system

Abstract

The system according to this embodiment aims to integrate the process from information input and analysis to the generation and provision of responses. [Solution] The system according to the embodiment comprises a reception unit, a generation unit, a display unit, and an audio output unit. The reception unit receives information input. The generation unit analyzes the information received by the reception unit and generates a response. The display unit displays the response generated by the generation unit. The audio output unit provides the response generated by the generation unit in audio format.

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, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, the processes from information input to analysis, answer generation, and answer provision are not integrated, and there is room for improvement.

[0005] The system according to the embodiment aims to perform the processes from information input to analysis, answer generation, and answer provision in an integrated manner.

Means for Solving the Problems

[0007] The system according to the embodiment includes a reception unit, a generation unit, a display unit, and an audio output unit. The reception unit receives information input. The generation unit analyzes the information received by the reception unit and generates an answer. The display unit displays the answer generated by the generation unit. The audio output unit provides the answer generated by the generation unit in audio. [Effects of the Invention]

[0007] The system according to this embodiment can perform the entire process from information input and analysis to response generation and provision in an integrated manner. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna. 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).

[0015] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52. <00001​​The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The robot-type smartphone system according to an embodiment of the present invention is a palm-sized robot-type smartphone that combines the cute appearance of a robot with advanced conversational capabilities such as generative AI. This robot-type smartphone system has a small display built into its chest and provides functions such as displaying news and weather forecasts and performing internet searches. For example, the user inputs information using voice input or a touchscreen. For example, the user inputs questions such as "What's the weather like today?" or "Tell me the latest news." This information is input to the generative AI. Next, the generative AI analyzes the input information and generates an appropriate answer to the user's question. The generative AI has advanced natural language processing capabilities and provides information based on the user's utterance. For example, it generates answers such as "The weather today is sunny" or "The latest news is XX." The generated answers are displayed on the small display built into the chest of the robot-type smartphone. This allows the user to visually confirm the information. In addition, the generated answers can also be provided by voice using the voice output function. This mechanism allows users to quickly obtain information and revitalizes daily communication. Furthermore, it improves the user's understanding of information and eliminates delays and inconveniences in accessing information. Furthermore, this robot-shaped smartphone is convenient for users who want to access information while on the go. For example, they can obtain information using voice input or a touchscreen while commuting or out and about. In this way, the fusion of robot technology and smartphones can bring about innovation in information and communication. The target audience is expected to be young to middle-aged users who are interested in technology. As a result, the robot-shaped smartphone system will enable users to obtain information quickly and efficiently, making information access in daily life easier.

[0029] The robot-type smartphone system according to this embodiment comprises a reception unit, a generation unit, a display unit, and an audio output unit. The reception unit receives information input. Information input includes, but is not limited to, voice input and touchscreen input. For example, if a user asks "What's the weather like today?", the reception unit receives that voice. The reception unit can also receive touch input if a user enters a question using a touchscreen. Furthermore, the reception unit can also receive other forms of information input, such as image input and text input. The generation unit analyzes the information received by the reception unit and generates an answer. The generation unit generates an appropriate answer to the user's question, for example, using a generation AI. The generation AI has advanced natural language processing capabilities and provides information based on the user's utterance. For example, if a user asks "What's the weather like today?", the generation unit generates an answer such as "The weather is sunny today." The generation unit can also generate an answer such as "The latest news is XX" if a user asks "Tell me the latest news." The display unit displays the answers generated by the generation unit. The display unit displays information on a small display built into the chest of the robot-type smartphone, for example. For example, the display unit displays an answer such as "Today's weather is sunny" on the display. The display unit can also visually display news and weather forecast information. Furthermore, the display unit can also display internet search results and other information. The voice output unit provides the answers generated by the generation unit in voice. The voice output unit outputs the generated answers in voice, for example, using a speaker. For example, the voice output unit provides an answer such as "Today's weather is sunny" in voice. Furthermore, the voice output unit can also provide news and weather forecast information in voice. Furthermore, the voice output unit can also provide internet search results and other information in voice. As a result, the robot-type smartphone system according to this embodiment can consistently perform everything from information input to analysis, display, and voice output.

