system

Abstract

We provide the system. [Solution] A speech recognition means that converts speech data received by a speech input means into text data, A generative AI means analyzes the text data obtained by the aforementioned speech recognition means to identify the user's intent, Information processing means that searches for necessary information and generates a response based on the user's intent identified by the aforementioned generation AI means, A system including an audio output means that outputs the generated response as audio.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, 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] Conventional car navigation systems have a voice operation function, but the voice operation is limited and cannot respond to complex requests from users. In addition, they lack the ability to monitor the vehicle's situation in real time and respond quickly when an abnormality is detected. As a result, drivers cannot obtain sufficient information and it is difficult to respond quickly to accidents or traffic jams. In addition, the system's ability to propose an optimal route to the destination is also limited, and there is no guarantee that the user can make an optimal decision based on the proposed route.

Means for Solving the Problems

[0005] This invention provides a means to accurately identify the user's intent by using a speech recognition means that utilizes generation AI to convert voice input from the user into text, and then analyzing that text data with the generation AI. This enables the system to handle complex requests. Furthermore, through an information processing means, necessary information is retrieved in real time based on the identified intent, and the generated response is transmitted to the user via a voice output means. In addition, by including means to monitor data from various sensors in the vehicle and issue a warning to the user when an abnormality is detected, a safer driving environment is provided. Moreover, by accessing an external database via a communication network, it becomes possible to acquire real-time traffic information and propose the optimal route.

[0006] "Voice input means" refers to a device or interface for receiving voice information from a user.

[0007] "Speech recognition means" refers to a technology or device for converting received speech data into text data.

[0008] "Generative AI methods" refer to artificial intelligence technologies used to analyze text data and identify user intent.

[0009] "Information processing means" refers to a system or device for retrieving information based on the user's intent identified by the generating AI means and generating an appropriate response.

[0010] "Voice output means" refers to a technology or device for conveying the generated response to the user in voice.

[0011] A "sensor" is a device used to monitor the condition of a vehicle and collect data from it.

[0012] "Means for detecting abnormalities" refers to technologies or devices that determine vehicle abnormalities from data collected by sensors and issue warnings to the user.

[0013] A "communication network" is a digital communication infrastructure used to access external databases.

[0014] An "external database" is a data storage system that contains information such as traffic data and is accessible via a communication network. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered 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.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention provides a car navigation system that utilizes generative AI. The system includes voice input means, voice recognition means, generative AI means, information processing means, and voice output means. The operation of each of these means will be explained below with specific examples.

[0037] First, the device uses microphones placed inside the vehicle to receive voice from the user in real time. The voice input method employs voice filtering technology specifically designed for the in-vehicle environment to remove noise and clearly capture the user's speech.

[0038] Next, the terminal converts the audio received through the speech recognition means into text data. The speech recognition means uses a high-precision speech recognition engine and can minimize misrecognition by learning the user's past speech patterns.

[0039] Subsequently, the server uses a generative AI to analyze the text data transmitted from the speech recognition system. The generative AI uses natural language processing technology to identify the user's intent and extract the necessary information.

[0040] Based on the analysis results, the server uses information processing tools to access external databases and real-time traffic information to create a response suitable for the user's request. For example, if a user requests "Find the best route," the server calculates the shortest route considering the current traffic conditions.

[0041] Finally, the terminal synthesizes the generated response into speech using an audio output device and presents it to the user. The audio output device generates natural-sounding speech and sets appropriate speaker settings to ensure sound quality.

[0042] Furthermore, sensors mounted on the vehicle monitor its condition, and if an abnormality is detected, the terminal immediately sounds an alarm to the user and provides necessary corrective actions via voice. For example, if the tire pressure is low, it will notify the user, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0043] In this way, this invention enables intuitive and interactive responses that allow users to enjoy a safer and more comfortable driving experience.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The device receives the user's voice through the in-car microphone. Here, a function that starts recording the moment a voice trigger word is recognized is activated. A noise reduction filter is also in operation to maintain optimal audio data quality.

[0047] Step 2:

[0048] The device converts voice data into text data via a speech recognition engine. The voice model performs highly accurate recognition, taking into account noise and echoes specific to the in-car environment. In addition, noise reduction is applied to the voice data as a preprocessing step.

[0049] Step 3:

[0050] The server sends text data to a generating AI. Here, the generating AI uses natural language processing techniques to analyze the user's intent from the text data and interpret its meaning. Once the intent is clearly identified, information is prepared for the next processing stage.

[0051] Step 4:

[0052] The server initiates a search for appropriate information based on the user's intent. It accesses external real-time traffic information, retrieves necessary information from vehicle sensor data and other relevant databases, and analyzes it using information processing tools to enable optimal decision-making.

[0053] Step 5:

[0054] The server collects the necessary information and uses generative AI to construct an appropriate response based on that information. Here, it generates instructions, route guidance, and problem-solving solutions in text in response to user requests.

[0055] Step 6:

[0056] The terminal sends the response text to the voice output device, which is then converted into natural-sounding speech using speech synthesis technology. The sound quality is adjusted to ensure the voice guidance is clear to the user, and it is then played back through the car's speakers.

[0057] Step 7:

[0058] The terminal continuously monitors vehicle sensors and immediately notifies the server if an anomaly is detected. This allows the user to receive voice warnings and specific countermeasures depending on the type of anomaly.

[0059] This series of processing steps allows users to interact with the system in a flexible manner and continue driving with peace of mind.

[0060] (Example 1)

[0061] 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."

[0062] Conventional car navigation systems suffer from problems such as low accuracy in voice recognition in noisy environments, leading to misinterpretation of user instructions, and the failure to provide timely information regarding vehicle malfunctions. In addition, they often struggle to provide dynamic information to quickly respond to real-time, changing traffic conditions.

[0063] 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.

[0064] In this invention, the server includes means for receiving the user's voice while removing ambient noise using a voice input device, means for converting the voice data received by the voice input device into text information, and generation AI means including natural language processing technology for analyzing the text information and identifying the user's intent. This improves the accuracy of voice recognition and enables dynamic and accurate navigation that takes traffic information into account in real time.

[0065] "Voice input devices" refer to all devices that receive voice from users and convert it into digital data.

[0066] "Audio data" refers to the digital representation of an audio signal captured through an audio input device.

[0067] "Textual information" refers to text data converted from audio data by speech recognition technology.

[0068] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and respond to human natural language.

[0069] "Generative AI means" refers to artificial intelligence technology that understands user intent and organizes and generates information based on that intent.

[0070] "External information sources" refer to all external information databases that are accessible via the internet or other communication networks.

[0071] "Real-time traffic information" refers to information about current traffic conditions that is updated in real time.

[0072] "Speech synthesis technology" refers to the technology that generates natural-sounding speech using text data.

[0073] The term "detector" refers to any sensor that measures various conditions of a vehicle and outputs them as digital data.

[0074] "Detecting a malfunction" refers to using sensors or other means to determine abnormal conditions or failures that deviate from the vehicle's normal operating state.

[0075] "Information transmission network" refers to all communication networks, including the internet and other protocols.

[0076] This invention provides a vehicle navigation system based on generative AI technology. The system includes a voice input device, voice recognition means, generative AI means, information processing means, and voice output means.

[0077] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. This uses voice filtering technology to reduce ambient noise. For example, noise cancellation algorithms reduce engine noise and road noise.

[0078] Once audio is acquired, the device uses a high-precision speech recognition engine to convert the audio data into text. This ensures that the user's utterances are clearly identified, and by considering past speech patterns, recognition accuracy is improved.

[0079] Next, the server receives the text information transmitted from the speech recognition system and performs analysis using a generative AI system. Natural language processing technology identifies the user's intent and extracts the necessary information. For example, if the user issues the command "Find the shortest route," the generative AI performs analysis based on that command.

[0080] The server uses information processing tools to access external information sources and retrieve necessary data. It refers to a database containing real-time traffic information and creates the optimal route guidance for the user. As a result, fast and accurate navigation information is generated.

[0081] Finally, the generated response is presented to the user by the device using speech synthesis technology. During this process, the volume and tone are adjusted to produce a natural and easy-to-understand voice.

[0082] Furthermore, the terminal constantly monitors information collected by multiple sensors installed in the vehicle and notifies the user in real time if an abnormality is detected. For example, if the tire pressure drops, it will issue a warning such as, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0083] This system allows users to enjoy an intuitive and interactive navigation experience, supporting safer and more comfortable driving.

[0084] Example of a prompt:

[0085] "Find the shortest route"

[0086] "Can you tell me the nearest gas station?"

[0087] "Turn right at the next intersection."

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. The input is the user's voice, which includes ambient noise. The voice input device uses a noise cancellation algorithm to remove the noise and obtain a clear voice signal. The output is the processed voice data.

[0091] Step 2:

[0092] The device utilizes speech recognition to convert the audio data obtained in Step 1 into text information. This process employs a highly accurate speech recognition engine. The input is the processed audio data, and the output is text information. Specifically, if the user voice-inputs "Find the best route," the output will be a text representation of that statement.

[0093] Step 3:

[0094] The server receives text information transmitted from the speech recognition system. The input is the recognized text information. The server uses generative AI to perform natural language processing and identify the user's intent. In this process, important information is extracted from the user's words and the user's request is analyzed. The output is the request information based on the analyzed user intent and its content.

[0095] Step 4:

[0096] The server uses information processing tools to access external information sources and real-time traffic information based on the user's intent obtained in step 3. The input is the user's request information. The server retrieves the necessary data and generates a response to the user's request. For example, in response to the request "Find the shortest route," the server calculates the optimal route considering real-time traffic conditions. The output is the response information provided to the user.

[0097] Step 5:

[0098] The terminal outputs the generated response information as speech using speech synthesis technology. The input is the response information from the server. The output is a synthesized speech message with adjusted volume and tone. Specifically, the terminal will inform the user via voice, "The best route at the moment is via Street A."

[0099] Step 6:

[0100] The terminal monitors data from sensors installed in the vehicle. The input is sensor information indicating the vehicle's status. If an abnormality is detected, it will sound a warning to the user based on that information. For example, if it detects that the tire pressure has dropped, it will provide a voice warning such as, "The air pressure in the front right tire is low. Please have it checked at the nearest service station." The output is a voice notification to the user.

[0101] (Application Example 1)

[0102] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0103] A major problem with autonomous vehicles is the lack of navigation systems that allow passengers to intuitively specify their destinations. Furthermore, there is a need for methods to provide fast and accurate route guidance utilizing real-time traffic information, but this is not yet adequately implemented. This hinders a comfortable and efficient travel experience.

[0104] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0105] In this invention, the server includes a speech recognition means that converts speech data received by a voice input means into text data, a generation AI means that analyzes the text data obtained by the speech recognition means to identify the user's intent, and a navigation means that calculates the optimal route based on traffic information acquired via a communication network. As a result, passengers can obtain quick and optimal route guidance simply by indicating their destination by voice.

[0106] "Voice input means" refers to a device or method for receiving voice data from a user.

[0107] "Speech recognition means" refers to a technology or device that analyzes received speech data and converts it into text data.

[0108] "Generative AI means" refers to artificial intelligence technology that analyzes text data obtained through speech recognition and interprets its intent.

[0109] "Information processing means" refers to a mechanism or software for retrieving necessary information and generating a response based on the intent identified by the generating AI means.

[0110] "Audio output means" refers to a technology or device for converting a generated response into audio and presenting it to the user.

[0111] An "autonomous vehicle" is a vehicle that can autonomously travel to its destination without the need for human intervention.

[0112] A "navigation system" is a technology or system that calculates and guides the optimal route to a destination based on traffic information and map data.

[0113] A "communication network" is a network infrastructure used to send and receive information.

[0114] "Route guidance" refers to information that directs the travel route from the starting point to the destination.

[0115] This invention implements a navigation system for autonomous vehicles that utilizes generative AI. The system includes a microphone for receiving voice input, a speech recognition engine for converting speech to text, a generative AI engine that utilizes advanced AI, an information processing device for acquiring traffic information and calculating a route, and a speaker for outputting the results as voice.

[0116] The server converts the audio data into text data using Google® or an equivalent speech recognition API. The converted text data is then analyzed using a generative AI model (e.g., OpenAI®'s GPT-3®) to identify the user's intent. This generative AI model enables advanced natural language analysis and can handle ambiguous requests from users.

[0117] The server then accesses an external traffic database via a communication network and obtains real-time traffic information as needed. Based on this, the system calculates the optimal route. This process uses programming languages ​​and libraries such as Python and Tensorflow®.

[0118] Once the optimal route is determined, the terminal provides instructions to the user using a voice output device. The voice is generated using speech synthesis technology that simulates natural pronunciation.

[0119] Specific example: For instance, if a user in an autonomous vehicle gives a voice command such as "Tell me the shortest route to the airport," the generating AI analyzes this command, and the server calculates the optimal route based on traffic information obtained from an external database. This route guidance is then provided to the user via voice.

[0120] Example prompt: "Please tell me the fastest route to the city center that avoids congestion."

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] The terminal receives voice input from the user via a microphone placed inside the vehicle. The input is voice data in which the user makes navigation requests. The terminal uses noise filtering technology to clarify this voice data and prepare accurate input data.

