system

Abstract

We provide the system. [Solution] A means of converting speech input into text data using natural language processing technology, A means for analyzing the speaker's intent from the aforementioned text data and selecting appropriate quotations or guiding words, A user interface means for displaying the selected quote or guideline, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern conversations, there is a problem that it is difficult to have persuasive and effective communication due to limited knowledge and expressiveness. As a result, there is a lack of self-expression in conversations, the content to be conveyed is not fully understood by the other party, and the possibility of misunderstanding increases. Therefore, in situations where effective communication is required, such as in business, education, counseling, etc., means to compensate for this are required.

Means for Solving the Problems

[0005] This invention provides a means to solve this problem by using natural language processing technology and generative models. The invention includes means for converting speech input into text data, analyzing the speaker's intent, and selecting appropriate quotations or guidelines. The selected content is then displayed via a user interface, allowing the user to intuitively select it, thereby enabling more persuasive and effective communication with the other party.

[0006] "Natural language processing technology" is a technology that enables computers to understand and process human language.

[0007] "Voice input" is an input method that allows a computer to read the voice spoken by the user.

[0008] "Text data" refers to data obtained by converting non-text data, such as audio or images, into textual information.

[0009] "Speaker's intent" refers to the content or purpose that the speaker is trying to convey in a conversation.

[0010] A "quote" is a text extracted from existing literature or statements that possesses a certain meaning or value.

[0011] A "guideline" is a set of words that serve as a standard for guiding actions and decisions.

[0012] "User interface" is a general term for the screens and input methods that a user uses when interacting with a computer.

[0013] A "generative model" refers to an algorithm or system used to create new content or information from data. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] 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. [[ID=*33]] [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a tagged processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a tagged storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, a tagged communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0021] <0,000,110>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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system that enables speakers to communicate more persuasively during conversations. Specifically, it implements a program that utilizes speech recognition technology and a generative AI model, and an embodiment thereof is shown below.

[0036] First, when a user begins a conversation, the device acquires the audio in real time through the microphone. This audio data is then converted into text data using speech recognition technology. The converted text data is then sent from the device to the server.

[0037] The server analyzes the received text data using natural language processing techniques to understand the context of the conversation and the speaker's intent. A generative AI model then uses this analysis to select appropriate quotes and guidelines from a database. Specifically, relevant quotes and helpful advice are chosen as candidates, thereby improving the quality of the conversation.

[0038] Next, the server sends the selected candidates to the terminal, which displays them on the user interface. The user can review the presented options and select the appropriate one. This selection allows the user to give weight to their words and effectively convey their message to the person they are talking to.

[0039] As a concrete example, consider a new proposal in a business meeting. When a user proposes a new idea, the device captures the statement, and the server displays a quote such as "New ideas are always the foundation of evolution" (a hypothetical famous quote). The user can then use this to enhance the persuasiveness of their proposal by stating, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way."

[0040] Thus, the system of the present invention helps to enrich the range of words and improve the quality of the message being conveyed in a variety of dialogue situations.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] When a user begins a conversation, the device captures their speech in real time via the microphone.

[0044] Step 2:

[0045] The device converts the acquired voice data into text data using its built-in speech recognition technology.

[0046] Step 3:

[0047] The terminal sends the generated text data to the server for analysis.

[0048] Step 4:

[0049] The server analyzes the received text data using natural language processing techniques to identify the context of the conversation and the speaker's intent.

[0050] Step 5:

[0051] The server uses a generated AI model to select candidates from a database that include appropriate quotations and guidelines based on the analysis results.

[0052] Step 6:

[0053] The server sends a list of selected quotes and guidelines to the terminal.

[0054] Step 7:

[0055] The selection results received by the terminal are displayed on the user interface, allowing the user to select the most appropriate option.

[0056] Step 8:

[0057] The user selects the appropriate word from the presented options and conveys their selection to the conversation partner.

[0058] (Example 1)

[0059] 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."

[0060] Conventional speech recognition systems only convert speech to text, and lack sufficient support to improve the quality of subsequent conversations. In particular, they lacked the ability to provide appropriate quotations and guidelines that align with the speaker's intent in real time, making it difficult to effectively assist the flow of dialogue. This invention aims to solve these problems and enable speakers to communicate more persuasively during conversations.

[0061] 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.

[0062] In this invention, the server includes means for acquiring speech and converting the speech input into text data; means for transmitting the converted text data to a data storage device via a communication network; and means for the storage device to analyze the text data using natural language processing technology and select appropriate quotations or guiding information from external information sources. This enables the speaker to acquire quotations and guiding information that match their intentions in real time, thereby improving the quality of the conversation.

[0063] "Acquiring speech" refers to the act of capturing a speaker's utterance as an acoustic signal into a device and using that signal for subsequent processing.

[0064] "Converting voice input to text data" refers to the act of using speech recognition technology to convert collected acoustic signals into corresponding string data.

[0065] A "communication network" refers to a means of connection for sending and receiving data, encompassing a wide range of digital communication methods, including the internet and dedicated lines.

[0066] A "data storage device" refers to a computing device or media that temporarily or permanently stores information and allows access to and use that information as needed.

[0067] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and analyze human language, and specifically refers to the technology used for classifying and semantic analysis of language data.

[0068] "External information sources" refer to a collection of information or information providers that exist outside the system and can provide the necessary data.

[0069] A “quote or instruction” is a statement or instruction that is intended to advise or refer to the speaker in a particular context, and is usually selected from a reliable source.

[0070] An "ergonomically designed user interface" refers to an operating surface designed to allow users to operate it intuitively and effectively, and includes elements that are optimized from a visual and operational standpoint.

[0071] This system enables speakers to communicate more persuasively during conversations and is implemented using speech recognition technology, generative AI models, and a sophisticated user interface.

[0072] When a user begins a conversation, the device's built-in microphone captures the audio. This audio is then converted into text data in real time using speech recognition technology. This process utilizes speech-to-text solutions such as Google® Speech-to-Text API. The text data generated by speech recognition is sent to a server via the communication network.

[0073] The server analyzes the received text data using natural language processing (NLTK) techniques. For analysis, natural language processing libraries such as spaCy and NLTK are used to extract the speaker's intent and conversational context from the text. Then, a generative AI model (for example, the GPT series) selects appropriate quotations and guidelines from external sources based on the analysis results. This selects the information necessary to improve the quality of the conversation.

[0074] Selected quotes and guidelines are transmitted from the server to the terminal and presented to the user through an ergonomically designed user interface. This interface offers excellent visibility and operability, allowing users to easily select quotes and guidelines and incorporate them into their conversations.

[0075] For example, when a user presents a new product idea in a business meeting, the system can recognize the statement and suggest a quote such as, "New ideas are always the foundation of evolution." The user can then use this information to increase the persuasiveness of their proposal by saying, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way." In such a situation, a prompt such as, "Please tell me some effective quotes to use when proposing a new product in a business meeting," would be useful.

[0076] This invention provides effective support for users to select words in various dialogue situations and improve the quality of their messages.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] When a user starts a conversation, the device's microphone acquires the voice. The voice data, as input, arrives at the microphone as sound waves. Specifically, the microphone converts changes in ambient sound pressure into electrical signals, which are then converted from analog to digital and stored as digital audio data.

[0080] Step 2:

[0081] The device passes the acquired audio data to a speech recognition module, which then converts the content into text data. The input is digital audio data, and the output is text data in which the audio is represented as characters. For example, the Google Speech-to-Text API is used as the speech recognition technology, and data conversion is performed by combining an acoustic model and a language model.

[0082] Step 3:

[0083] The terminal sends the converted text data to the server. Here, the input is text data, and the output is secure data transmission using a communication protocol (e.g., HTTPS). Specifically, the terminal breaks down the text data into packets and sends them to the server over the network.

[0084] Step 4:

[0085] The server analyzes the received text data using a natural language processing library (e.g., spaCy). The input is text data, and the output is the analyzed conversational context and keywords. Specifically, the server analyzes the text data based on its grammatical structure and extracts the speaker's intent and context.

[0086] Step 5:

[0087] The server runs a generative AI model (e.g., the GPT series) and selects quotations and guidelines based on the analysis results. The input is the analyzed contextual information, and the output is the generated quotations and guidelines. Specifically, the AI ​​model retrieves the most suitable materials from the database based on the analysis results and generates appropriate wording.

[0088] Step 6:

[0089] The server sends the selected quotes and guidelines to the terminal. Here, the input is the quotes and guidelines, and the output is the transmission of data for display on the user interface. Specifically, the server incorporates the generated text into a packet and delivers it to the terminal via a secure route.

[0090] Step 7:

[0091] The device displays received quotations and guidelines on its user interface. The input consists of quotations and guidelines sent from the server, and the output is a visually verifiable screen display. Specifically, the device uses a UI library to display a list of quotations on the screen as a pop-up or a dedicated app.

[0092] Step 8:

[0093] The user reviews the presented quotes and guidelines and makes selections as needed. The input is the displayed options, and the output is the user's selection action. Specifically, the user selects the optimal option through touch or click operations and incorporates it into their own speech.

[0094] (Application Example 1)

[0095] 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."

[0096] In many modern retail settings, customer service staff are expected to provide effective and accurate suggestions to customers. However, human memory and knowledge have limitations, making it difficult to provide optimal information in every situation. Furthermore, accurately understanding a customer's purchase intent within a limited time and responding quickly is also a challenge.

[0097] 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.

[0098] In this invention, the server includes means for converting voice input into text data using natural language processing technology, means for analyzing the speaker's intent from the text data and selecting appropriate quotations or guiding words, and means for generating appropriate product information or promotional text based on the voice input using generative AI technology. This enables effective and rapid information provision tailored to the situation.

[0099] "Natural language processing technology" refers to technologies that understand meaning from speech and text data and extract or generate appropriate information.

[0100] "Voice input" refers to audio data acquired through a microphone or other audio capture device.

[0101] "Text data" refers to character data converted from speech input, in a format that can be processed and analyzed by a computer.

[0102] "Speaker's intent" refers to the purpose or meaning that the speaker is trying to convey in a conversation or statement.

[0103] A "quote or instruction" is a useful sentence or instruction used in conversation to complement or emphasize something.

[0104] "Information presentation means" refers to devices or systems that display and provide selected information to users visually or audibly.

[0105] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate new information and content.

[0106] "Product information" refers to information that includes detailed descriptions of the product's features, specifications, and benefits.

[0107] "Advertising copy" refers to text created for advertising or promotional purposes to make a product or service appear appealing.

[0108] A "personal display device" refers to an information display device that is used individually by a user, such as smart glasses or mobile devices.

[0109] The system realizing this invention primarily operates through the cooperation of three entities: a server, a terminal, and a user. Specifically, the server utilizes natural language processing and generative AI technologies to analyze voice provided through the terminal and generate and present appropriate information. The terminal receives voice input and provides an interface for processing in cooperation with the server. The user uses this terminal to facilitate communication in daily work and life.

[0110] Specifically, when the server receives voice input, it first converts it into text data using natural language processing techniques. Specific software used for this purpose includes the Google Cloud Speech-to-Text API. The converted text data is then analyzed using a generative AI model to understand the user's intent. This process utilizes generative AI models such as Hugging Face's GPT-2 model.

[0111] The server then generates relevant product information and promotional text based on the analysis results. The generation AI technology used here suggests appropriate content in response to prompts entered by the user. For example, a possible prompt might be, "If the customer is looking for a new trench coat, generate a suggestion based on the product's features."

[0112] The generated information is presented to the user via a personal display device. For example, smart glasses or mobile devices can be used in this way, and the selected information is displayed in real time on their screens, allowing users to immediately utilize it during interactions. This entire process enables persuasive communication in customer interactions.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The terminal captures the user's voice input in real time through its built-in microphone. This voice input data is then acquired as a digital signal and prepared for transmission to the server.

[0116] Step 2:

[0117] The server converts the received voice input data into text data using natural language processing techniques. Here, data processing using a speech recognition API is performed, converting the voice signal into a corresponding string. The output of this process is text data containing what the user said.

[0118] Step 3:

[0119] The server uses a generative AI model to analyze the user's intent from the converted text data. Based on the text data as input, a natural language understanding algorithm performs calculations to extract the context and topic of the conversation. The output of this step is a prompt sentence or keywords based on the analyzed intent.

