[0071] "Analysis means" refers to a method for examining received data and identifying specific elements or patterns. This means uses natural language processing techniques to analyze the data in detail.

[0072] "Emotional expression" refers to words and phrases that express emotions included in text or conversation. This includes emotional nuances such as positive, negative, and aggressive.

[0073] A "conversion method" refers to a way of expressing specific expressions or data in a different format. This makes it possible to appropriately convey the intended nuances.

[0074] An "inaccurate description" refers to a sentence that contains spelling mistakes, grammatical errors, or expressions with unclear meaning. This can lead to misunderstandings or confusion.

[0075] "Correction measures" refer to methods for changing detected inaccurate elements into the correct format. This includes functions that apply correct words and grammar by referring to dictionaries and databases.

[0076] The "recipient" refers to the person or organization to which electronic communications are sent. This is the final destination where the communication content will be delivered.

[0077] "Style" refers to the manner of language and expression used in writing and conversation. Style should be adjusted according to the recipient and the situation.

[0078] "Adjustment methods" refer to techniques for modifying writing style and expression to suit specific purposes. This ensures that communication with the recipient is appropriate.

[0079] This invention is an information processing system for more clearly and appropriately representing the content of electronic communications. Specifically, communication content entered by a user using a terminal is transmitted to a server. The server is a system designed to adjust emotional expression, inaccuracies, and stylistic changes based on the received data.

[0080] The user uses a terminal to input a communication message and sends its contents to the server. The server uses natural language processing technology to analyze the text. The server detects emotional expressions and converts them into appropriate expressions depending on the context and recipient. For example, the expression "I'm really in trouble!" is converted to "I would appreciate your support."

[0081] Furthermore, the server refers to the dictionary database to detect and correct inaccurate descriptions. This is achieved by automatically identifying grammar and spelling errors using a language model. For example, when "これからいこかん" is input, it is corrected to "これから行こうか".

[0082] The server also adjusts the style of the message based on the recipient information. With this function, for example, it is possible to format the message to a business partner in a formal style.

[0083] The corrected and adjusted communication content is returned from the server to the user's terminal, and the user can check the content. After the final confirmation, the user sends the message to the specified recipient.

[0084] Examples of specific prompt sentences are as follows.

[0085] "The message entered by the user: {user input}. Please improve the tone of this message, correct typos and convert it to a formal style."

[0086] By implementing this invention, the user can surely send the message as intended, prevent misunderstandings, and improve the quality of communication.

[0087] The flow of the specific process in Example 1 will be described using FIG. 11.

[0088] Step 1:

[0089] The user inputs an email or message into the terminal. At that time, the input text is sent from the terminal to the server as communication data. The input data is the body of the message the user intends.

[0090] Step 2:

[0091] The server receives communication data sent from the terminal. The server uses natural language processing techniques to analyze the data and identify specific emotional expressions. This analysis extracts positive or negative elements from the message.

[0092] Step 3:

[0093] The server performs transformation operations based on the analyzed sentiment expressions. Specifically, it uses a generative AI model to convert aggressive or negative expressions into more neutral or positive ones. The output of this process is the improved message expression.

[0094] Step 4:

[0095] The server then detects and corrects typographical errors in the text, following the conversion of emotional expressions. This process involves referencing a dictionary database and performing string manipulation. For example, it corrects text with spelling mistakes or grammatical errors to accurate expressions. The output is the corrected, accurate text.

[0096] Step 5:

[0097] The server applies an algorithm to adjust the writing style based on the recipient information. Depending on the recipient's attributes, it converts casual writing to formal writing, or vice versa, making appropriate adjustments. The adjusted text is then generated as output.

[0098] Step 6:

[0099] The server sends the final corrected and adjusted version of the message to the user's terminal. The user reviews the proposed changes and makes further edits as needed. After final confirmation, the user decides whether to send the message to the recipient.

[0100] This allows users to deliver their intended message to recipients without misunderstanding.

[0101] (Application Example 1)

[0102] 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."

[0103] In modern society, communication via electronic means plays a crucial role, but misunderstandings can arise due to insufficient politeness, incorrect wording, and typographical errors. Furthermore, while smooth and accurate communication is essential in purchasing interactions, no system currently exists to suggest the most appropriate language. Improving the quality of such communication is a challenge.

[0104] 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.

[0105] In this invention, the server includes a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the dialogue content in real time and suggesting the most appropriate language to support communication during purchasing conversations. This makes it possible to reduce misunderstandings and discomfort during electronic communication and conversations, and to achieve smooth communication.

[0106] An "information processing device that generates electronic communications" is a device that has the function of generating, transmitting, or storing communications in digital format based on user input.

[0107] A "device for analyzing input communication text" is a device that understands the content of text entered by a user and performs calculations to identify emotional or grammatical elements.

[0108] A "device for detecting emotional expression" is a device that analyzes expressions within text and has the function of identifying the emotions that those expressions convey.

[0109] A "device that transforms emotional expressions into more pleasant ones" is a device that has the function of changing detected emotional content into something milder.

[0110] A "device for detecting and correcting errors" is a device that checks for typographical errors or misuses in communication content and corrects them as necessary.

[0111] A "device that adjusts writing style based on recipient information" is a device that has the function of changing the writing style and wording to an appropriate one depending on the recipient of the communication.

[0112] A "device that analyzes conversation content in real time and suggests the most appropriate wording to support communication during purchasing conversations" is a device that analyzes conversations that take place in situations such as purchasing in real time and has the function of suggesting appropriate responses to the other party.

[0113] The system for realizing this invention consists of a server, a user's terminal, and a network connecting them. The server receives the communication text input from the user. At this time, the user's terminal generates text data and sends it to the server via the network.

[0114] The server analyzes the communication text using natural language processing techniques to detect emotional expressions and typographical errors. For this analysis, natural language processing toolkits such as SpaCy and NLTK may be used. Detected emotional expressions are converted to milder expressions, and typographical errors are corrected by referring to a dictionary database.

[0115] Next, the server adjusts the writing style based on the recipient information. In this step, it selects formal or casual language depending on the intended recipient. In particular, to support communication during purchasing conversations, it analyzes the conversation content in real time and suggests the most appropriate wording. When voice input is used, a speech recognition system such as Google® Speech-to-Text API is utilized.

[0116] The adjusted message body is sent back from the server to the user's terminal. The user then confirms it and sends it to complete the communication.

[0117] As a concrete example, when a user asks "Does this product still have a shelf life?" at a grocery store, the application translates this into a more formal expression such as "This product still has a shelf life remaining, so it will keep for a while."

[0118] An example of a prompt sentence to input into a generative AI model might be: "Design an app that suggests appropriate language when a user is purchasing food. This includes real-time translation using natural language processing and speech recognition."

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The user's terminal generates the communication body entered by the user in text format and sends that data to the server. The input here is the raw text message typed by the user, and the output is the text data sent to the server over the network. In this step, the terminal transfers the initial communication data without processing it.

[0122] Step 2:

[0123] The server analyzes text data received over the network using natural language processing techniques, particularly for detecting emotional expressions. The input is the text data from step 1, and the output is a list of detected emotional elements. The server then uses this to determine if the text contains the user's intended emotion or negative expression.

[0124] Step 3:

[0125] The server converts emotional expressions into milder ones. In this step, the emotional elements detected in step 2 are used as input, and the converted text is generated as output. Specifically, negative expressions are replaced with more neutral phrases.

[0126] Step 4:

[0127] The server consults a dictionary database to detect and correct errors in the communication text. The input for this step is the text edited in step 3, and the output is the corrected text. String manipulation is performed here to correct spelling and grammatical errors.

[0128] Step 5:

[0129] The server adjusts the writing style based on the recipient information. The input requires the corrected text from step 4 and the recipient information, and the output is text with the adjusted writing style. At this stage, the entire document is revised to use language appropriate for the recipient.

[0130] Step 6:

[0131] The server analyzes the conversation in real time and suggests the most appropriate wording to support communication during the purchasing process. The input is the text adjusted in step 5, and the output is the final suggested message. Specifically, when voice input is converted to text, the server suggests the most appropriate response based on that content.

[0132] Step 7:

[0133] The user's terminal receives the final message from the server and presents it to the user. In this step, the input is the edited text sent from the server, and the output is the text that the user confirms on the screen. This action allows the user to finally confirm the message and send it if necessary.

[0134] 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.

[0135] The system according to the present invention achieves more appropriate and effective correction by combining an emotion engine with the generation of electronic communications by a user using an information processing device. In this system, the emotion engine recognizes the user's emotional state when the server receives and analyzes the communication text input from the user terminal. This enables the detection and conversion of emotional expressions, correction of typographical errors, and adjustment of writing style in a detailed manner according to the user's emotions.

[0136] First, when a user enters an email or message on their device, the server uses an emotion engine to check the user's emotional state before analyzing the message body. The emotion engine automatically infers the user's emotions based on their input patterns and past communication history. For example, if a user appears to be in a hurry when typing, the emotion engine will recognize a sense of urgency.

[0137] Subsequently, the server analyzes the communication text using natural language processing techniques, taking into account the emotional state recognized by the emotion engine. If emotional expressions are detected, they are converted into softer, more polite phrasing. This conversion process can utilize the results of the emotion engine to adjust the degree of expression conversion required. For example, if the expression "I can't wait any longer!" is recognized as the user being angry, it will be converted to "We apologize for the inconvenience. Could you please hurry?"

[0138] In addition, the server detects typos by referring to a dictionary database and corrects them to the correct words and grammar. It then adjusts the writing style based on the queried recipient information and the user's emotional state. If the user is judged to be calm, the tone can be maintained without significant adjustments.

[0139] This ensures that the corrections provided to the user accurately reflect their emotions while facilitating smooth and misunderstanding-free communication. The user then performs a final review and, after confirming the corrections are satisfactory, formally sends the email. Through this process, the user can convey their intentions with appropriate tone and expression, resulting in improved communication quality.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user enters the electronic communication information on the terminal. Here, the user composes the body of the email or message using the usual methods.

[0143] Step 2:

[0144] The terminal sends the entered message body and destination information to the server. This process transfers the information to the server in data format.

[0145] Step 3:

[0146] The emotion engine is activated as soon as the server receives the communication message. The emotion engine analyzes the user's input patterns and past communication history to infer the user's emotional state.

[0147] Step 4:

[0148] The server applies natural language processing techniques to analyze the communication text based on emotional information obtained from the emotion engine. Particular attention is paid to context and word choice in order to detect emotional expressions.

[0149] Step 5:

[0150] The emotional engine then modifies the emotional expressions detected by the server to the extent instructed by the server. For example, if the emotional engine recognizes the user's anger, it adjusts the expression to make it milder.

[0151] Step 6:

[0152] The server detects errors in the communication text by referring to a dictionary database and corrects them to the correct expression. This includes general spell checking and grammatical correction.

[0153] Step 7:

[0154] The server analyzes the recipient information and adjusts the writing style based on sentiment. For example, if it's an email to a superior, it will change the language to be more formal and polite.

[0155] Step 8:

[0156] The server sends the corrected message to the user's terminal. The user checks the correction results on their terminal and makes any necessary manual adjustments.

[0157] Step 9:

[0158] The user makes a final review of the corrections, and if there are no problems, officially sends the email. The process is completed when the device forwards this email to the designated recipient.

[0159] (Example 2)

[0160] 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 will be referred to as the "terminal."

[0161] In communication, the inappropriate transmission of the sender's emotions can lead to misunderstandings and interpersonal friction. Furthermore, typographical errors or inappropriate writing styles can negatively impact the recipient's impression of the message. The challenge lies in resolving these issues and achieving smooth, misunderstanding-free communication.

[0162] 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.

[0163] In this invention, the server includes a means for receiving the communication text and inferring the emotional state, an analysis means for analyzing the input communication text and detecting emotional expressions, and an adjustment means for adjusting the writing style based on the destination information and emotional state. This makes it possible to make appropriate adjustments to expressions and writing style according to emotions, thereby promoting smooth communication without misunderstandings.

[0164] "Communication body" refers to the main text content of text messages and emails sent and received via information processing equipment.

[0165] "Input means" refers to a device or interface that provides a function for a user to input information.

[0166] "Inference methods" refer to functions that analyze data to identify the user's emotional state and infer the appropriate emotional category.

[0167] "Analysis means" refers to a mechanism for processing input data and extracting or understanding necessary information.

[0168] "Conversion means" refers to a system or device for converting data in one format to another.