[0124] Step 2:

[0125] The server uses a speech recognition engine to convert the audio data into text data. The input is the audio data filtered in step 1, and the output is text data representing the user's utterance. This formats the data so that it can be used in subsequent processing.

[0126] Step 3:

[0127] The server uses a generative AI model to analyze the converted text data and identify the user's intent. The input is the text data obtained in step 2, and the output is the analysis result that defines the user's intent. By utilizing generative AI, even ambiguous requests can be understood with high accuracy.

[0128] Step 4:

[0129] The server uses a communication network to access an external traffic database and obtain the latest traffic information. The input is the user's intent identified in step 3. The output is real-time information about traffic conditions, providing a basis for calculating the optimal route.

[0130] Step 5:

[0131] The server calculates the optimal route based on traffic information and analysis results. The input is the traffic information obtained in step 4 and the user's intent, and the output is specific route guidance information. Python and its libraries are used for the calculations.

[0132] Step 6:

[0133] The terminal converts the calculated route guidance into speech using speech synthesis technology and provides it to the user. The input is the route guidance information calculated in step 5, and the output is the voice route guidance. The user can reach their destination based on this.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention provides a more advanced interactive experience by combining a car navigation system that utilizes generative AI with an emotion engine that recognizes user emotions. The system takes the form of a voice input means, a voice recognition means, a generative AI means, an information processing means, a voice output means, and an emotion recognition means.

[0136] First, the device receives the user's voice via the in-car microphone. The voice undergoes noise filtering and is converted into text data by speech recognition. This text data is then analyzed by a generative AI.

[0137] Next, the server uses AI generation tools to identify the user's intent, and then analyzes the voice data using emotion recognition tools to understand the user's emotional state. The emotion engine analyzes elements such as tone, speed, and volume of the voice to identify emotions such as joy, anger, sadness, and happiness.

[0138] Once the user's intentions and emotions are identified, the server uses that information to search for necessary information in real time and generate the most appropriate response for the user's current situation. This includes adjusting the content and tone of voice according to the user's emotional state.

[0139] For example, if a user says in an anxious tone, "I think I might be lost," the server will check their location in real time and generate a reassuring response in a soft tone, such as, "I've confirmed your current location, you're safe, you can reach your destination by turning right at the next turn."

[0140] This allows the device to communicate responses to the user using voice output. Utilizing speech synthesis technology, it provides natural-sounding dialogue that takes the user's emotions into consideration, even though it uses synthesized speech.

[0141] Furthermore, the system monitors various sensors in the vehicle, and if an abnormality is detected, that information is also included in the response to the user. For example, to help the user react calmly, it might issue instructions such as, "The engine temperature is above normal; please decelerate immediately."

[0142] This system allows users to enjoy emotionally responsive and flexible support, enabling them to drive their vehicles with peace of mind.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] The device receives the user's voice through a microphone installed inside the vehicle. The microphone uses a filter to reduce ambient noise, ensuring clear audio data. This audio data is then transmitted in real time to the speech recognition process.

[0146] Step 2:

[0147] The device uses speech recognition to convert received audio data into text data. This process generates an accurate textual representation of the user's speech, shaping it in a way that facilitates subsequent analysis and processing.

[0148] Step 3:

[0149] The server sends the text data obtained through speech recognition to a generating AI system, which then analyzes the user's intent. This analysis uses natural language processing techniques and focuses on identifying what the user wants from the system.

[0150] Step 4:

[0151] The server simultaneously processes the audio data using emotion recognition tools to identify the user's emotional state. This process analyzes the tone, pitch, and speed of the voice to classify the user's state, such as happy, anxious, or angry.

[0152] Step 5:

[0153] The server uses information processing tools to retrieve necessary information based on the user's intent and emotional state. It integrates real-time traffic information, vehicle sensor data, and other relevant information tailored to the user's needs to generate an appropriate response for the user.

[0154] Step 6:

[0155] The server generates a response, which is then adjusted according to the user's emotions and finally converted into text format necessary for audio output. This step prepares the system to output considerate information, such as matching the wording and tone to the user's emotions.

[0156] Step 7:

[0157] The device uses a voice output device to synthesize prepared response text into speech and transmit it to the user as audio. The synthesized speech is played in a soft, gentle tone, allowing the user to receive information in a way that is considerate of their emotions.

[0158] This process ensures that users always feel secure while obtaining information, and the system provides interaction that is attentive to the user's emotions.

[0159] (Example 2)

[0160] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0161] In the automotive driving environment, conventional navigation systems have struggled to accurately understand user voice commands and emotions and provide appropriate responses in real time. Furthermore, the lack of means to provide flexible responses tailored to the user's psychological state raised concerns about reduced safety and ease of operation while driving. Additionally, there were limitations to their ability to monitor vehicle status and promptly notify of abnormalities.

[0162] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0163] In this invention, the server includes means for receiving audio data and extracting a clear audio signal by reducing noise, speech recognition means for converting the audio data into text data, natural language processing means for analyzing the user's intentions and emotional state, and emotion analysis means. This makes it possible to accurately grasp the user's intentions and emotions and generate an optimal response in real time. Furthermore, by monitoring the vehicle's status and promptly issuing warnings to the user in the event of an abnormality, driving safety and peace of mind can be improved.

[0164] "Audio data" refers to information recorded in digital format, used for electronically processing audio signals.

[0165] "Means for reducing noise and extracting clear audio signals" refers to technologies and devices that minimize ambient noise and background noise to clarify audio signals.

[0166] "Speech recognition means" refers to a technology or device for analyzing received speech data and converting it into corresponding text data.

[0167] "Natural language processing" refers to technologies that analyze text data and understand the meaning and structure of language to identify the user's intent.

[0168] "Emotional analysis methods" refer to technologies that analyze emotional elements contained in voice data to identify the user's emotional state.

[0169] "Means for generating the optimal response" refers to technologies and systems that generate the most appropriate information and instructions based on the user's requests and circumstances.

[0170] "Monitoring" refers to the process of continuously observing a specific object to check for any changes or abnormalities.

[0171] "Notifying of an anomaly" refers to the act of informing the user of data or situations that deviate from the normal range.

[0172] This invention relates to a system for automotive navigation systems that analyzes user voice commands and emotions in real time and provides the optimal response. The system consists of the following elements:

[0173] First, the terminal receives the user's voice using a microphone installed inside the vehicle. The collected voice data is then processed into a clear audio signal using noise reduction technology. General-purpose noise-canceling software can be used for noise filtering.

[0174] Next, the speech data is converted into text data by a speech recognition engine. Speech recognition software such as Google Cloud Speech-to-Text can be used for this process.

[0175] Next, the server uses a generative AI model to analyze the text data using natural language processing and identify the user's intent. The generative AI model used here includes models from OpenAI. Based on the analysis results, the server processes the audio data with an emotion recognition engine to extract the user's emotional state.

[0176] Based on the extracted intent and emotions, the server quickly searches for the necessary information through information processing tools and generates the most appropriate response. This response is tailored to the user's emotional state and has the ability to adjust its content and tone of voice. The generated response is output by the terminal using a speech synthesis engine. In this process, text-to-speech solutions such as Amazon Polly are utilized.

[0177] The system also monitors data from various monitoring devices installed in the vehicle and has the capability to quickly notify the user in the event of an anomaly. For example, if a user says in an anxious tone, "I think I might be lost," the server will check the location information and generate a reassuring response such as, "We have confirmed your current location, you are safe, you can reach your destination by turning right at the next turn."

[0178] An example of a prompt message could be: "The user said 'I don't know the way' in an anxious tone. Please create a supportive response for them." This would allow the user to enjoy a comfortable and safe driving experience.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The terminal uses the in-car microphone to receive the user's voice. The input here is audio data including ambient noise, and noise filtering technology is used to reduce the noise and extract a clear audio signal. The output of this process is audio data with the noise removed.

[0182] Step 2:

[0183] The terminal inputs noise-reduced audio data into the speech recognition engine, which converts it into text data. The input data is the noise-reduced audio data, which is then output as structured text data through speech recognition. Through this conversion process, commands spoken during driving are captured as text information.

[0184] Step 3:

[0185] The server inputs text data it has acquired into a generating AI model, which then analyzes the user's intent. The input is text data from speech recognition results, and the generating AI model uses natural language processing to identify the user's intent. This analysis then outputs what the user wants in sentence form.

[0186] Step 4:

[0187] The server simultaneously inputs audio data into the emotion analysis engine to identify the user's emotional state. The input data is audio data containing voice features, and the emotional state is output as a label through analysis. This allows for an understanding of the user's emotional nuances.

[0188] Step 5:

[0189] Based on the identified user's intent and emotional state, the server utilizes information processing tools to retrieve necessary information and generate an optimal response. The input is the user's intent and emotional information, and the response is generated in text format while referencing relevant information. This output response includes content appropriate to the user's state.

[0190] Step 6:

[0191] The terminal receives a response from the server and outputs it as speech using a speech synthesis engine. The input is response data in text format, which is output as speech-playable data using speech synthesis technology. Through this process, the user can enjoy a natural conversation by ear.

[0192] Step 7:

[0193] The server receives data from various monitoring devices in the vehicle and monitors the vehicle's status. Input data comes from various sensors, and if an abnormality is detected, data is output to notify the user as an alarm. This ensures the user can always ensure the safety of their vehicle.

[0194] (Application Example 2)

[0195] 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".

[0196] Current car navigation systems lack sufficient user interaction that takes emotions into consideration, resulting in limited effectiveness in reducing driver stress. Furthermore, a system is needed that integrates visual and audio information to enable drivers to drive with greater peace of mind.

[0197] 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.

[0198] In this invention, the server includes voice recognition means, generation AI means, information processing means, and means for presenting visual information to the user via a visual display device. This enables natural dialogue that takes the user's emotions into consideration and flexible driving navigation that combines visual and auditory elements.

[0199] A "voice input device" is a device for receiving a user's voice as data.

[0200] "Speech recognition means" refers to technology that converts received speech data into text data.

[0201] "Generative AI means" refers to artificial intelligence technology that analyzes text data to identify the user's intentions and emotional state.

[0202] "Information processing means" refers to technology that retrieves necessary information based on the intent and emotions of an identified user and generates an appropriate response.

[0203] "Audio output means" refers to a technology for outputting the generated response as audio and presenting it to the user.

[0204] "Means of presenting visual information to a user via a visual display device" refers to a technology that provides necessary information to a user using a device that displays visual information.

[0205] "Vehicle sensors" refer to various sensing devices installed to monitor the vehicle's condition and surrounding environment.

[0206] A "communication network" is an electronic network infrastructure used to send and receive data.

[0207] An "external database" is a collection of information that exists outside the system and can be accessed via a network.

[0208] "Means of issuing warnings visually and audibly" refers to technologies that provide warnings visually or audibly.

[0209] "Route guidance" is the process of providing users with route information to reach their destination.

[0210] The present invention aims to realize a driver assistance system for users wearing smart glasses. The system comprises voice input means, voice recognition means, generation AI means, information processing means, and voice and visual output means.

[0211] The server converts user voice data received via voice input devices installed in the vehicle into text data using a speech recognition engine (such as the Google Speech-to-Text API). The resulting text data is then analyzed using generative AI (such as OpenAI's GPT model) to identify the user's intent and emotional state. This analysis utilizes sentiment analysis libraries such as NVIDIA's Riva AI.

[0212] The server generates optimal navigation information using information processing means based on the user's intentions and emotional state. The generated information is presented to the user via a visual display device. The navigation information displayed on the smart glasses is designed to be intuitively understandable both visually and audibly, with the color and emphasis adjusted according to the driver's emotions.

[0213] For example, if a user expresses anxiety and says, "I wish we could get there sooner," the AI ​​will recognize that emotion and provide relaxing scenery as visual information. In voice, it will respond in a soft tone, "We have found the optimal route based on current traffic information," to provide reassurance.

[0214] An example of a prompt for a generative AI model is: "User utterance: 'I wish we could get there sooner,' emotion: 'anxiety.' As a response, provide suggestions to reduce the user's psychological burden."

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] The terminal uses the in-car microphone to receive the user's voice. It acquires voice data as input and processes it into clear voice data using noise filtering technology. The filtered voice data is then sent to the server.

[0218] Step 2:

[0219] The server feeds the received audio data into the speech recognition engine. The speech recognition engine converts the audio data into text data, obtaining character information as output. This character information is used for the next analysis.

[0220] Step 3:

[0221] The server inputs text data into a generative AI model, which then analyzes the user's intent. The generative AI model uses natural language processing techniques to analyze the text and generate appropriate prompts for the user's intent and Anfrage. The analysis results are obtained as output.

[0222] Step 4:

[0223] Based on the analysis results, the server uses an emotion analysis library to analyze the tone and speed of the voice data to identify the user's emotions. The emotional state is obtained as output, and the process proceeds to the next step along with the output of the generative AI model.

[0224] Step 5:

[0225] The server uses information processing tools to plan the optimal response based on the user's intentions and emotional state. This includes accessing external databases containing real-time traffic information. The output is generated as a response to the user.

[0226] Step 6:

[0227] The server passes the generated response to the speech synthesis engine, which then generates a voice response. The output voice data is transmitted to the user via the terminal. The voice data is given a tone appropriate to the user's emotions.