[0030] The reception unit accepts information input. This input includes, but is not limited to, voice input and touchscreen input. For example, if a user asks a question aloud, such as "What's the weather like today?", the reception unit will accept that voice input. It can also accept touch input if the user enters a question using a touchscreen. Furthermore, the reception unit can accept other forms of information input, such as image input and text input. Specifically, for voice input, the reception unit uses a high-sensitivity microphone to accurately capture the user's voice and noise cancellation technology to remove ambient noise. For touchscreen input, a capacitive touch panel is used to detect the user's finger movements with high precision. For image input, a camera is used to capture the image presented by the user, and OCR (optical character recognition) technology is used to analyze the text within the image. For text input, the reception unit accepts text entered by the user using a keyboard or software keyboard. This allows the reception unit to support diverse input formats and improve user convenience. Furthermore, the reception unit temporarily stores the input information and performs pre-processing as needed before sending it to the generation unit. For example, in the case of voice input, speech recognition technology is used to convert the speech into text, which is then sent to the generation unit. This allows the receiving unit to smoothly handle everything from information input to transmission to the generation unit.

[0031] The generation unit analyzes the information received by the reception unit and generates responses. For example, the generation unit uses a generation AI to generate appropriate answers to user questions. The generation AI has advanced natural language processing capabilities and provides information based on the user's utterances. Specifically, the generation AI analyzes the user's question and considers the context to understand the intent of the question. For example, if a user asks, "What's the weather like today?", the generation AI considers the current date and the user's location to provide appropriate weather information. The generation AI also retrieves the latest news and weather forecasts from internet sources to keep the information provided to the user up-to-date. Furthermore, the generation AI can learn the user's past question history and preferences to provide more personalized responses. For example, if a user frequently shows interest in a particular news category, the generation AI will prioritize providing the latest news related to that category. This allows the generation unit to generate highly accurate responses that meet the user's needs and improve the user experience. In addition, the generation unit reviews the content of the generated responses and makes corrections as needed before sending them to the display unit and audio output unit. This ensures the accuracy and reliability of the information provided to the user.

[0032] The display unit displays the answers generated by the generation unit. For example, the display unit displays information on a small display built into the chest of a robot-shaped smartphone. Specifically, the display unit employs a high-resolution LCD or OLED display to achieve a clear and easy-to-read display. For example, the display unit displays answers such as "Today's weather is sunny." The display unit can also visually display news and weather forecast information. For example, in the case of weather forecasts, icons and graphs are used to make the information visually easy to understand. Furthermore, the display unit can also display internet search results and other information. For example, if a user asks "What's the latest news?", the display unit displays news headlines and summaries, allowing the user to view details. The display unit has touchscreen functionality, allowing users to interact with the displayed information by touching it. This enables the display unit to not only provide visual information to the user but also to enable interactive operation. Furthermore, the display unit automatically adjusts the brightness and contrast of the backlight to provide optimal display according to the ambient light. This allows the display unit to provide a display that is easy to read in various environments, improving user convenience.

[0033] The voice output unit provides the generated answers in voice. The voice output unit outputs the generated answers in voice, for example, using a speaker. Specifically, the voice output unit incorporates a high-quality speaker to provide clear and natural voice. For example, the voice output unit provides answers such as, "Today's weather is sunny." The voice output unit can also provide news and weather forecast information in voice. For example, by reading the latest news aloud, users can obtain information without relying on visual information. Furthermore, the voice output unit can provide internet search results and other information in voice. For example, if a user asks, "Tell me the latest movie information," the voice output unit will provide the titles and showtimes of the latest movies in voice. The voice output unit uses speech synthesis technology to achieve natural pronunciation and intonation. This allows users to have a natural voice experience, as if they were conversing with a human. Furthermore, the voice output unit can adjust the tone and speed of the voice according to the user's preferences. For example, if a user prefers a slow voice, the voice output unit will adjust the speed of the voice to provide a slower voice. This allows the audio output unit to provide users with high-quality, personalized audio information, thereby improving the user experience.