[0169] "Correction means" refers to a device or program that has the function of detecting errors and correcting them to appropriate information.

[0170] "Adjustment mechanism" refers to a mechanism that has the function of appropriately changing writing style and expression to conform to predetermined standards.

[0171] A "generative AI model" refers to an artificial intelligence model that learns from large amounts of data and generates or transforms new data.

[0172] "Natural language processing technology" refers to all technologies that enable computers to understand and process human language.

[0173] A "language database" refers to a collection of data that gathers information on the meaning, usage, and related aspects of words and expressions.

[0174] This system is configured to analyze and appropriately correct electronic communications entered by the user using a terminal. A specific embodiment is shown below.

[0175] First, the user enters an email or message on a device such as a smartphone or computer. The device then sends the message body to the server via the input method. At this time, the message body contains the user's natural language expression.

[0176] The server analyzes the received communication text using an emotion engine as a means of prediction to recognize the user's emotional state. This emotion engine is designed based on a generative AI model and automatically predicts emotions by analyzing past communication history and input patterns.

[0177] Next, the server analyzes the communication text using natural language processing techniques as an analysis tool. During the analysis process, emotional expressions are detected, and these are converted into more polite expressions using a conversion tool. Because this conversion depends on the emotional state, very fine-tuning is possible.

[0178] For typographical errors, the correction mechanism refers to a language database and corrects incorrectly entered words to their correct form. During this process, conversion and correction are performed in parallel, ensuring that the user's intent is preserved to the greatest extent possible.

[0179] Finally, the adjustment mechanism optimizes the writing style based on the recipient information and the user's emotional state. The server can maintain the original tone without applying overly complex adjustments, for example, in situations where concise and straightforward expression is appropriate.

[0180] As an example, if a user wants to express gratitude in a work-related message, the entered message "Thank you!" will be automatically converted into a more respectful expression such as "Thank you for your cooperation."

[0181] An example of a prompt for a generative AI model is, "Analyze the user's communication and generate appropriate expressions that reflect their emotions." This prompt enables the software to adjust the language to match the user's intent.

[0182] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0183] Step 1:

[0184] The user types an email or message on their device and presses the send button. The input may include concise sentences or casual expressions. The device sends this as the message body to the server. The output at this stage is the exact message body entered by the user.

[0185] Step 2:

[0186] The server sends the received communication text to the emotion engine to recognize the emotional state. It receives the communication text as input and analyzes its content using a generative AI model. The emotion engine evaluates past data history and the current sentence structure to infer the user's emotion (e.g., hurried, cautious). The output at this stage is the category of the inferred emotional state.

[0187] Step 3:

[0188] The server analyzes the communication text using natural language processing techniques, taking into account the output of the emotion engine. It uses the results of the emotion engine and the communication text as input to detect emotional phrasing. Data processing involves using text analysis techniques to identify important key phrases and tones. The output of this process is a list of emotional expressions.

[0189] Step 4:

[0190] Based on the analysis results, the server uses a conversion mechanism to soften emotional expressions. This conversion process takes a list of emotional expressions and their emotional categories as input, and outputs the converted expressions. For example, a sentence expressing frustration, such as "Please reply quickly!", is converted into a more polite expression like "We would appreciate it if you could reply as soon as possible."

[0191] Step 5:

[0192] The server uses correction tools to check for errors and correct them if necessary. It receives the converted document as input and detects errors by referring to a language database. This data processing corrects typos and omissions, resulting in an accurate document output.

[0193] Step 6:

[0194] The server uses recipient information and sentiment status to adjust the writing style and finalize the document. It uses recipient information and sentiment categories as input to determine the need for adjustment. The output of this step is a communication body optimized with a contextually appropriate writing style.

[0195] Step 7:

[0196] The user performs a final check, viewing the revised message on their device and verifying its content. After confirming that the output message body is correct, the user confirms sending. This completes the message that will ultimately be sent to the recipient.

[0197] (Application Example 2)

[0198] 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".

[0199] In modern society, electronic communication has become an important means of communication, but expressions that do not accurately reflect the sender's emotions often lead to misunderstandings and friction. Furthermore, in order for service providers to properly handle customer service, it is necessary to generate responses that respond quickly and accurately in accordance with the customer's emotions. For this reason, the development of automated response generation systems that take emotions into consideration is urgently needed.

[0200] 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.

[0201] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and detecting emotional expressions, and a selection and generation means for selecting and generating an automatic response according to the user's emotional state. This enables accurate expression adjustment and automatic response generation according to the user's emotions.

[0202] A "computer" is an electronic device used for inputting, processing, and outputting information.

[0203] "Communication content" refers to messages and data that are transmitted or received electronically.

[0204] An "input means" is an interface that allows a user to provide communication content to a computing device.

[0205] "Analysis means" refers to techniques for analyzing input communication content and identifying the emotional expressions contained within it.

[0206] "Emotional expressions" are expressions that appear in a text to indicate the sender's feelings or emotional state.

[0207] A "conversion mechanism" is a function that changes detected emotional expressions into other expressions.

[0208] "Correction methods" refer to the process of detecting errors in communication content and correcting them to their accurate form.

[0209] "Adjustment mechanism" refers to a mechanism for changing the style of emails and messages according to the circumstances of the recipient and sender.

[0210] A "selection and generation means" is a system for selecting and generating an appropriate automated response based on a specified emotional state.

[0211] A "control system" is a central management system that manages the entire process and issues instructions to ensure that each system functions properly.

[0212] The system program for realizing this invention involves a server and a user terminal working together to process communication content. Specifically, the user terminal provides means for inputting communication content and sends it to the server. The server uses analysis means for analyzing the received communication content and utilizes natural language processing technology to recognize emotional expressions within the input message.

[0213] Based on these analysis results, the server identifies the user's emotional state and uses conversion tools to transform it into appropriate expressions. This conversion process utilizes an emotion engine; for example, a message perceived as angry might be changed to a polite and calm expression. In addition, the server has correction tools to detect and correct typos. By referring to a dictionary database, incorrect words and grammar can be corrected to their correct form.

[0214] Furthermore, the server activates an adjustment mechanism that adjusts the writing style based on recipient information and the user's emotional state. This allows recipients to receive messages in the most appropriate style for their specific situation. In addition, the server provides a selection and generation mechanism that selects and generates an automated response that corresponds to the user's emotions, resulting in a fast and efficient response.

[0215] The hardware used includes cloud servers (e.g., Amazon Web Services), and the software utilizes natural language processing libraries (e.g., spaCy, Google Cloud AI's Natural Language API). As a concrete example of this system, if a customer sends a message such as "This service is completely useless!", the server detects the emotion and translates it into a calmer response.

[0216] Examples of prompt statements for generative AI models include the following:

[0217] "If a customer sends a message expressing dissatisfaction, please craft a polite reply that mitigates the content of their complaint."

[0218] Therefore, this system enables the generation of advanced electronic communications that take human emotions into consideration.

[0219] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0220] Step 1:

[0221] The user inputs the communication content using a terminal and sends it to the server. The input here is the message typed by the user, and the server receives this message. The output received by the server is text data ready for analysis.

[0222] Step 2:

[0223] The server analyzes the received message using analysis tools. The input data is the text data received in step 1, which is then analyzed using natural language processing techniques. These techniques include spaCy and Google Cloud AI's natural language API. As part of the data processing, emotional expressions are identified from the message. The output is data showing the extracted emotional expressions and their types.

[0224] Step 3:

[0225] The server uses a conversion mechanism to transform necessary expressions based on the analysis results. The input is the analysis result from step 2, and upon receiving it, the server uses its emotion engine to apply a transformation that softens the identified emotional expressions. Specifically, it changes expressions indicating that the user is angry to expressions with a calmer tone. The output is the transformed text data.

[0226] Step 4:

[0227] The server uses correction tools to correct errors in the converted message. The input data is the converted message obtained in step 3, and the server searches for errors by referring to a dictionary database. Specifically, it corrects spelling mistakes and grammatical errors into the appropriate format. The output is the corrected text data.

[0228] Step 5:

[0229] The server uses adjustment tools to refine the writing style based on recipient information and sentiment. The input is the modified message from step 4, which also includes recipient information. The server uses this information to modify the tone and style of the message as needed. Specific actions include formal adjustments for business use. The output is the final, refined message.

[0230] Step 6:

[0231] The server uses a selection generation mechanism to generate an automated response based on the user's emotions. The inputs are the final message from step 5 and the emotion data identified in step 2. The server uses a generation AI model to create an automated response utilizing the most appropriate prompt sentences. Specifically, the generated response is refined into a polite and appropriate response based on the prompts. The output is the final automated response message.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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".

[0248] The system according to the present invention is implemented in which, when a user generates an electronic communication, the server receives the communication text sent from the user's terminal, analyzes it, corrects it appropriately, and then presents it to the user. This system integrates multiple functions to perform emotional expression conversion, correction of typographical errors, and adjustment of writing style according to the recipient information.

[0249] When a user types an email or message, its content is sent from the user's device to the server. The server first uses natural language processing technology to analyze the message body and detect emotional expressions. For example, if an email contains aggressive language, it is converted into more polite language. This function can mitigate the negative impact that emotional expressions may have on the recipient.

[0250] Next, the server detects typos and corrects them to the correct words and grammar. This process involves string manipulation and dictionary database lookups, and spell and grammar checks are performed automatically. For example, if the input is "おはようござまう", it will be corrected to "おはようございます".

[0251] Furthermore, the server has the ability to select an appropriate writing style based on the recipient information and adjust the entire document as needed. This allows you to change emails addressed to superiors or clients to be more respectful. For example, it can correct a document containing casual language with more formal language as necessary.

[0252] The corrected message body is sent from the server to the user's terminal, where the user performs a final check. After the check, if the user determines that there are no problems, the email is sent to the designated recipient.

[0253] By implementing this system, users can send messages exactly as intended, avoiding misunderstandings and inappropriate tones. As a result, smoother communication can be achieved.

[0254] The following describes the processing flow.

[0255] Step 1:

[0256] The user enters an email or message on their device. The user enters text and specifies the recipient as usual.

[0257] Step 2:

[0258] The terminal sends the entered message body and recipient information to the server. At this time, the email is transferred to the server in data format.

[0259] Step 3:

[0260] The server analyzes the text of the communication it receives. Natural language processing techniques are used to identify emotional expressions within the text.

[0261] Step 4:

[0262] The server converts emotionally charged expressions it identifies into more polite language. For example, the expression "It's taking too long!" would be changed to "It seems to be taking a little longer than expected, could you please provide an update on the progress?"

[0263] Step 5:

[0264] The server detects errors in the text. It performs spell checks and grammar checks, and corrects them by referring to a dictionary database.

[0265] Step 6:

[0266] The server analyzes the recipient information to determine and adjust the appropriate writing style. For example, it might rewrite an email addressed to a superior to be more formal.

[0267] Step 7:

[0268] The server sends the corrected message to the terminal. The corrections are presented to the user, and they are asked to confirm them.

[0269] Step 8:

[0270] The user can review the correction results. They can also make manual fine adjustments as needed.

[0271] Step 9:

[0272] The user confirms the message content and then formally sends it. The process is completed when the device sends the email to the designated recipient.

[0273] (Example 1)

[0274] 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."

[0275] In modern electronic communications, misleading emotional expressions, inaccurate descriptions, and stylistic inconsistencies hinder smooth communication. This can create unnecessary tension between senders and receivers, leading to inefficiencies in business and personal interactions. Therefore, there is a need for a system that appropriately translates emotional expressions, automatically corrects inaccurate descriptions, and quickly and accurately adjusts writing style to suit the recipient.

[0276] 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.

[0277] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and identifying emotional expressions, and a conversion means for converting the identified emotional expressions into more appropriate expressions. This makes it possible to efficiently perform appropriate conversion of emotional expressions in electronic communications, correction of inaccurate descriptions, and consistency of writing style.

[0278] An "information processing system" refers to the entire apparatus or network used to generate or process electronic communications. This system integrates multiple means to effectively and efficiently manage information.

[0279] "Input means" refers to the interface or method by which a user provides the content of electronic communications to a system. This allows the user to input text messages or data.

[0280] The "analysis means" refers to a method for inspecting the received data and identifying specific elements or patterns. This means analyzes the data in detail using natural language processing technology.

[0281] The "emotional expression" refers to words or phrases indicating emotions contained in text or conversations. This includes emotional nuances such as positive, negative, and aggressive.