[0120] Step 4:

[0121] The server uses generative AI technology to generate relevant product information or promotional text in response to the prompt. Here, the AI ​​model generates text using the prompt obtained through intent analysis as input. The output is text with content appropriate for presenting to the user.

[0122] Step 5:

[0123] The server sends the generated product information or promotional text to the terminal. This output data is then formatted for visualization on the terminal.

[0124] Step 6:

[0125] The terminal displays generated information received from the server in real time on a personal display device (such as smart glasses or a mobile device display) via a user interface. This allows the user to immediately support customer interactions by utilizing the displayed information.

[0126] 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.

[0127] This invention is a system for achieving more appropriate and persuasive communication by taking emotions into consideration during interactions with users. Specifically, it implements a program that utilizes speech recognition technology, natural language processing technology, and an emotion recognition engine, and its embodiments are shown below.

[0128] First, when a user starts a conversation, the device captures the audio in real time and converts it into text data using speech recognition technology. This text data is then sent to a server for analysis.

[0129] The server analyzes the received text data using natural language processing techniques to identify the context and the speaker's intent. During this process, an emotion recognition engine analyzes the linguistic features contained in the text data to recognize the user's current emotional state. This emotion analysis is used to deepen the understanding of the text's context and to better align the selected quotes or guidelines with the user's emotions.

[0130] Next, the server uses a generative AI model based on the analysis results and emotional state to select appropriate quotes and guidelines from the database. Since the recognized emotions are heavily reflected in the selection process, it is possible to provide the user with the most appropriate content for the situation.

[0131] The server sends selected quotes and guidelines to the terminal, which then displays them on the user interface. From the displayed options, the user selects the one that best suits their situation and feelings, and uses that selection to convey a message to the other person.

[0132] As a concrete example, consider a meeting where emotions are fluctuating. When a user is feeling stressed, the emotion engine recognizes that emotion from the audio captured by the device and presents a quote such as, "He who remains calm is the strongest" (a hypothetical quote). The user can then use this quote to say, "Remaining calm is the key to success," thereby regaining their composure and ensuring the meeting proceeds smoothly.

[0133] This system can improve the quality of conversations and support effective communication that is attentive to the user's emotions.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] When a user starts a conversation, the device captures the user's voice in real time through the microphone.

[0137] Step 2:

[0138] The device converts the acquired audio data into text data using speech recognition technology. This converted text is then formatted for later analysis.

[0139] Step 3:

[0140] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing technology to identify the context.

[0141] Step 4:

[0142] The server uses an emotion recognition engine to analyze the emotions contained in the text data. This analysis identifies the emotions the user is currently experiencing.

[0143] Step 5:

[0144] The server uses a generated AI model to select the most appropriate quotes and guidelines from the database based on the analyzed context and identified sentiment.

[0145] Step 6:

[0146] The server sends selected quotations and guideline candidates to the terminal.

[0147] Step 7:

[0148] The terminal displays the received candidates in a list format on the user interface, allowing the user to select one.

[0149] Step 8:

[0150] The user selects the most appropriate option from the presented choices and conveys those words to their conversation partner. Through this selection, the user can communicate in a way that resonates with their emotions.

[0151] (Example 2)

[0152] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0153] Existing communication support systems simply interpret the speaker's statements as text, making it difficult to suggest appropriate responses or guidelines that take into account the emotions contained within. Therefore, there is a need to provide support that is appropriate to the emotional state and to improve the quality of communication.

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

[0155] In this invention, the server includes means for acquiring voice input and converting the voice data into text data, means for analyzing the context and speaker's intent using natural language processing technology, and means for identifying the speaker's emotional state using emotion recognition technology. This makes it possible to select and provide appropriate quotes and guidelines to the user based on the speaker's utterances and emotions.

[0156] "Voice input" refers to the process of acquiring information spoken by a user as a digital signal.

[0157] "Text data" refers to character-based information converted using speech recognition technology.

[0158] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0159] "Context" refers to information that indicates the situation in which linguistic information is used.

[0160] "Speaker's intent" refers to the true meaning or purpose that the speaker is trying to convey.

[0161] "Emotion recognition technology" is a technology that identifies a user's emotional state based on text and audio information.

[0162] A "generative AI model" is an artificial intelligence model that automatically generates new information and content based on large amounts of data.

[0163] A "quote or guideline" refers to a sentence that offers advice or guidance relevant to the speaker's situation.

[0164] A "database" is a system for efficiently storing and managing structured information.

[0165] A "user interface" refers to the display screen and operating methods that a user uses to interact with a system.

[0166] This system effectively supports user interaction by utilizing speech recognition technology, natural language processing technology, and emotion recognition technology. First, when the user speaks aloud into the device, the device captures the audio. Using speech recognition software (for example, a general speech recognition library), this audio data is converted into text data.

[0167] The device sends the converted text data to the server via the internet. The server analyzes the text data using natural language processing techniques (e.g., general natural language processing libraries) to identify the context of the statement and the speaker's intent. Furthermore, an emotion recognition engine is integrated to determine the user's emotional state from the text.

[0168] Based on these results, the server uses a generative AI model to select appropriate quotes or guidelines from the database. During this process, the recognized emotions are reflected in the selection, resulting in more relevant content. The selected content is then transmitted back to the terminal via the internet and displayed in the user interface.

[0169] As a concrete example, consider a situation where a user expresses anxiety about a project. In this case, the device captures the user's words, and the server identifies the emotion "anxiety." The generative AI model selects a guideline from the database, such as "When you feel anxious, it's important to take things one step at a time," and displays it on the device.

[0170] An example of a prompt might be, "Suggest some quotes to alleviate concerns about the project." This prompt allows the system to provide effective advice tailored to the user's needs.

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

[0172] Step 1:

[0173] The user speaks using their voice.

[0174] Input: User's spoken words.

[0175] Operation: The device captures the user's voice in real time using the microphone.

[0176] Output: Saved as audio data.

[0177] Step 2:

[0178] The device converts the audio data into text data.

[0179] Input: Acquired audio data.

[0180] Data processing: Use speech recognition software to convert speech data into text data.

[0181] Output: Saved as text data.

[0182] Step 3:

[0183] The terminal sends text data to the server.

[0184] Input: Converted text data.

[0185] Operation: Sends text data to a server via the internet.

[0186] Output: The server receives text data.

[0187] Step 4:

[0188] The server parses the text data.

[0189] Input: Text data sent to the server.

[0190] Data processing: Use NLP techniques to analyze context and speaker intent.

[0191] Output: The analysis results generate contextual and intent data.

[0192] Step 5:

[0193] The server performs emotion recognition.

[0194] Input: Parsed text data.

[0195] Data processing: Use emotion recognition technology to identify the speaker's emotional state.

[0196] Output: Saved as emotional state data.

[0197] Step 6:

[0198] The server selects an appropriate quote or guideline.

[0199] Input: Analysis results and emotional state data.

[0200] Data processing: Using a generative AI model, select quotes and guidelines from a database that are appropriate for the sentiment.

[0201] Output: Selected quotations or guidelines.

[0202] Step 7:

[0203] The server sends the selection results to the terminal.

[0204] Input: Selected quotes or guidelines.

[0205] Operation: Sends the selection results to the terminal via the internet.

[0206] Output: The terminal receives a quote or guidance.

[0207] Step 8:

[0208] The device displays a quote or guideline in the user interface.

[0209] Input: A quote or guideline received from the server.

[0210] Function: Display information on the user interface so that the user can verify it.

[0211] Output: The displayed content is reviewed by the user.

[0212] Step 9:

[0213] The user selects a displayed quote or guideline.

[0214] Input: Multiple options displayed in the user interface.

[0215] Data processing: The user selects the most appropriate quote or guideline.

[0216] Output: An action based on the selected quote or guideline is expected.

[0217] (Application Example 2)

[0218] 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".

[0219] In customer service and interpersonal communication settings, it is difficult to appropriately recognize the speaker's intentions and emotions and to provide appropriate responses and recommendations accordingly. In particular, conventional systems can only generate formulaic responses without considering emotional states, which contributes to decreased customer satisfaction. There is a need for systems that can solve this problem and support more emotionally sensitive and effective communication.

[0220] 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.

[0221] In this invention, the server includes a device that converts voice input into text data, a device that analyzes the speaker's intent and emotional state and selects appropriate quotations or guidelines, and a user information provision device that displays the information. This makes it possible to generate and present optimal responses and recommendations based on emotions.

[0222] "Natural language processing technology" refers to technologies for interpreting, analyzing, and generating human language from speech or text data.

[0223] A "device that converts voice input to text data" is a device that has a mechanism for converting speech to text in real time, and includes a speech recognition module.

[0224] A "device for analyzing speaker intent and emotional state" is a device that analyzes text data contextually and emotionally to identify the speaker's intended message and current emotions.

[0225] A "device for selecting quotations or guidelines" is a device equipped with a mechanism for selecting appropriate responses or advice based on analyzed intentions and emotions.

[0226] A "user-facing information provision device" is a user device that visually displays selected quotations and guidelines to users.

[0227] "Generative AI functionality" refers to AI technology that generates content and has the ability to provide responses and suggested phrases based on specific conditions.

[0228] This invention is a system designed to enable effective communication between staff and customers, particularly in physical stores. The core of the system consists of speech recognition technology, natural language processing technology, an emotion recognition engine, and generative AI technology.

[0229] First, the device acquires the customer's speech as voice input in real time. The acquired voice data is converted into text data using a speech recognition module. This process utilizes speech recognition software such as the Google Cloud Speech-to-Text API.

[0230] The converted text data is sent to a server, where natural language processing techniques are used to identify the speaker's intent and context. Furthermore, an emotion recognition engine, such as IBM Watson® Tone Analyzer, is used to analyze the speaker's emotional state.

[0231] Based on the analysis results, the server uses a generative AI model to select appropriate quotes and guidelines from the database. In this process, models such as the GPT model provided by OpenAI (registered trademark) are used to generate appropriate responses that match the user's emotions.

[0232] Selected quotes and guidelines are provided to the user's device. Smartphones and tablets, acting as user information providers, assist staff operations. For example, if a customer expresses anxiety, the system might suggest "offering reassuring words."

[0233] An example of a prompt for this generative AI model is, "Create several reassuring messages for customer service when customers are feeling stressed. The tone should be polite and professional." Using this prompt, the AI ​​generates appropriate customer responses tailored to the situation.

[0234] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0235] Step 1:

[0236] The device acquires customer voices in real time via a microphone. The input is raw audio data, and the output is voice data sent to a speech recognition module. This data is then sent to a speech recognition engine for analyzing the voice.

[0237] Step 2:

[0238] The server uses a speech recognition engine to convert the input speech data into text data. The software used is the Google Cloud Speech-to-Text API. In this step, the speech signal is output as text.

[0239] Step 3:

[0240] The server analyzes text data using natural language processing techniques to identify the speaker's intent and context. The input is text data converted from speech, and the output is the analyzed contextual information and intent. Libraries such as SpaCy are used.

[0241] Step 4:

[0242] The server uses an emotion recognition engine to analyze the speaker's emotional state from text data. The analysis is performed using IBM Watson Tone Analyzer, and information about the emotion is extracted. The input is the text data from the previous step, and the output is the emotional state.

[0243] Step 5:

[0244] The server uses a generative AI model to select the most appropriate quotes and guidelines based on the speaker's intent and emotions. OpenAI's GPT model is used, with contextual information and emotional states as input, and the output being the generated quotes and guidelines.

[0245] Step 6:

[0246] The terminal displays quoted texts and guidelines received from the server to staff via a user-facing information device. This allows staff to obtain information and advice that can be used in interactions with customers. The input is quoted texts and guidelines from the server, and the output is the content displayed on the staff's display.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] [Second Embodiment]

[0251] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0252] 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.

[0253] 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).

[0254] 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.

[0255] 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.

[0256] 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).

[0257] 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.

[0258] 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.

[0259] 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.

[0260] 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.

[0261] 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.

[0262] 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".

[0263] This invention is a system that enables speakers to communicate more persuasively during conversations. Specifically, it implements a program that utilizes speech recognition technology and a generative AI model, and an embodiment thereof is shown below.