[0034] The reception desk can support both voice input and touchscreen input. For example, if a user enters a question by voice, the reception desk will receive the voice input. The reception desk can also accept touch input if a user enters a question using a touchscreen. For example, the reception desk can receive voice input using a microphone. The voice input is analyzed using speech recognition technology and converted into text data. Furthermore, the reception desk can receive touchscreen input using a touch panel. The touchscreen input is analyzed using gesture recognition technology to understand the user's intent. This support for both voice and touchscreen input improves user convenience.

[0035] The generation unit can provide information based on the user's utterances. For example, the generation unit uses a generation AI to analyze the user's utterances and generate appropriate responses. The generation AI has advanced natural language processing capabilities and provides information based on the user's utterances. For example, if the user asks, "What's the weather like today?", the generation unit will generate a response such as, "The weather today is sunny." The generation unit can also generate a response such as, "The latest news is XX," if the user asks, "Tell me the latest news." In this way, by providing information based on the user's utterances, it can generate appropriate responses.

[0036] The display unit can display information on a small display built into the chest. For example, the display unit can display information on a small display built into the chest of a robot-shaped smartphone. For example, the display unit can display answers such as "Today's weather is sunny." The display unit can also visually display news and weather forecast information. Furthermore, the display unit can display internet search results and other information. This allows users to visually confirm information by displaying it on a small display built into the chest.

[0037] The voice output unit can provide the generated response in voice. For example, the voice output unit uses a speaker to output the generated response as voice. For instance, the voice output unit can provide a voice response such as, "Today's weather is sunny." The voice output unit can also provide news and weather forecast information in voice. Furthermore, the voice output unit can provide internet search results and other information in voice. This allows users to receive information by voice by providing the generated response.

[0038] The system can be equipped with features to support information access even while on the go. For example, the system can allow users to obtain information using voice input or a touchscreen while commuting or out and about. For instance, if a user on the go asks "What's the weather like today?" by voice, the system can receive the voice input, generate an appropriate answer, and provide it by voice. Alternatively, if a user on the go enters a question using a touchscreen, the system can receive the touch input, generate an appropriate answer, and display it on the screen. This supports information access even while on the go, allowing users to obtain information wherever they are.

[0039] The reception desk can analyze a user's past input history and suggest the most suitable input method. For example, it can prioritize suggesting input methods that the user has frequently used in the past (such as voice or touchscreen). Furthermore, the reception desk can predict and suggest input methods that the user will use during specific time periods based on their past input history. In addition, the reception desk can suggest relevant input methods based on content the user has previously entered. This allows the system to suggest the most suitable input method by analyzing the user's past input history.

[0040] The reception unit can detect the ambient noise level during voice input and automatically adjust noise cancellation. For example, if the surroundings are quiet, the reception unit will accept voice input with minimal noise cancellation. Conversely, if the surroundings are noisy, the reception unit can accept voice input with maximum noise cancellation. Furthermore, the reception unit can adjust the intensity of noise cancellation in real time according to the ambient noise level. This automatic adjustment of noise cancellation according to the ambient noise level improves the accuracy of voice input.

[0041] The reception system can prioritize receiving highly relevant information by considering the user's geographical location during voice input. For example, if the user is in a specific location, the reception system will prioritize receiving information related to that location. Furthermore, if the user is on the move, the reception system can prioritize receiving relevant information based on their current location. Additionally, if the user is in a specific region, the reception system can prioritize receiving information related to that region. This allows the system to prioritize receiving highly relevant information by considering the user's geographical location.

[0042] The input unit can recognize user gestures and complete input during touchscreen input. For example, if the user performs a specific gesture, the input unit will automatically complete the corresponding input. Furthermore, if the user combines multiple gestures, the input unit can complete the input based on that combination. In addition, the input unit can consider the speed and direction of the user's gestures to complete the optimal input. This allows the input to be completed by recognizing the user's gestures.

[0043] The generation unit can improve the accuracy of its answers by referring to the user's past question history during the generation process. For example, the generation unit generates relevant answers based on the content of questions the user has asked in the past. Furthermore, the generation unit can identify specific patterns from the user's past question history and generate highly accurate answers. In addition, the generation unit can analyze the content of questions the user has asked in the past and generate the optimal answer. This allows for improved answer accuracy by referring to the user's past question history.