[0282] The "conversion means" refers to a method for re-expressing specific expressions or data in another format. This makes it possible to appropriately convey the intended nuance.

[0283] The "inaccurate description" refers to a sentence containing spelling mistakes, grammar errors, or expressions with unclear meanings. This may cause misunderstandings or confusion.

[0284] The "correction means" refers to a method for changing the detected inaccurate elements into the correct format. This includes functions for applying correct words and grammar by referring to a dictionary or database.

[0285] The "recipient" refers to a person or organization that is the destination of an electronic communication. This is the destination where the communication content is finally delivered.

[0286] The "style" refers to the word usage and expression style in an article or conversation. The style should be adjusted according to the recipient and the situation.

[0287] The "adjustment means" refers to a method for changing the style and expression according to a specific application. This makes the communication with the recipient appropriate.

[0288] This invention is an information processing system for expressing the content of electronic communication more clearly and appropriately. Specifically, the communication content input by the user using the terminal is transmitted to the server. The server is a system designed to adjust emotional expressions, inaccurate descriptions, and styles based on the received data.

[0289] The user uses the terminal to input a communication message and sends its content to the server. The server utilizes natural language processing technology to analyze the text. The server detects emotional expressions and converts them into appropriate expressions according to the context and the recipient. For example, an expression like "I'm really in trouble!" is converted to "I would be grateful if you could offer your support."

[0290] Furthermore, the server refers to the dictionary database to detect and correct inaccurate descriptions. This is achieved by automatically identifying grammar and spelling errors using a language model. For example, when "これからいこかん" (This is an incorrect Japanese input) is entered, it is corrected to "これから行こうか" (Let's go from now on).

[0291] The server also adjusts the style of the message based on the recipient information. With this function, for example, it is possible to format a message to a business partner in a formal style.

[0292] The corrected and adjusted communication content is sent back from the server to the user's terminal, and the user can check the content. After the final confirmation, the user sends the message to the designated recipient.

[0293] Examples of specific prompt sentences are as follows.

[0294] "The message entered by the user: {user input}. Please improve the tone of this message, correct typos and convert it into a formal style."

[0295] By implementing this invention, the user can surely send a message as intended, prevent misunderstandings, and improve the quality of communication.

[0296] The flow of specific processing in Example 1 will be described using FIG. 11.

[0297] Step 1:

[0298] The user inputs an email or a message into the terminal. At this time, the input text is transmitted from the terminal to the server as communication data. The input data is the body of the message intended by the user.

[0299] Step 2:

[0300] The server receives the communication data transmitted from the terminal. The server uses natural language processing technology to analyze the data and identify specific emotional expressions. Through this analysis, positive or negative elements in the message are extracted.

[0301] Step 3:

[0302] The server performs a conversion operation based on the analyzed emotional expressions. Specifically, a generative AI model is used to convert aggressive or negative expressions into more neutral or positive expressions. The output of this process is an improved message expression.

[0303] Step 4:

[0304] After converting the emotional expressions, the server detects and corrects misspellings in the text. In this process, a dictionary database is referenced and string operations are performed. For example, text with spelling mistakes or grammar errors is corrected into an accurate expression. The output is an accurate text after correction.

[0305] Step 5:

[0306] The server applies an algorithm to adjust the style based on the recipient information. Depending on the attributes of the recipient, it converts a casual style into a formal one or appropriately adjusts it even in the reverse case. The adjusted text is generated as the output.

[0307] Step 6:

[0308] The server sends the final corrected and adjusted version of the message to the user's terminal. The user reviews the proposed changes and makes further edits as needed. After final confirmation, the user decides whether to send the message to the recipient.

[0309] This allows users to deliver their intended message to recipients without misunderstanding.

[0310] (Application Example 1)

[0311] 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."

[0312] In modern society, communication via electronic means plays a crucial role, but misunderstandings can arise due to insufficient politeness, incorrect wording, and typographical errors. Furthermore, while smooth and accurate communication is essential in purchasing interactions, no system currently exists to suggest the most appropriate language. Improving the quality of such communication is a challenge.

[0313] 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.

[0314] In this invention, the server includes a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the dialogue content in real time and suggesting the most appropriate language to support communication during purchasing conversations. This makes it possible to reduce misunderstandings and discomfort during electronic communication and conversations, and to achieve smooth communication.

[0315] An "information processing device that generates electronic communications" is a device that has the function of generating, transmitting, or storing communications in digital format based on user input.

[0316] A "device for analyzing input communication text" is a device that understands the content of text entered by a user and performs calculations to identify emotional or grammatical elements.

[0317] A "device for detecting emotional expression" is a device that analyzes expressions within text and has the function of identifying the emotions that those expressions convey.

[0318] A "device that transforms emotional expressions into more pleasant ones" is a device that has the function of changing detected emotional content into something milder.

[0319] A "device for detecting and correcting errors" is a device that checks for typographical errors or misuses in communication content and corrects them as necessary.

[0320] A "device that adjusts writing style based on recipient information" is a device that has the function of changing the writing style and wording to an appropriate one depending on the recipient of the communication.

[0321] A "device that analyzes conversation content in real time and suggests the most appropriate wording to support communication during purchasing conversations" is a device that analyzes conversations that take place in situations such as purchasing in real time and has the function of suggesting appropriate responses to the other party.

[0322] The system for realizing this invention consists of a server, a user's terminal, and a network connecting them. The server receives the communication text input from the user. At this time, the user's terminal generates text data and sends it to the server via the network.

[0323] The server analyzes the communication text using natural language processing techniques to detect emotional expressions and typographical errors. For this analysis, natural language processing toolkits such as SpaCy and NLTK may be used. Detected emotional expressions are converted to milder expressions, and typographical errors are corrected by referring to a dictionary database.

[0324] Next, the server adjusts the writing style based on the recipient information. In this step, it selects formal or casual language depending on the intended recipient. In particular, to support communication during purchase conversations, it analyzes the conversation content in real time and suggests the most appropriate wording. When voice input is used, a speech recognition system such as the Google Speech-to-Text API is utilized.

[0325] The adjusted message body is sent back from the server to the user's terminal. The user then confirms it and sends it to complete the communication.

[0326] As a concrete example, when a user asks "Does this product still have a shelf life?" at a grocery store, the application translates this into a more formal expression such as "This product still has a shelf life remaining, so it will keep for a while."

[0327] An example of a prompt sentence to input into a generative AI model might be: "Design an app that suggests appropriate language when a user is purchasing food. This includes real-time translation using natural language processing and speech recognition."

[0328] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0329] Step 1:

[0330] The user's terminal generates the communication body entered by the user in text format and sends that data to the server. The input here is the raw text message typed by the user, and the output is the text data sent to the server over the network. In this step, the terminal transfers the initial communication data without processing it.

[0331] Step 2:

[0332] The server analyzes text data received over the network using natural language processing techniques, particularly for detecting emotional expressions. The input is the text data from step 1, and the output is a list of detected emotional elements. The server then uses this to determine if the text contains the user's intended emotion or negative expression.

[0333] Step 3:

[0334] The server converts emotional expressions into milder ones. In this step, the emotional elements detected in step 2 are used as input, and the converted text is generated as output. Specifically, negative expressions are replaced with more neutral phrases.

[0335] Step 4:

[0336] The server consults a dictionary database to detect and correct errors in the communication text. The input for this step is the text edited in step 3, and the output is the corrected text. String manipulation is performed here to correct spelling and grammatical errors.

[0337] Step 5:

[0338] The server adjusts the writing style based on the recipient information. The input requires the corrected text from step 4 and the recipient information, and the output is text with the adjusted writing style. At this stage, the entire document is revised to use language appropriate for the recipient.

[0339] Step 6:

[0340] The server analyzes the conversation in real time and suggests the most appropriate wording to support communication during the purchasing process. The input is the text adjusted in step 5, and the output is the final suggested message. Specifically, when voice input is converted to text, the server suggests the most appropriate response based on that content.

[0341] Step 7:

[0342] The user's terminal receives the final message from the server and presents it to the user. In this step, the input is the edited text sent from the server, and the output is the text that the user confirms on the screen. This action allows the user to finally confirm the message and send it if necessary.

[0343] 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.

[0344] The system according to the present invention achieves more appropriate and effective correction by combining an emotion engine with the generation of electronic communications by a user using an information processing device. In this system, the emotion engine recognizes the user's emotional state when the server receives and analyzes the communication text input from the user terminal. This enables the detection and conversion of emotional expressions, correction of typographical errors, and adjustment of writing style in a detailed manner according to the user's emotions.

[0345] First, when a user enters an email or message on their device, the server uses an emotion engine to check the user's emotional state before analyzing the message body. The emotion engine automatically infers the user's emotions based on their input patterns and past communication history. For example, if a user appears to be in a hurry when typing, the emotion engine will recognize a sense of urgency.

[0346] Subsequently, the server analyzes the communication text using natural language processing techniques, taking into account the emotional state recognized by the emotion engine. If emotional expressions are detected, they are converted into softer, more polite phrasing. This conversion process can utilize the results of the emotion engine to adjust the degree of expression conversion required. For example, if the expression "I can't wait any longer!" is recognized as the user being angry, it will be converted to "We apologize for the inconvenience. Could you please hurry?"

[0347] In addition, the server detects typos by referring to a dictionary database and corrects them to the correct words and grammar. It then adjusts the writing style based on the queried recipient information and the user's emotional state. If the user is judged to be calm, the tone can be maintained without significant adjustments.

[0348] This ensures that the corrections provided to the user accurately reflect their emotions while facilitating smooth and misunderstanding-free communication. The user then performs a final review and, after confirming the corrections are satisfactory, formally sends the email. Through this process, the user can convey their intentions with appropriate tone and expression, resulting in improved communication quality.

[0349] The following describes the processing flow.

[0350] Step 1:

[0351] The user enters the electronic communication information on the terminal. Here, the user composes the body of the email or message using the usual methods.

[0352] Step 2:

[0353] The terminal sends the entered message body and destination information to the server. This process transfers the information to the server in data format.

[0354] Step 3:

[0355] The emotion engine is activated as soon as the server receives the communication message. The emotion engine analyzes the user's input patterns and past communication history to infer the user's emotional state.

[0356] Step 4:

[0357] The server applies natural language processing techniques to analyze the communication text based on emotional information obtained from the emotion engine. Particular attention is paid to context and word choice in order to detect emotional expressions.

[0358] Step 5:

[0359] The emotional engine then modifies the emotional expressions detected by the server to the extent instructed by the server. For example, if the emotional engine recognizes the user's anger, it adjusts the expression to make it milder.

[0360] Step 6:

[0361] The server detects errors in the communication text by referring to a dictionary database and corrects them to the correct expression. This includes general spell checking and grammatical correction.

[0362] Step 7:

[0363] The server analyzes the recipient information and adjusts the writing style based on sentiment. For example, if it's an email to a superior, it will change the language to be more formal and polite.

[0364] Step 8:

[0365] The server sends the corrected message to the user's terminal. The user checks the correction results on their terminal and makes any necessary manual adjustments.

[0366] Step 9:

[0367] The user makes a final review of the corrections, and if there are no problems, officially sends the email. The process is completed when the device forwards this email to the designated recipient.

[0368] (Example 2)

[0369] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0370] In communication, the inappropriate transmission of the sender's emotions can lead to misunderstandings and interpersonal friction. Furthermore, typographical errors or inappropriate writing styles can negatively impact the recipient's impression of the message. The challenge lies in resolving these issues and achieving smooth, misunderstanding-free communication.

[0371] 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.

[0372] In this invention, the server includes a means for receiving the communication text and inferring the emotional state, an analysis means for analyzing the input communication text and detecting emotional expressions, and an adjustment means for adjusting the writing style based on the destination information and emotional state. This makes it possible to make appropriate adjustments to expressions and writing style according to emotions, thereby promoting smooth communication without misunderstandings.

[0373] "Communication body" refers to the main text content of text messages and emails sent and received via information processing equipment.

[0374] "Input means" refers to a device or interface that provides a function for a user to input information.

[0375] "Inference methods" refer to functions that analyze data to identify the user's emotional state and infer the appropriate emotional category.

[0376] "Analysis means" refers to a mechanism for processing input data and extracting or understanding necessary information.

[0377] "Conversion means" refers to a system or device for converting data in one format to another.

[0378] "Correction means" refers to a device or program that has the function of detecting errors and correcting them to appropriate information.