[0264] First, when a user begins a conversation, the device acquires the audio in real time through the microphone. This audio data is then converted into text data using speech recognition technology. The converted text data is then sent from the device to the server.

[0265] The server analyzes the received text data using natural language processing techniques to understand the context of the conversation and the speaker's intent. A generative AI model then uses this analysis to select appropriate quotes and guidelines from a database. Specifically, relevant quotes and helpful advice are chosen as candidates, thereby improving the quality of the conversation.

[0266] Next, the server sends the selected candidates to the terminal, which displays them on the user interface. The user can review the presented options and select the appropriate one. This selection allows the user to give weight to their words and effectively convey their message to the person they are talking to.

[0267] As a concrete example, consider a new proposal in a business meeting. When a user proposes a new idea, the device captures the statement, and the server displays a quote such as "New ideas are always the foundation of evolution" (a hypothetical famous quote). The user can then use this to enhance the persuasiveness of their proposal by stating, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way."

[0268] Thus, the system of the present invention helps to enrich the range of words and improve the quality of the message being conveyed in a variety of dialogue situations.

[0269] The following describes the processing flow.

[0270] Step 1:

[0271] When a user begins a conversation, the device captures their speech in real time via the microphone.

[0272] Step 2:

[0273] The device converts the acquired voice data into text data using its built-in speech recognition technology.

[0274] Step 3:

[0275] The terminal transmits the text data generated by it to the server for analysis.

[0276] Step 4:

[0277] The server analyzes the text data received by it using natural language processing technology to identify the context of the conversation and the intention of the speaker.

[0278] Step 5:

[0279] The server uses the generated AI model to select candidates including appropriate quotations and guidelines from the database based on the analysis results.

[0280] Step 6:

[0281] The server transmits the list of quotations and guidelines selected by it to the terminal.

[0282] Step 7:

[0283] The terminal displays the selection result received by it on the user interface so that the user can select the most appropriate one.

[0284] Step 8:

[0285] The user selects appropriate words from the presented options and conveys the selected content to the conversation partner.

[0286] (Example 1)

[0287] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] Conventional speech recognition systems only convert speech to text, and lack sufficient support to improve the quality of subsequent conversations. In particular, they lacked the ability to provide appropriate quotations and guidelines that align with the speaker's intent in real time, making it difficult to effectively assist the flow of dialogue. This invention aims to solve these problems and enable speakers to communicate more persuasively during conversations.

[0289] 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.

[0290] In this invention, the server includes means for acquiring speech and converting the speech input into text data; means for transmitting the converted text data to a data storage device via a communication network; and means for the storage device to analyze the text data using natural language processing technology and select appropriate quotations or guiding information from external information sources. This enables the speaker to acquire quotations and guiding information that match their intentions in real time, thereby improving the quality of the conversation.

[0291] "Acquiring speech" refers to the act of capturing a speaker's utterance as an acoustic signal into a device and using that signal for subsequent processing.

[0292] "Converting voice input to text data" refers to the act of using speech recognition technology to convert collected acoustic signals into corresponding string data.

[0293] A "communication network" refers to a means of connection for sending and receiving data, encompassing a wide range of digital communication methods, including the internet and dedicated lines.

[0294] A "data storage device" refers to a computing device or media that temporarily or permanently stores information and allows access to and use that information as needed.

[0295] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and analyze human language, and specifically refers to the technology used for classifying and semantic analysis of language data.

[0296] "External information sources" refer to a collection of information or information providers that exist outside the system and can provide the necessary data.

[0297] A “quote or instruction” is a statement or instruction that is intended to advise or refer to the speaker in a particular context, and is usually selected from a reliable source.

[0298] An "ergonomically designed user interface" refers to an operating surface designed to allow users to operate it intuitively and effectively, and includes elements that are optimized from a visual and operational standpoint.

[0299] This system enables speakers to communicate more persuasively during conversations and is implemented using speech recognition technology, generative AI models, and a sophisticated user interface.

[0300] When a user begins a conversation, the device's built-in microphone captures the audio. This audio is then converted into text data in real time using speech recognition technology. This process utilizes speech-to-text solutions such as the Google Speech-to-Text API. The text data generated by speech recognition is then sent to a server via the communication network.

[0301] The server analyzes the received text data using natural language processing (NLTK) techniques. For analysis, natural language processing libraries such as spaCy and NLTK are used to extract the speaker's intent and conversational context from the text. Then, a generative AI model (for example, the GPT series) selects appropriate quotations and guidelines from external sources based on the analysis results. This selects the information necessary to improve the quality of the conversation.

[0302] The selected quotations and guidelines are sent from the server to the terminal and presented to the user through a human - engineered user interface. This interface is excellent in visibility and operability, enabling the user to easily select quotations and guidelines and incorporate them into the conversation.

[0303] As a specific example, when a user presents an idea for a new product at a business meeting, the system can recognize the speech and present quotations such as "New ideas are always the basis for evolution." The user can utilize this information and enhance the persuasiveness of the proposal by stating, for example, "Although it is said that new ideas are always the basis for evolution, our proposal should contribute in the same way." In such a scenario, a prompt sentence such as "Please teach me effective quotations when proposing a new product at a business meeting." is useful.

[0304] This invention provides effective support for a user to select words in various dialogue scenarios and improve the quality of messages.

[0305] The flow of the specific process in Example 1 will be described using FIG. 11.

[0306] Step 1:

[0307] When the user starts a conversation, the microphone of the terminal acquires the voice. The voice data as an input reaches the microphone as sound waves. Specifically, the microphone converts the change in ambient sound pressure into an electrical signal, and then converts it from analog to digital and stores it as digital voice data.

[0308] Step 2:

[0309] The terminal passes the acquired voice data to the voice recognition module and converts its content into text data. The input is digital voice data, and the output is text data in which the voice is expressed as characters. For example, Google Speech - to - Text API is used as the voice recognition technology, and the acoustic model and the language model are combined to perform data conversion.

[0310] Step 3:

[0311] The terminal sends the converted text data to the server. Here, the input is text data, and the output is secure data transmission using a communication protocol (e.g., HTTPS). Specifically, the terminal breaks down the text data into packets and sends them to the server over the network.

[0312] Step 4:

[0313] The server analyzes the received text data using a natural language processing library (e.g., spaCy). The input is text data, and the output is the analyzed conversational context and keywords. Specifically, the server analyzes the text data based on its grammatical structure and extracts the speaker's intent and context.

[0314] Step 5:

[0315] The server runs a generative AI model (e.g., the GPT series) and selects quotations and guidelines based on the analysis results. The input is the analyzed contextual information, and the output is the generated quotations and guidelines. Specifically, the AI ​​model retrieves the most suitable materials from the database based on the analysis results and generates appropriate wording.

[0316] Step 6:

[0317] The server sends the selected quotes and guidelines to the terminal. Here, the input is the quotes and guidelines, and the output is the transmission of data for display on the user interface. Specifically, the server incorporates the generated text into a packet and delivers it to the terminal via a secure route.

[0318] Step 7:

[0319] The device displays received quotations and guidelines on its user interface. The input consists of quotations and guidelines sent from the server, and the output is a visually verifiable screen display. Specifically, the device uses a UI library to display a list of quotations on the screen as a pop-up or a dedicated app.

[0320] Step 8:

[0321] The user reviews the presented quotes and guidelines and makes selections as needed. The input is the displayed options, and the output is the user's selection action. Specifically, the user selects the optimal option through touch or click operations and incorporates it into their own speech.

[0322] (Application Example 1)

[0323] 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."

[0324] In many modern retail settings, customer service staff are expected to provide effective and accurate suggestions to customers. However, human memory and knowledge have limitations, making it difficult to provide optimal information in every situation. Furthermore, accurately understanding a customer's purchase intent within a limited time and responding quickly is also a challenge.

[0325] 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.

[0326] In this invention, the server includes means for converting voice input into text data using natural language processing technology, means for analyzing the speaker's intent from the text data and selecting appropriate quotations or guiding words, and means for generating appropriate product information or promotional text based on the voice input using generative AI technology. This enables effective and rapid information provision tailored to the situation.

[0327] "Natural language processing technology" refers to technologies that understand meaning from speech and text data and extract or generate appropriate information.

[0328] "Voice input" refers to audio data acquired through a microphone or other audio capture device.

[0329] "Text data" refers to character data converted from speech input, in a format that can be processed and analyzed by a computer.

[0330] "Speaker's intent" refers to the purpose or meaning that the speaker is trying to convey in a conversation or statement.

[0331] A "quote or instruction" is a useful sentence or instruction used in conversation to complement or emphasize something.

[0332] "Information presentation means" refers to devices or systems that display and provide selected information to users visually or audibly.

[0333] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate new information and content.

[0334] "Product information" refers to information that includes detailed descriptions of the product's features, specifications, and benefits.

[0335] "Advertising copy" refers to text created for advertising or promotional purposes to make a product or service appear appealing.

[0336] A "personal display device" refers to an information display device that is used individually by a user, such as smart glasses or mobile devices.

[0337] The system realizing this invention primarily operates through the cooperation of three entities: a server, a terminal, and a user. Specifically, the server utilizes natural language processing and generative AI technologies to analyze voice provided through the terminal and generate and present appropriate information. The terminal receives voice input and provides an interface for processing in cooperation with the server. The user uses this terminal to facilitate communication in daily work and life.

[0338] Specifically, when the server receives voice input, it first converts it into text data using natural language processing techniques. Specific software used for this purpose includes the Google Cloud Speech-to-Text API. The converted text data is then analyzed using a generative AI model to understand the user's intent. This process utilizes generative AI models such as Hugging Face's GPT-2 model.

[0339] The server then generates relevant product information and promotional text based on the analysis results. The generation AI technology used here suggests appropriate content in response to prompts entered by the user. For example, a possible prompt might be, "If the customer is looking for a new trench coat, generate a suggestion based on the product's features."

[0340] The generated information is presented to the user via a personal display device. For example, smart glasses or mobile devices can be used in this way, and the selected information is displayed in real time on their screens, allowing users to immediately utilize it during interactions. This entire process enables persuasive communication in customer interactions.

[0341] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0342] Step 1:

[0343] The terminal captures the user's voice input in real time through its built-in microphone. This voice input data is then acquired as a digital signal and prepared for transmission to the server.

[0344] Step 2:

[0345] The server converts the received voice input data into text data using natural language processing techniques. Here, data processing using a speech recognition API is performed, converting the voice signal into a corresponding string. The output of this process is text data containing what the user said.

[0346] Step 3:

[0347] The server uses a generative AI model to analyze the user's intent from the converted text data. Based on the text data as input, a natural language understanding algorithm performs calculations to extract the context and topic of the conversation. The output of this step is a prompt sentence or keywords based on the analyzed intent.

[0348] Step 4:

[0349] The server uses generative AI technology to generate relevant product information or promotional text in response to the prompt. Here, the AI ​​model generates text using the prompt obtained through intent analysis as input. The output is text with content appropriate for presenting to the user.

[0350] Step 5:

[0351] The server sends the generated product information or promotional text to the terminal. This output data is then formatted for visualization on the terminal.

[0352] Step 6:

[0353] The terminal displays generated information received from the server in real time on a personal display device (such as smart glasses or a mobile device display) via a user interface. This allows the user to immediately support customer interactions by utilizing the displayed information.

[0354] 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.

[0355] This invention is a system for achieving more appropriate and persuasive communication by taking emotions into consideration during interactions with users. Specifically, it implements a program that utilizes speech recognition technology, natural language processing technology, and an emotion recognition engine, and its embodiments are shown below.

[0356] First, when a user starts a conversation, the device captures the audio in real time and converts it into text data using speech recognition technology. This text data is then sent to a server for analysis.

[0357] The server analyzes the received text data using natural language processing techniques to identify the context and the speaker's intent. During this process, an emotion recognition engine analyzes the linguistic features contained in the text data to recognize the user's current emotional state. This emotion analysis is used to deepen the understanding of the text's context and to better align the selected quotes or guidelines with the user's emotions.