[0044] The generation unit can customize the response content based on the user's current interests during generation. For example, the generation unit generates relevant responses based on topics the user is currently interested in. It can also analyze the user's current interests and customize the response content accordingly. Furthermore, the generation unit can generate responses related to the user's interests based on their recent searches. This allows for the provision of more relevant responses by customizing the response content based on the user's current interests.

[0045] The generation unit can provide highly relevant information by considering the user's geographical location during generation. For example, if the user is in a specific location, the generation unit can provide information related to that location. Furthermore, if the user is on the move, the generation unit can provide relevant information based on their current location. Additionally, if the user is in a specific region, the generation unit can provide information related to that region. This allows the generation unit to provide highly relevant information by considering the user's geographical location.

[0046] The generation unit can analyze the user's social media activity during generation to supplement the response content. For example, the generation unit generates relevant responses based on information shared by the user on social media. It can also analyze the user's interests from their social media activity and supplement the response content accordingly. Furthermore, the generation unit can generate relevant responses based on information about accounts the user follows on social media. This allows for the supplementation of response content by analyzing the user's social media activity.

[0047] The display unit can automatically adjust font size and color based on the user's visual characteristics during display. For example, if the user has poor eyesight, the display unit will display in a larger font size. Furthermore, if the user has color vision deficiency, the display unit can adjust the color contrast. In addition, the display unit can automatically adjust the optimal font size and color based on the user's visual characteristics. This automatic adjustment of font size and color based on the user's visual characteristics improves visibility.

[0048] The display unit can select the optimal display layout by referring to the user's past browsing history when displaying information. For example, the display unit can prioritize displaying relevant information based on the content the user has previously viewed. Furthermore, the display unit can select the optimal display layout from the user's past browsing history. In addition, the display unit can analyze the content the user has previously viewed and provide the optimal display method. This allows the display unit to select the optimal display layout by referring to the user's past browsing history.

[0049] The display unit can prioritize displaying highly relevant information by considering the user's geographical location. For example, if the user is in a specific location, the display unit will prioritize displaying information related to that location. Furthermore, if the user is on the move, the display unit can prioritize displaying relevant information based on their current location. Additionally, if the user is in a specific region, the display unit can prioritize displaying information related to that region. This allows the display to prioritize highly relevant information by considering the user's geographical location.

[0050] The display unit can select the optimal display method by considering the user's device information when displaying information. For example, if the user is using a smartphone, the display unit provides a display method that matches the screen size. Furthermore, if the user is using a tablet, the display unit can provide a display method optimized for a larger screen. In addition, if the user is using a smartwatch, the display unit can provide a concise and highly visible display method. This allows the optimal display method to be selected by considering the user's device information.

[0051] The audio output unit can automatically adjust the volume and sound quality based on the user's hearing characteristics when outputting audio. For example, if the user has poor hearing, the audio output unit will automatically increase the volume. Furthermore, if the user has difficulty hearing high frequencies, the audio output unit can adjust the sound quality to emphasize those frequencies. In addition, the audio output unit can automatically adjust the optimal volume and sound quality based on the user's hearing characteristics. This allows for optimal audio output by automatically adjusting the volume and sound quality based on the user's hearing characteristics.

[0052] The audio output unit can provide optimal audio feedback by referring to the user's past listening history when outputting audio. For example, the audio output unit can provide optimal audio based on audio feedback that the user has previously enjoyed listening to. Furthermore, the audio output unit can identify specific patterns from the user's past listening history and provide optimal audio feedback. In addition, the audio output unit can analyze content the user has previously listened to and provide optimal audio feedback. This allows the system to provide optimal audio feedback by referring to the user's past listening history.

[0053] The audio output unit can prioritize outputting highly relevant information by considering the user's geographical location. For example, if the user is in a specific location, the audio output unit will prioritize outputting information related to that location. Furthermore, if the user is on the move, the audio output unit can prioritize outputting relevant information based on their current location. Additionally, if the user is in a specific region, the audio output unit can prioritize outputting information related to that region. This allows for the prioritization of highly relevant information by considering the user's geographical location.