[0379] "Adjustment mechanism" refers to a mechanism that has the function of appropriately changing writing style and expression to conform to predetermined standards.

[0380] A "generative AI model" refers to an artificial intelligence model that learns from large amounts of data and generates or transforms new data.

[0381] "Natural language processing technology" refers to all technologies that enable computers to understand and process human language.

[0382] A "language database" refers to a collection of data that gathers information on the meaning, usage, and related aspects of words and expressions.

[0383] This system is configured to analyze and appropriately correct electronic communications entered by the user using a terminal. A specific embodiment is shown below.

[0384] First, the user enters an email or message on a device such as a smartphone or computer. The device then sends the message body to the server via the input method. At this time, the message body contains the user's natural language expression.

[0385] The server analyzes the received communication text using an emotion engine as a means of prediction to recognize the user's emotional state. This emotion engine is designed based on a generative AI model and automatically predicts emotions by analyzing past communication history and input patterns.

[0386] Next, the server analyzes the communication text using natural language processing techniques as an analysis tool. During the analysis process, emotional expressions are detected, and these are converted into more polite expressions using a conversion tool. Because this conversion depends on the emotional state, very fine-tuning is possible.

[0387] For typographical errors, the correction mechanism refers to a language database and corrects incorrectly entered words to their correct form. During this process, conversion and correction are performed in parallel, ensuring that the user's intent is preserved to the greatest extent possible.

[0388] Finally, the adjustment mechanism optimizes the writing style based on the recipient information and the user's emotional state. The server can maintain the original tone without applying overly complex adjustments, for example, in situations where concise and straightforward expression is appropriate.

[0389] As an example, if a user wants to express gratitude in a work-related message, the entered message "Thank you!" will be automatically converted into a more respectful expression such as "Thank you for your cooperation."

[0390] An example of a prompt for a generative AI model is, "Analyze the user's communication and generate appropriate expressions that reflect their emotions." This prompt enables the software to adjust the language to match the user's intent.

[0391] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0392] Step 1:

[0393] The user types an email or message on their device and presses the send button. The input may include concise sentences or casual expressions. The device sends this as the message body to the server. The output at this stage is the exact message body entered by the user.

[0394] Step 2:

[0395] The server sends the received communication text to the emotion engine to recognize the emotional state. It receives the communication text as input and analyzes its content using a generative AI model. The emotion engine evaluates past data history and the current sentence structure to infer the user's emotion (e.g., hurried, cautious). The output at this stage is the category of the inferred emotional state.

[0396] Step 3:

[0397] The server analyzes the communication text using natural language processing techniques, taking into account the output of the emotion engine. It uses the results of the emotion engine and the communication text as input to detect emotional phrasing. Data processing involves using text analysis techniques to identify important key phrases and tones. The output of this process is a list of emotional expressions.

[0398] Step 4:

[0399] Based on the analysis results, the server uses a conversion mechanism to soften emotional expressions. This conversion process takes a list of emotional expressions and their emotional categories as input, and outputs the converted expressions. For example, a sentence expressing frustration, such as "Please reply quickly!", is converted into a more polite expression like "We would appreciate it if you could reply as soon as possible."

[0400] Step 5:

[0401] The server uses correction tools to check for errors and correct them if necessary. It receives the converted document as input and detects errors by referring to a language database. This data processing corrects typos and omissions, resulting in an accurate document output.

[0402] Step 6:

[0403] The server uses recipient information and sentiment status to adjust the writing style and finalize the document. It uses recipient information and sentiment categories as input to determine the need for adjustment. The output of this step is a communication body optimized with a contextually appropriate writing style.

[0404] Step 7:

[0405] The user performs a final check, viewing the revised message on their device and verifying its content. After confirming that the output message body is correct, the user confirms sending. This completes the message that will ultimately be sent to the recipient.

[0406] (Application Example 2)

[0407] 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."

[0408] In modern society, electronic communication has become an important means of communication, but expressions that do not accurately reflect the sender's emotions often lead to misunderstandings and friction. Furthermore, in order for service providers to properly handle customer service, it is necessary to generate responses that respond quickly and accurately in accordance with the customer's emotions. For this reason, the development of automated response generation systems that take emotions into consideration is urgently needed.

[0409] 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.

[0410] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and detecting emotional expressions, and a selection and generation means for selecting and generating an automatic response according to the user's emotional state. This enables accurate expression adjustment and automatic response generation according to the user's emotions.

[0411] A "computer" is an electronic device used for inputting, processing, and outputting information.

[0412] "Communication content" refers to messages and data that are transmitted or received electronically.

[0413] An "input means" is an interface that allows a user to provide communication content to a computing device.

[0414] "Analysis means" refers to techniques for analyzing input communication content and identifying the emotional expressions contained within it.

[0415] "Emotional expressions" are expressions that appear in a text to indicate the sender's feelings or emotional state.

[0416] A "conversion mechanism" is a function that changes detected emotional expressions into other expressions.

[0417] "Correction methods" refer to the process of detecting errors in communication content and correcting them to their accurate form.

[0418] "Adjustment mechanism" refers to a mechanism for changing the style of emails and messages according to the circumstances of the recipient and sender.

[0419] A "selection and generation means" is a system for selecting and generating an appropriate automated response based on a specified emotional state.

[0420] A "control system" is a central management system that manages the entire process and issues instructions to ensure that each system functions properly.

[0421] The system program for realizing this invention involves a server and a user terminal working together to process communication content. Specifically, the user terminal provides means for inputting communication content and sends it to the server. The server uses analysis means for analyzing the received communication content and utilizes natural language processing technology to recognize emotional expressions within the input message.

[0422] Based on these analysis results, the server identifies the user's emotional state and uses conversion tools to transform it into appropriate expressions. This conversion process utilizes an emotion engine; for example, a message perceived as angry might be changed to a polite and calm expression. In addition, the server has correction tools to detect and correct typos. By referring to a dictionary database, incorrect words and grammar can be corrected to their correct form.

[0423] Furthermore, the server activates an adjustment mechanism that adjusts the writing style based on recipient information and the user's emotional state. This allows recipients to receive messages in the most appropriate style for their specific situation. In addition, the server provides a selection and generation mechanism that selects and generates an automated response that corresponds to the user's emotions, resulting in a fast and efficient response.

[0424] The hardware used includes cloud servers (e.g., Amazon Web Services), and the software utilizes natural language processing libraries (e.g., spaCy, Google Cloud AI's Natural Language API). As a concrete example of this system, if a customer sends a message such as "This service is completely useless!", the server detects the emotion and translates it into a calmer response.

[0425] Examples of prompt statements for generative AI models include the following:

[0426] "If a customer sends a message expressing dissatisfaction, please craft a polite reply that mitigates the content of their complaint."

[0427] Therefore, this system enables the generation of advanced electronic communications that take human emotions into consideration.

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] The user inputs the communication content using a terminal and sends it to the server. The input here is the message typed by the user, and the server receives this message. The output received by the server is text data ready for analysis.

[0431] Step 2:

[0432] The server analyzes the received message using analysis tools. The input data is the text data received in step 1, which is then analyzed using natural language processing techniques. These techniques include spaCy and Google Cloud AI's natural language API. As part of the data processing, emotional expressions are identified from the message. The output is data showing the extracted emotional expressions and their types.

[0433] Step 3:

[0434] The server uses a conversion mechanism to transform necessary expressions based on the analysis results. The input is the analysis result from step 2, and upon receiving it, the server uses its emotion engine to apply a transformation that softens the identified emotional expressions. Specifically, it changes expressions indicating that the user is angry to expressions with a calmer tone. The output is the transformed text data.

[0435] Step 4:

[0436] The server uses correction tools to correct errors in the converted message. The input data is the converted message obtained in step 3, and the server searches for errors by referring to a dictionary database. Specifically, it corrects spelling mistakes and grammatical errors into the appropriate format. The output is the corrected text data.

[0437] Step 5:

[0438] The server uses adjustment tools to refine the writing style based on recipient information and sentiment. The input is the modified message from step 4, which also includes recipient information. The server uses this information to modify the tone and style of the message as needed. Specific actions include formal adjustments for business use. The output is the final, refined message.

[0439] Step 6:

[0440] The server uses a selection generation mechanism to generate an automated response based on the user's emotions. The inputs are the final message from step 5 and the emotion data identified in step 2. The server uses a generation AI model to create an automated response utilizing the most appropriate prompt sentences. Specifically, the generated response is refined into a polite and appropriate response based on the prompts. The output is the final automated response message.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] [Third Embodiment]

[0445] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0446] 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.

[0447] 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).

[0448] 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.

[0449] 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.

[0450] 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).

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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".

[0457] The system according to the present invention is implemented in which, when a user generates an electronic communication, the server receives the communication text sent from the user's terminal, analyzes it, corrects it appropriately, and then presents it to the user. This system integrates multiple functions to perform emotional expression conversion, correction of typographical errors, and adjustment of writing style according to the recipient information.

[0458] When a user types an email or message, its content is sent from the user's device to the server. The server first uses natural language processing technology to analyze the message body and detect emotional expressions. For example, if an email contains aggressive language, it is converted into more polite language. This function can mitigate the negative impact that emotional expressions may have on the recipient.

[0459] Next, the server detects typos and corrects them to the correct words and grammar. This process involves string manipulation and dictionary database lookups, and spell and grammar checks are performed automatically. For example, if the input is "おはようござまう", it will be corrected to "おはようございます".

[0460] Furthermore, the server has the ability to select an appropriate writing style based on the recipient information and adjust the entire document as needed. This allows you to change emails addressed to superiors or clients to be more respectful. For example, it can correct a document containing casual language with more formal language as necessary.

[0461] The corrected message body is sent from the server to the user's terminal, where the user performs a final check. After the check, if the user determines that there are no problems, the email is sent to the designated recipient.

[0462] By implementing this system, users can send messages exactly as intended, avoiding misunderstandings and inappropriate tones. As a result, smoother communication can be achieved.

[0463] The following describes the processing flow.

[0464] Step 1:

[0465] The user enters an email or message on their device. The user enters text and specifies the recipient as usual.

[0466] Step 2:

[0467] The terminal sends the entered message body and recipient information to the server. At this time, the email is transferred to the server in data format.

[0468] Step 3:

[0469] The server analyzes the text of the communication it receives. Natural language processing techniques are used to identify emotional expressions within the text.

[0470] Step 4:

[0471] The server converts emotionally charged expressions it identifies into more polite language. For example, the expression "It's taking too long!" would be changed to "It seems to be taking a little longer than expected, could you please provide an update on the progress?"

[0472] Step 5:

[0473] The server detects errors in the text. It performs spell checks and grammar checks, and corrects them by referring to a dictionary database.

[0474] Step 6:

[0475] The server analyzes the recipient information to determine and adjust the appropriate writing style. For example, it might rewrite an email addressed to a superior to be more formal.

[0476] Step 7:

[0477] The server sends the corrected message to the terminal. The corrections are presented to the user, and they are asked to confirm them.

[0478] Step 8:

[0479] The user can review the correction results. They can also make manual fine adjustments as needed.

[0480] Step 9:

[0481] The user confirms the message content and then formally sends it. The process is completed when the device sends the email to the designated recipient.

[0482] (Example 1)

[0483] 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."

[0484] In modern electronic communications, misleading emotional expressions, inaccurate descriptions, and stylistic inconsistencies hinder smooth communication. This can create unnecessary tension between senders and receivers, leading to inefficiencies in business and personal interactions. Therefore, there is a need for a system that appropriately translates emotional expressions, automatically corrects inaccurate descriptions, and quickly and accurately adjusts writing style to suit the recipient.

[0485] 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.

[0486] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and identifying emotional expressions, and a conversion means for converting the identified emotional expressions into more appropriate expressions. This makes it possible to efficiently perform appropriate conversion of emotional expressions in electronic communications, correction of inaccurate descriptions, and consistency of writing style.

[0487] An "information processing system" refers to the entire apparatus or network used to generate or process electronic communications. This system integrates multiple means to effectively and efficiently manage information.

[0488] "Input means" refers to the interface or method by which a user provides the content of electronic communications to a system. This allows the user to input text messages or data.

[0489] "Analysis means" refers to a method for examining received data and identifying specific elements or patterns. This means uses natural language processing techniques to analyze the data in detail.

[0490] "Emotional expression" refers to words and phrases that express emotions included in text or conversation. This includes emotional nuances such as positive, negative, and aggressive.