[0358] Next, the server uses a generative AI model based on the analysis results and emotional state to select appropriate quotes and guidelines from the database. Since the recognized emotions are heavily reflected in the selection process, it is possible to provide the user with the most appropriate content for the situation.

[0359] The server sends selected quotes and guidelines to the terminal, which then displays them on the user interface. From the displayed options, the user selects the one that best suits their situation and feelings, and uses that selection to convey a message to the other person.

[0360] As a concrete example, consider a meeting where emotions are fluctuating. When a user is feeling stressed, the emotion engine recognizes that emotion from the audio captured by the device and presents a quote such as, "He who remains calm is the strongest" (a hypothetical quote). The user can then use this quote to say, "Remaining calm is the key to success," thereby regaining their composure and ensuring the meeting proceeds smoothly.

[0361] This system can improve the quality of conversations and support effective communication that is attentive to the user's emotions.

[0362] The following describes the processing flow.

[0363] Step 1:

[0364] When a user starts a conversation, the device captures the user's voice in real time through the microphone.

[0365] Step 2:

[0366] The device converts the acquired audio data into text data using speech recognition technology. This converted text is then formatted for later analysis.

[0367] Step 3:

[0368] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing technology to identify the context.

[0369] Step 4:

[0370] The server uses an emotion recognition engine to analyze the emotions contained in the text data. This analysis identifies the emotions the user is currently experiencing.

[0371] Step 5:

[0372] The server uses a generated AI model to select the most appropriate quotes and guidelines from the database based on the analyzed context and identified sentiment.

[0373] Step 6:

[0374] The server sends selected quotations and guideline candidates to the terminal.

[0375] Step 7:

[0376] The terminal displays the received candidates in a list format on the user interface, allowing the user to select one.

[0377] Step 8:

[0378] The user selects the most appropriate option from the presented choices and conveys those words to their conversation partner. Through this selection, the user can communicate in a way that resonates with their emotions.

[0379] (Example 2)

[0380] 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".

[0381] Existing communication support systems simply interpret the speaker's statements as text, making it difficult to suggest appropriate responses or guidelines that take into account the emotions contained within. Therefore, there is a need to provide support that is appropriate to the emotional state and to improve the quality of communication.

[0382] 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.

[0383] In this invention, the server includes means for acquiring voice input and converting the voice data into text data, means for analyzing the context and speaker's intent using natural language processing technology, and means for identifying the speaker's emotional state using emotion recognition technology. This makes it possible to select and provide appropriate quotes and guidelines to the user based on the speaker's utterances and emotions.

[0384] "Voice input" refers to the process of acquiring information spoken by a user as a digital signal.

[0385] "Text data" refers to character-based information converted using speech recognition technology.

[0386] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0387] "Context" refers to information that indicates the situation in which linguistic information is used.

[0388] "Speaker's intent" refers to the true meaning or purpose that the speaker is trying to convey.

[0389] "Emotion recognition technology" is a technology that identifies a user's emotional state based on text and audio information.

[0390] A "generative AI model" is an artificial intelligence model that automatically generates new information and content based on large amounts of data.

[0391] A "quote or guideline" refers to a sentence that offers advice or guidance relevant to the speaker's situation.

[0392] A "database" is a system for efficiently storing and managing structured information.

[0393] A "user interface" refers to the display screen and operating methods that a user uses to interact with a system.

[0394] This system effectively supports user interaction by utilizing speech recognition technology, natural language processing technology, and emotion recognition technology. First, when the user speaks aloud into the device, the device captures the audio. Using speech recognition software (for example, a general speech recognition library), this audio data is converted into text data.

[0395] The device sends the converted text data to the server via the internet. The server analyzes the text data using natural language processing techniques (e.g., general natural language processing libraries) to identify the context of the statement and the speaker's intent. Furthermore, an emotion recognition engine is integrated to determine the user's emotional state from the text.

[0396] Based on these results, the server uses a generative AI model to select appropriate quotes or guidelines from the database. During this process, the recognized emotions are reflected in the selection, resulting in more relevant content. The selected content is then transmitted back to the terminal via the internet and displayed in the user interface.

[0397] As a concrete example, consider a situation where a user expresses anxiety about a project. In this case, the device captures the user's words, and the server identifies the emotion "anxiety." The generative AI model selects a guideline from the database, such as "When you feel anxious, it's important to take things one step at a time," and displays it on the device.

[0398] An example of a prompt might be, "Suggest some quotes to alleviate concerns about the project." This prompt allows the system to provide effective advice tailored to the user's needs.

[0399] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0400] Step 1:

[0401] The user speaks using their voice.

[0402] Input: User's spoken words.

[0403] Operation: The device captures the user's voice in real time using the microphone.

[0404] Output: Saved as audio data.

[0405] Step 2:

[0406] The device converts the audio data into text data.

[0407] Input: Acquired audio data.

[0408] Data processing: Use speech recognition software to convert speech data into text data.

[0409] Output: Saved as text data.

[0410] Step 3:

[0411] The terminal sends text data to the server.

[0412] Input: Converted text data.

[0413] Operation: Sends text data to a server via the internet.

[0414] Output: The server receives text data.

[0415] Step 4:

[0416] The server parses the text data.

[0417] Input: Text data sent to the server.

[0418] Data processing: Use NLP techniques to analyze context and speaker intent.

[0419] Output: The analysis results generate contextual and intent data.

[0420] Step 5:

[0421] The server performs emotion recognition.

[0422] Input: Parsed text data.

[0423] Data processing: Use emotion recognition technology to identify the speaker's emotional state.

[0424] Output: Saved as emotional state data.

[0425] Step 6:

[0426] The server selects an appropriate quote or guideline.

[0427] Input: Analysis results and emotional state data.

[0428] Data processing: Using a generative AI model, select quotes and guidelines from a database that are appropriate for the sentiment.

[0429] Output: Selected quotations or guidelines.

[0430] Step 7:

[0431] The server sends the selection results to the terminal.

[0432] Input: Selected quotes or guidelines.

[0433] Operation: Sends the selection results to the terminal via the internet.

[0434] Output: The terminal receives a quote or guidance.

[0435] Step 8:

[0436] The device displays a quote or guideline in the user interface.

[0437] Input: A quote or guideline received from the server.

[0438] Function: Display information on the user interface so that the user can verify it.

[0439] Output: The displayed content is reviewed by the user.

[0440] Step 9:

[0441] The user selects a displayed quote or guideline.

[0442] Input: Multiple options displayed in the user interface.

[0443] Data processing: The user selects the most appropriate quote or guideline.

[0444] Output: An action based on the selected quote or guideline is expected.

[0445] (Application Example 2)

[0446] 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."

[0447] In customer service and interpersonal communication settings, it is difficult to appropriately recognize the speaker's intentions and emotions and to provide appropriate responses and recommendations accordingly. In particular, conventional systems can only generate formulaic responses without considering emotional states, which contributes to decreased customer satisfaction. There is a need for systems that can solve this problem and support more emotionally sensitive and effective communication.

[0448] 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.

[0449] In this invention, the server includes a device that converts voice input into text data, a device that analyzes the speaker's intent and emotional state and selects appropriate quotations or guidelines, and a user information provision device that displays the information. This makes it possible to generate and present optimal responses and recommendations based on emotions.

[0450] "Natural language processing technology" refers to technologies for interpreting, analyzing, and generating human language from speech or text data.

[0451] A "device that converts voice input to text data" is a device that has a mechanism for converting speech to text in real time, and includes a speech recognition module.

[0452] A "device for analyzing speaker intent and emotional state" is a device that analyzes text data contextually and emotionally to identify the speaker's intended message and current emotions.

[0453] A "device for selecting quotations or guidelines" is a device equipped with a mechanism for selecting appropriate responses or advice based on analyzed intentions and emotions.

[0454] A "user-facing information provision device" is a user device that visually displays selected quotations and guidelines to users.

[0455] "Generative AI functionality" refers to AI technology that generates content and has the ability to provide responses and suggested phrases based on specific conditions.

[0456] This invention is a system designed to enable effective communication between staff and customers, particularly in physical stores. The core of the system consists of speech recognition technology, natural language processing technology, an emotion recognition engine, and generative AI technology.

[0457] First, the device acquires the customer's speech as voice input in real time. The acquired voice data is converted into text data using a speech recognition module. This process utilizes speech recognition software such as the Google Cloud Speech-to-Text API.

[0458] The converted text data is sent to a server, where natural language processing techniques are used to identify the speaker's intent and context. Furthermore, an emotion recognition engine, such as IBM Watson Tone Analyzer, is used to analyze the speaker's emotional state.

[0459] Based on the analysis results, the server uses a generative AI model to select appropriate quotes and guidelines from the database. In this process, models such as the GPT model provided by OpenAI are used to generate appropriate responses that match the user's emotions.

[0460] Selected quotes and guidelines are provided to the user's device. Smartphones and tablets, acting as user information providers, assist staff operations. For example, if a customer expresses anxiety, the system might suggest "offering reassuring words."

[0461] An example of a prompt for this generative AI model is, "Create several reassuring messages for customer service when customers are feeling stressed. The tone should be polite and professional." Using this prompt, the AI ​​generates appropriate customer responses tailored to the situation.

[0462] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0463] Step 1:

[0464] The device acquires customer voices in real time via a microphone. The input is raw audio data, and the output is voice data sent to a speech recognition module. This data is then sent to a speech recognition engine for analyzing the voice.

[0465] Step 2:

[0466] The server uses a speech recognition engine to convert the input speech data into text data. The software used is the Google Cloud Speech-to-Text API. In this step, the speech signal is output as text.

[0467] Step 3:

[0468] The server analyzes text data using natural language processing techniques to identify the speaker's intent and context. The input is text data converted from speech, and the output is the analyzed contextual information and intent. Libraries such as SpaCy are used.

[0469] Step 4:

[0470] The server uses an emotion recognition engine to analyze the speaker's emotional state from text data. The analysis is performed using IBM Watson Tone Analyzer, and information about the emotion is extracted. The input is the text data from the previous step, and the output is the emotional state.

[0471] Step 5:

[0472] The server uses a generative AI model to select the most appropriate quotes and guidelines based on the speaker's intent and emotions. OpenAI's GPT model is used, with contextual information and emotional states as input, and the output being the generated quotes and guidelines.

[0473] Step 6:

[0474] The terminal displays quoted texts and guidelines received from the server to staff via a user-facing information device. This allows staff to obtain information and advice that can be used in interactions with customers. The input is quoted texts and guidelines from the server, and the output is the content displayed on the staff's display.

[0475] 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.

[0476] 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.

[0477] 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.

[0478] [Third Embodiment]

[0479] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0480] 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.

[0481] 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).

[0482] 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.

[0483] 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.

[0484] 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).

[0485] 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.

[0486] 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.

[0487] 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.

[0488] 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.

[0489] 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.

[0490] 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".

[0491] This invention is a system that enables speakers to communicate more persuasively during conversations. Specifically, it implements a program that utilizes speech recognition technology and a generative AI model, and an embodiment thereof is shown below.

[0492] First, when a user begins a conversation, the device acquires the audio in real time through the microphone. This audio data is then converted into text data using speech recognition technology. The converted text data is then sent from the device to the server.

[0493] The server analyzes the received text data using natural language processing techniques to understand the context of the conversation and the speaker's intent. A generative AI model then uses this analysis to select appropriate quotes and guidelines from a database. Specifically, relevant quotes and helpful advice are chosen as candidates, thereby improving the quality of the conversation.

[0494] Next, the server sends the selected candidates to the terminal, which displays them on the user interface. The user can review the presented options and select the appropriate one. This selection allows the user to give weight to their words and effectively convey their message to the person they are talking to.

[0495] As a concrete example, consider a new proposal in a business meeting. When a user proposes a new idea, the device captures the statement, and the server displays a quote such as "New ideas are always the foundation of evolution" (a hypothetical famous quote). The user can then use this to enhance the persuasiveness of their proposal by stating, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way."

[0496] Thus, the system of the present invention helps to enrich the range of words and improve the quality of the message being conveyed in a variety of dialogue situations.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] When a user begins a conversation, the device captures their speech in real time via the microphone.

[0500] Step 2:

[0501] The device converts the acquired voice data into text data using its built-in speech recognition technology.