[0054] The audio output unit can select the optimal audio output method by considering the user's device information when outputting audio. For example, if the user is using a smartphone, the audio output unit can provide audio output optimized for the smartphone's speaker. Furthermore, if the user is using headphones, the audio output unit can provide audio output optimized for headphones. In addition, if the user is using an in-car system, the audio output unit can provide audio output optimized for the in-car speaker. This allows the system to select the optimal audio output method by considering the user's device information.

[0055] The mobile information access support function can optimize the timing of information delivery by detecting the user's current speed and direction of movement. For example, if the user is moving at high speed, the mobile information access support function will speed up the timing of information delivery. Conversely, if the user is moving at low speed, the mobile information access support function can delay the timing of information delivery. Furthermore, the mobile information access support function can select the optimal timing of information delivery based on the user's direction of movement. In this way, the timing of information delivery can be optimized by detecting the user's current speed and direction of movement.

[0056] The on-the-go information access support function can select the optimal information delivery method by referring to the user's past travel history while they are on the move. For example, the on-the-go information access support function can select the optimal information delivery method based on the travel routes the user has used in the past. It can also identify specific patterns from the user's past travel history and select the optimal information delivery method. Furthermore, the on-the-go information access support function can analyze information the user has received while traveling in the past and select the optimal information delivery method. In this way, the optimal information delivery method can be selected by referring to the user's past travel history.

[0057] The mobile information access support feature prioritizes providing relevant information while the user is on the move, taking into account their geographical location. For example, if the user is in a specific location, the mobile information access support feature prioritizes information related to that location. Furthermore, if the user is in a specific region, the mobile information access support feature can prioritize information related to that region. This allows for the prioritization of highly relevant information by considering the user's geographical location.

[0058] The mobile information access support function can select the optimal information delivery method while the user is on the move, taking into account the user's device information. For example, if the user is using a smartphone, the mobile information access support function will select an information delivery method optimized for smartphones. It can also select an information delivery method optimized for tablets if the user is using a tablet, and even for smartwatches if the user is using a smartwatch. This allows the system to select the most suitable information delivery method by considering the user's device information.

[0059] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0060] The generator can refer to the user's past question history to generate answers based on the user's interests. For example, if a user has frequently asked questions about the weather in the past, the generator will determine that the user is interested in the weather and provide detailed information about it. Similarly, if a user has asked questions about news in the past, the generator will determine that the user is interested in news and can provide the latest news. Furthermore, if a user has asked questions about a specific topic in the past, the generator can prioritize providing information related to that topic. In this way, by referring to the user's past question history, more relevant information can be provided.

[0061] The display unit can automatically adjust the font size and color of the displayed content based on the user's visual characteristics. For example, if the user has poor eyesight, the display unit will increase the font size. If the user has color vision deficiency, the display unit can adjust the color contrast. Furthermore, if the user is using the device at night, the display unit can automatically adjust the screen brightness to provide a more eye-friendly display. In this way, visibility can be improved by adjusting the displayed content based on the user's visual characteristics.

[0062] The reception desk can prioritize receiving highly relevant information by considering the user's geographical location. For example, if the user is in a specific location, it will prioritize receiving information related to that location. Furthermore, if the user is on the move, it can prioritize receiving relevant information based on their current location. Additionally, if the user is in a specific region, it can prioritize receiving information related to that region. In this way, by considering the user's geographical location, it can prioritize receiving highly relevant information.

[0063] The display unit can select the optimal display layout by referring to the user's past browsing history. For example, it can prioritize displaying relevant information based on the content the user has previously viewed. It can also select the optimal display layout from the user's past browsing history. Furthermore, it can analyze the content the user has previously viewed and provide the optimal display method. In this way, the optimal display layout can be selected by referring to the user's past browsing history.

[0064] The information access support function while on the move can select the optimal information delivery method by referring to the user's past travel history. For example, it can select the optimal information delivery method based on the travel routes the user has used in the past. It can also identify specific patterns from the user's past travel history and select the optimal information delivery method. Furthermore, it can analyze information the user has received while traveling in the past and select the optimal information delivery method. In this way, the optimal information delivery method can be selected by referring to the user's past travel history.