[0491] A "conversion method" refers to a way of expressing specific expressions or data in a different format. This makes it possible to appropriately convey the intended nuances.

[0492] An "inaccurate description" refers to a sentence that contains spelling mistakes, grammatical errors, or expressions with unclear meaning. This can lead to misunderstandings or confusion.

[0493] "Correction measures" refer to methods for changing detected inaccurate elements into the correct format. This includes functions that apply correct words and grammar by referring to dictionaries and databases.

[0494] The "recipient" refers to the person or organization to which electronic communications are sent. This is the final destination where the communication content will be delivered.

[0495] "Style" refers to the manner of language and expression used in writing and conversation. Style should be adjusted according to the recipient and the situation.

[0496] "Adjustment methods" refer to techniques for modifying writing style and expression to suit specific purposes. This ensures that communication with the recipient is appropriate.

[0497] This invention is an information processing system for more clearly and appropriately representing the content of electronic communications. Specifically, communication content entered by a user using a terminal is transmitted to a server. The server is a system designed to adjust emotional expression, inaccuracies, and stylistic changes based on the received data.

[0498] The user uses the terminal to input a communication message and sends its content to the server. The server utilizes natural language processing technology to analyze the text. The server detects emotional expressions and converts them into appropriate expressions according to the context and the recipient. For example, an expression like "I'm really in trouble!" is converted to "I would be grateful for your support."

[0499] Furthermore, the server refers to the dictionary database to detect and correct inaccurate descriptions. This is achieved by automatically identifying grammar and spelling errors using a language model. For example, when "これからいこかん" (which might be something like "From now on, go?") is input, it is corrected to "これから行こうか" (From now on, shall we go?).

[0500] The server also adjusts the style of the message based on the recipient information. With this function, for example, it is possible to format a message to a business partner in a formal style.

[0501] The corrected and adjusted communication content is returned from the server to the user's terminal, and the user can check the content. After the final confirmation, the user sends the message to the designated recipient.

[0502] Examples of specific prompt sentences are as follows.

[0503] "The message entered by the user: {user input}. Please improve the tone of this message, correct spelling and grammar errors, and convert it to a formal style."

[0504] By implementing this invention, the user can surely send a message as intended, prevent misunderstandings, and improve the quality of communication.

[0505] The flow of specific processing in Example 1 will be described using FIG. 11.

[0506] Step 1:

[0507] The user enters an email or message into their device. The entered text is then sent from the device to the server as communication data. This input data is the body of the message intended by the user.

[0508] Step 2:

[0509] The server receives communication data sent from the terminal. The server uses natural language processing techniques to analyze the data and identify specific emotional expressions. This analysis extracts positive or negative elements from the message.

[0510] Step 3:

[0511] The server performs transformation operations based on the analyzed sentiment expressions. Specifically, it uses a generative AI model to convert aggressive or negative expressions into more neutral or positive ones. The output of this process is the improved message expression.

[0512] Step 4:

[0513] The server then detects and corrects typographical errors in the text, following the conversion of emotional expressions. This process involves referencing a dictionary database and performing string manipulation. For example, it corrects text with spelling mistakes or grammatical errors to accurate expressions. The output is the corrected, accurate text.

[0514] Step 5:

[0515] The server applies an algorithm to adjust the writing style based on the recipient information. Depending on the recipient's attributes, it converts casual writing to formal writing, or vice versa, making appropriate adjustments. The adjusted text is then generated as output.

[0516] Step 6:

[0517] The server sends the final corrected and adjusted version of the message to the user's terminal. The user reviews the proposed changes and makes further edits as needed. After final confirmation, the user decides whether to send the message to the recipient.

[0518] This allows users to deliver their intended message to recipients without misunderstanding.

[0519] (Application Example 1)

[0520] 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."

[0521] In modern society, communication via electronic means plays a crucial role, but misunderstandings can arise due to insufficient politeness, incorrect wording, and typographical errors. Furthermore, while smooth and accurate communication is essential in purchasing interactions, no system currently exists to suggest the most appropriate language. Improving the quality of such communication is a challenge.

[0522] 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.

[0523] In this invention, the server includes a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the dialogue content in real time and suggesting the most appropriate language to support communication during purchasing conversations. This makes it possible to reduce misunderstandings and discomfort during electronic communication and conversations, and to achieve smooth communication.

[0524] An "information processing device that generates electronic communications" is a device that has the function of generating, transmitting, or storing communications in digital format based on user input.

[0525] A "device for analyzing input communication text" is a device that understands the content of text entered by a user and performs calculations to identify emotional or grammatical elements.

[0526] A "device for detecting emotional expression" is a device that analyzes expressions within text and has the function of identifying the emotions that those expressions convey.

[0527] A "device that transforms emotional expressions into more pleasant ones" is a device that has the function of changing detected emotional content into something milder.

[0528] A "device for detecting and correcting errors" is a device that checks for typographical errors or misuses in communication content and corrects them as necessary.

[0529] A "device that adjusts writing style based on recipient information" is a device that has the function of changing the writing style and wording to an appropriate one depending on the recipient of the communication.

[0530] A "device that analyzes conversation content in real time and suggests the most appropriate wording to support communication during purchasing conversations" is a device that analyzes conversations that take place in situations such as purchasing in real time and has the function of suggesting appropriate responses to the other party.

[0531] The system for realizing this invention consists of a server, a user's terminal, and a network connecting them. The server receives the communication text input from the user. At this time, the user's terminal generates text data and sends it to the server via the network.

[0532] The server analyzes the communication text using natural language processing techniques to detect emotional expressions and typographical errors. For this analysis, natural language processing toolkits such as SpaCy and NLTK may be used. Detected emotional expressions are converted to milder expressions, and typographical errors are corrected by referring to a dictionary database.

[0533] Next, the server adjusts the writing style based on the recipient information. In this step, it selects formal or casual language depending on the intended recipient. In particular, to support communication during purchase conversations, it analyzes the conversation content in real time and suggests the most appropriate wording. When voice input is used, a speech recognition system such as the Google Speech-to-Text API is utilized.

[0534] The adjusted message body is sent back from the server to the user's terminal. The user then confirms it and sends it to complete the communication.

[0535] As a concrete example, when a user asks "Does this product still have a shelf life?" at a grocery store, the application translates this into a more formal expression such as "This product still has a shelf life remaining, so it will keep for a while."

[0536] An example of a prompt sentence to input into a generative AI model might be: "Design an app that suggests appropriate language when a user is purchasing food. This includes real-time translation using natural language processing and speech recognition."

[0537] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0538] Step 1:

[0539] The user's terminal generates the communication body entered by the user in text format and sends that data to the server. The input here is the raw text message typed by the user, and the output is the text data sent to the server over the network. In this step, the terminal transfers the initial communication data without processing it.

[0540] Step 2:

[0541] The server analyzes text data received over the network using natural language processing techniques, particularly for detecting emotional expressions. The input is the text data from step 1, and the output is a list of detected emotional elements. The server then uses this to determine if the text contains the user's intended emotion or negative expression.

[0542] Step 3:

[0543] The server converts emotional expressions into milder ones. In this step, the emotional elements detected in step 2 are used as input, and the converted text is generated as output. Specifically, negative expressions are replaced with more neutral phrases.

[0544] Step 4:

[0545] The server consults a dictionary database to detect and correct errors in the communication text. The input for this step is the text edited in step 3, and the output is the corrected text. String manipulation is performed here to correct spelling and grammatical errors.

[0546] Step 5:

[0547] The server adjusts the writing style based on the recipient information. The input requires the corrected text from step 4 and the recipient information, and the output is text with the adjusted writing style. At this stage, the entire document is revised to use language appropriate for the recipient.

[0548] Step 6:

[0549] The server analyzes the conversation in real time and suggests the most appropriate wording to support communication during the purchasing process. The input is the text adjusted in step 5, and the output is the final suggested message. Specifically, when voice input is converted to text, the server suggests the most appropriate response based on that content.

[0550] Step 7:

[0551] The user's terminal receives the final message from the server and presents it to the user. In this step, the input is the edited text sent from the server, and the output is the text that the user confirms on the screen. This action allows the user to finally confirm the message and send it if necessary.

[0552] 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.

[0553] The system according to the present invention achieves more appropriate and effective correction by combining an emotion engine with the generation of electronic communications by a user using an information processing device. In this system, the emotion engine recognizes the user's emotional state when the server receives and analyzes the communication text input from the user terminal. This enables the detection and conversion of emotional expressions, correction of typographical errors, and adjustment of writing style in a detailed manner according to the user's emotions.

[0554] First, when a user enters an email or message on their device, the server uses an emotion engine to check the user's emotional state before analyzing the message body. The emotion engine automatically infers the user's emotions based on their input patterns and past communication history. For example, if a user appears to be in a hurry when typing, the emotion engine will recognize a sense of urgency.

[0555] Subsequently, the server analyzes the communication text using natural language processing techniques, taking into account the emotional state recognized by the emotion engine. If emotional expressions are detected, they are converted into softer, more polite phrasing. This conversion process can utilize the results of the emotion engine to adjust the degree of expression conversion required. For example, if the expression "I can't wait any longer!" is recognized as the user being angry, it will be converted to "We apologize for the inconvenience. Could you please hurry?"

[0556] In addition, the server detects typos by referring to a dictionary database and corrects them to the correct words and grammar. It then adjusts the writing style based on the queried recipient information and the user's emotional state. If the user is judged to be calm, the tone can be maintained without significant adjustments.

[0557] This ensures that the corrections provided to the user accurately reflect their emotions while facilitating smooth and misunderstanding-free communication. The user then performs a final review and, after confirming the corrections are satisfactory, formally sends the email. Through this process, the user can convey their intentions with appropriate tone and expression, resulting in improved communication quality.

[0558] The following describes the processing flow.

[0559] Step 1:

[0560] The user enters the electronic communication information on the terminal. Here, the user composes the body of the email or message using the usual methods.

[0561] Step 2:

[0562] The terminal sends the entered message body and destination information to the server. This process transfers the information to the server in data format.

[0563] Step 3:

[0564] The emotion engine is activated as soon as the server receives the communication message. The emotion engine analyzes the user's input patterns and past communication history to infer the user's emotional state.

[0565] Step 4:

[0566] The server applies natural language processing techniques to analyze the communication text based on emotional information obtained from the emotion engine. Particular attention is paid to context and word choice in order to detect emotional expressions.

[0567] Step 5:

[0568] The emotional engine then modifies the emotional expressions detected by the server to the extent instructed by the server. For example, if the emotional engine recognizes the user's anger, it adjusts the expression to make it milder.

[0569] Step 6:

[0570] The server detects errors in the communication text by referring to a dictionary database and corrects them to the correct expression. This includes general spell checking and grammatical correction.

[0571] Step 7:

[0572] The server analyzes the recipient information and adjusts the writing style based on sentiment. For example, if it's an email to a superior, it will change the language to be more formal and polite.

[0573] Step 8:

[0574] The server sends the corrected message to the user's terminal. The user checks the correction results on their terminal and makes any necessary manual adjustments.

[0575] Step 9:

[0576] The user makes a final review of the corrections, and if there are no problems, officially sends the email. The process is completed when the device forwards this email to the designated recipient.

[0577] (Example 2)

[0578] 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."

[0579] In communication, the inappropriate transmission of the sender's emotions can lead to misunderstandings and interpersonal friction. Furthermore, typographical errors or inappropriate writing styles can negatively impact the recipient's impression of the message. The challenge lies in resolving these issues and achieving smooth, misunderstanding-free communication.

[0580] 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.

[0581] In this invention, the server includes a means for receiving the communication text and inferring the emotional state, an analysis means for analyzing the input communication text and detecting emotional expressions, and an adjustment means for adjusting the writing style based on the destination information and emotional state. This makes it possible to make appropriate adjustments to expressions and writing style according to emotions, thereby promoting smooth communication without misunderstandings.

[0582] "Communication body" refers to the main text content of text messages and emails sent and received via information processing equipment.

[0583] "Input means" refers to a device or interface that provides a function for a user to input information.

[0584] "Inference methods" refer to functions that analyze data to identify the user's emotional state and infer the appropriate emotional category.

[0585] "Analysis means" refers to a mechanism for processing input data and extracting or understanding necessary information.

[0586] "Conversion means" refers to a system or device for converting data in one format to another.

[0587] "Correction means" refers to a device or program that has the function of detecting errors and correcting them to appropriate information.