[0502] Step 3:

[0503] The text data generated by the terminal is sent to the server for analysis.

[0504] Step 4:

[0505] The server analyzes the received text data using natural language processing techniques to identify the context of the conversation and the speaker's intent.

[0506] Step 5:

[0507] The server uses a generated AI model to select candidates from a database that include appropriate quotations and guidelines based on the analysis results.

[0508] Step 6:

[0509] The server sends a list of selected quotes and guidelines to the terminal.

[0510] Step 7:

[0511] The selection results received by the terminal are displayed on the user interface, allowing the user to select the most appropriate option.

[0512] Step 8:

[0513] The user selects the appropriate words from the presented options and conveys their selection to the conversation partner.

[0514] (Example 1)

[0515] 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."

[0516] Conventional speech recognition systems only convert speech to text, and lack sufficient support to improve the quality of subsequent conversations. In particular, they lacked the ability to provide appropriate quotations and guidelines that align with the speaker's intent in real time, making it difficult to effectively assist the flow of dialogue. This invention aims to solve these problems and enable speakers to communicate more persuasively during conversations.

[0517] 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.

[0518] In this invention, the server includes means for acquiring speech and converting the speech input into text data; means for transmitting the converted text data to a data storage device via a communication network; and means for the storage device to analyze the text data using natural language processing technology and select appropriate quotations or guiding information from external information sources. This enables the speaker to acquire quotations and guiding information that match their intentions in real time, thereby improving the quality of the conversation.

[0519] "Acquiring speech" refers to the act of capturing a speaker's utterance as an acoustic signal into a device and using that signal for subsequent processing.

[0520] "Converting voice input to text data" refers to the act of using speech recognition technology to convert collected acoustic signals into corresponding string data.

[0521] A "communication network" refers to a means of connection for sending and receiving data, encompassing a wide range of digital communication methods, including the internet and dedicated lines.

[0522] A "data storage device" refers to a computing device or media that temporarily or permanently stores information and allows access to and use that information as needed.

[0523] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and analyze human language, and specifically refers to the technology used for classifying and semantic analysis of language data.

[0524] "External information sources" refer to a collection of information or information providers that exist outside the system and can provide the necessary data.

[0525] A “quote or instruction” is a statement or instruction that is intended to advise or refer to the speaker in a particular context, and is usually selected from a reliable source.

[0526] An "ergonomically designed user interface" refers to an operating surface designed to allow users to operate it intuitively and effectively, and includes elements that are optimized from a visual and operational standpoint.

[0527] This system enables speakers to communicate more persuasively during conversations and is implemented using speech recognition technology, generative AI models, and a sophisticated user interface.

[0528] When a user begins a conversation, the device's built-in microphone captures the audio. This audio is then converted into text data in real time using speech recognition technology. This process utilizes speech-to-text solutions such as the Google Speech-to-Text API. The text data generated by speech recognition is then sent to a server via the communication network.

[0529] The server analyzes the received text data using natural language processing (NLTK) techniques. For analysis, natural language processing libraries such as spaCy and NLTK are used to extract the speaker's intent and conversational context from the text. Then, a generative AI model (for example, the GPT series) selects appropriate quotations and guidelines from external sources based on the analysis results. This selects the information necessary to improve the quality of the conversation.

[0530] Selected quotes and guidelines are transmitted from the server to the terminal and presented to the user through an ergonomically designed user interface. This interface offers excellent visibility and operability, allowing users to easily select quotes and guidelines and incorporate them into their conversations.

[0531] For example, when a user presents a new product idea in a business meeting, the system can recognize the statement and suggest a quote such as, "New ideas are always the foundation of evolution." The user can then use this information to increase the persuasiveness of their proposal by saying, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way." In such a situation, a prompt such as, "Please tell me some effective quotes to use when proposing a new product in a business meeting," would be useful.

[0532] This invention provides effective support for users to select words in various dialogue situations and improve the quality of their messages.

[0533] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0534] Step 1:

[0535] When a user starts a conversation, the device's microphone acquires the voice. The voice data, as input, arrives at the microphone as sound waves. Specifically, the microphone converts changes in ambient sound pressure into electrical signals, which are then converted from analog to digital and stored as digital audio data.

[0536] Step 2:

[0537] The device passes the acquired audio data to a speech recognition module, which then converts the content into text data. The input is digital audio data, and the output is text data in which the audio is represented as characters. For example, the Google Speech-to-Text API is used as the speech recognition technology, and data conversion is performed by combining an acoustic model and a language model.

[0538] Step 3:

[0539] The terminal sends the converted text data to the server. Here, the input is text data, and the output is secure data transmission using a communication protocol (e.g., HTTPS). Specifically, the terminal breaks down the text data into packets and sends them to the server over the network.

[0540] Step 4:

[0541] The server analyzes the received text data using a natural language processing library (e.g., spaCy). The input is text data, and the output is the analyzed conversational context and keywords. Specifically, the server analyzes the text data based on its grammatical structure and extracts the speaker's intent and context.

[0542] Step 5:

[0543] The server runs a generative AI model (e.g., the GPT series) and selects quotations and guidelines based on the analysis results. The input is the analyzed contextual information, and the output is the generated quotations and guidelines. Specifically, the AI ​​model retrieves the most suitable materials from the database based on the analysis results and generates appropriate wording.

[0544] Step 6:

[0545] The server sends the selected quotes and guidelines to the terminal. Here, the input is the quotes and guidelines, and the output is the transmission of data for display on the user interface. Specifically, the server incorporates the generated text into a packet and delivers it to the terminal via a secure route.

[0546] Step 7:

[0547] The device displays received quotations and guidelines on its user interface. The input consists of quotations and guidelines sent from the server, and the output is a visually verifiable screen display. Specifically, the device uses a UI library to display a list of quotations on the screen as a pop-up or a dedicated app.

[0548] Step 8:

[0549] The user reviews the presented quotes and guidelines and makes selections as needed. The input is the displayed options, and the output is the user's selection action. Specifically, the user selects the optimal option through touch or click operations and incorporates it into their own speech.

[0550] (Application Example 1)

[0551] 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."

[0552] In many modern retail settings, customer service staff are expected to provide effective and accurate suggestions to customers. However, human memory and knowledge have limitations, making it difficult to provide optimal information in every situation. Furthermore, accurately understanding a customer's purchase intent within a limited time and responding quickly is also a challenge.

[0553] 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.

[0554] In this invention, the server includes means for converting voice input into text data using natural language processing technology, means for analyzing the speaker's intent from the text data and selecting appropriate quotations or guiding words, and means for generating appropriate product information or promotional text based on the voice input using generative AI technology. This enables effective and rapid information provision tailored to the situation.

[0555] "Natural language processing technology" refers to technologies that understand meaning from speech and text data and extract or generate appropriate information.

[0556] "Voice input" refers to audio data acquired through a microphone or other audio capture device.

[0557] "Text data" refers to character data converted from speech input, in a format that can be processed and analyzed by a computer.

[0558] "Speaker's intent" refers to the purpose or meaning that the speaker is trying to convey in a conversation or statement.

[0559] A "quote or instruction" is a useful sentence or instruction used in conversation to complement or emphasize something.

[0560] "Information presentation means" refers to devices or systems that display and provide selected information to users visually or audibly.

[0561] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate new information and content.

[0562] "Product information" refers to information that includes detailed descriptions of the product's features, specifications, and benefits.

[0563] "Advertising copy" refers to text created for advertising or promotional purposes to make a product or service appear appealing.

[0564] A "personal display device" refers to an information display device that is used individually by a user, such as smart glasses or mobile devices.

[0565] The system realizing this invention primarily operates through the cooperation of three entities: a server, a terminal, and a user. Specifically, the server utilizes natural language processing and generative AI technologies to analyze voice provided through the terminal and generate and present appropriate information. The terminal receives voice input and provides an interface for processing in cooperation with the server. The user uses this terminal to facilitate communication in daily work and life.

[0566] Specifically, when the server receives voice input, it first converts it into text data using natural language processing techniques. Specific software used for this purpose includes the Google Cloud Speech-to-Text API. The converted text data is then analyzed using a generative AI model to understand the user's intent. This process utilizes generative AI models such as Hugging Face's GPT-2 model.

[0567] The server then generates relevant product information and promotional text based on the analysis results. The generation AI technology used here suggests appropriate content in response to prompts entered by the user. For example, a possible prompt might be, "If the customer is looking for a new trench coat, generate a suggestion based on the product's features."

[0568] The generated information is presented to the user via a personal display device. For example, smart glasses or mobile devices can be used in this way, and the selected information is displayed in real time on their screens, allowing users to immediately utilize it during interactions. This entire process enables persuasive communication in customer interactions.

[0569] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0570] Step 1:

[0571] The terminal captures the user's voice input in real time through its built-in microphone. This voice input data is then acquired as a digital signal and prepared for transmission to the server.

[0572] Step 2:

[0573] The server converts the received voice input data into text data using natural language processing techniques. Here, data processing using a speech recognition API is performed, converting the voice signal into a corresponding string. The output of this process is text data containing what the user said.

[0574] Step 3:

[0575] The server uses a generative AI model to analyze the user's intent from the converted text data. Based on the text data as input, a natural language understanding algorithm performs calculations to extract the context and topic of the conversation. The output of this step is a prompt sentence or keywords based on the analyzed intent.

[0576] Step 4:

[0577] The server uses generative AI technology to generate relevant product information or promotional text in response to the prompt. Here, the AI ​​model generates text using the prompt obtained through intent analysis as input. The output is text with content appropriate for presenting to the user.

[0578] Step 5:

[0579] The server sends the generated product information or promotional text to the terminal. This output data is then formatted for visualization on the terminal.

[0580] Step 6:

[0581] The terminal displays generated information received from the server in real time on a personal display device (such as smart glasses or a mobile device display) via a user interface. This allows the user to immediately support customer interactions by utilizing the displayed information.

[0582] 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.

[0583] This invention is a system for achieving more appropriate and persuasive communication by taking emotions into consideration during interactions with users. Specifically, it implements a program that utilizes speech recognition technology, natural language processing technology, and an emotion recognition engine, and its embodiments are shown below.

[0584] First, when a user starts a conversation, the device captures the audio in real time and converts it into text data using speech recognition technology. This text data is then sent to a server for analysis.

[0585] The server analyzes the received text data using natural language processing techniques to identify the context and the speaker's intent. During this process, an emotion recognition engine analyzes the linguistic features contained in the text data to recognize the user's current emotional state. This emotion analysis is used to deepen the understanding of the text's context and to better align the selected quotes or guidelines with the user's emotions.

[0586] Next, the server uses a generative AI model based on the analysis results and emotional state to select appropriate quotes and guidelines from the database. Since the recognized emotions are heavily reflected in the selection process, it is possible to provide the user with the most appropriate content for the situation.

[0587] The server sends selected quotes and guidelines to the terminal, which then displays them on the user interface. From the displayed options, the user selects the one that best suits their situation and feelings, and uses that selection to convey a message to the other person.

[0588] As a concrete example, consider a meeting where emotions are fluctuating. When a user is feeling stressed, the emotion engine recognizes that emotion from the audio captured by the device and presents a quote such as, "He who remains calm is the strongest" (a hypothetical quote). The user can then use this quote to say, "Remaining calm is the key to success," thereby regaining their composure and ensuring the meeting proceeds smoothly.

[0589] This system can improve the quality of conversations and support effective communication that is attentive to the user's emotions.

[0590] The following describes the processing flow.

[0591] Step 1:

[0592] When a user starts a conversation, the device captures the user's voice in real time through the microphone.

[0593] Step 2:

[0594] The device converts the acquired audio data into text data using speech recognition technology. This converted text is then formatted for later analysis.

[0595] Step 3:

[0596] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing technology to identify the context.

[0597] Step 4:

[0598] The server uses an emotion recognition engine to analyze the emotions contained in the text data. This analysis identifies the emotions the user is currently experiencing.

[0599] Step 5:

[0600] The server uses a generated AI model to select the most appropriate quotes and guidelines from the database based on the analyzed context and identified sentiment.

[0601] Step 6:

[0602] The server sends selected quotations and guideline candidates to the terminal.