[0065] The following briefly describes the processing flow for example form 1.

[0066] Step 1: The reception desk accepts information input. This includes voice input, touchscreen input, image input, and text input. For example, if a user asks "What's the weather like today?" by voice, the reception desk will accept that voice input. Alternatively, if a user enters a question using a touchscreen, the reception desk can also accept that touch input. Step 2: The generation unit analyzes the information received by the reception unit and generates a response. The generation unit uses a generation AI to generate an appropriate response to the user's question. For example, if the user asks "What's the weather like today?", it will generate a response such as "The weather today is sunny." Step 3: The display unit displays the answer generated by the generation unit. The display unit displays the information on a small display built into the chest of the robot-shaped smartphone. For example, it displays an answer such as "Today's weather is sunny." Step 4: The audio output unit provides the answer generated by the generation unit as audio. The audio output unit outputs the generated answer as audio using a speaker. For example, it provides an answer such as "The weather today is sunny" as audio.

[0067] (Example of form 2) The robot-type smartphone system according to an embodiment of the present invention is a palm-sized robot-type smartphone that combines the cute appearance of a robot with advanced conversational capabilities such as generative AI. This robot-type smartphone system has a small display built into its chest and provides functions such as displaying news and weather forecasts and performing internet searches. For example, the user inputs information using voice input or a touchscreen. For example, the user inputs questions such as "What's the weather like today?" or "Tell me the latest news." This information is input to the generative AI. Next, the generative AI analyzes the input information and generates an appropriate answer to the user's question. The generative AI has advanced natural language processing capabilities and provides information based on the user's utterance. For example, it generates answers such as "The weather today is sunny" or "The latest news is XX." The generated answers are displayed on the small display built into the chest of the robot-type smartphone. This allows the user to visually confirm the information. In addition, the generated answers can also be provided by voice using the voice output function. This mechanism allows users to quickly obtain information and revitalizes daily communication. Furthermore, it improves the user's understanding of information and eliminates delays and inconveniences in accessing information. Furthermore, this robot-shaped smartphone is convenient for users who want to access information while on the go. For example, they can obtain information using voice input or a touchscreen while commuting or out and about. In this way, the fusion of robot technology and smartphones can bring about innovation in information and communication. The target audience is expected to be young to middle-aged users who are interested in technology. As a result, the robot-shaped smartphone system will enable users to obtain information quickly and efficiently, making information access in daily life easier.

[0068] The robot-type smartphone system according to this embodiment comprises a reception unit, a generation unit, a display unit, and an audio output unit. The reception unit receives information input. Information input includes, but is not limited to, voice input and touchscreen input. For example, if a user asks "What's the weather like today?", the reception unit receives that voice. The reception unit can also receive touch input if a user enters a question using a touchscreen. Furthermore, the reception unit can also receive other forms of information input, such as image input and text input. The generation unit analyzes the information received by the reception unit and generates an answer. The generation unit generates an appropriate answer to the user's question, for example, using a generation AI. The generation AI has advanced natural language processing capabilities and provides information based on the user's utterance. For example, if a user asks "What's the weather like today?", the generation unit generates an answer such as "The weather is sunny today." The generation unit can also generate an answer such as "The latest news is XX" if a user asks "Tell me the latest news." The display unit displays the answers generated by the generation unit. The display unit displays information on a small display built into the chest of the robot-type smartphone, for example. For example, the display unit displays an answer such as "Today's weather is sunny" on the display. The display unit can also visually display news and weather forecast information. Furthermore, the display unit can also display internet search results and other information. The voice output unit provides the answers generated by the generation unit in voice. The voice output unit outputs the generated answers in voice, for example, using a speaker. For example, the voice output unit provides an answer such as "Today's weather is sunny" in voice. Furthermore, the voice output unit can also provide news and weather forecast information in voice. Furthermore, the voice output unit can also provide internet search results and other information in voice. As a result, the robot-type smartphone system according to this embodiment can consistently perform everything from information input to analysis, display, and voice output.