[0588] "Adjustment mechanism" refers to a mechanism that has the function of appropriately changing writing style and expression to conform to predetermined standards.

[0589] A "generative AI model" refers to an artificial intelligence model that learns from large amounts of data and generates or transforms new data.

[0590] "Natural language processing technology" refers to all technologies that enable computers to understand and process human language.

[0591] A "language database" refers to a collection of data that gathers information on the meaning, usage, and related aspects of words and expressions.

[0592] This system is configured to analyze and appropriately correct electronic communications entered by the user using a terminal. A specific embodiment is shown below.

[0593] First, the user enters an email or message on a device such as a smartphone or computer. The device then sends the message body to the server via the input method. At this time, the message body contains the user's natural language expression.

[0594] The server analyzes the received communication text using an emotion engine as a means of prediction to recognize the user's emotional state. This emotion engine is designed based on a generative AI model and automatically predicts emotions by analyzing past communication history and input patterns.

[0595] Next, the server analyzes the communication text using natural language processing techniques as an analysis tool. During the analysis process, emotional expressions are detected, and these are converted into more polite expressions using a conversion tool. Because this conversion depends on the emotional state, very fine-tuning is possible.

[0596] For typographical errors, the correction mechanism refers to a language database and corrects incorrectly entered words to their correct form. During this process, conversion and correction are performed in parallel, ensuring that the user's intent is preserved to the greatest extent possible.

[0597] Finally, the adjustment mechanism optimizes the writing style based on the recipient information and the user's emotional state. The server can maintain the original tone without applying overly complex adjustments, for example, in situations where concise and straightforward expression is appropriate.

[0598] As an example, if a user wants to express gratitude in a work-related message, the entered message "Thank you!" will be automatically converted into a more respectful expression such as "Thank you for your cooperation."

[0599] An example of a prompt for a generative AI model is, "Analyze the user's communication and generate appropriate expressions that reflect their emotions." This prompt enables the software to adjust the language to match the user's intent.

[0600] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0601] Step 1:

[0602] The user types an email or message on their device and presses the send button. The input may include concise sentences or casual expressions. The device sends this as the message body to the server. The output at this stage is the exact message body entered by the user.

[0603] Step 2:

[0604] The server sends the received communication text to the emotion engine to recognize the emotional state. It receives the communication text as input and analyzes its content using a generative AI model. The emotion engine evaluates past data history and the current sentence structure to infer the user's emotion (e.g., hurried, cautious). The output at this stage is the category of the inferred emotional state.

[0605] Step 3:

[0606] The server analyzes the communication text using natural language processing techniques, taking into account the output of the emotion engine. It uses the results of the emotion engine and the communication text as input to detect emotional phrasing. Data processing involves using text analysis techniques to identify important key phrases and tones. The output of this process is a list of emotional expressions.

[0607] Step 4:

[0608] Based on the analysis results, the server uses a conversion mechanism to soften emotional expressions. This conversion process takes a list of emotional expressions and their emotional categories as input, and outputs the converted expressions. For example, a sentence expressing frustration, such as "Please reply quickly!", is converted into a more polite expression like "We would appreciate it if you could reply as soon as possible."

[0609] Step 5:

[0610] The server uses correction tools to check for errors and correct them if necessary. It receives the converted document as input and detects errors by referring to a language database. This data processing corrects typos and omissions, resulting in an accurate document output.

[0611] Step 6:

[0612] The server uses recipient information and sentiment status to adjust the writing style and finalize the document. It uses recipient information and sentiment categories as input to determine the need for adjustment. The output of this step is a communication body optimized with a contextually appropriate writing style.

[0613] Step 7:

[0614] The user performs a final check, viewing the revised message on their device and verifying its content. After confirming that the output message body is correct, the user confirms sending. This completes the message that will ultimately be sent to the recipient.

[0615] (Application Example 2)

[0616] 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."

[0617] In modern society, electronic communication has become an important means of communication, but expressions that do not accurately reflect the sender's emotions often lead to misunderstandings and friction. Furthermore, in order for service providers to properly handle customer service, it is necessary to generate responses that respond quickly and accurately in accordance with the customer's emotions. For this reason, the development of automated response generation systems that take emotions into consideration is urgently needed.

[0618] 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.

[0619] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and detecting emotional expressions, and a selection and generation means for selecting and generating an automatic response according to the user's emotional state. This enables accurate expression adjustment and automatic response generation according to the user's emotions.

[0620] A "computer" is an electronic device used for inputting, processing, and outputting information.

[0621] "Communication content" refers to messages and data that are transmitted or received electronically.

[0622] An "input means" is an interface that allows a user to provide communication content to a computing device.

[0623] "Analysis means" refers to techniques for analyzing input communication content and identifying the emotional expressions contained within it.

[0624] "Emotional expressions" are expressions that appear in a text to indicate the sender's feelings or emotional state.

[0625] A "conversion mechanism" is a function that changes detected emotional expressions into other expressions.

[0626] "Correction methods" refer to the process of detecting errors in communication content and correcting them to their accurate form.

[0627] "Adjustment mechanism" refers to a mechanism for changing the style of emails and messages according to the circumstances of the recipient and sender.

[0628] A "selection and generation means" is a system for selecting and generating an appropriate automated response based on a specified emotional state.

[0629] A "control system" is a central management system that manages the entire process and issues instructions to ensure that each system functions properly.

[0630] The system program for realizing this invention involves a server and a user terminal working together to process communication content. Specifically, the user terminal provides means for inputting communication content and sends it to the server. The server uses analysis means for analyzing the received communication content and utilizes natural language processing technology to recognize emotional expressions within the input message.

[0631] Based on these analysis results, the server identifies the user's emotional state and uses conversion tools to transform it into appropriate expressions. This conversion process utilizes an emotion engine; for example, a message perceived as angry might be changed to a polite and calm expression. In addition, the server has correction tools to detect and correct typos. By referring to a dictionary database, incorrect words and grammar can be corrected to their correct form.

[0632] Furthermore, the server activates an adjustment mechanism that adjusts the writing style based on recipient information and the user's emotional state. This allows recipients to receive messages in the most appropriate style for their specific situation. In addition, the server provides a selection and generation mechanism that selects and generates an automated response that corresponds to the user's emotions, resulting in a fast and efficient response.

[0633] The hardware used includes cloud servers (e.g., Amazon Web Services), and the software utilizes natural language processing libraries (e.g., spaCy, Google Cloud AI's Natural Language API). As a concrete example of this system, if a customer sends a message such as "This service is completely useless!", the server detects the emotion and translates it into a calmer response.

[0634] Examples of prompt statements for generative AI models include the following:

[0635] "If a customer sends a message expressing dissatisfaction, please craft a polite reply that mitigates the content of their complaint."

[0636] Therefore, this system enables the generation of advanced electronic communications that take human emotions into consideration.

[0637] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0638] Step 1:

[0639] The user inputs the communication content using a terminal and sends it to the server. The input here is the message typed by the user, and the server receives this message. The output received by the server is text data ready for analysis.

[0640] Step 2:

[0641] The server analyzes the received message using analysis tools. The input data is the text data received in step 1, which is then analyzed using natural language processing techniques. These techniques include spaCy and Google Cloud AI's natural language API. As part of the data processing, emotional expressions are identified from the message. The output is data showing the extracted emotional expressions and their types.

[0642] Step 3:

[0643] The server uses a conversion mechanism to transform necessary expressions based on the analysis results. The input is the analysis result from step 2, and upon receiving it, the server uses its emotion engine to apply a transformation that softens the identified emotional expressions. Specifically, it changes expressions indicating that the user is angry to expressions with a calmer tone. The output is the transformed text data.

[0644] Step 4:

[0645] The server uses correction tools to correct errors in the converted message. The input data is the converted message obtained in step 3, and the server searches for errors by referring to a dictionary database. Specifically, it corrects spelling mistakes and grammatical errors into the appropriate format. The output is the corrected text data.

[0646] Step 5:

[0647] The server uses adjustment tools to refine the writing style based on recipient information and sentiment. The input is the modified message from step 4, which also includes recipient information. The server uses this information to modify the tone and style of the message as needed. Specific actions include formal adjustments for business use. The output is the final, refined message.

[0648] Step 6:

[0649] The server uses a selection generation mechanism to generate an automated response based on the user's emotions. The inputs are the final message from step 5 and the emotion data identified in step 2. The server uses a generation AI model to create an automated response utilizing the most appropriate prompt sentences. Specifically, the generated response is refined into a polite and appropriate response based on the prompts. The output is the final automated response message.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] [Fourth Embodiment]

[0654] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0655] 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.

[0656] 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).

[0657] 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.

[0658] 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.

[0659] 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).

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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.

[0664] 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.

[0665] 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.

[0666] 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".

[0667] The system according to the present invention is implemented in which, when a user generates an electronic communication, the server receives the communication text sent from the user's terminal, analyzes it, corrects it appropriately, and then presents it to the user. This system integrates multiple functions to perform emotional expression conversion, correction of typographical errors, and adjustment of writing style according to the recipient information.

[0668] When a user types an email or message, its content is sent from the user's device to the server. The server first uses natural language processing technology to analyze the message body and detect emotional expressions. For example, if an email contains aggressive language, it is converted into more polite language. This function can mitigate the negative impact that emotional expressions may have on the recipient.

[0669] Next, the server detects typos and corrects them to the correct words and grammar. This process involves string manipulation and dictionary database lookups, and spell and grammar checks are performed automatically. For example, if the input is "おはようござまう", it will be corrected to "おはようございます".

[0670] Furthermore, the server has the ability to select an appropriate writing style based on the recipient information and adjust the entire document as needed. This allows you to change emails addressed to superiors or clients to be more respectful. For example, it can correct a document containing casual language with more formal language as necessary.

[0671] The corrected message body is sent from the server to the user's terminal, where the user performs a final check. After the check, if the user determines that there are no problems, the email is sent to the designated recipient.

[0672] By implementing this system, users can send messages exactly as intended, avoiding misunderstandings and inappropriate tones. As a result, smoother communication can be achieved.

[0673] The following describes the processing flow.

[0674] Step 1:

[0675] The user enters an email or message on their device. The user enters text and specifies the recipient as usual.

[0676] Step 2:

[0677] The terminal sends the entered message body and recipient information to the server. At this time, the email is transferred to the server in data format.

[0678] Step 3:

[0679] The server analyzes the text of the communication it receives. Natural language processing techniques are used to identify emotional expressions within the text.

[0680] Step 4:

[0681] The server converts emotionally charged expressions it identifies into more polite language. For example, the expression "It's taking too long!" would be changed to "It seems to be taking a little longer than expected, could you please provide an update on the progress?"

[0682] Step 5:

[0683] The server detects errors in the text. It performs spell checks and grammar checks, and corrects them by referring to a dictionary database.

[0684] Step 6:

[0685] The server analyzes the recipient information to determine and adjust the appropriate writing style. For example, it might rewrite an email addressed to a superior to be more formal.

[0686] Step 7:

[0687] The server sends the corrected message to the terminal. The corrections are presented to the user, and they are asked to confirm them.

[0688] Step 8:

[0689] The user can review the correction results. They can also make manual fine adjustments as needed.

[0690] Step 9:

[0691] The user confirms the message content and then formally sends it. The process is completed when the device sends the email to the designated recipient.

[0692] (Example 1)

[0693] 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".

[0694] In modern electronic communications, misleading emotional expressions, inaccurate descriptions, and stylistic inconsistencies hinder smooth communication. This can create unnecessary tension between senders and receivers, leading to inefficiencies in business and personal interactions. Therefore, there is a need for a system that appropriately translates emotional expressions, automatically corrects inaccurate descriptions, and quickly and accurately adjusts writing style to suit the recipient.

[0695] 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.

[0696] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and identifying emotional expressions, and a conversion means for converting the identified emotional expressions into more appropriate expressions. This makes it possible to efficiently perform appropriate conversion of emotional expressions in electronic communications, correction of inaccurate descriptions, and consistency of writing style.

[0697] An "information processing system" refers to the entire apparatus or network used to generate or process electronic communications. This system integrates multiple means to effectively and efficiently manage information.

[0698] "Input means" refers to the interface or method by which a user provides the content of electronic communications to a system. This allows the user to input text messages or data.

[0699] "Analysis means" refers to a method for examining received data and identifying specific elements or patterns. This means uses natural language processing techniques to analyze the data in detail.