[0603] Step 7:

[0604] The terminal displays the received candidates in a list format on the user interface, allowing the user to select one.

[0605] Step 8:

[0606] The user selects the most appropriate option from the presented choices and conveys those words to their conversation partner. Through this selection, the user can communicate in a way that resonates with their emotions.

[0607] (Example 2)

[0608] 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."

[0609] Existing communication support systems simply interpret the speaker's statements as text, making it difficult to suggest appropriate responses or guidelines that take into account the emotions contained within. Therefore, there is a need to provide support that is appropriate to the emotional state and to improve the quality of communication.

[0610] 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.

[0611] In this invention, the server includes means for acquiring voice input and converting the voice data into text data, means for analyzing the context and speaker's intent using natural language processing technology, and means for identifying the speaker's emotional state using emotion recognition technology. This makes it possible to select and provide appropriate quotes and guidelines to the user based on the speaker's utterances and emotions.

[0612] "Voice input" refers to the process of acquiring information spoken by a user as a digital signal.

[0613] "Text data" refers to character-based information converted using speech recognition technology.

[0614] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0615] "Context" refers to information that indicates the situation in which linguistic information is used.

[0616] "Speaker's intent" refers to the true meaning or purpose that the speaker is trying to convey.

[0617] "Emotion recognition technology" is a technology that identifies a user's emotional state based on text and audio information.

[0618] A "generative AI model" is an artificial intelligence model that automatically generates new information and content based on large amounts of data.

[0619] A "quote or guideline" refers to a sentence that offers advice or guidance relevant to the speaker's situation.

[0620] A "database" is a system for efficiently storing and managing structured information.

[0621] A "user interface" refers to the display screen and operating methods that a user uses to interact with a system.

[0622] This system effectively supports user interaction by utilizing speech recognition technology, natural language processing technology, and emotion recognition technology. First, when the user speaks aloud into the device, the device captures the audio. Using speech recognition software (for example, a general speech recognition library), this audio data is converted into text data.

[0623] The device sends the converted text data to the server via the internet. The server analyzes the text data using natural language processing techniques (e.g., general natural language processing libraries) to identify the context of the statement and the speaker's intent. Furthermore, an emotion recognition engine is integrated to determine the user's emotional state from the text.

[0624] Based on these results, the server uses a generative AI model to select appropriate quotes or guidelines from the database. During this process, the recognized emotions are reflected in the selection, resulting in more relevant content. The selected content is then transmitted back to the terminal via the internet and displayed in the user interface.

[0625] As a concrete example, consider a situation where a user expresses anxiety about a project. In this case, the device captures the user's words, and the server identifies the emotion "anxiety." The generative AI model selects a guideline from the database, such as "When you feel anxious, it's important to take things one step at a time," and displays it on the device.

[0626] An example of a prompt might be, "Suggest some quotes to alleviate concerns about the project." This prompt allows the system to provide effective advice tailored to the user's needs.

[0627] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0628] Step 1:

[0629] The user speaks using their voice.

[0630] Input: User's spoken words.

[0631] Operation: The device captures the user's voice in real time using the microphone.

[0632] Output: Saved as audio data.

[0633] Step 2:

[0634] The device converts the audio data into text data.

[0635] Input: Acquired audio data.

[0636] Data processing: Use speech recognition software to convert speech data into text data.

[0637] Output: Saved as text data.

[0638] Step 3:

[0639] The terminal sends text data to the server.

[0640] Input: Converted text data.

[0641] Operation: Sends text data to a server via the internet.

[0642] Output: The server receives text data.

[0643] Step 4:

[0644] The server parses the text data.

[0645] Input: Text data sent to the server.

[0646] Data processing: Use NLP techniques to analyze context and speaker intent.

[0647] Output: The analysis results generate contextual and intent data.

[0648] Step 5:

[0649] The server performs emotion recognition.

[0650] Input: Parsed text data.

[0651] Data processing: Use emotion recognition technology to identify the speaker's emotional state.

[0652] Output: Saved as emotional state data.

[0653] Step 6:

[0654] The server selects an appropriate quote or guideline.

[0655] Input: Analysis results and emotional state data.

[0656] Data processing: Using a generative AI model, select quotes and guidelines from a database that are appropriate for the sentiment.

[0657] Output: Selected quotations or guidelines.

[0658] Step 7:

[0659] The server sends the selection results to the terminal.

[0660] Input: Selected quotes or guidelines.

[0661] Operation: Sends the selection results to the terminal via the internet.

[0662] Output: The terminal receives a quote or guidance.

[0663] Step 8:

[0664] The device displays a quote or guideline in the user interface.

[0665] Input: A quote or guideline received from the server.

[0666] Function: Display information on the user interface so that the user can verify it.

[0667] Output: The displayed content is reviewed by the user.

[0668] Step 9:

[0669] The user selects a displayed quote or guideline.

[0670] Input: Multiple options displayed in the user interface.

[0671] Data processing: The user selects the most appropriate quote or guideline.

[0672] Output: An action based on the selected quote or guideline is expected.

[0673] (Application Example 2)

[0674] 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."

[0675] In customer service and interpersonal communication settings, it is difficult to appropriately recognize the speaker's intentions and emotions and to provide appropriate responses and recommendations accordingly. In particular, conventional systems can only generate formulaic responses without considering emotional states, which contributes to decreased customer satisfaction. There is a need for systems that can solve this problem and support more emotionally sensitive and effective communication.

[0676] 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.

[0677] In this invention, the server includes a device that converts voice input into text data, a device that analyzes the speaker's intent and emotional state and selects appropriate quotations or guidelines, and a user information provision device that displays the information. This makes it possible to generate and present optimal responses and recommendations based on emotions.

[0678] "Natural language processing technology" refers to technologies for interpreting, analyzing, and generating human language from speech or text data.

[0679] A "device that converts voice input to text data" is a device that has a mechanism for converting speech to text in real time, and includes a speech recognition module.

[0680] A "device for analyzing speaker intent and emotional state" is a device that analyzes text data contextually and emotionally to identify the speaker's intended message and current emotions.

[0681] A "device for selecting quotations or guidelines" is a device equipped with a mechanism for selecting appropriate responses or advice based on analyzed intentions and emotions.

[0682] A "user-facing information provision device" is a user device that visually displays selected quotations and guidelines to users.

[0683] "Generative AI functionality" refers to AI technology that generates content and has the ability to provide responses and suggested phrases based on specific conditions.

[0684] This invention is a system designed to enable effective communication between staff and customers, particularly in physical stores. The core of the system consists of speech recognition technology, natural language processing technology, an emotion recognition engine, and generative AI technology.

[0685] First, the device acquires the customer's speech as voice input in real time. The acquired voice data is converted into text data using a speech recognition module. This process utilizes speech recognition software such as the Google Cloud Speech-to-Text API.

[0686] The converted text data is sent to a server, where natural language processing techniques are used to identify the speaker's intent and context. Furthermore, an emotion recognition engine, such as IBM Watson Tone Analyzer, is used to analyze the speaker's emotional state.

[0687] Based on the analysis results, the server uses a generative AI model to select appropriate quotes and guidelines from the database. In this process, models such as the GPT model provided by OpenAI are used to generate appropriate responses that match the user's emotions.

[0688] Selected quotes and guidelines are provided to the user's device. Smartphones and tablets, acting as user information providers, assist staff operations. For example, if a customer expresses anxiety, the system might suggest "offering reassuring words."

[0689] An example of a prompt for this generative AI model is, "Create several reassuring messages for customer service when customers are feeling stressed. The tone should be polite and professional." Using this prompt, the AI ​​generates appropriate customer responses tailored to the situation.

[0690] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0691] Step 1:

[0692] The device acquires customer voices in real time via a microphone. The input is raw audio data, and the output is voice data sent to a speech recognition module. This data is then sent to a speech recognition engine for analyzing the voice.

[0693] Step 2:

[0694] The server uses a speech recognition engine to convert the input speech data into text data. The software used is the Google Cloud Speech-to-Text API. In this step, the speech signal is output as text.

[0695] Step 3:

[0696] The server analyzes text data using natural language processing techniques to identify the speaker's intent and context. The input is text data converted from speech, and the output is the analyzed contextual information and intent. Libraries such as SpaCy are used.

[0697] Step 4:

[0698] The server uses an emotion recognition engine to analyze the speaker's emotional state from text data. The analysis is performed using IBM Watson Tone Analyzer, and information about the emotion is extracted. The input is the text data from the previous step, and the output is the emotional state.

[0699] Step 5:

[0700] The server uses a generative AI model to select the most appropriate quotes and guidelines based on the speaker's intent and emotions. OpenAI's GPT model is used, with contextual information and emotional states as input, and the output being the generated quotes and guidelines.

[0701] Step 6:

[0702] The terminal displays quoted texts and guidelines received from the server to staff via a user-facing information device. This allows staff to obtain information and advice that can be used in interactions with customers. The input is quoted texts and guidelines from the server, and the output is the content displayed on the staff's display.

[0703] 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.

[0704] 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.

[0705] 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.

[0706] [Fourth Embodiment]

[0707] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0708] 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.

[0709] 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).

[0710] 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.

[0711] 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.

[0712] 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).

[0713] 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.

[0714] 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.

[0715] 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.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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".

[0720] This invention is a system that enables speakers to communicate more persuasively during conversations. Specifically, it implements a program that utilizes speech recognition technology and a generative AI model, and an embodiment thereof is shown below.

[0721] First, when a user begins a conversation, the device acquires the audio in real time through the microphone. This audio data is then converted into text data using speech recognition technology. The converted text data is then sent from the device to the server.

[0722] The server analyzes the received text data using natural language processing techniques to understand the context of the conversation and the speaker's intent. A generative AI model then uses this analysis to select appropriate quotes and guidelines from a database. Specifically, relevant quotes and helpful advice are chosen as candidates, thereby improving the quality of the conversation.

[0723] Next, the server sends the selected candidates to the terminal, which displays them on the user interface. The user can review the presented options and select the appropriate one. This selection allows the user to give weight to their words and effectively convey their message to the person they are talking to.

[0724] As a concrete example, consider a new proposal in a business meeting. When a user proposes a new idea, the device captures the statement, and the server displays a quote such as "New ideas are always the foundation of evolution" (a hypothetical famous quote). The user can then use this to enhance the persuasiveness of their proposal by stating, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way."

[0725] Thus, the system of the present invention helps to enrich the range of words and improve the quality of the message being conveyed in a variety of dialogue situations.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] When a user begins a conversation, the device captures their speech in real time via the microphone.

[0729] Step 2:

[0730] The device converts the acquired voice data into text data using its built-in speech recognition technology.

[0731] Step 3:

[0732] The terminal sends the generated text data to the server for analysis.

[0733] Step 4:

[0734] The server analyzes the received text data using natural language processing techniques to identify the context of the conversation and the speaker's intent.

[0735] Step 5:

[0736] The server uses a generated AI model to select candidates from a database that include appropriate quotations and guidelines based on the analysis results.

[0737] Step 6:

[0738] The server sends a list of selected quotes and guidelines to the terminal.

[0739] Step 7:

[0740] The selection results received by the terminal are displayed on the user interface, allowing the user to select the most appropriate option.

[0741] Step 8:

[0742] The user selects the appropriate word from the presented options and conveys their selection to the conversation partner.

[0743] (Example 1)

[0744] 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".

[0745] Conventional speech recognition systems only convert speech to text, and lack sufficient support to improve the quality of subsequent conversations. In particular, they lacked the ability to provide appropriate quotations and guidelines that align with the speaker's intent in real time, making it difficult to effectively assist the flow of dialogue. This invention aims to solve these problems and enable speakers to communicate more persuasively during conversations.

[0746] 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.

[0747] In this invention, the server includes means for acquiring speech and converting the speech input into text data; means for transmitting the converted text data to a data storage device via a communication network; and means for the storage device to analyze the text data using natural language processing technology and select appropriate quotations or guiding information from external information sources. This enables the speaker to acquire quotations and guiding information that match their intentions in real time, thereby improving the quality of the conversation.

[0748] "Acquiring speech" refers to the act of capturing a speaker's utterance as an acoustic signal into a device and using that signal for subsequent processing.

[0749] "Converting voice input to text data" refers to the act of using speech recognition technology to convert collected acoustic signals into corresponding string data.