[0228] Step 7:

[0229] The device uses smart glasses to present visual information to the user. It visualizes the response sent from the server and displays the information within the user's field of vision. The visual information is dynamically adjusted according to the driving situation.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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).

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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".

[0246] This invention provides a car navigation system that utilizes generative AI. The system includes voice input means, voice recognition means, generative AI means, information processing means, and voice output means. The operation of each of these means will be explained below with specific examples.

[0247] First, the device uses microphones placed inside the vehicle to receive voice from the user in real time. The voice input method employs voice filtering technology specifically designed for the in-vehicle environment to remove noise and clearly capture the user's speech.

[0248] Next, the terminal converts the audio received through the speech recognition means into text data. The speech recognition means uses a high-precision speech recognition engine and can minimize misrecognition by learning the user's past speech patterns.

[0249] Subsequently, the server uses a generative AI to analyze the text data transmitted from the speech recognition system. The generative AI uses natural language processing technology to identify the user's intent and extract the necessary information.

[0250] Based on the analysis results, the server uses information processing tools to access external databases and real-time traffic information to create a response suitable for the user's request. For example, if a user requests "Find the best route," the server calculates the shortest route considering the current traffic conditions.

[0251] Finally, the terminal synthesizes the generated response into speech using an audio output device and presents it to the user. The audio output device generates natural-sounding speech and sets appropriate speaker settings to ensure sound quality.

[0252] Furthermore, sensors mounted on the vehicle monitor its condition, and if an abnormality is detected, the terminal immediately sounds an alarm to the user and provides necessary corrective actions via voice. For example, if the tire pressure is low, it will notify the user, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0253] In this way, this invention enables intuitive and interactive responses that allow users to enjoy a safer and more comfortable driving experience.

[0254] The following describes the processing flow.

[0255] Step 1:

[0256] The device receives the user's voice through the in-car microphone. Here, a function that starts recording the moment a voice trigger word is recognized is activated. A noise reduction filter is also in operation to maintain optimal audio data quality.

[0257] Step 2:

[0258] The device converts voice data into text data via a speech recognition engine. The voice model performs highly accurate recognition, taking into account noise and echoes specific to the in-car environment. In addition, noise reduction is applied to the voice data as a preprocessing step.

[0259] Step 3:

[0260] The server sends text data to a generating AI. Here, the generating AI uses natural language processing techniques to analyze the user's intent from the text data and interpret its meaning. Once the intent is clearly identified, information is prepared for the next processing stage.

[0261] Step 4:

[0262] The server initiates a search for appropriate information based on the user's intent. It accesses external real-time traffic information, retrieves necessary information from vehicle sensor data and other relevant databases, and analyzes it using information processing tools to enable optimal decision-making.

[0263] Step 5:

[0264] The server collects the necessary information and uses generative AI to construct an appropriate response based on that information. Here, it generates instructions, route guidance, and problem-solving solutions in text in response to user requests.

[0265] Step 6:

[0266] The terminal sends the response text to the voice output device, which is then converted into natural-sounding speech using speech synthesis technology. The sound quality is adjusted to ensure the voice guidance is clear to the user, and it is then played back through the car's speakers.

[0267] Step 7:

[0268] The terminal continuously monitors vehicle sensors and immediately notifies the server if an anomaly is detected. This allows the user to receive voice warnings and specific countermeasures depending on the type of anomaly.

[0269] This series of processing steps allows users to interact with the system in a flexible manner and continue driving with peace of mind.

[0270] (Example 1)

[0271] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0272] Conventional car navigation systems suffer from problems such as low accuracy in voice recognition in noisy environments, leading to misinterpretation of user instructions, and the failure to provide timely information regarding vehicle malfunctions. In addition, they often struggle to provide dynamic information to quickly respond to real-time, changing traffic conditions.

[0273] 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.

[0274] In this invention, the server includes means for receiving the user's voice while removing ambient noise using a voice input device, means for converting the voice data received by the voice input device into text information, and generation AI means including natural language processing technology for analyzing the text information and identifying the user's intent. This improves the accuracy of voice recognition and enables dynamic and accurate navigation that takes traffic information into account in real time.

[0275] The "voice input device" generally refers to all devices for receiving voice from users and converting it into digital data.

[0276] "Voice data" refers to the digital representation of acoustic signals captured through a voice input device. <​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​The present invention provides a vehicle navigation system based on generative AI technology. The system includes a voice input device, a voice recognition means, a generative AI means, an information processing means, and a voice output means.

[0287] The terminal receives a voice command from the user using a voice input device installed in the vehicle. For this, voice filtering technology for reducing ambient noise is used. For example, engine noise and road noise are reduced by a noise cancellation algorithm.

[0288] When the voice is acquired, the terminal converts the voice data into character information using a high-precision voice recognition engine. As a result, the content of the user's speech is clearly identified, and past speech patterns are also considered to improve the recognition accuracy.

[0289] Subsequently, the server receives the character information transmitted from the voice recognition means and performs analysis using the generative AI means. By natural language processing technology, the user's intention is identified and the necessary information is extracted. As a specific example, when the user issues a command "Find the shortest route", the generative AI performs analysis based on it.

[0290] The server uses the information processing means to access an external information source and acquire the necessary data. By referring to a database including real-time traffic information, it creates an optimal route guidance for the user. As a result, quick and accurate navigation information is generated.

[0291] Finally, the generated response is presented to the user by the terminal through voice synthesis technology. In this process, the volume and tone are adjusted so that natural and easy-to-hear voice is generated.

[0292] Furthermore, the terminal constantly monitors information collected by multiple sensors installed in the vehicle and notifies the user in real time if an abnormality is detected. For example, if the tire pressure drops, it will issue a warning such as, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0293] This system allows users to enjoy an intuitive and interactive navigation experience, supporting safer and more comfortable driving.

[0294] Example of a prompt:

[0295] "Find the shortest route"

[0296] "Can you tell me the nearest gas station?"

[0297] "Turn right at the next intersection."

[0298] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0299] Step 1:

[0300] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. The input is the user's voice, which includes ambient noise. The voice input device uses a noise cancellation algorithm to remove the noise and obtain a clear voice signal. The output is the processed voice data.

[0301] Step 2:

[0302] The device utilizes speech recognition to convert the audio data obtained in Step 1 into text information. This process employs a highly accurate speech recognition engine. The input is the processed audio data, and the output is text information. Specifically, if the user voice-inputs "Find the best route," the output will be a text representation of that statement.

[0303] Step 3:

[0304] The server receives the character information sent from the voice recognition means. The input is the recognized character information. The server performs natural language processing using the generation AI means to identify the user's intention. In this process, important information is extracted from the user's words and the user's request is analyzed. The output is the request information based on the analyzed user's intention and its content.

[0305] Step 4:

[0306] The server uses the information processing means to access external information sources and real-time traffic information based on the user's intention obtained in Step 3. The input is the user's request information. The server obtains the necessary data and generates a response to the user's request. For example, for a request such as "Find the shortest route", the server calculates the optimal route considering the real-time traffic situation. The output is the response information to be provided to the user.

[0307] Step 5:

[0308] The terminal outputs the generated response information in voice using voice synthesis technology. The input is the response information from the server. The output is the synthesized voice message with adjusted volume and tone. As a specific operation, the terminal guides the user by voice, saying "The current optimal route is via Route A".

[0309] Step 6:

[0310] The terminal monitors the data from the detector mounted on the vehicle. The input is the sensor information indicating the state of the vehicle. When an abnormality is detected, a warning is sounded to the user based on that information. For example, when it is detected that the tire pressure has dropped, a warning such as "The tire pressure of the right front tire has dropped. Please have it checked at the nearest service station" is provided by voice. The output is the voice notification to the user.

[0311] (Application Example 1)

[0312] 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."

[0313] A major problem with autonomous vehicles is the lack of navigation systems that allow passengers to intuitively specify their destinations. Furthermore, there is a need for methods to provide fast and accurate route guidance utilizing real-time traffic information, but this is not yet adequately implemented. This hinders a comfortable and efficient travel experience.

[0314] 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.

[0315] In this invention, the server includes a speech recognition means that converts speech data received by a voice input means into text data, a generation AI means that analyzes the text data obtained by the speech recognition means to identify the user's intent, and a navigation means that calculates the optimal route based on traffic information acquired via a communication network. As a result, passengers can obtain quick and optimal route guidance simply by indicating their destination by voice.

[0316] "Voice input means" refers to a device or method for receiving voice data from a user.

[0317] "Speech recognition means" refers to a technology or device that analyzes received speech data and converts it into text data.

[0318] "Generative AI means" refers to artificial intelligence technology that analyzes text data obtained through speech recognition and interprets its intent.

[0319] "Information processing means" refers to a mechanism or software for retrieving necessary information and generating a response based on the intent identified by the generating AI means.

[0320] "Audio output means" refers to a technology or device for converting a generated response into audio and presenting it to the user.

[0321] An "autonomous vehicle" is a vehicle that can autonomously travel to its destination without the need for human intervention.

[0322] A "navigation system" is a technology or system that calculates and guides the optimal route to a destination based on traffic information and map data.

[0323] A "communication network" is a network infrastructure used to send and receive information.

[0324] "Route guidance" refers to information that directs the travel route from the starting point to the destination.

[0325] This invention implements a navigation system for autonomous vehicles that utilizes generative AI. The system includes a microphone for receiving voice input, a speech recognition engine for converting speech to text, a generative AI engine that utilizes advanced AI, an information processing device for acquiring traffic information and calculating a route, and a speaker for outputting the results as voice.

[0326] The server converts the audio data into text data using Google or an equivalent speech recognition API. The converted text data is then analyzed using a generative AI model (such as OpenAI's GPT-3) to identify the user's intent. This generative AI model enables advanced natural language analysis and can handle ambiguous requests from users.

[0327] The server then accesses an external traffic database via a communication network and retrieves real-time traffic information as needed. Based on this, the system calculates the optimal route. This process uses programming languages ​​and libraries such as Python and TensorFlow.

[0328] Once the optimal route is determined, the terminal provides instructions to the user using a voice output device. The voice is generated using speech synthesis technology that simulates natural pronunciation.

[0329] Specific example: For instance, if a user in an autonomous vehicle gives a voice command such as "Tell me the shortest route to the airport," the generating AI analyzes this command, and the server calculates the optimal route based on traffic information obtained from an external database. This route guidance is then provided to the user via voice.

[0330] Example prompt: "Please tell me the fastest route to the city center that avoids congestion."

[0331] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0332] Step 1:

[0333] The terminal receives voice input from the user via a microphone placed inside the vehicle. The input is voice data in which the user makes navigation requests. The terminal uses noise filtering technology to clarify this voice data and prepare accurate input data.

[0334] Step 2:

[0335] The server uses a speech recognition engine to convert the audio data into text data. The input is the audio data filtered in step 1, and the output is text data representing the user's utterance. This formats the data so that it can be used in subsequent processing.

[0336] Step 3:

[0337] The server uses a generative AI model to analyze the converted text data and identify the user's intent. The input is the text data obtained in step 2, and the output is the analysis result that defines the user's intent. By utilizing generative AI, even ambiguous requests can be understood with high accuracy.

[0338] Step 4:

[0339] The server uses a communication network to access an external traffic database and obtain the latest traffic information. The input is the user's intent identified in step 3. The output is real-time information about traffic conditions, providing a basis for calculating the optimal route.

[0340] Step 5:

[0341] The server calculates the optimal route based on traffic information and analysis results. The input is the traffic information obtained in step 4 and the user's intent, and the output is specific route guidance information. Python and its libraries are used for the calculations.

[0342] Step 6:

[0343] The terminal converts the calculated route guidance into speech using speech synthesis technology and provides it to the user. The input is the route guidance information calculated in step 5, and the output is the voice route guidance. The user can reach their destination based on this.

[0344] 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.

[0345] This invention provides a more advanced interactive experience by combining a car navigation system that utilizes generative AI with an emotion engine that recognizes user emotions. The system takes the form of a voice input means, a voice recognition means, a generative AI means, an information processing means, a voice output means, and an emotion recognition means.

[0346] First, the device receives the user's voice via the in-car microphone. The voice undergoes noise filtering and is converted into text data by speech recognition. This text data is then analyzed by a generative AI.

[0347] Next, the server uses AI generation tools to identify the user's intent, and then analyzes the voice data using emotion recognition tools to understand the user's emotional state. The emotion engine analyzes elements such as tone, speed, and volume of the voice to identify emotions such as joy, anger, sadness, and happiness.

[0348] Once the user's intentions and emotions are identified, the server uses that information to search for necessary information in real time and generate the most appropriate response for the user's current situation. This includes adjusting the content and tone of voice according to the user's emotional state.

[0349] For example, if a user says in an anxious tone, "I think I might be lost," the server will check their location in real time and generate a reassuring response in a soft tone, such as, "I've confirmed your current location, you're safe, you can reach your destination by turning right at the next turn."

[0350] This allows the device to communicate responses to the user using voice output. Utilizing speech synthesis technology, it provides natural-sounding dialogue that takes the user's emotions into consideration, even though it uses synthesized speech.