[0700] "Emotional expression" refers to words and phrases that express emotions included in text or conversation. This includes emotional nuances such as positive, negative, and aggressive.

[0701] A "conversion method" refers to a way of expressing specific expressions or data in a different format. This makes it possible to appropriately convey the intended nuances.

[0702] An "inaccurate description" refers to a sentence that contains spelling mistakes, grammatical errors, or expressions with unclear meaning. This can lead to misunderstandings or confusion.

[0703] "Correction measures" refer to methods for changing detected inaccurate elements into the correct format. This includes functions that apply correct words and grammar by referring to dictionaries and databases.

[0704] The "recipient" refers to the person or organization to which electronic communications are sent. This is the final destination where the communication content will be delivered.

[0705] "Style" refers to the manner of language and expression used in writing and conversation. Style should be adjusted according to the recipient and the situation.

[0706] "Adjustment means" refers to a method for changing the style and expression according to a specific use. This makes the communication with the recipient appropriate.

[0707] This invention is an information processing system for expressing the content of electronic communication more clearly and appropriately. Specifically, the communication content input by the user using the terminal is transmitted to the server. The server is a system designed to adjust emotional expressions, inaccurate descriptions, and style based on the received data.

[0708] The user inputs a communication message using the terminal and transmits its content to the server. The server utilizes natural language processing technology to analyze the text. The server detects emotional expressions and converts them into appropriate expressions according to the context and the recipient. For example, the expression "I'm really in trouble!" is converted to "I would be grateful for your support."

[0709] Furthermore, the server refers to the dictionary database to detect and correct inaccurate descriptions. This is achieved by automatically identifying grammar and spelling errors using a language model. For example, when "これからいこかん" (which is incorrect Japanese for "Let's go from now on") is input, it is corrected to "これから行こうか" (the correct form).

[0710] The server also adjusts the style of the message based on the recipient information. With this function, for example, it is possible to format a message to a business partner in a formal style.

[0711] The corrected and adjusted communication content is returned from the server to the user's terminal, and the user can confirm the content. After the final confirmation, the user transmits the message to the designated recipient.

[0712] Examples of specific prompt sentences are as follows.

[0713] "Message input by the user: {user input}. Please improve the tone of this message, correct typos and convert it to a formal style."

[0714] By implementing this invention, users can reliably send messages as intended, prevent misunderstandings, and improve the quality of communication.

[0715] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0716] Step 1:

[0717] The user enters an email or message into their device. The entered text is then sent from the device to the server as communication data. This input data is the body of the message intended by the user.

[0718] Step 2:

[0719] The server receives communication data sent from the terminal. The server uses natural language processing techniques to analyze the data and identify specific emotional expressions. This analysis extracts positive or negative elements from the message.

[0720] Step 3:

[0721] The server performs transformation operations based on the analyzed sentiment expressions. Specifically, it uses a generative AI model to convert aggressive or negative expressions into more neutral or positive ones. The output of this process is the improved message expression.

[0722] Step 4:

[0723] The server then detects and corrects typographical errors in the text, following the conversion of emotional expressions. This process involves referencing a dictionary database and performing string manipulation. For example, it corrects text with spelling mistakes or grammatical errors to accurate expressions. The output is the corrected, accurate text.

[0724] Step 5:

[0725] The server applies an algorithm to adjust the writing style based on the recipient information. Depending on the recipient's attributes, it converts casual writing to formal writing, or vice versa, making appropriate adjustments. The adjusted text is then generated as output.

[0726] Step 6:

[0727] The server sends the final corrected and adjusted version of the message to the user's terminal. The user reviews the proposed changes and makes further edits as needed. After final confirmation, the user decides whether to send the message to the recipient.

[0728] This allows users to deliver their intended message to recipients without misunderstanding.

[0729] (Application Example 1)

[0730] 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".

[0731] In modern society, communication via electronic means plays a crucial role, but misunderstandings can arise due to insufficient politeness, incorrect wording, and typographical errors. Furthermore, while smooth and accurate communication is essential in purchasing interactions, no system currently exists to suggest the most appropriate language. Improving the quality of such communication is a challenge.

[0732] 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.

[0733] In this invention, the server includes a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the dialogue content in real time and suggesting the most appropriate language to support communication during purchasing conversations. This makes it possible to reduce misunderstandings and discomfort during electronic communication and conversations, and to achieve smooth communication.

[0734] An "information processing device that generates electronic communications" is a device that has the function of generating, transmitting, or storing communications in digital format based on user input.

[0735] A "device for analyzing input communication text" is a device that understands the content of text entered by a user and performs calculations to identify emotional or grammatical elements.

[0736] A "device for detecting emotional expression" is a device that analyzes expressions within text and has the function of identifying the emotions that those expressions convey.

[0737] A "device that transforms emotional expressions into more pleasant ones" is a device that has the function of changing detected emotional content into something milder.

[0738] A "device for detecting and correcting errors" is a device that checks for typographical errors or misuses in communication content and corrects them as necessary.

[0739] A "device that adjusts writing style based on recipient information" is a device that has the function of changing the writing style and wording to an appropriate one depending on the recipient of the communication.

[0740] A "device that analyzes conversation content in real time and suggests the most appropriate wording to support communication during purchasing conversations" is a device that analyzes conversations that take place in situations such as purchasing in real time and has the function of suggesting appropriate responses to the other party.

[0741] The system for realizing this invention consists of a server, a user's terminal, and a network connecting them. The server receives the communication text input from the user. At this time, the user's terminal generates text data and sends it to the server via the network.

[0742] The server analyzes the communication text using natural language processing techniques to detect emotional expressions and typographical errors. For this analysis, natural language processing toolkits such as SpaCy and NLTK may be used. Detected emotional expressions are converted to milder expressions, and typographical errors are corrected by referring to a dictionary database.

[0743] Next, the server adjusts the writing style based on the recipient information. In this step, it selects formal or casual language depending on the intended recipient. In particular, to support communication during purchase conversations, it analyzes the conversation content in real time and suggests the most appropriate wording. When voice input is used, a speech recognition system such as the Google Speech-to-Text API is utilized.

[0744] The adjusted message body is sent back from the server to the user's terminal. The user then confirms it and sends it to complete the communication.

[0745] As a concrete example, when a user asks "Does this product still have a shelf life?" at a grocery store, the application translates this into a more formal expression such as "This product still has a shelf life remaining, so it will keep for a while."

[0746] An example of a prompt sentence to input into a generative AI model might be: "Design an app that suggests appropriate language when a user is purchasing food. This includes real-time translation using natural language processing and speech recognition."

[0747] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0748] Step 1:

[0749] The user's terminal generates the communication body entered by the user in text format and sends that data to the server. The input here is the raw text message typed by the user, and the output is the text data sent to the server over the network. In this step, the terminal transfers the initial communication data without processing it.

[0750] Step 2:

[0751] The server analyzes text data received over the network using natural language processing techniques, particularly for detecting emotional expressions. The input is the text data from step 1, and the output is a list of detected emotional elements. The server then uses this to determine if the text contains the user's intended emotion or negative expression.

[0752] Step 3:

[0753] The server converts emotional expressions into milder ones. In this step, the emotional elements detected in step 2 are used as input, and the converted text is generated as output. Specifically, negative expressions are replaced with more neutral phrases.

[0754] Step 4:

[0755] The server consults a dictionary database to detect and correct errors in the communication text. The input for this step is the text edited in step 3, and the output is the corrected text. String manipulation is performed here to correct spelling and grammatical errors.

[0756] Step 5:

[0757] The server adjusts the writing style based on the recipient information. The input requires the corrected text from step 4 and the recipient information, and the output is text with the adjusted writing style. At this stage, the entire document is revised to use language appropriate for the recipient.

[0758] Step 6:

[0759] The server analyzes the conversation in real time and suggests the most appropriate wording to support communication during the purchasing process. The input is the text adjusted in step 5, and the output is the final suggested message. Specifically, when voice input is converted to text, the server suggests the most appropriate response based on that content.

[0760] Step 7:

[0761] The user's terminal receives the final message from the server and presents it to the user. In this step, the input is the edited text sent from the server, and the output is the text that the user confirms on the screen. This action allows the user to finally confirm the message and send it if necessary.

[0762] 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.

[0763] The system according to the present invention achieves more appropriate and effective correction by combining an emotion engine with the generation of electronic communications by a user using an information processing device. In this system, the emotion engine recognizes the user's emotional state when the server receives and analyzes the communication text input from the user terminal. This enables the detection and conversion of emotional expressions, correction of typographical errors, and adjustment of writing style in a detailed manner according to the user's emotions.

[0764] First, when a user enters an email or message on their device, the server uses an emotion engine to check the user's emotional state before analyzing the message body. The emotion engine automatically infers the user's emotions based on their input patterns and past communication history. For example, if a user appears to be in a hurry when typing, the emotion engine will recognize a sense of urgency.

[0765] Subsequently, the server analyzes the communication text using natural language processing techniques, taking into account the emotional state recognized by the emotion engine. If emotional expressions are detected, they are converted into softer, more polite phrasing. This conversion process can utilize the results of the emotion engine to adjust the degree of expression conversion required. For example, if the expression "I can't wait any longer!" is recognized as the user being angry, it will be converted to "We apologize for the inconvenience. Could you please hurry?"

[0766] In addition, the server detects typos by referring to a dictionary database and corrects them to the correct words and grammar. It then adjusts the writing style based on the queried recipient information and the user's emotional state. If the user is judged to be calm, the tone can be maintained without significant adjustments.

[0767] This ensures that the corrections provided to the user accurately reflect their emotions while facilitating smooth and misunderstanding-free communication. The user then performs a final review and, after confirming the corrections are satisfactory, formally sends the email. Through this process, the user can convey their intentions with appropriate tone and expression, resulting in improved communication quality.

[0768] The following describes the processing flow.

[0769] Step 1:

[0770] The user enters the electronic communication information on the terminal. Here, the user composes the body of the email or message using the usual methods.

[0771] Step 2:

[0772] The terminal sends the entered message body and destination information to the server. This process transfers the information to the server in data format.

[0773] Step 3:

[0774] The emotion engine is activated as soon as the server receives the communication message. The emotion engine analyzes the user's input patterns and past communication history to infer the user's emotional state.

[0775] Step 4:

[0776] The server applies natural language processing techniques to analyze the communication text based on emotional information obtained from the emotion engine. Particular attention is paid to context and word choice in order to detect emotional expressions.

[0777] Step 5:

[0778] The emotional engine then modifies the emotional expressions detected by the server to the extent instructed by the server. For example, if the emotional engine recognizes the user's anger, it adjusts the expression to make it milder.

[0779] Step 6:

[0780] The server detects errors in the communication text by referring to a dictionary database and corrects them to the correct expression. This includes general spell checking and grammatical correction.

[0781] Step 7:

[0782] The server analyzes the recipient information and adjusts the writing style based on sentiment. For example, if it's an email to a superior, it will change the language to be more formal and polite.

[0783] Step 8:

[0784] The server sends the corrected message to the user's terminal. The user checks the correction results on their terminal and makes any necessary manual adjustments.

[0785] Step 9:

[0786] The user makes a final review of the corrections, and if there are no problems, officially sends the email. The process is completed when the device forwards this email to the designated recipient.

[0787] (Example 2)

[0788] 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".

[0789] In communication, the inappropriate transmission of the sender's emotions can lead to misunderstandings and interpersonal friction. Furthermore, typographical errors or inappropriate writing styles can negatively impact the recipient's impression of the message. The challenge lies in resolving these issues and achieving smooth, misunderstanding-free communication.

[0790] 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.

[0791] In this invention, the server includes a means for receiving the communication text and inferring the emotional state, an analysis means for analyzing the input communication text and detecting emotional expressions, and an adjustment means for adjusting the writing style based on the destination information and emotional state. This makes it possible to make appropriate adjustments to expressions and writing style according to emotions, thereby promoting smooth communication without misunderstandings.

[0792] "Communication body" refers to the main text content of text messages and emails sent and received via information processing equipment.

[0793] "Input means" refers to a device or interface that provides a function for a user to input information.

[0794] "Inference methods" refer to functions that analyze data to identify the user's emotional state and infer the appropriate emotional category.

[0795] "Analysis means" refers to a mechanism for processing input data and extracting or understanding necessary information.

[0796] "Conversion means" refers to a system or device for converting data in one format to another.