[0750] A "communication network" refers to a means of connection for sending and receiving data, encompassing a wide range of digital communication methods, including the internet and dedicated lines.

[0751] A "data storage device" refers to a computing device or media that temporarily or permanently stores information and allows access to and use that information as needed.

[0752] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and analyze human language, and specifically refers to the technology used for classifying and semantic analysis of language data.

[0753] "External information sources" refer to a collection of information or information providers that exist outside the system and can provide the necessary data.

[0754] A “quote or instruction” is a statement or instruction that is intended to advise or refer to the speaker in a particular context, and is usually selected from a reliable source.

[0755] An "ergonomically designed user interface" refers to an operating surface designed to allow users to operate it intuitively and effectively, and includes elements that are optimized from a visual and operational standpoint.

[0756] This system enables speakers to communicate more persuasively during conversations and is implemented using speech recognition technology, generative AI models, and a sophisticated user interface.

[0757] When a user begins a conversation, the device's built-in microphone captures the audio. This audio is then converted into text data in real time using speech recognition technology. This process utilizes speech-to-text solutions such as the Google Speech-to-Text API. The text data generated by speech recognition is then sent to a server via the communication network.

[0758] The server analyzes the received text data using natural language processing (NLTK) techniques. For analysis, natural language processing libraries such as spaCy and NLTK are used to extract the speaker's intent and conversational context from the text. Then, a generative AI model (for example, the GPT series) selects appropriate quotations and guidelines from external sources based on the analysis results. This selects the information necessary to improve the quality of the conversation.

[0759] Selected quotes and guidelines are transmitted from the server to the terminal and presented to the user through an ergonomically designed user interface. This interface offers excellent visibility and operability, allowing users to easily select quotes and guidelines and incorporate them into their conversations.

[0760] For example, when a user presents a new product idea in a business meeting, the system can recognize the statement and suggest a quote such as, "New ideas are always the foundation of evolution." The user can then use this information to increase the persuasiveness of their proposal by saying, "It is said that new ideas are always the foundation of evolution, and our proposal should contribute in the same way." In such a situation, a prompt such as, "Please tell me some effective quotes to use when proposing a new product in a business meeting," would be useful.

[0761] This invention provides effective support for users to select words in various dialogue situations and improve the quality of their messages.

[0762] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0763] Step 1:

[0764] When a user starts a conversation, the device's microphone acquires the voice. The voice data, as input, arrives at the microphone as sound waves. Specifically, the microphone converts changes in ambient sound pressure into electrical signals, which are then converted from analog to digital and stored as digital audio data.

[0765] Step 2:

[0766] The device passes the acquired audio data to a speech recognition module, which then converts the content into text data. The input is digital audio data, and the output is text data in which the audio is represented as characters. For example, the Google Speech-to-Text API is used as the speech recognition technology, and data conversion is performed by combining an acoustic model and a language model.

[0767] Step 3:

[0768] The terminal sends the converted text data to the server. Here, the input is text data, and the output is secure data transmission using a communication protocol (e.g., HTTPS). Specifically, the terminal breaks down the text data into packets and sends them to the server over the network.

[0769] Step 4:

[0770] The server analyzes the received text data using a natural language processing library (e.g., spaCy). The input is text data, and the output is the analyzed conversational context and keywords. Specifically, the server analyzes the text data based on its grammatical structure and extracts the speaker's intent and context.

[0771] Step 5:

[0772] The server runs a generative AI model (e.g., the GPT series) and selects quotations and guidelines based on the analysis results. The input is the analyzed contextual information, and the output is the generated quotations and guidelines. Specifically, the AI ​​model retrieves the most suitable materials from the database based on the analysis results and generates appropriate wording.

[0773] Step 6:

[0774] The server sends the selected quotes and guidelines to the terminal. Here, the input is the quotes and guidelines, and the output is the transmission of data for display on the user interface. Specifically, the server incorporates the generated text into a packet and delivers it to the terminal via a secure route.

[0775] Step 7:

[0776] The device displays received quotations and guidelines on its user interface. The input consists of quotations and guidelines sent from the server, and the output is a visually verifiable screen display. Specifically, the device uses a UI library to display a list of quotations on the screen as a pop-up or a dedicated app.

[0777] Step 8:

[0778] The user reviews the presented quotes and guidelines and makes selections as needed. The input is the displayed options, and the output is the user's selection action. Specifically, the user selects the optimal option through touch or click operations and incorporates it into their own speech.

[0779] (Application Example 1)

[0780] 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".

[0781] In many modern retail settings, customer service staff are expected to provide effective and accurate suggestions to customers. However, human memory and knowledge have limitations, making it difficult to provide optimal information in every situation. Furthermore, accurately understanding a customer's purchase intent within a limited time and responding quickly is also a challenge.

[0782] 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.

[0783] In this invention, the server includes means for converting voice input into text data using natural language processing technology, means for analyzing the speaker's intent from the text data and selecting appropriate quotations or guiding words, and means for generating appropriate product information or promotional text based on the voice input using generative AI technology. This enables effective and rapid information provision tailored to the situation.

[0784] "Natural language processing technology" refers to technologies that understand meaning from speech and text data and extract or generate appropriate information.

[0785] "Voice input" refers to audio data acquired through a microphone or other audio capture device.

[0786] "Text data" refers to character data converted from speech input, in a format that can be processed and analyzed by a computer.

[0787] "Speaker's intent" refers to the purpose or meaning that the speaker is trying to convey in a conversation or statement.

[0788] A "quote or instruction" is a useful sentence or instruction used in conversation to complement or emphasize something.

[0789] "Information presentation means" refers to devices or systems that display and provide selected information to users visually or audibly.

[0790] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate new information and content.

[0791] "Product information" refers to information that includes detailed descriptions of the product's features, specifications, and benefits.

[0792] "Advertising copy" refers to text created for advertising or promotional purposes to make a product or service appear appealing.

[0793] A "personal display device" refers to an information display device that is used individually by a user, such as smart glasses or mobile devices.

[0794] The system realizing this invention primarily operates through the cooperation of three entities: a server, a terminal, and a user. Specifically, the server utilizes natural language processing and generative AI technologies to analyze voice provided through the terminal and generate and present appropriate information. The terminal receives voice input and provides an interface for processing in cooperation with the server. The user uses this terminal to facilitate communication in daily work and life.

[0795] Specifically, when the server receives voice input, it first converts it into text data using natural language processing techniques. Specific software used for this purpose includes the Google Cloud Speech-to-Text API. The converted text data is then analyzed using a generative AI model to understand the user's intent. This process utilizes generative AI models such as Hugging Face's GPT-2 model.

[0796] The server then generates relevant product information and promotional text based on the analysis results. The generation AI technology used here suggests appropriate content in response to prompts entered by the user. For example, a possible prompt might be, "If the customer is looking for a new trench coat, generate a suggestion based on the product's features."

[0797] The generated information is presented to the user via a personal display device. For example, smart glasses or mobile devices can be used in this way, and the selected information is displayed in real time on their screens, allowing users to immediately utilize it during interactions. This entire process enables persuasive communication in customer interactions.

[0798] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0799] Step 1:

[0800] The terminal captures the user's voice input in real time through its built-in microphone. This voice input data is then acquired as a digital signal and prepared for transmission to the server.

[0801] Step 2:

[0802] The server converts the received voice input data into text data using natural language processing techniques. Here, data processing using a speech recognition API is performed, converting the voice signal into a corresponding string. The output of this process is text data containing what the user said.

[0803] Step 3:

[0804] The server uses a generative AI model to analyze the user's intent from the converted text data. Based on the text data as input, a natural language understanding algorithm performs calculations to extract the context and topic of the conversation. The output of this step is a prompt sentence or keywords based on the analyzed intent.

[0805] Step 4:

[0806] The server uses generative AI technology to generate relevant product information or promotional text in response to the prompt. Here, the AI ​​model generates text using the prompt obtained through intent analysis as input. The output is text with content appropriate for presenting to the user.

[0807] Step 5:

[0808] The server sends the generated product information or promotional text to the terminal. This output data is then formatted for visualization on the terminal.

[0809] Step 6:

[0810] The terminal displays generated information received from the server in real time on a personal display device (such as smart glasses or a mobile device display) via a user interface. This allows the user to immediately support customer interactions by utilizing the displayed information.

[0811] 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.

[0812] This invention is a system for achieving more appropriate and persuasive communication by taking emotions into consideration during interactions with users. Specifically, it implements a program that utilizes speech recognition technology, natural language processing technology, and an emotion recognition engine, and its embodiments are shown below.

[0813] First, when a user starts a conversation, the device captures the audio in real time and converts it into text data using speech recognition technology. This text data is then sent to a server for analysis.

[0814] The server analyzes the received text data using natural language processing techniques to identify the context and the speaker's intent. During this process, an emotion recognition engine analyzes the linguistic features contained in the text data to recognize the user's current emotional state. This emotion analysis is used to deepen the understanding of the text's context and to better align the selected quotes or guidelines with the user's emotions.

[0815] Next, the server uses a generative AI model based on the analysis results and emotional state to select appropriate quotes and guidelines from the database. Since the recognized emotions are heavily reflected in the selection process, it is possible to provide the user with the most appropriate content for the situation.

[0816] The server sends selected quotes and guidelines to the terminal, which then displays them on the user interface. From the displayed options, the user selects the one that best suits their situation and feelings, and uses that selection to convey a message to the other person.

[0817] As a concrete example, consider a meeting where emotions are fluctuating. When a user is feeling stressed, the emotion engine recognizes that emotion from the audio captured by the device and presents a quote such as, "He who remains calm is the strongest" (a hypothetical quote). The user can then use this quote to say, "Remaining calm is the key to success," thereby regaining their composure and ensuring the meeting proceeds smoothly.

[0818] This system can improve the quality of conversations and support effective communication that is attentive to the user's emotions.

[0819] The following describes the processing flow.

[0820] Step 1:

[0821] When a user starts a conversation, the device captures the user's voice in real time through the microphone.

[0822] Step 2:

[0823] The device converts the acquired audio data into text data using speech recognition technology. This converted text is then formatted for later analysis.

[0824] Step 3:

[0825] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing technology to identify the context.

[0826] Step 4:

[0827] The server uses an emotion recognition engine to analyze the emotions contained in the text data. This analysis identifies the emotions the user is currently experiencing.

[0828] Step 5:

[0829] The server uses a generated AI model to select the most appropriate quotes and guidelines from the database based on the analyzed context and identified sentiment.

[0830] Step 6:

[0831] The server sends selected quotations and guideline candidates to the terminal.

[0832] Step 7:

[0833] The terminal displays the received candidates in a list format on the user interface, allowing the user to select one.

[0834] Step 8:

[0835] The user selects the most appropriate option from the presented choices and conveys those words to their conversation partner. Through this selection, the user can communicate in a way that resonates with their emotions.

[0836] (Example 2)

[0837] 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".

[0838] Existing communication support systems simply interpret the speaker's statements as text, making it difficult to suggest appropriate responses or guidelines that take into account the emotions contained within. Therefore, there is a need to provide support that is appropriate to the emotional state and to improve the quality of communication.

[0839] 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.

[0840] In this invention, the server includes means for acquiring voice input and converting the voice data into text data, means for analyzing the context and speaker's intent using natural language processing technology, and means for identifying the speaker's emotional state using emotion recognition technology. This makes it possible to select and provide appropriate quotes and guidelines to the user based on the speaker's utterances and emotions.

[0841] "Voice input" refers to the process of acquiring information spoken by a user as a digital signal.

[0842] "Text data" refers to character-based information converted using speech recognition technology.

[0843] "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language.

[0844] "Context" refers to information that indicates the situation in which linguistic information is used.

[0845] "Speaker's intent" refers to the true meaning or purpose that the speaker is trying to convey.

[0846] "Emotion recognition technology" is a technology that identifies a user's emotional state based on text and audio information.

[0847] A "generative AI model" is an artificial intelligence model that automatically generates new information and content based on large amounts of data.

[0848] A "quote or guideline" refers to a sentence that offers advice or guidance relevant to the speaker's situation.

[0849] A "database" is a system for efficiently storing and managing structured information.