[0351] Furthermore, the system monitors various sensors in the vehicle, and if an abnormality is detected, that information is also included in the response to the user. For example, to help the user react calmly, it might issue instructions such as, "The engine temperature is above normal; please decelerate immediately."

[0352] This system allows users to enjoy emotionally responsive and flexible support, enabling them to drive their vehicles with peace of mind.

[0353] The following describes the processing flow.

[0354] Step 1:

[0355] The device receives the user's voice through a microphone installed inside the vehicle. The microphone uses a filter to reduce ambient noise, ensuring clear audio data. This audio data is then transmitted in real time to the speech recognition process.

[0356] Step 2:

[0357] The device uses speech recognition to convert received audio data into text data. This process generates an accurate textual representation of the user's speech, shaping it in a way that facilitates subsequent analysis and processing.

[0358] Step 3:

[0359] The server sends the text data obtained through speech recognition to a generating AI system, which then analyzes the user's intent. This analysis uses natural language processing techniques and focuses on identifying what the user wants from the system.

[0360] Step 4:

[0361] The server simultaneously processes the audio data using emotion recognition tools to identify the user's emotional state. This process analyzes the tone, pitch, and speed of the voice to classify the user's state, such as happy, anxious, or angry.

[0362] Step 5:

[0363] The server uses information processing tools to retrieve necessary information based on the user's intent and emotional state. It integrates real-time traffic information, vehicle sensor data, and other relevant information tailored to the user's needs to generate an appropriate response for the user.

[0364] Step 6:

[0365] The server generates a response, which is then adjusted according to the user's emotions and finally converted into text format necessary for audio output. This step prepares the system to output considerate information, such as matching the wording and tone to the user's emotions.

[0366] Step 7:

[0367] The device uses a voice output device to synthesize prepared response text into speech and transmit it to the user as audio. The synthesized speech is played in a soft, gentle tone, allowing the user to receive information in a way that is considerate of their emotions.

[0368] This process ensures that users always feel secure while obtaining information, and the system provides interaction that is attentive to the user's emotions.

[0369] (Example 2)

[0370] 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".

[0371] In the automotive driving environment, conventional navigation systems have struggled to accurately understand user voice commands and emotions and provide appropriate responses in real time. Furthermore, the lack of means to provide flexible responses tailored to the user's psychological state raised concerns about reduced safety and ease of operation while driving. Additionally, there were limitations to their ability to monitor vehicle status and promptly notify of abnormalities.

[0372] 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.

[0373] In this invention, the server includes means for receiving audio data and extracting a clear audio signal by reducing noise, speech recognition means for converting the audio data into text data, natural language processing means for analyzing the user's intentions and emotional state, and emotion analysis means. This makes it possible to accurately grasp the user's intentions and emotions and generate an optimal response in real time. Furthermore, by monitoring the vehicle's status and promptly issuing warnings to the user in the event of an abnormality, driving safety and peace of mind can be improved.

[0374] "Audio data" refers to information recorded in digital format, used for electronically processing audio signals.

[0375] "Means for reducing noise and extracting clear audio signals" refers to technologies and devices that minimize ambient noise and background noise to clarify audio signals.

[0376] "Speech recognition means" refers to a technology or device for analyzing received speech data and converting it into corresponding text data.

[0377] "Natural language processing" refers to technologies that analyze text data and understand the meaning and structure of language to identify the user's intent.

[0378] "Emotional analysis methods" refer to technologies that analyze emotional elements contained in voice data to identify the user's emotional state.

[0379] "Means for generating the optimal response" refers to technologies and systems that generate the most appropriate information and instructions based on the user's requests and circumstances.

[0380] "Monitoring" refers to the process of continuously observing a specific object to check for any changes or abnormalities.

[0381] "Notifying of an anomaly" refers to the act of informing the user of data or situations that deviate from the normal range.

[0382] This invention relates to a system for automotive navigation systems that analyzes user voice commands and emotions in real time and provides the optimal response. The system consists of the following elements:

[0383] First, the terminal receives the user's voice using a microphone installed inside the vehicle. The collected voice data is then processed into a clear audio signal using noise reduction technology. General-purpose noise-canceling software can be used for noise filtering.

[0384] Next, the speech data is converted into text data by a speech recognition engine. Speech recognition software such as Google Cloud Speech-to-Text can be used for this process.

[0385] Next, the server uses a generative AI model to analyze the text data using natural language processing and identify the user's intent. The generative AI model used here includes models from OpenAI. Based on the analysis results, the server processes the audio data with an emotion recognition engine to extract the user's emotional state.

[0386] Based on the extracted intent and emotions, the server quickly searches for the necessary information through information processing tools and generates the most appropriate response. This response is tailored to the user's emotional state and has the ability to adjust its content and tone of voice. The generated response is output by the terminal using a speech synthesis engine. In this process, text-to-speech solutions such as Amazon Polly are utilized.

[0387] The system also monitors data from various monitoring devices installed in the vehicle and has the capability to quickly notify the user in the event of an anomaly. For example, if a user says in an anxious tone, "I think I might be lost," the server will check the location information and generate a reassuring response such as, "We have confirmed your current location, you are safe, you can reach your destination by turning right at the next turn."

[0388] An example of a prompt message could be: "The user said 'I don't know the way' in an anxious tone. Please create a supportive response for them." This would allow the user to enjoy a comfortable and safe driving experience.

[0389] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0390] Step 1:

[0391] The terminal uses the in-car microphone to receive the user's voice. The input here is audio data including ambient noise, and noise filtering technology is used to reduce the noise and extract a clear audio signal. The output of this process is audio data with the noise removed.

[0392] Step 2:

[0393] The terminal inputs noise-reduced audio data into the speech recognition engine, which converts it into text data. The input data is the noise-reduced audio data, which is then output as structured text data through speech recognition. Through this conversion process, commands spoken during driving are captured as text information.

[0394] Step 3:

[0395] The server inputs text data it has acquired into a generating AI model, which then analyzes the user's intent. The input is text data from speech recognition results, and the generating AI model uses natural language processing to identify the user's intent. This analysis then outputs what the user wants in sentence form.

[0396] Step 4:

[0397] The server simultaneously inputs audio data into the emotion analysis engine to identify the user's emotional state. The input data is audio data containing voice features, and the emotional state is output as a label through analysis. This allows for an understanding of the user's emotional nuances.

[0398] Step 5:

[0399] Based on the identified user's intent and emotional state, the server utilizes information processing tools to retrieve necessary information and generate an optimal response. The input is the user's intent and emotional information, and the response is generated in text format while referencing relevant information. This output response includes content appropriate to the user's state.

[0400] Step 6:

[0401] The terminal receives a response from the server and outputs it as speech using a speech synthesis engine. The input is response data in text format, which is output as speech-playable data using speech synthesis technology. Through this process, the user can enjoy a natural conversation by ear.

[0402] Step 7:

[0403] The server receives data from various monitoring devices in the vehicle and monitors the vehicle's status. Input data comes from various sensors, and if an abnormality is detected, data is output to notify the user as an alarm. This ensures the user can always ensure the safety of their vehicle.

[0404] (Application Example 2)

[0405] 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."

[0406] Current car navigation systems lack sufficient user interaction that takes emotions into consideration, resulting in limited effectiveness in reducing driver stress. Furthermore, a system is needed that integrates visual and audio information to enable drivers to drive with greater peace of mind.

[0407] 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.

[0408] In this invention, the server includes voice recognition means, generation AI means, information processing means, and means for presenting visual information to the user via a visual display device. This enables natural dialogue that takes the user's emotions into consideration and flexible driving navigation that combines visual and auditory elements.

[0409] A "voice input device" is a device for receiving a user's voice as data.

[0410] "Speech recognition means" refers to technology that converts received speech data into text data.

[0411] "Generative AI means" refers to artificial intelligence technology that analyzes text data to identify the user's intentions and emotional state.

[0412] "Information processing means" refers to technology that retrieves necessary information based on the intent and emotions of an identified user and generates an appropriate response.

[0413] "Audio output means" refers to a technology for outputting the generated response as audio and presenting it to the user.

[0414] "Means of presenting visual information to a user via a visual display device" refers to a technology that provides necessary information to a user using a device that displays visual information.

[0415] "Vehicle sensors" refer to various sensing devices installed to monitor the vehicle's condition and surrounding environment.

[0416] A "communication network" is an electronic network infrastructure used to send and receive data.

[0417] An "external database" is a collection of information that exists outside the system and can be accessed via a network.

[0418] "Means of issuing warnings visually and audibly" refers to technologies that provide warnings visually or audibly.

[0419] "Route guidance" is the process of providing users with route information to reach their destination.

[0420] The present invention aims to realize a driver assistance system for users wearing smart glasses. The system comprises voice input means, voice recognition means, generation AI means, information processing means, and voice and visual output means.

[0421] The server converts user voice data received via voice input devices installed in the vehicle into text data using a speech recognition engine (such as the Google Speech-to-Text API). The resulting text data is then analyzed using generative AI (such as OpenAI's GPT model) to identify the user's intent and emotional state. This analysis utilizes sentiment analysis libraries such as NVIDIA's Riva AI.

[0422] The server generates optimal navigation information using information processing means based on the user's intentions and emotional state. The generated information is presented to the user via a visual display device. The navigation information displayed on the smart glasses is designed to be intuitively understandable both visually and audibly, with the color and emphasis adjusted according to the driver's emotions.

[0423] For example, if a user expresses anxiety and says, "I wish we could get there sooner," the AI ​​will recognize that emotion and provide relaxing scenery as visual information. In voice, it will respond in a soft tone, "We have found the optimal route based on current traffic information," to provide reassurance.

[0424] An example of a prompt for a generative AI model is: "User utterance: 'I wish we could get there sooner,' emotion: 'anxiety.' As a response, provide suggestions to reduce the user's psychological burden."

[0425] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0426] Step 1:

[0427] The terminal uses the in-car microphone to receive the user's voice. It acquires voice data as input and processes it into clear voice data using noise filtering technology. The filtered voice data is then sent to the server.

[0428] Step 2:

[0429] The server feeds the received audio data into the speech recognition engine. The speech recognition engine converts the audio data into text data, obtaining character information as output. This character information is used for the next analysis.

[0430] Step 3:

[0431] The server inputs text data into a generative AI model, which then analyzes the user's intent. The generative AI model uses natural language processing techniques to analyze the text and generate appropriate prompts for the user's intent and Anfrage. The analysis results are obtained as output.

[0432] Step 4:

[0433] Based on the analysis results, the server uses an emotion analysis library to analyze the tone and speed of the voice data to identify the user's emotions. The emotional state is obtained as output, and the process proceeds to the next step along with the output of the generative AI model.

[0434] Step 5:

[0435] The server uses information processing tools to plan the optimal response based on the user's intentions and emotional state. This includes accessing external databases containing real-time traffic information. The output is generated as a response to the user.

[0436] Step 6:

[0437] The server passes the generated response to the speech synthesis engine, which then generates a voice response. The output voice data is transmitted to the user via the terminal. The voice data is given a tone appropriate to the user's emotions.

[0438] Step 7:

[0439] The device uses smart glasses to present visual information to the user. It visualizes the response sent from the server and displays the information within the user's field of vision. The visual information is dynamically adjusted according to the driving situation.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] [Third Embodiment]

[0444] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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).

[0450] 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.

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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".

[0456] This invention provides a car navigation system that utilizes generative AI. The system includes voice input means, voice recognition means, generative AI means, information processing means, and voice output means. The operation of each of these means will be explained below with specific examples.

[0457] First, the device uses microphones placed inside the vehicle to receive voice from the user in real time. The voice input method employs voice filtering technology specifically designed for the in-vehicle environment to remove noise and clearly capture the user's speech.

[0458] Next, the terminal converts the audio received through the speech recognition means into text data. The speech recognition means uses a high-precision speech recognition engine and can minimize misrecognition by learning the user's past speech patterns.

[0459] Subsequently, the server uses a generative AI to analyze the text data transmitted from the speech recognition system. The generative AI uses natural language processing technology to identify the user's intent and extract the necessary information.

[0460] Based on the analysis results, the server uses information processing tools to access external databases and real-time traffic information to create a response suitable for the user's request. For example, if a user requests "Find the best route," the server calculates the shortest route considering the current traffic conditions.

[0461] Finally, the terminal synthesizes the generated response into speech using an audio output device and presents it to the user. The audio output device generates natural-sounding speech and sets appropriate speaker settings to ensure sound quality.

[0462] Furthermore, sensors mounted on the vehicle monitor its condition, and if an abnormality is detected, the terminal immediately sounds an alarm to the user and provides necessary corrective actions via voice. For example, if the tire pressure is low, it will notify the user, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0463] In this way, this invention enables intuitive and interactive responses that allow users to enjoy a safer and more comfortable driving experience.

[0464] The following describes the processing flow.

[0465] Step 1:

[0466] The device receives the user's voice through the in-car microphone. Here, a function that starts recording the moment a voice trigger word is recognized is activated. A noise reduction filter is also in operation to maintain optimal audio data quality.

[0467] Step 2:

[0468] The device converts voice data into text data via a speech recognition engine. The voice model performs highly accurate recognition, taking into account noise and echoes specific to the in-car environment. In addition, noise reduction is applied to the voice data as a preprocessing step.