[0797] "Correction means" refers to a device or program that has the function of detecting errors and correcting them to appropriate information.

[0798] "Adjustment mechanism" refers to a mechanism that has the function of appropriately changing writing style and expression to conform to predetermined standards.

[0799] A "generative AI model" refers to an artificial intelligence model that learns from large amounts of data and generates or transforms new data.

[0800] "Natural language processing technology" refers to all technologies that enable computers to understand and process human language.

[0801] A "language database" refers to a collection of data that gathers information on the meaning, usage, and related aspects of words and expressions.

[0802] This system is configured to analyze and appropriately correct electronic communications entered by the user using a terminal. A specific embodiment is shown below.

[0803] First, the user enters an email or message on a device such as a smartphone or computer. The device then sends the message body to the server via the input method. At this time, the message body contains the user's natural language expression.

[0804] The server analyzes the received communication text using an emotion engine as a means of prediction to recognize the user's emotional state. This emotion engine is designed based on a generative AI model and automatically predicts emotions by analyzing past communication history and input patterns.

[0805] Next, the server analyzes the communication text using natural language processing techniques as an analysis tool. During the analysis process, emotional expressions are detected, and these are converted into more polite expressions using a conversion tool. Because this conversion depends on the emotional state, very fine-tuning is possible.

[0806] For typographical errors, the correction mechanism refers to a language database and corrects incorrectly entered words to their correct form. During this process, conversion and correction are performed in parallel, ensuring that the user's intent is preserved to the greatest extent possible.

[0807] Finally, the adjustment mechanism optimizes the writing style based on the recipient information and the user's emotional state. The server can maintain the original tone without applying overly complex adjustments, for example, in situations where concise and straightforward expression is appropriate.

[0808] As an example, if a user wants to express gratitude in a work-related message, the entered message "Thank you!" will be automatically converted into a more respectful expression such as "Thank you for your cooperation."

[0809] An example of a prompt for a generative AI model is, "Analyze the user's communication and generate appropriate expressions that reflect their emotions." This prompt enables the software to adjust the language to match the user's intent.

[0810] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0811] Step 1:

[0812] The user types an email or message on their device and presses the send button. The input may include concise sentences or casual expressions. The device sends this as the message body to the server. The output at this stage is the exact message body entered by the user.

[0813] Step 2:

[0814] The server sends the received communication text to the emotion engine to recognize the emotional state. It receives the communication text as input and analyzes its content using a generative AI model. The emotion engine evaluates past data history and the current sentence structure to infer the user's emotion (e.g., hurried, cautious). The output at this stage is the category of the inferred emotional state.

[0815] Step 3:

[0816] The server analyzes the communication text using natural language processing techniques, taking into account the output of the emotion engine. It uses the results of the emotion engine and the communication text as input to detect emotional phrasing. Data processing involves using text analysis techniques to identify important key phrases and tones. The output of this process is a list of emotional expressions.

[0817] Step 4:

[0818] Based on the analysis results, the server uses a conversion mechanism to soften emotional expressions. This conversion process takes a list of emotional expressions and their emotional categories as input, and outputs the converted expressions. For example, a sentence expressing frustration, such as "Please reply quickly!", is converted into a more polite expression like "We would appreciate it if you could reply as soon as possible."

[0819] Step 5:

[0820] The server uses correction tools to check for errors and correct them if necessary. It receives the converted document as input and detects errors by referring to a language database. This data processing corrects typos and omissions, resulting in an accurate document output.

[0821] Step 6:

[0822] The server uses recipient information and sentiment status to adjust the writing style and finalize the document. It uses recipient information and sentiment categories as input to determine the need for adjustment. The output of this step is a communication body optimized with a contextually appropriate writing style.

[0823] Step 7:

[0824] The user performs a final check, viewing the revised message on their device and verifying its content. After confirming that the output message body is correct, the user confirms sending. This completes the message that will ultimately be sent to the recipient.

[0825] (Application Example 2)

[0826] 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".

[0827] In modern society, electronic communication has become an important means of communication, but expressions that do not accurately reflect the sender's emotions often lead to misunderstandings and friction. Furthermore, in order for service providers to properly handle customer service, it is necessary to generate responses that respond quickly and accurately in accordance with the customer's emotions. For this reason, the development of automated response generation systems that take emotions into consideration is urgently needed.

[0828] 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.

[0829] In this invention, the server includes an input means for inputting communication content, an analysis means for analyzing the input communication content and detecting emotional expressions, and a selection and generation means for selecting and generating an automatic response according to the user's emotional state. This enables accurate expression adjustment and automatic response generation according to the user's emotions.

[0830] A "computer" is an electronic device used for inputting, processing, and outputting information.

[0831] "Communication content" refers to messages and data that are transmitted or received electronically.

[0832] An "input means" is an interface that allows a user to provide communication content to a computing device.

[0833] "Analysis means" refers to techniques for analyzing input communication content and identifying the emotional expressions contained within it.

[0834] "Emotional expressions" are expressions that appear in a text to indicate the sender's feelings or emotional state.

[0835] A "conversion mechanism" is a function that changes detected emotional expressions into other expressions.

[0836] "Correction methods" refer to the process of detecting errors in communication content and correcting them to their accurate form.

[0837] "Adjustment mechanism" refers to a mechanism for changing the style of emails and messages according to the circumstances of the recipient and sender.

[0838] A "selection and generation means" is a system for selecting and generating an appropriate automated response based on a specified emotional state.

[0839] A "control system" is a central management system that manages the entire process and issues instructions to ensure that each system functions properly.

[0840] The system program for realizing this invention involves a server and a user terminal working together to process communication content. Specifically, the user terminal provides means for inputting communication content and sends it to the server. The server uses analysis means for analyzing the received communication content and utilizes natural language processing technology to recognize emotional expressions within the input message.

[0841] Based on these analysis results, the server identifies the user's emotional state and uses conversion tools to transform it into appropriate expressions. This conversion process utilizes an emotion engine; for example, a message perceived as angry might be changed to a polite and calm expression. In addition, the server has correction tools to detect and correct typos. By referring to a dictionary database, incorrect words and grammar can be corrected to their correct form.

[0842] Furthermore, the server activates an adjustment mechanism that adjusts the writing style based on recipient information and the user's emotional state. This allows recipients to receive messages in the most appropriate style for their specific situation. In addition, the server provides a selection and generation mechanism that selects and generates an automated response that corresponds to the user's emotions, resulting in a fast and efficient response.

[0843] The hardware used includes cloud servers (e.g., Amazon Web Services), and the software utilizes natural language processing libraries (e.g., spaCy, Google Cloud AI's Natural Language API). As a concrete example of this system, if a customer sends a message such as "This service is completely useless!", the server detects the emotion and translates it into a calmer response.

[0844] Examples of prompt statements for generative AI models include the following:

[0845] "If a customer sends a message expressing dissatisfaction, please craft a polite reply that mitigates the content of their complaint."

[0846] Therefore, this system enables the generation of advanced electronic communications that take human emotions into consideration.

[0847] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0848] Step 1:

[0849] The user inputs the communication content using a terminal and sends it to the server. The input here is the message typed by the user, and the server receives this message. The output received by the server is text data ready for analysis.

[0850] Step 2:

[0851] The server analyzes the received message using analysis tools. The input data is the text data received in step 1, which is then analyzed using natural language processing techniques. These techniques include spaCy and Google Cloud AI's natural language API. As part of the data processing, emotional expressions are identified from the message. The output is data showing the extracted emotional expressions and their types.

[0852] Step 3:

[0853] The server uses a conversion mechanism to transform necessary expressions based on the analysis results. The input is the analysis result from step 2, and upon receiving it, the server uses its emotion engine to apply a transformation that softens the identified emotional expressions. Specifically, it changes expressions indicating that the user is angry to expressions with a calmer tone. The output is the transformed text data.

[0854] Step 4:

[0855] The server uses correction tools to correct errors in the converted message. The input data is the converted message obtained in step 3, and the server searches for errors by referring to a dictionary database. Specifically, it corrects spelling mistakes and grammatical errors into the appropriate format. The output is the corrected text data.

[0856] Step 5:

[0857] The server uses adjustment tools to refine the writing style based on recipient information and sentiment. The input is the modified message from step 4, which also includes recipient information. The server uses this information to modify the tone and style of the message as needed. Specific actions include formal adjustments for business use. The output is the final, refined message.

[0858] Step 6:

[0859] The server uses a selection generation mechanism to generate an automated response based on the user's emotions. The inputs are the final message from step 5 and the emotion data identified in step 2. The server uses a generation AI model to create an automated response utilizing the most appropriate prompt sentences. Specifically, the generated response is refined into a polite and appropriate response based on the prompts. The output is the final automated response message.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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."

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] The following is further disclosed regarding the embodiments described above.

[0882] (Claim 1)

[0883] A system comprising an information processing device for generating electronic communications, comprising an input means for inputting the body of a communications message, an analysis means for analyzing the input body of a communications message and detecting emotional expressions, a conversion means for converting the detected emotional expressions into more pleasant expressions, a correction means for detecting and correcting errors, and a control means for adjusting the writing style based on destination information.

[0884] (Claim 2)

[0885] The system according to claim 1, wherein the analysis means uses natural language processing technology.

[0886] (Claim 3)

[0887] The system according to claim 1, wherein the correction means refers to a dictionary database to detect a typographical error.

[0888] "Example 1"

[0889] (Claim 1)

[0890] In an information processing system that generates electronic communications, an input means for inputting communication content,

[0891] An analysis means for analyzing the input communication content and identifying emotional expressions,

[0892] A means of converting identified emotional expressions into more appropriate expressions,

[0893] A correction method for detecting and correcting inaccurate descriptions,

[0894] A control means that controls an adjustment means that adjusts the style of writing based on the recipient's information,

[0895] A system including a means for presenting the aforementioned modifications to the user and allowing for final confirmation.

[0896] (Claim 2)

[0897] The system according to claim 1, wherein the analysis means uses machine learning technology.

[0898] (Claim 3)

[0899] The system according to claim 1, wherein the correction means refers to a database to detect an inaccurate description.

[0900] "Application Example 1"

[0901] (Claim 1)

[0902] A system for controlling an information processing device that generates electronic communications, including a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the content of a conversation in real time and suggesting the most appropriate language to support communication in a purchasing conversation.

[0903] (Claim 2)

[0904] The system according to claim 1, wherein the analysis device uses natural language processing technology.

[0905] (Claim 3)

[0906] The system according to claim 1, wherein the correction device refers to a dictionary database to detect a typographical error.

[0907] "Example 2 of combining an emotion engine"

[0908] (Claim 1)

[0909] An input method for entering the message body,

[0910] A means for receiving the message text and inferring the emotional state,

[0911] An analysis means for analyzing the input communication text to detect emotional expressions,

[0912] A means of converting detected emotional expressions into expressions with a better atmosphere,

[0913] A correction method for detecting and correcting errors,

[0914] A means for adjusting the writing style based on recipient information and emotional state,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, wherein the analysis means uses natural language processing technology with a generative AI model.

[0918] (Claim 3)

[0919] The system according to claim 1, wherein the correction means refers to a language database to detect a typographical error.

[0920] "Application example 2 when combining with an emotional engine"

[0921] (Claim 1)

[0922] A computing device for generating electronic communications, comprising: an input means for inputting communication content; an analysis means for analyzing the input communication content and detecting emotional expressions; a conversion means for converting the detected emotional expressions into more pleasant expressions; a correction means for detecting and correcting typographical errors; an adjustment means for adjusting the writing style based on destination information; and a control means for controlling a selection and generation means that selects and generates an automatic response according to the user's emotional state.

[0923] (Claim 2)

[0924] The system according to claim 1, wherein the analysis means uses natural language processing technology.

[0925] (Claim 3)

[0926] The system according to claim 1, wherein the correction means refers to a dictionary database to detect a typographical error. [Explanation of Symbols]

[0927] 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 system for controlling an information processing device that generates electronic communications, including a device for inputting the communication text, a device for analyzing the input communication text and detecting emotional expressions, a device for converting the detected emotional expressions into more pleasant expressions, a device for detecting and correcting typographical errors, a device for adjusting the writing style based on recipient information, and a device for analyzing the content of a conversation in real time and suggesting the most appropriate language to support communication in a purchasing conversation.

2. The system according to claim 1, wherein the analysis device uses natural language processing technology.

3. The system according to claim 1, wherein the correction device refers to a dictionary database to detect a typographical error.

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