[0069] The reception unit accepts information input. This input includes, but is not limited to, voice input and touchscreen input. For example, if a user asks a question aloud, such as "What's the weather like today?", the reception unit will accept that voice input. It can also accept touch input if the user enters a question using a touchscreen. Furthermore, the reception unit can accept other forms of information input, such as image input and text input. Specifically, for voice input, the reception unit uses a high-sensitivity microphone to accurately capture the user's voice and noise cancellation technology to remove ambient noise. For touchscreen input, a capacitive touch panel is used to detect the user's finger movements with high precision. For image input, a camera is used to capture the image presented by the user, and OCR (optical character recognition) technology is used to analyze the text within the image. For text input, the reception unit accepts text entered by the user using a keyboard or software keyboard. This allows the reception unit to support diverse input formats and improve user convenience. Furthermore, the reception unit temporarily stores the input information and performs pre-processing as needed before sending it to the generation unit. For example, in the case of voice input, speech recognition technology is used to convert the speech into text, which is then sent to the generation unit. This allows the receiving unit to smoothly handle everything from information input to transmission to the generation unit.

[0070] The generation unit analyzes the information received by the reception unit and generates responses. For example, the generation unit uses a generation AI to generate appropriate answers to user questions. The generation AI has advanced natural language processing capabilities and provides information based on the user's utterances. Specifically, the generation AI analyzes the user's question and considers the context to understand the intent of the question. For example, if a user asks, "What's the weather like today?", the generation AI considers the current date and the user's location to provide appropriate weather information. The generation AI also retrieves the latest news and weather forecasts from internet sources to keep the information provided to the user up-to-date. Furthermore, the generation AI can learn the user's past question history and preferences to provide more personalized responses. For example, if a user frequently shows interest in a particular news category, the generation AI will prioritize providing the latest news related to that category. This allows the generation unit to generate highly accurate responses that meet the user's needs and improve the user experience. In addition, the generation unit reviews the content of the generated responses and makes corrections as needed before sending them to the display unit and audio output unit. This ensures the accuracy and reliability of the information provided to the user.

[0071] The display unit displays the answers generated by the generation unit. For example, the display unit displays information on a small display built into the chest of a robot-shaped smartphone. Specifically, the display unit employs a high-resolution LCD or OLED display to achieve a clear and easy-to-read display. For example, the display unit displays answers such as "Today's weather is sunny." The display unit can also visually display news and weather forecast information. For example, in the case of weather forecasts, icons and graphs are used to make the information visually easy to understand. Furthermore, the display unit can also display internet search results and other information. For example, if a user asks "What's the latest news?", the display unit displays news headlines and summaries, allowing the user to view details. The display unit has touchscreen functionality, allowing users to interact with the displayed information by touching it. This enables the display unit to not only provide visual information to the user but also to enable interactive operation. Furthermore, the display unit automatically adjusts the brightness and contrast of the backlight to provide optimal display according to the ambient light. This allows the display unit to provide a display that is easy to read in various environments, improving user convenience.

[0072] The voice output unit provides the generated answers in voice. The voice output unit outputs the generated answers in voice, for example, using a speaker. Specifically, the voice output unit incorporates a high-quality speaker to provide clear and natural voice. For example, the voice output unit provides answers such as, "Today's weather is sunny." The voice output unit can also provide news and weather forecast information in voice. For example, by reading the latest news aloud, users can obtain information without relying on visual information. Furthermore, the voice output unit can provide internet search results and other information in voice. For example, if a user asks, "Tell me the latest movie information," the voice output unit will provide the titles and showtimes of the latest movies in voice. The voice output unit uses speech synthesis technology to achieve natural pronunciation and intonation. This allows users to have a natural voice experience, as if they were conversing with a human. Furthermore, the voice output unit can adjust the tone and speed of the voice according to the user's preferences. For example, if a user prefers a slow voice, the voice output unit will adjust the speed of the voice to provide a slower voice. This allows the audio output unit to provide users with high-quality, personalized audio information, thereby improving the user experience.