[0469] Step 3:

[0470] The server sends text data to a generating AI. Here, the generating AI uses natural language processing techniques to analyze the user's intent from the text data and interpret its meaning. Once the intent is clearly identified, information is prepared for the next processing stage.

[0471] Step 4:

[0472] The server initiates a search for appropriate information based on the user's intent. It accesses external real-time traffic information, retrieves necessary information from vehicle sensor data and other relevant databases, and analyzes it using information processing tools to enable optimal decision-making.

[0473] Step 5:

[0474] The server collects the necessary information and uses generative AI to construct an appropriate response based on that information. Here, it generates instructions, route guidance, and problem-solving solutions in text in response to user requests.

[0475] Step 6:

[0476] The terminal sends the response text to the voice output device, which is then converted into natural-sounding speech using speech synthesis technology. The sound quality is adjusted to ensure the voice guidance is clear to the user, and it is then played back through the car's speakers.

[0477] Step 7:

[0478] The terminal continuously monitors vehicle sensors and immediately notifies the server if an anomaly is detected. This allows the user to receive voice warnings and specific countermeasures depending on the type of anomaly.

[0479] This series of processing steps allows users to interact with the system in a flexible manner and continue driving with peace of mind.

[0480] (Example 1)

[0481] 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."

[0482] Conventional car navigation systems suffer from problems such as low accuracy in voice recognition in noisy environments, leading to misinterpretation of user instructions, and the failure to provide timely information regarding vehicle malfunctions. In addition, they often struggle to provide dynamic information to quickly respond to real-time, changing traffic conditions.

[0483] 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.

[0484] In this invention, the server includes means for receiving the user's voice while removing ambient noise using a voice input device, means for converting the voice data received by the voice input device into text information, and generation AI means including natural language processing technology for analyzing the text information and identifying the user's intent. This improves the accuracy of voice recognition and enables dynamic and accurate navigation that takes traffic information into account in real time.

[0485] "Voice input devices" refer to all devices that receive voice from users and convert it into digital data.

[0486] "Audio data" refers to the digital representation of an audio signal captured through an audio input device.

[0487] "Textual information" refers to text data converted from audio data by speech recognition technology.

[0488] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and respond to human natural language.

[0489] "Generative AI means" refers to artificial intelligence technology that understands user intent and organizes and generates information based on that intent.

[0490] "External information sources" refer to all external information databases that are accessible via the internet or other communication networks.

[0491] "Real-time traffic information" refers to information about current traffic conditions that is updated in real time.

[0492] "Speech synthesis technology" refers to the technology that generates natural-sounding speech using text data.

[0493] The term "detector" refers to any sensor that measures various conditions of a vehicle and outputs them as digital data.

[0494] "Detecting a malfunction" refers to using sensors or other means to determine abnormal conditions or failures that deviate from the vehicle's normal operating state.

[0495] "Information transmission network" refers to all communication networks, including the internet and other protocols.

[0496] This invention provides a vehicle navigation system based on generative AI technology. The system includes a voice input device, voice recognition means, generative AI means, information processing means, and voice output means.

[0497] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. This uses voice filtering technology to reduce ambient noise. For example, noise cancellation algorithms reduce engine noise and road noise.

[0498] Once audio is acquired, the device uses a high-precision speech recognition engine to convert the audio data into text. This ensures that the user's utterances are clearly identified, and by considering past speech patterns, recognition accuracy is improved.

[0499] Next, the server receives the text information transmitted from the speech recognition system and performs analysis using a generative AI system. Natural language processing technology identifies the user's intent and extracts the necessary information. For example, if the user issues the command "Find the shortest route," the generative AI performs analysis based on that command.

[0500] The server uses information processing tools to access external information sources and retrieve necessary data. It refers to a database containing real-time traffic information and creates the optimal route guidance for the user. As a result, fast and accurate navigation information is generated.

[0501] Finally, the generated response is presented to the user by the device using speech synthesis technology. During this process, the volume and tone are adjusted to produce a natural and easy-to-understand voice.

[0502] Furthermore, the terminal constantly monitors information collected by multiple sensors installed in the vehicle and notifies the user in real time if an abnormality is detected. For example, if the tire pressure drops, it will issue a warning such as, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0503] This system allows users to enjoy an intuitive and interactive navigation experience, supporting safer and more comfortable driving.

[0504] Example of a prompt:

[0505] "Find the shortest route"

[0506] "Can you tell me the nearest gas station?"

[0507] "Turn right at the next intersection."

[0508] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0509] Step 1:

[0510] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. The input is the user's voice, which includes ambient noise. The voice input device uses a noise cancellation algorithm to remove the noise and obtain a clear voice signal. The output is the processed voice data.

[0511] Step 2:

[0512] The device utilizes speech recognition to convert the audio data obtained in Step 1 into text information. This process employs a highly accurate speech recognition engine. The input is the processed audio data, and the output is text information. Specifically, if the user voice-inputs "Find the best route," the output will be a text representation of that statement.

[0513] Step 3:

[0514] The server receives text information transmitted from the speech recognition system. The input is the recognized text information. The server uses generative AI to perform natural language processing and identify the user's intent. In this process, important information is extracted from the user's words and the user's request is analyzed. The output is the request information based on the analyzed user intent and its content.

[0515] Step 4:

[0516] The server uses information processing tools to access external information sources and real-time traffic information based on the user's intent obtained in step 3. The input is the user's request information. The server retrieves the necessary data and generates a response to the user's request. For example, in response to the request "Find the shortest route," the server calculates the optimal route considering real-time traffic conditions. The output is the response information provided to the user.

[0517] Step 5:

[0518] The terminal outputs the generated response information as speech using speech synthesis technology. The input is the response information from the server. The output is a synthesized speech message with adjusted volume and tone. Specifically, the terminal will inform the user via voice, "The best route at the moment is via Street A."

[0519] Step 6:

[0520] The terminal monitors data from sensors installed in the vehicle. The input is sensor information indicating the vehicle's status. If an abnormality is detected, it will sound a warning to the user based on that information. For example, if it detects that the tire pressure has dropped, it will provide a voice warning such as, "The air pressure in the front right tire is low. Please have it checked at the nearest service station." The output is a voice notification to the user.

[0521] (Application Example 1)

[0522] 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."

[0523] A major problem with autonomous vehicles is the lack of navigation systems that allow passengers to intuitively specify their destinations. Furthermore, there is a need for methods to provide fast and accurate route guidance utilizing real-time traffic information, but this is not yet adequately implemented. This hinders a comfortable and efficient travel experience.

[0524] 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.

[0525] In this invention, the server includes a speech recognition means that converts speech data received by a voice input means into text data, a generation AI means that analyzes the text data obtained by the speech recognition means to identify the user's intent, and a navigation means that calculates the optimal route based on traffic information acquired via a communication network. As a result, passengers can obtain quick and optimal route guidance simply by indicating their destination by voice.

[0526] "Voice input means" refers to a device or method for receiving voice data from a user.

[0527] "Speech recognition means" refers to a technology or device that analyzes received speech data and converts it into text data.

[0528] "Generative AI means" refers to artificial intelligence technology that analyzes text data obtained through speech recognition and interprets its intent.

[0529] "Information processing means" refers to a mechanism or software for retrieving necessary information and generating a response based on the intent identified by the generating AI means.

[0530] "Audio output means" refers to a technology or device for converting a generated response into audio and presenting it to the user.

[0531] An "autonomous vehicle" is a vehicle that can autonomously travel to its destination without the need for human intervention.

[0532] A "navigation system" is a technology or system that calculates and guides the optimal route to a destination based on traffic information and map data.

[0533] A "communication network" is a network infrastructure used to send and receive information.

[0534] "Route guidance" refers to information that directs the travel route from the starting point to the destination.

[0535] This invention implements a navigation system for autonomous vehicles that utilizes generative AI. The system includes a microphone for receiving voice input, a speech recognition engine for converting speech to text, a generative AI engine that utilizes advanced AI, an information processing device for acquiring traffic information and calculating a route, and a speaker for outputting the results as voice.

[0536] The server converts the audio data into text data using Google or an equivalent speech recognition API. The converted text data is then analyzed using a generative AI model (such as OpenAI's GPT-3) to identify the user's intent. This generative AI model enables advanced natural language analysis and can handle ambiguous requests from users.

[0537] The server then accesses an external traffic database via a communication network and retrieves real-time traffic information as needed. Based on this, the system calculates the optimal route. This process uses programming languages ​​and libraries such as Python and TensorFlow.

[0538] Once the optimal route is determined, the terminal provides instructions to the user using a voice output device. The voice is generated using speech synthesis technology that simulates natural pronunciation.

[0539] Specific example: For instance, if a user in an autonomous vehicle gives a voice command such as "Tell me the shortest route to the airport," the generating AI analyzes this command, and the server calculates the optimal route based on traffic information obtained from an external database. This route guidance is then provided to the user via voice.

[0540] Example prompt: "Please tell me the fastest route to the city center that avoids congestion."

[0541] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0542] Step 1:

[0543] The terminal receives voice input from the user via a microphone placed inside the vehicle. The input is voice data in which the user makes navigation requests. The terminal uses noise filtering technology to clarify this voice data and prepare accurate input data.

[0544] Step 2:

[0545] The server uses a speech recognition engine to convert the audio data into text data. The input is the audio data filtered in step 1, and the output is text data representing the user's utterance. This formats the data so that it can be used in subsequent processing.

[0546] Step 3:

[0547] The server uses a generative AI model to analyze the converted text data and identify the user's intent. The input is the text data obtained in step 2, and the output is the analysis result that defines the user's intent. By utilizing generative AI, even ambiguous requests can be understood with high accuracy.

[0548] Step 4:

[0549] The server uses a communication network to access an external traffic database and obtain the latest traffic information. The input is the user's intent identified in step 3. The output is real-time information about traffic conditions, providing a basis for calculating the optimal route.

[0550] Step 5:

[0551] The server calculates the optimal route based on traffic information and analysis results. The input is the traffic information obtained in step 4 and the user's intent, and the output is specific route guidance information. Python and its libraries are used for the calculations.

[0552] Step 6:

[0553] The terminal converts the calculated route guidance into speech using speech synthesis technology and provides it to the user. The input is the route guidance information calculated in step 5, and the output is the voice route guidance. The user can reach their destination based on this.

[0554] 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.

[0555] This invention provides a more advanced interactive experience by combining a car navigation system that utilizes generative AI with an emotion engine that recognizes user emotions. The system takes the form of a voice input means, a voice recognition means, a generative AI means, an information processing means, a voice output means, and an emotion recognition means.

[0556] First, the device receives the user's voice via the in-car microphone. The voice undergoes noise filtering and is converted into text data by speech recognition. This text data is then analyzed by a generative AI.

[0557] Next, the server uses AI generation tools to identify the user's intent, and then analyzes the voice data using emotion recognition tools to understand the user's emotional state. The emotion engine analyzes elements such as tone, speed, and volume of the voice to identify emotions such as joy, anger, sadness, and happiness.

[0558] Once the user's intentions and emotions are identified, the server uses that information to search for necessary information in real time and generate the most appropriate response for the user's current situation. This includes adjusting the content and tone of voice according to the user's emotional state.

[0559] For example, if a user says in an anxious tone, "I think I might be lost," the server will check their location in real time and generate a reassuring response in a soft tone, such as, "I've confirmed your current location, you're safe, you can reach your destination by turning right at the next turn."

[0560] This allows the device to communicate responses to the user using voice output. Utilizing speech synthesis technology, it provides natural-sounding dialogue that takes the user's emotions into consideration, even though it uses synthesized speech.

[0561] Furthermore, the system monitors various sensors in the vehicle, and if an abnormality is detected, that information is also included in the response to the user. For example, to help the user react calmly, it might issue instructions such as, "The engine temperature is above normal; please decelerate immediately."

[0562] This system allows users to enjoy emotionally responsive and flexible support, enabling them to drive their vehicles with peace of mind.

[0563] The following describes the processing flow.

[0564] Step 1:

[0565] The device receives the user's voice through a microphone installed inside the vehicle. The microphone uses a filter to reduce ambient noise, ensuring clear audio data. This audio data is then transmitted in real time to the speech recognition process.

[0566] Step 2:

[0567] The device uses speech recognition to convert received audio data into text data. This process generates an accurate textual representation of the user's speech, shaping it in a way that facilitates subsequent analysis and processing.

[0568] Step 3:

[0569] The server sends the text data obtained through speech recognition to a generating AI system, which then analyzes the user's intent. This analysis uses natural language processing techniques and focuses on identifying what the user wants from the system.

[0570] Step 4:

[0571] The server simultaneously processes the audio data using emotion recognition tools to identify the user's emotional state. This process analyzes the tone, pitch, and speed of the voice to classify the user's state, such as happy, anxious, or angry.

[0572] Step 5:

[0573] The server uses information processing tools to retrieve necessary information based on the user's intent and emotional state. It integrates real-time traffic information, vehicle sensor data, and other relevant information tailored to the user's needs to generate an appropriate response for the user.

[0574] Step 6:

[0575] The server generates a response, which is then adjusted according to the user's emotions and finally converted into text format necessary for audio output. This step prepares the system to output considerate information, such as matching the wording and tone to the user's emotions.