[0850] A "user interface" refers to the display screen and operating methods that a user uses to interact with a system.

[0851] This system effectively supports user interaction by utilizing speech recognition technology, natural language processing technology, and emotion recognition technology. First, when the user speaks aloud into the device, the device captures the audio. Using speech recognition software (for example, a general speech recognition library), this audio data is converted into text data.

[0852] The device sends the converted text data to the server via the internet. The server analyzes the text data using natural language processing techniques (e.g., general natural language processing libraries) to identify the context of the statement and the speaker's intent. Furthermore, an emotion recognition engine is integrated to determine the user's emotional state from the text.

[0853] Based on these results, the server uses a generative AI model to select appropriate quotes or guidelines from the database. During this process, the recognized emotions are reflected in the selection, resulting in more relevant content. The selected content is then transmitted back to the terminal via the internet and displayed in the user interface.

[0854] As a concrete example, consider a situation where a user expresses anxiety about a project. In this case, the device captures the user's words, and the server identifies the emotion "anxiety." The generative AI model selects a guideline from the database, such as "When you feel anxious, it's important to take things one step at a time," and displays it on the device.

[0855] An example of a prompt might be, "Suggest some quotes to alleviate concerns about the project." This prompt allows the system to provide effective advice tailored to the user's needs.

[0856] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0857] Step 1:

[0858] The user speaks using their voice.

[0859] Input: User's spoken words.

[0860] Operation: The device captures the user's voice in real time using the microphone.

[0861] Output: Saved as audio data.

[0862] Step 2:

[0863] The device converts the audio data into text data.

[0864] Input: Acquired audio data.

[0865] Data processing: Use speech recognition software to convert speech data into text data.

[0866] Output: Saved as text data.

[0867] Step 3:

[0868] The terminal sends text data to the server.

[0869] Input: Converted text data.

[0870] Operation: Sends text data to a server via the internet.

[0871] Output: The server receives text data.

[0872] Step 4:

[0873] The server parses the text data.

[0874] Input: Text data sent to the server.

[0875] Data processing: Use NLP techniques to analyze context and speaker intent.

[0876] Output: The analysis results generate contextual and intent data.

[0877] Step 5:

[0878] The server performs emotion recognition.

[0879] Input: Parsed text data.

[0880] Data processing: Use emotion recognition technology to identify the speaker's emotional state.

[0881] Output: Saved as emotional state data.

[0882] Step 6:

[0883] The server selects an appropriate quote or guideline.

[0884] Input: Analysis results and emotional state data.

[0885] Data processing: Using a generative AI model, select quotes and guidelines from a database that are appropriate for the sentiment.

[0886] Output: Selected quotations or guidelines.

[0887] Step 7:

[0888] The server sends the selection results to the terminal.

[0889] Input: Selected quotes or guidelines.

[0890] Operation: Sends the selection results to the terminal via the internet.

[0891] Output: The terminal receives a quote or guidance.

[0892] Step 8:

[0893] The device displays a quote or guideline in the user interface.

[0894] Input: A quote or guideline received from the server.

[0895] Function: Display information on the user interface so that the user can verify it.

[0896] Output: The displayed content is reviewed by the user.

[0897] Step 9:

[0898] The user selects a displayed quote or guideline.

[0899] Input: Multiple options displayed in the user interface.

[0900] Data processing: The user selects the most appropriate quote or guideline.

[0901] Output: An action based on the selected quote or guideline is expected.

[0902] (Application Example 2)

[0903] 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".

[0904] In customer service and interpersonal communication settings, it is difficult to appropriately recognize the speaker's intentions and emotions and to provide appropriate responses and recommendations accordingly. In particular, conventional systems can only generate formulaic responses without considering emotional states, which contributes to decreased customer satisfaction. There is a need for systems that can solve this problem and support more emotionally sensitive and effective communication.

[0905] 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.

[0906] In this invention, the server includes a device that converts voice input into text data, a device that analyzes the speaker's intent and emotional state and selects appropriate quotations or guidelines, and a user information provision device that displays the information. This makes it possible to generate and present optimal responses and recommendations based on emotions.

[0907] "Natural language processing technology" refers to technologies for interpreting, analyzing, and generating human language from speech or text data.

[0908] A "device that converts voice input to text data" is a device that has a mechanism for converting speech to text in real time, and includes a speech recognition module.

[0909] A "device for analyzing speaker intent and emotional state" is a device that analyzes text data contextually and emotionally to identify the speaker's intended message and current emotions.

[0910] A "device for selecting quotations or guidelines" is a device equipped with a mechanism for selecting appropriate responses or advice based on analyzed intentions and emotions.

[0911] A "user-facing information provision device" is a user device that visually displays selected quotations and guidelines to users.

[0912] "Generative AI functionality" refers to AI technology that generates content and has the ability to provide responses and suggested phrases based on specific conditions.

[0913] This invention is a system designed to enable effective communication between staff and customers, particularly in physical stores. The core of the system consists of speech recognition technology, natural language processing technology, an emotion recognition engine, and generative AI technology.

[0914] First, the device acquires the customer's speech as voice input in real time. The acquired voice data is converted into text data using a speech recognition module. This process utilizes speech recognition software such as the Google Cloud Speech-to-Text API.

[0915] The converted text data is sent to a server, where natural language processing techniques are used to identify the speaker's intent and context. Furthermore, an emotion recognition engine, such as IBM Watson Tone Analyzer, is used to analyze the speaker's emotional state.

[0916] Based on the analysis results, the server uses a generative AI model to select appropriate quotes and guidelines from the database. In this process, models such as the GPT model provided by OpenAI are used to generate appropriate responses that match the user's emotions.

[0917] Selected quotes and guidelines are provided to the user's device. Smartphones and tablets, acting as user information providers, assist staff operations. For example, if a customer expresses anxiety, the system might suggest "offering reassuring words."

[0918] An example of a prompt for this generative AI model is, "Create several reassuring messages for customer service when customers are feeling stressed. The tone should be polite and professional." Using this prompt, the AI ​​generates appropriate customer responses tailored to the situation.

[0919] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0920] Step 1:

[0921] The device acquires customer voices in real time via a microphone. The input is raw audio data, and the output is voice data sent to a speech recognition module. This data is then sent to a speech recognition engine for analyzing the voice.

[0922] Step 2:

[0923] The server uses a speech recognition engine to convert the input speech data into text data. The software used is the Google Cloud Speech-to-Text API. In this step, the speech signal is output as text.

[0924] Step 3:

[0925] The server analyzes text data using natural language processing techniques to identify the speaker's intent and context. The input is text data converted from speech, and the output is the analyzed contextual information and intent. Libraries such as SpaCy are used.

[0926] Step 4:

[0927] The server uses an emotion recognition engine to analyze the speaker's emotional state from text data. The analysis is performed using IBM Watson Tone Analyzer, and information about the emotion is extracted. The input is the text data from the previous step, and the output is the emotional state.

[0928] Step 5:

[0929] The server uses a generative AI model to select the most appropriate quotes and guidelines based on the speaker's intent and emotions. OpenAI's GPT model is used, with contextual information and emotional states as input, and the output being the generated quotes and guidelines.

[0930] Step 6:

[0931] The terminal displays quoted texts and guidelines received from the server to staff via a user-facing information device. This allows staff to obtain information and advice that can be used in interactions with customers. The input is quoted texts and guidelines from the server, and the output is the content displayed on the staff's display.

[0932] 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.

[0933] 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.

[0934] 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.

[0935] 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.

[0936] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0937] 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.

[0938] 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.

[0939] 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.

[0940] 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."

[0941] 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.

[0942] 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.

[0943] 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.

[0944] 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.

[0945] 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.

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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.

[0952] 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.

[0953] The following is further disclosed regarding the embodiments described above.

[0954] (Claim 1)

[0955] A means of converting speech input into text data using natural language processing technology,

[0956] A means for analyzing the speaker's intent from the aforementioned text data and selecting appropriate quotations or guiding words,

[0957] A user interface means for displaying the selected quote or guideline,

[0958] A system that includes this.

[0959] (Claim 2)

[0960] The system according to claim 1, further comprising means for extracting keywords based on context and the subject of the conversation when selecting the aforementioned quotations or guidelines.

[0961] (Claim 3)

[0962] The system according to claim 1, further comprising means for presenting a selection of quotations or guidelines in a list format, allowing the user to select from among them, in the user interface means.

[0963] "Example 1"

[0964] (Claim 1)

[0965] A means of acquiring audio and converting audio input into text data,

[0966] Means for transmitting the converted text data to a data storage device via a communication network,

[0967] The aforementioned storage device analyzes the text data using natural language processing technology and provides means for selecting appropriate quoted text or guiding information from external sources,

[0968] An ergonomically designed user interface means for presenting the selected quote or guideline,

[0969] A system that includes this.

[0970] (Claim 2)

[0971] The system according to claim 1, further comprising means for analyzing and extracting linguistic elements based on a subject.

[0972] (Claim 3)

[0973] The system according to claim 1, further comprising means for listing multiple quotations or guidelines as options and allowing a user to select one.

[0974] "Application Example 1"

[0975] (Claim 1)

[0976] A means of converting speech input into text data using natural language processing technology,

[0977] A means for analyzing the speaker's intent from the aforementioned text data and selecting appropriate quotations or guiding words,

[0978] Information display means for displaying the selected quoted text or guidelines,

[0979] A generation means that generates appropriate product information or advertising text based on voice input,

[0980] Means for visualizing the generated product information or advertising text and presenting it on a personal display device,

[0981] A system that includes this.

[0982] (Claim 2)

[0983] The system according to claim 1, further comprising means for extracting keywords based on context and the subject of the conversation when selecting the aforementioned quotations or guidelines.

[0984] (Claim 3)

[0985] The system according to claim 1, further comprising means for presenting a selection of quoted texts or guidelines in a list format, allowing the user to select from among them, and further comprising means for emphasizing the characteristics of the relevant products when presenting the generated product information or advertising text.

[0986] "Example 2 of combining an emotion engine"

[0987] (Claim 1)

[0988] A means for acquiring voice input and converting that voice data into text data,

[0989] A means for analyzing the context and speaker's intent using natural language processing techniques with the aforementioned text data,

[0990] Based on the aforementioned analysis results, a means for identifying the speaker's emotional state by utilizing emotion recognition technology,

[0991] A means for selecting an appropriate quote or guideline from a database using a generative AI model based on the aforementioned emotional state and analysis results,

[0992] A user interface means for displaying the selected quote or guideline,

[0993] A system that includes this.

[0994] (Claim 2)

[0995] The system according to claim 1, further comprising means for selecting quotations or guidelines, which include extracting keywords based on context and the subject of the conversation, and taking into account the speaker's emotional state.

[0996] (Claim 3)

[0997] The system according to claim 1, further comprising means for presenting a selection of quotations or guidelines in a list format, allowing the user to select from among them, in the user interface means.

[0998] "Application example 2 when combining with an emotional engine"

[0999] (Claim 1)

[1000] A device that converts speech input into text data using natural language processing technology,

[1001] A device that analyzes the speaker's intent and emotional state from the aforementioned text data and selects an appropriate quote or guideline,

[1002] A user information device that displays the selected quoted text or guidelines,

[1003] A device including a generation AI function that generates recommendations based on the aforementioned emotional state,

[1004] A system that includes this.

[1005] (Claim 2)

[1006] The system according to claim 1, further comprising a device for extracting keywords based on context, topic of conversation, and emotional state when selecting the aforementioned quotations or guidelines.

[1007] (Claim 3)

[1008] The system according to claim 1, further comprising a device that provides user information, which presents a selection of quoted texts or guidelines in a table format, allowing the user to select from among them. [Explanation of Symbols]

[1009] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of converting speech input into text data using natural language processing technology, A means for analyzing the speaker's intent from the aforementioned text data and selecting appropriate quotations or guiding words, A user interface means for displaying the selected quote or guideline, A system that includes this.

2. The system according to claim 1, further comprising means for extracting keywords based on context and the subject of the conversation when selecting the aforementioned quotations or guidelines.

3. The system according to claim 1, further comprising means for presenting a list of selected quotes or guidelines in a user interface, and allowing the user to select from among them.

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