[0576] Step 7:

[0577] The device uses a voice output device to synthesize prepared response text into speech and transmit it to the user as audio. The synthesized speech is played in a soft, gentle tone, allowing the user to receive information in a way that is considerate of their emotions.

[0578] This process ensures that users always feel secure while obtaining information, and the system provides interaction that is attentive to the user's emotions.

[0579] (Example 2)

[0580] 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."

[0581] In the automotive driving environment, conventional navigation systems have struggled to accurately understand user voice commands and emotions and provide appropriate responses in real time. Furthermore, the lack of means to provide flexible responses tailored to the user's psychological state raised concerns about reduced safety and ease of operation while driving. Additionally, there were limitations to their ability to monitor vehicle status and promptly notify of abnormalities.

[0582] 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.

[0583] In this invention, the server includes means for receiving audio data and extracting a clear audio signal by reducing noise, speech recognition means for converting the audio data into text data, natural language processing means for analyzing the user's intentions and emotional state, and emotion analysis means. This makes it possible to accurately grasp the user's intentions and emotions and generate an optimal response in real time. Furthermore, by monitoring the vehicle's status and promptly issuing warnings to the user in the event of an abnormality, driving safety and peace of mind can be improved.

[0584] "Audio data" refers to information recorded in digital format, used for electronically processing audio signals.

[0585] "Means for reducing noise and extracting clear audio signals" refers to technologies and devices that minimize ambient noise and background noise to clarify audio signals.

[0586] "Speech recognition means" refers to a technology or device for analyzing received speech data and converting it into corresponding text data.

[0587] "Natural language processing" refers to technologies that analyze text data and understand the meaning and structure of language to identify the user's intent.

[0588] "Emotional analysis methods" refer to technologies that analyze emotional elements contained in voice data to identify the user's emotional state.

[0589] "Means for generating the optimal response" refers to technologies and systems that generate the most appropriate information and instructions based on the user's requests and circumstances.

[0590] "Monitoring" refers to the process of continuously observing a specific object to check for any changes or abnormalities.

[0591] "Notifying of an anomaly" refers to the act of informing the user of data or situations that deviate from the normal range.

[0592] This invention relates to a system for automotive navigation systems that analyzes user voice commands and emotions in real time and provides the optimal response. The system consists of the following elements:

[0593] First, the terminal receives the user's voice using a microphone installed inside the vehicle. The collected voice data is then processed into a clear audio signal using noise reduction technology. General-purpose noise-canceling software can be used for noise filtering.

[0594] Next, the speech data is converted into text data by a speech recognition engine. Speech recognition software such as Google Cloud Speech-to-Text can be used for this process.

[0595] Next, the server uses a generative AI model to analyze the text data using natural language processing and identify the user's intent. The generative AI model used here includes models from OpenAI. Based on the analysis results, the server processes the audio data with an emotion recognition engine to extract the user's emotional state.

[0596] Based on the extracted intent and emotions, the server quickly searches for the necessary information through information processing tools and generates the most appropriate response. This response is tailored to the user's emotional state and has the ability to adjust its content and tone of voice. The generated response is output by the terminal using a speech synthesis engine. In this process, text-to-speech solutions such as Amazon Polly are utilized.

[0597] The system also monitors data from various monitoring devices installed in the vehicle and has the capability to quickly notify the user in the event of an anomaly. For example, if a user says in an anxious tone, "I think I might be lost," the server will check the location information and generate a reassuring response such as, "We have confirmed your current location, you are safe, you can reach your destination by turning right at the next turn."

[0598] An example of a prompt message could be: "The user said 'I don't know the way' in an anxious tone. Please create a supportive response for them." This would allow the user to enjoy a comfortable and safe driving experience.

[0599] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0600] Step 1:

[0601] The terminal uses the in-car microphone to receive the user's voice. The input here is audio data including ambient noise, and noise filtering technology is used to reduce the noise and extract a clear audio signal. The output of this process is audio data with the noise removed.

[0602] Step 2:

[0603] The terminal inputs noise-reduced audio data into the speech recognition engine, which converts it into text data. The input data is the noise-reduced audio data, which is then output as structured text data through speech recognition. Through this conversion process, commands spoken during driving are captured as text information.

[0604] Step 3:

[0605] The server inputs text data it has acquired into a generating AI model, which then analyzes the user's intent. The input is text data from speech recognition results, and the generating AI model uses natural language processing to identify the user's intent. This analysis then outputs what the user wants in sentence form.

[0606] Step 4:

[0607] The server simultaneously inputs audio data into the emotion analysis engine to identify the user's emotional state. The input data is audio data containing voice features, and the emotional state is output as a label through analysis. This allows for an understanding of the user's emotional nuances.

[0608] Step 5:

[0609] Based on the identified user's intent and emotional state, the server utilizes information processing tools to retrieve necessary information and generate an optimal response. The input is the user's intent and emotional information, and the response is generated in text format while referencing relevant information. This output response includes content appropriate to the user's state.

[0610] Step 6:

[0611] The terminal receives a response from the server and outputs it as speech using a speech synthesis engine. The input is response data in text format, which is output as speech-playable data using speech synthesis technology. Through this process, the user can enjoy a natural conversation by ear.

[0612] Step 7:

[0613] The server receives data from various monitoring devices in the vehicle and monitors the vehicle's status. Input data comes from various sensors, and if an abnormality is detected, data is output to notify the user as an alarm. This ensures the user can always ensure the safety of their vehicle.

[0614] (Application Example 2)

[0615] 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."

[0616] Current car navigation systems lack sufficient user interaction that takes emotions into consideration, resulting in limited effectiveness in reducing driver stress. Furthermore, a system is needed that integrates visual and audio information to enable drivers to drive with greater peace of mind.

[0617] 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.

[0618] In this invention, the server includes voice recognition means, generation AI means, information processing means, and means for presenting visual information to the user via a visual display device. This enables natural dialogue that takes the user's emotions into consideration and flexible driving navigation that combines visual and auditory elements.

[0619] A "voice input device" is a device for receiving a user's voice as data.

[0620] "Speech recognition means" refers to technology that converts received speech data into text data.

[0621] "Generative AI means" refers to artificial intelligence technology that analyzes text data to identify the user's intentions and emotional state.

[0622] "Information processing means" refers to technology that retrieves necessary information based on the intent and emotions of an identified user and generates an appropriate response.

[0623] "Audio output means" refers to a technology for outputting the generated response as audio and presenting it to the user.

[0624] "Means of presenting visual information to a user via a visual display device" refers to a technology that provides necessary information to a user using a device that displays visual information.

[0625] "Vehicle sensors" refer to various sensing devices installed to monitor the vehicle's condition and surrounding environment.

[0626] A "communication network" is an electronic network infrastructure used to send and receive data.

[0627] An "external database" is a collection of information that exists outside the system and can be accessed via a network.

[0628] "Means of issuing warnings visually and audibly" refers to technologies that provide warnings visually or audibly.

[0629] "Route guidance" is the process of providing users with route information to reach their destination.

[0630] The present invention aims to realize a driver assistance system for users wearing smart glasses. The system comprises voice input means, voice recognition means, generation AI means, information processing means, and voice and visual output means.

[0631] The server converts user voice data received via voice input devices installed in the vehicle into text data using a speech recognition engine (such as the Google Speech-to-Text API). The resulting text data is then analyzed using generative AI (such as OpenAI's GPT model) to identify the user's intent and emotional state. This analysis utilizes sentiment analysis libraries such as NVIDIA's Riva AI.

[0632] The server generates optimal navigation information using information processing means based on the user's intentions and emotional state. The generated information is presented to the user via a visual display device. The navigation information displayed on the smart glasses is designed to be intuitively understandable both visually and audibly, with the color and emphasis adjusted according to the driver's emotions.

[0633] For example, if a user expresses anxiety and says, "I wish we could get there sooner," the AI ​​will recognize that emotion and provide relaxing scenery as visual information. In voice, it will respond in a soft tone, "We have found the optimal route based on current traffic information," to provide reassurance.

[0634] An example of a prompt for a generative AI model is: "User utterance: 'I wish we could get there sooner,' emotion: 'anxiety.' As a response, provide suggestions to reduce the user's psychological burden."

[0635] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0636] Step 1:

[0637] The terminal uses the in-car microphone to receive the user's voice. It acquires voice data as input and processes it into clear voice data using noise filtering technology. The filtered voice data is then sent to the server.

[0638] Step 2:

[0639] The server feeds the received audio data into the speech recognition engine. The speech recognition engine converts the audio data into text data, obtaining character information as output. This character information is used for the next analysis.

[0640] Step 3:

[0641] The server inputs text data into a generative AI model, which then analyzes the user's intent. The generative AI model uses natural language processing techniques to analyze the text and generate appropriate prompts for the user's intent and Anfrage. The analysis results are obtained as output.

[0642] Step 4:

[0643] Based on the analysis results, the server uses an emotion analysis library to analyze the tone and speed of the voice data to identify the user's emotions. The emotional state is obtained as output, and the process proceeds to the next step along with the output of the generative AI model.

[0644] Step 5:

[0645] The server uses information processing tools to plan the optimal response based on the user's intentions and emotional state. This includes accessing external databases containing real-time traffic information. The output is generated as a response to the user.

[0646] Step 6:

[0647] The server passes the generated response to the speech synthesis engine, which then generates a voice response. The output voice data is transmitted to the user via the terminal. The voice data is given a tone appropriate to the user's emotions.

[0648] Step 7:

[0649] The device uses smart glasses to present visual information to the user. It visualizes the response sent from the server and displays the information within the user's field of vision. The visual information is dynamically adjusted according to the driving situation.

[0650] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0651] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0652] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0653] [Fourth Embodiment]

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

[0655] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0656] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0657] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0658] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0659] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0660] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0661] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0662] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0663] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0664] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0665] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0666] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0667] This invention provides a car navigation system that utilizes generative AI. The system includes voice input means, voice recognition means, generative AI means, information processing means, and voice output means. The operation of each of these means will be explained below with specific examples.

[0668] First, the device uses microphones placed inside the vehicle to receive voice from the user in real time. The voice input method employs voice filtering technology specifically designed for the in-vehicle environment to remove noise and clearly capture the user's speech.

[0669] Next, the terminal converts the audio received through the speech recognition means into text data. The speech recognition means uses a high-precision speech recognition engine and can minimize misrecognition by learning the user's past speech patterns.

[0670] Subsequently, the server uses a generative AI to analyze the text data transmitted from the speech recognition system. The generative AI uses natural language processing technology to identify the user's intent and extract the necessary information.

[0671] Based on the analysis results, the server uses information processing tools to access external databases and real-time traffic information to create a response suitable for the user's request. For example, if a user requests "Find the best route," the server calculates the shortest route considering the current traffic conditions.

[0672] Finally, the terminal synthesizes the generated response into speech using an audio output device and presents it to the user. The audio output device generates natural-sounding speech and sets appropriate speaker settings to ensure sound quality.

[0673] Furthermore, sensors mounted on the vehicle monitor its condition, and if an abnormality is detected, the terminal immediately sounds an alarm to the user and provides necessary corrective actions via voice. For example, if the tire pressure is low, it will notify the user, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0674] In this way, this invention enables intuitive and interactive responses that allow users to enjoy a safer and more comfortable driving experience.

[0675] The following describes the processing flow.

[0676] Step 1:

[0677] The device receives the user's voice through the in-car microphone. Here, a function that starts recording the moment a voice trigger word is recognized is activated. A noise reduction filter is also in operation to maintain optimal audio data quality.

[0678] Step 2:

[0679] The device converts voice data into text data via a speech recognition engine. The voice model performs highly accurate recognition, taking into account noise and echoes specific to the in-car environment. In addition, noise reduction is applied to the voice data as a preprocessing step.

[0680] Step 3:

[0681] The server sends text data to a generating AI. Here, the generating AI uses natural language processing techniques to analyze the user's intent from the text data and interpret its meaning. Once the intent is clearly identified, information is prepared for the next processing stage.

[0682] Step 4:

[0683] The server initiates a search for appropriate information based on the user's intent. It accesses external real-time traffic information, retrieves necessary information from vehicle sensor data and other relevant databases, and analyzes it using information processing tools to enable optimal decision-making.

[0684] Step 5:

[0685] The server collects the necessary information and uses generative AI to construct an appropriate response based on that information. Here, it generates instructions, route guidance, and problem-solving solutions in text in response to user requests.

[0686] Step 6:

[0687] The terminal sends the response text to the voice output device, which is then converted into natural-sounding speech using speech synthesis technology. The sound quality is adjusted to ensure the voice guidance is clear to the user, and it is then played back through the car's speakers.

[0688] Step 7:

[0689] The terminal continuously monitors vehicle sensors and immediately notifies the server if an anomaly is detected. This allows the user to receive voice warnings and specific countermeasures depending on the type of anomaly.

[0690] This series of processing steps allows users to interact with the system in a flexible manner and continue driving with peace of mind.

[0691] (Example 1)

[0692] 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".

[0693] Conventional car navigation systems suffer from problems such as low accuracy in voice recognition in noisy environments, leading to misinterpretation of user instructions, and the failure to provide timely information regarding vehicle malfunctions. In addition, they often struggle to provide dynamic information to quickly respond to real-time, changing traffic conditions.

[0694] 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.

[0695] In this invention, the server includes means for receiving the user's voice while removing ambient noise using a voice input device, means for converting the voice data received by the voice input device into text information, and generation AI means including natural language processing technology for analyzing the text information and identifying the user's intent. This improves the accuracy of voice recognition and enables dynamic and accurate navigation that takes traffic information into account in real time.

[0696] "Voice input devices" refer to all devices that receive voice from users and convert it into digital data.

[0697] "Audio data" refers to the digital representation of an audio signal captured through an audio input device.

[0698] "Textual information" refers to text data converted from audio data by speech recognition technology.

[0699] "Natural language processing technology" refers to the technology that enables computers to understand, generate, and respond to human natural language.

[0700] "Generative AI means" refers to artificial intelligence technology that understands user intent and organizes and generates information based on that intent.

[0701] "External information sources" refer to all external information databases that are accessible via the internet or other communication networks.

[0702] "Real-time traffic information" refers to information about current traffic conditions that is updated in real time.

[0703] "Speech synthesis technology" refers to the technology that generates natural-sounding speech using text data.

[0704] The term "detector" refers to any sensor that measures various conditions of a vehicle and outputs them as digital data.

[0705] "Detecting a malfunction" refers to using sensors or other means to determine abnormal conditions or failures that deviate from the vehicle's normal operating state.

[0706] "Information transmission network" refers to all communication networks, including the internet and other protocols.

[0707] This invention provides a vehicle navigation system based on generative AI technology. The system includes a voice input device, voice recognition means, generative AI means, information processing means, and voice output means.

[0708] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. This uses voice filtering technology to reduce ambient noise. For example, noise cancellation algorithms reduce engine noise and road noise.

[0709] Once audio is acquired, the device uses a high-precision speech recognition engine to convert the audio data into text. This ensures that the user's utterances are clearly identified, and by considering past speech patterns, recognition accuracy is improved.

[0710] Next, the server receives the text information transmitted from the speech recognition system and performs analysis using a generative AI system. Natural language processing technology identifies the user's intent and extracts the necessary information. For example, if the user issues the command "Find the shortest route," the generative AI performs analysis based on that command.

[0711] The server uses information processing tools to access external information sources and retrieve necessary data. It refers to a database containing real-time traffic information and creates the optimal route guidance for the user. As a result, fast and accurate navigation information is generated.

[0712] Finally, the generated response is presented to the user by the device using speech synthesis technology. During this process, the volume and tone are adjusted to produce a natural and easy-to-understand voice.

[0713] Furthermore, the terminal constantly monitors information collected by multiple sensors installed in the vehicle and notifies the user in real time if an abnormality is detected. For example, if the tire pressure drops, it will issue a warning such as, "The air pressure in the front right tire is low. Please refuel at the nearest gas station."

[0714] This system allows users to enjoy an intuitive and interactive navigation experience, supporting safer and more comfortable driving.

[0715] Example of a prompt:

[0716] "Find the shortest route"

[0717] "Can you tell me the nearest gas station?"

[0718] "Turn right at the next intersection."

[0719] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0720] Step 1:

[0721] The terminal receives voice commands from the user using a voice input device installed inside the vehicle. The input is the user's voice, which includes ambient noise. The voice input device uses a noise cancellation algorithm to remove the noise and obtain a clear voice signal. The output is the processed voice data.

[0722] Step 2:

[0723] The device utilizes speech recognition to convert the audio data obtained in Step 1 into text information. This process employs a highly accurate speech recognition engine. The input is the processed audio data, and the output is text information. Specifically, if the user voice-inputs "Find the best route," the output will be a text representation of that statement.

[0724] Step 3:

[0725] The server receives text information transmitted from the speech recognition system. The input is the recognized text information. The server uses generative AI to perform natural language processing and identify the user's intent. In this process, important information is extracted from the user's words and the user's request is analyzed. The output is the request information based on the analyzed user intent and its content.

[0726] Step 4:

[0727] The server uses information processing tools to access external information sources and real-time traffic information based on the user's intent obtained in step 3. The input is the user's request information. The server retrieves the necessary data and generates a response to the user's request. For example, in response to the request "Find the shortest route," the server calculates the optimal route considering real-time traffic conditions. The output is the response information provided to the user.

[0728] Step 5:

[0729] The terminal outputs the generated response information as speech using speech synthesis technology. The input is the response information from the server. The output is a synthesized speech message with adjusted volume and tone. Specifically, the terminal will inform the user via voice, "The best route at the moment is via Street A."

[0730] Step 6:

[0731] The terminal monitors data from sensors installed in the vehicle. The input is sensor information indicating the vehicle's status. If an abnormality is detected, it will sound a warning to the user based on that information. For example, if it detects that the tire pressure has dropped, it will provide a voice warning such as, "The air pressure in the front right tire is low. Please have it checked at the nearest service station." The output is a voice notification to the user.

[0732] (Application Example 1)

[0733] 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".

[0734] A major problem with autonomous vehicles is the lack of navigation systems that allow passengers to intuitively specify their destinations. Furthermore, there is a need for methods to provide fast and accurate route guidance utilizing real-time traffic information, but this is not yet adequately implemented. This hinders a comfortable and efficient travel experience.

[0735] 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.

[0736] In this invention, the server includes a speech recognition means that converts speech data received by a voice input means into text data, a generation AI means that analyzes the text data obtained by the speech recognition means to identify the user's intent, and a navigation means that calculates the optimal route based on traffic information acquired via a communication network. As a result, passengers can obtain quick and optimal route guidance simply by indicating their destination by voice.

[0737] "Voice input means" refers to a device or method for receiving voice data from a user.

[0738] "Speech recognition means" refers to a technology or device that analyzes received speech data and converts it into text data.

[0739] "Generative AI means" refers to artificial intelligence technology that analyzes text data obtained through speech recognition and interprets its intent.

[0740] "Information processing means" refers to a mechanism or software for retrieving necessary information and generating a response based on the intent identified by the generating AI means.

[0741] "Audio output means" refers to a technology or device for converting a generated response into audio and presenting it to the user.

[0742] An "autonomous vehicle" is a vehicle that can autonomously travel to its destination without the need for human intervention.

[0743] A "navigation system" is a technology or system that calculates and guides the optimal route to a destination based on traffic information and map data.

[0744] A "communication network" is a network infrastructure used to send and receive information.

[0745] "Route guidance" refers to information that directs the travel route from the starting point to the destination.

[0746] This invention implements a navigation system for autonomous vehicles that utilizes generative AI. The system includes a microphone for receiving voice input, a speech recognition engine for converting speech to text, a generative AI engine that utilizes advanced AI, an information processing device for acquiring traffic information and calculating a route, and a speaker for outputting the results as voice.

[0747] The server converts the audio data into text data using Google or an equivalent speech recognition API. The converted text data is then analyzed using a generative AI model (such as OpenAI's GPT-3) to identify the user's intent. This generative AI model enables advanced natural language analysis and can handle ambiguous requests from users.

[0748] The server then accesses an external traffic database via a communication network and retrieves real-time traffic information as needed. Based on this, the system calculates the optimal route. This process uses programming languages ​​and libraries such as Python and TensorFlow.

[0749] Once the optimal route is determined, the terminal provides instructions to the user using a voice output device. The voice is generated using speech synthesis technology that simulates natural pronunciation.

[0750] Specific example: For instance, if a user in an autonomous vehicle gives a voice command such as "Tell me the shortest route to the airport," the generating AI analyzes this command, and the server calculates the optimal route based on traffic information obtained from an external database. This route guidance is then provided to the user via voice.

[0751] Example prompt: "Please tell me the fastest route to the city center that avoids congestion."

[0752] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0753] Step 1:

[0754] The terminal receives voice input from the user via a microphone placed inside the vehicle. The input is voice data in which the user makes navigation requests. The terminal uses noise filtering technology to clarify this voice data and prepare accurate input data.

[0755] Step 2:

[0756] The server uses a speech recognition engine to convert the audio data into text data. The input is the audio data filtered in step 1, and the output is text data representing the user's utterance. This formats the data so that it can be used in subsequent processing.

[0757] Step 3:

[0758] The server uses a generative AI model to analyze the converted text data and identify the user's intent. The input is the text data obtained in step 2, and the output is the analysis result that defines the user's intent. By utilizing generative AI, even ambiguous requests can be understood with high accuracy.

[0759] Step 4:

[0760] The server uses a communication network to access an external traffic database and obtain the latest traffic information. The input is the user's intent identified in step 3. The output is real-time information about traffic conditions, providing a basis for calculating the optimal route.

[0761] Step 5:

[0762] The server calculates the optimal route based on traffic information and analysis results. The input is the traffic information obtained in step 4 and the user's intent, and the output is specific route guidance information. Python and its libraries are used for the calculations.

[0763] Step 6:

[0764] The terminal converts the calculated route guidance into speech using speech synthesis technology and provides it to the user. The input is the route guidance information calculated in step 5, and the output is the voice route guidance. The user can reach their destination based on this.

[0765] 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.

[0766] This invention provides a more advanced interactive experience by combining a car navigation system that utilizes generative AI with an emotion engine that recognizes user emotions. The system takes the form of a voice input means, a voice recognition means, a generative AI means, an information processing means, a voice output means, and an emotion recognition means.

[0767] First, the device receives the user's voice via the in-car microphone. The voice undergoes noise filtering and is converted into text data by speech recognition. This text data is then analyzed by a generative AI.

[0768] Next, the server uses AI generation tools to identify the user's intent, and then analyzes the voice data using emotion recognition tools to understand the user's emotional state. The emotion engine analyzes elements such as tone, speed, and volume of the voice to identify emotions such as joy, anger, sadness, and happiness.

[0769] Once the user's intentions and emotions are identified, the server uses that information to search for necessary information in real time and generate the most appropriate response for the user's current situation. This includes adjusting the content and tone of voice according to the user's emotional state.

[0770] For example, if a user says in an anxious tone, "I think I might be lost," the server will check their location in real time and generate a reassuring response in a soft tone, such as, "I've confirmed your current location, you're safe, you can reach your destination by turning right at the next turn."

[0771] This allows the device to communicate responses to the user using voice output. Utilizing speech synthesis technology, it provides natural-sounding dialogue that takes the user's emotions into consideration, even though it uses synthesized speech.

[0772] Furthermore, the system monitors various sensors in the vehicle, and if an abnormality is detected, that information is also included in the response to the user. For example, to help the user react calmly, it might issue instructions such as, "The engine temperature is above normal; please decelerate immediately."

[0773] This system allows users to enjoy emotionally responsive and flexible support, enabling them to drive their vehicles with peace of mind.

[0774] The following describes the processing flow.

[0775] Step 1:

[0776] The device receives the user's voice through a microphone installed inside the vehicle. The microphone uses a filter to reduce ambient noise, ensuring clear audio data. This audio data is then transmitted in real time to the speech recognition process.

[0777] Step 2:

[0778] The device uses speech recognition to convert received audio data into text data. This process generates an accurate textual representation of the user's speech, shaping it in a way that facilitates subsequent analysis and processing.

[0779] Step 3:

[0780] The server sends the text data obtained through speech recognition to a generating AI system, which then analyzes the user's intent. This analysis uses natural language processing techniques and focuses on identifying what the user wants from the system.

[0781] Step 4:

[0782] The server simultaneously processes the audio data using emotion recognition tools to identify the user's emotional state. This process analyzes the tone, pitch, and speed of the voice to classify the user's state, such as happy, anxious, or angry.

[0783] Step 5:

[0784] The server uses information processing tools to retrieve necessary information based on the user's intent and emotional state. It integrates real-time traffic information, vehicle sensor data, and other relevant information tailored to the user's needs to generate an appropriate response for the user.

[0785] Step 6:

[0786] The server generates a response, which is then adjusted according to the user's emotions and finally converted into text format necessary for audio output. This step prepares the system to output considerate information, such as matching the wording and tone to the user's emotions.

[0787] Step 7:

[0788] The device uses a voice output device to synthesize prepared response text into speech and transmit it to the user as audio. The synthesized speech is played in a soft, gentle tone, allowing the user to receive information in a way that is considerate of their emotions.

[0789] This process ensures that users always feel secure while obtaining information, and the system provides interaction that is attentive to the user's emotions.

[0790] (Example 2)

[0791] 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".

[0792] In the automotive driving environment, conventional navigation systems have struggled to accurately understand user voice commands and emotions and provide appropriate responses in real time. Furthermore, the lack of means to provide flexible responses tailored to the user's psychological state raised concerns about reduced safety and ease of operation while driving. Additionally, there were limitations to their ability to monitor vehicle status and promptly notify of abnormalities.

[0793] 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.

[0794] In this invention, the server includes means for receiving audio data and extracting a clear audio signal by reducing noise, speech recognition means for converting the audio data into text data, natural language processing means for analyzing the user's intentions and emotional state, and emotion analysis means. This makes it possible to accurately grasp the user's intentions and emotions and generate an optimal response in real time. Furthermore, by monitoring the vehicle's status and promptly issuing warnings to the user in the event of an abnormality, driving safety and peace of mind can be improved.

[0795] "Audio data" refers to information recorded in digital format, used for electronically processing audio signals.

[0796] "Means for reducing noise and extracting clear audio signals" refers to technologies and devices that minimize ambient noise and background noise to clarify audio signals.

[0797] "Speech recognition means" refers to a technology or device for analyzing received speech data and converting it into corresponding text data.

[0798] "Natural language processing" refers to technologies that analyze text data and understand the meaning and structure of language to identify the user's intent.

[0799] "Emotional analysis methods" refer to technologies that analyze emotional elements contained in voice data to identify the user's emotional state.

[0800] "Means for generating the optimal response" refers to technologies and systems that generate the most appropriate information and instructions based on the user's requests and circumstances.

[0801] "Monitoring" refers to the process of continuously observing a specific object to check for any changes or abnormalities.

[0802] "Notifying of an anomaly" refers to the act of informing the user of data or situations that deviate from the normal range.

[0803] This invention relates to a system for automotive navigation systems that analyzes user voice commands and emotions in real time and provides the optimal response. The system consists of the following elements:

[0804] First, the terminal receives the user's voice using a microphone installed inside the vehicle. The collected voice data is then processed into a clear audio signal using noise reduction technology. General-purpose noise-canceling software can be used for noise filtering.

[0805] Next, the speech data is converted into text data by a speech recognition engine. Speech recognition software such as Google Cloud Speech-to-Text can be used for this process.

[0806] Next, the server uses a generative AI model to analyze the text data using natural language processing and identify the user's intent. The generative AI model used here includes models from OpenAI. Based on the analysis results, the server processes the audio data with an emotion recognition engine to extract the user's emotional state.

[0807] Based on the extracted intent and emotions, the server quickly searches for the necessary information through information processing tools and generates the most appropriate response. This response is tailored to the user's emotional state and has the ability to adjust its content and tone of voice. The generated response is output by the terminal using a speech synthesis engine. In this process, text-to-speech solutions such as Amazon Polly are utilized.

[0808] The system also monitors data from various monitoring devices installed in the vehicle and has the capability to quickly notify the user in the event of an anomaly. For example, if a user says in an anxious tone, "I think I might be lost," the server will check the location information and generate a reassuring response such as, "We have confirmed your current location, you are safe, you can reach your destination by turning right at the next turn."

[0809] An example of a prompt message could be: "The user said 'I don't know the way' in an anxious tone. Please create a supportive response for them." This would allow the user to enjoy a comfortable and safe driving experience.

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

[0811] Step 1:

[0812] The terminal uses the in-car microphone to receive the user's voice. The input here is audio data including ambient noise, and noise filtering technology is used to reduce the noise and extract a clear audio signal. The output of this process is audio data with the noise removed.

[0813] Step 2:

[0814] The terminal inputs noise-reduced audio data into the speech recognition engine, which converts it into text data. The input data is the noise-reduced audio data, which is then output as structured text data through speech recognition. Through this conversion process, commands spoken during driving are captured as text information.

[0815] Step 3:

[0816] The server inputs text data it has acquired into a generating AI model, which then analyzes the user's intent. The input is text data from speech recognition results, and the generating AI model uses natural language processing to identify the user's intent. This analysis then outputs what the user wants in sentence form.

[0817] Step 4:

[0818] The server simultaneously inputs audio data into the emotion analysis engine to identify the user's emotional state. The input data is audio data containing voice features, and the emotional state is output as a label through analysis. This allows for an understanding of the user's emotional nuances.

[0819] Step 5:

[0820] Based on the identified user's intent and emotional state, the server utilizes information processing tools to retrieve necessary information and generate an optimal response. The input is the user's intent and emotional information, and the response is generated in text format while referencing relevant information. This output response includes content appropriate to the user's state.

[0821] Step 6:

[0822] The terminal receives a response from the server and outputs it as speech using a speech synthesis engine. The input is response data in text format, which is output as speech-playable data using speech synthesis technology. Through this process, the user can enjoy a natural conversation by ear.

[0823] Step 7:

[0824] The server receives data from various monitoring devices in the vehicle and monitors the vehicle's status. Input data comes from various sensors, and if an abnormality is detected, data is output to notify the user as an alarm. This ensures the user can always ensure the safety of their vehicle.

[0825] (Application Example 2)

[0826] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0827] Current car navigation systems lack sufficient user interaction that takes emotions into consideration, resulting in limited effectiveness in reducing driver stress. Furthermore, a system is needed that integrates visual and audio information to enable drivers to drive with greater peace of mind.

[0828] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0829] In this invention, the server includes voice recognition means, generation AI means, information processing means, and means for presenting visual information to the user via a visual display device. This enables natural dialogue that takes the user's emotions into consideration and flexible driving navigation that combines visual and auditory elements.

[0830] A "voice input device" is a device for receiving a user's voice as data.

[0831] "Speech recognition means" refers to technology that converts received speech data into text data.

[0832] "Generative AI means" refers to artificial intelligence technology that analyzes text data to identify the user's intentions and emotional state.

[0833] "Information processing means" refers to technology that retrieves necessary information based on the intent and emotions of an identified user and generates an appropriate response.

[0834] "Audio output means" refers to a technology for outputting the generated response as audio and presenting it to the user.

[0835] "Means of presenting visual information to a user via a visual display device" refers to a technology that provides necessary information to a user using a device that displays visual information.

[0836] "Vehicle sensors" refer to various sensing devices installed to monitor the vehicle's condition and surrounding environment.

[0837] A "communication network" is an electronic network infrastructure used to send and receive data.

[0838] An "external database" is a collection of information that exists outside the system and can be accessed via a network.

[0839] "Means of issuing warnings visually and audibly" refers to technologies that provide warnings visually or audibly.

[0840] "Route guidance" is the process of providing users with route information to reach their destination.

[0841] The present invention aims to realize a driver assistance system for users wearing smart glasses. The system comprises voice input means, voice recognition means, generation AI means, information processing means, and voice and visual output means.

[0842] The server converts user voice data received via voice input devices installed in the vehicle into text data using a speech recognition engine (such as the Google Speech-to-Text API). The resulting text data is then analyzed using generative AI (such as OpenAI's GPT model) to identify the user's intent and emotional state. This analysis utilizes sentiment analysis libraries such as NVIDIA's Riva AI.

[0843] The server generates optimal navigation information using information processing means based on the user's intentions and emotional state. The generated information is presented to the user via a visual display device. The navigation information displayed on the smart glasses is designed to be intuitively understandable both visually and audibly, with the color and emphasis adjusted according to the driver's emotions.

[0844] For example, if a user expresses anxiety and says, "I wish we could get there sooner," the AI ​​will recognize that emotion and provide relaxing scenery as visual information. In voice, it will respond in a soft tone, "We have found the optimal route based on current traffic information," to provide reassurance.

[0845] An example of a prompt for a generative AI model is: "User utterance: 'I wish we could get there sooner,' emotion: 'anxiety.' As a response, provide suggestions to reduce the user's psychological burden."

[0846] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0847] Step 1:

[0848] The terminal uses the in-car microphone to receive the user's voice. It acquires voice data as input and processes it into clear voice data using noise filtering technology. The filtered voice data is then sent to the server.

[0849] Step 2:

[0850] The server feeds the received audio data into the speech recognition engine. The speech recognition engine converts the audio data into text data, obtaining character information as output. This character information is used for the next analysis.

[0851] Step 3:

[0852] The server inputs text data into a generative AI model, which then analyzes the user's intent. The generative AI model uses natural language processing techniques to analyze the text and generate appropriate prompts for the user's intent and Anfrage. The analysis results are obtained as output.

[0853] Step 4:

[0854] Based on the analysis results, the server uses an emotion analysis library to analyze the tone and speed of the voice data to identify the user's emotions. The emotional state is obtained as output, and the process proceeds to the next step along with the output of the generative AI model.

[0855] Step 5:

[0856] The server uses information processing tools to plan the optimal response based on the user's intentions and emotional state. This includes accessing external databases containing real-time traffic information. The output is generated as a response to the user.

[0857] Step 6:

[0858] The server passes the generated response to the speech synthesis engine, which then generates a voice response. The output voice data is transmitted to the user via the terminal. The voice data is given a tone appropriate to the user's emotions.

[0859] Step 7:

[0860] The device uses smart glasses to present visual information to the user. It visualizes the response sent from the server and displays the information within the user's field of vision. The visual information is dynamically adjusted according to the driving situation.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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."

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] The following is further disclosed regarding the embodiments described above.

[0883] (Claim 1)

[0884] A speech recognition means that converts speech data received by a speech input means into text data,

[0885] A generative AI means analyzes the text data obtained by the aforementioned speech recognition means to identify the user's intent,

[0886] Information processing means that searches for necessary information and generates a response based on the user's intent identified by the aforementioned generation AI means,

[0887] A system including an audio output means that outputs the generated response as audio.

[0888] (Claim 2)

[0889] The system according to claim 1, comprising means for monitoring data collected by various sensors in the vehicle and issuing a warning to the user when an abnormality is detected.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising means for accessing an external database via a communication network and obtaining traffic information in real time.

[0892] "Example 1"

[0893] (Claim 1)

[0894] A means of receiving the user's voice while eliminating ambient noise using an audio input device,

[0895] Means for converting audio data received by the aforementioned audio input device into text information,

[0896] A generative AI means including natural language processing technology that analyzes the aforementioned textual information and identifies the user's intent,

[0897] A means for generating a response using external information sources and real-time traffic information, based on the user's intent identified by the aforementioned generating AI means,

[0898] A system including means for presenting the generated response using speech synthesis technology.

[0899] (Claim 2)

[0900] The system according to claim 1, comprising means for monitoring information collected by a plurality of detectors installed in the vehicle and notifying the user of a warning if a malfunction is detected.

[0901] (Claim 3)

[0902] The system according to claim 1, comprising means for accessing external information sources via an information transmission network and obtaining traffic information provided in real time.

[0903] "Application Example 1"

[0904] (Claim 1)

[0905] A speech recognition means that converts speech data received by a speech input means into text data,

[0906] A generative AI means analyzes the text data obtained by the aforementioned speech recognition means and identifies the user's intent,

[0907] Information processing means that searches for necessary information and generates a response based on the user's intent identified by the aforementioned generation AI means,

[0908] A voice output means that outputs the generated response as voice,

[0909] A navigation system for autonomous vehicles that receives instructions from passengers via voice and calculates the optimal route based on traffic information acquired via a communication network,

[0910] Means for presenting the route guidance visually or through audio output,

[0911] ...

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, comprising means for improving the driving experience in an autonomous vehicle by calculating and presenting an optimal route based on the voice instructions of a passenger.

[0915] (Claim 3)

[0916] The system according to claim 1, comprising means for calculating the optimal route based on real-time road conditions by accessing an external information database.

[0917] "Example 2 of combining an emotion engine"

[0918] (Claim 1)

[0919] A means for receiving audio data, reducing noise, and extracting a clear audio signal,

[0920] A speech recognition means for converting the aforementioned speech data into text data,

[0921] A natural language processing means analyzes the text data obtained by the aforementioned speech recognition means and identifies the user's intent.

[0922] An emotion analysis method that analyzes voice data to identify the user's emotional state,

[0923] Information processing means that rapidly retrieves necessary information and generates an optimal response based on the user's intentions and emotional state identified by the natural language processing means and the emotion analysis means,

[0924] A system including a speech synthesis means that outputs the generated response as speech.

[0925] (Claim 2)

[0926] The system according to claim 1, comprising means for monitoring data collected by various monitoring devices of a vehicle and issuing a warning to the user when an abnormality is detected.

[0927] (Claim 3)

[0928] The system according to claim 1, comprising means for accessing an external database via a communication infrastructure and obtaining traffic information in real time.

[0929] "Application example 2 when combining with an emotional engine"

[0930] (Claim 1)

[0931] A speech recognition means that converts speech data received by a speech input means into text data,

[0932] A generative AI means analyzes the text data obtained by the aforementioned speech recognition means to identify the user's intent,

[0933] Information processing means that searches for necessary information based on the user's intentions and emotional state identified by the aforementioned generation AI means and generates a response in a tone appropriate to the user's emotions,

[0934] A voice output means that outputs the generated response as voice,

[0935] A means of presenting visual information to a user via a visual display device,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, comprising means for monitoring data collected by various sensors in the vehicle and issuing visual and audible warnings to the user when an abnormality is detected.

[0939] (Claim 3)

[0940] The system according to claim 1, comprising means for accessing an external database via a communication network, obtaining traffic information in real time, and providing optimal route guidance according to the user's emotional state. [Explanation of symbols]

[0941] 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 speech recognition means that converts speech data received by a speech input means into text data, A generative AI means analyzes the text data obtained by the aforementioned speech recognition means to identify the user's intent, Information processing means that searches for necessary information and generates a response based on the user's intent identified by the aforementioned generation AI means, A system including an audio output means that outputs the generated response as audio.

2. The system according to claim 1, further comprising means for monitoring data collected by various sensors in the vehicle and issuing a warning to the user when an abnormality is detected.

3. The system according to claim 1, comprising means for accessing an external database via a communication network and obtaining traffic information in real time.

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