[0073] The reception desk can support both voice input and touchscreen input. For example, if a user enters a question by voice, the reception desk will receive the voice input. The reception desk can also accept touch input if a user enters a question using a touchscreen. For example, the reception desk can receive voice input using a microphone. The voice input is analyzed using speech recognition technology and converted into text data. Furthermore, the reception desk can receive touchscreen input using a touch panel. The touchscreen input is analyzed using gesture recognition technology to understand the user's intent. This support for both voice and touchscreen input improves user convenience.

[0074] The generation unit can provide information based on the user's utterances. For example, the generation unit uses a generation AI to analyze the user's utterances and generate appropriate responses. The generation AI has advanced natural language processing capabilities and provides information based on the user's utterances. For example, if the user asks, "What's the weather like today?", the generation unit will generate a response such as, "The weather today is sunny." The generation unit can also generate a response such as, "The latest news is XX," if the user asks, "Tell me the latest news." In this way, by providing information based on the user's utterances, it can generate appropriate responses.

[0075] The display unit can display information on a small display built into the chest. For example, the display unit can display information on a small display built into the chest of a robot-shaped smartphone. For example, the display unit can display answers such as "Today's weather is sunny." The display unit can also visually display news and weather forecast information. Furthermore, the display unit can display internet search results and other information. This allows users to visually confirm information by displaying it on a small display built into the chest.

[0076] The voice output unit can provide the generated response in voice. For example, the voice output unit uses a speaker to output the generated response as voice. For instance, the voice output unit can provide a voice response such as, "Today's weather is sunny." The voice output unit can also provide news and weather forecast information in voice. Furthermore, the voice output unit can provide internet search results and other information in voice. This allows users to receive information by voice by providing the generated response.

[0077] The system can be equipped with features to support information access even while on the go. For example, the system can allow users to obtain information using voice input or a touchscreen while commuting or out and about. For instance, if a user on the go asks "What's the weather like today?" by voice, the system can receive the voice input, generate an appropriate answer, and provide it by voice. Alternatively, if a user on the go enters a question using a touchscreen, the system can receive the touch input, generate an appropriate answer, and display it on the screen. This supports information access even while on the go, allowing users to obtain information wherever they are.

[0078] The reception system can estimate the user's emotions and adjust the timing of input acceptance based on the estimated emotions. For example, if the user is stressed, the reception system can delay input acceptance and wait until the user is relaxed. Conversely, if the user is relaxed, the reception system can speed up input acceptance to smoothly receive information. Furthermore, if the user is in a hurry, the reception system can adjust to accept input immediately. By adjusting the timing of input acceptance according to the user's emotions, information can be received at a more appropriate time. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0079] The reception desk can analyze a user's past input history and suggest the most suitable input method. For example, it can prioritize suggesting input methods that the user has frequently used in the past (such as voice or touchscreen). Furthermore, the reception desk can predict and suggest input methods that the user will use during specific time periods based on their past input history. In addition, the reception desk can suggest relevant input methods based on content the user has previously entered. This allows the system to suggest the most suitable input method by analyzing the user's past input history.

[0080] The reception unit can detect the ambient noise level during voice input and automatically adjust noise cancellation. For example, if the surroundings are quiet, the reception unit will accept voice input with minimal noise cancellation. Conversely, if the surroundings are noisy, the reception unit can accept voice input with maximum noise cancellation. Furthermore, the reception unit can adjust the intensity of noise cancellation in real time according to the ambient noise level. This automatic adjustment of noise cancellation according to the ambient noise level improves the accuracy of voice input.

[0081] The reception desk can estimate the user's emotions and prioritize input based on those emotions. For example, if the user is stressed, the reception desk will prioritize receiving important information. If the user is relaxed, the reception desk can also accept all input equally. Furthermore, if the user is in a hurry, the reception desk can prioritize receiving urgent information. In this way, by prioritizing input according to the user's emotions, important information can be received preferentially. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0082] The reception system can prioritize receiving highly relevant information by considering the user's geographical location during voice input. For example, if the user is in a specific location, the reception system will prioritize receiving information related to that location. Furthermore, if the user is on the move, the reception system can prioritize receiving relevant information based on their current location. Additionally, if the user is in a specific region, the reception system can prioritize receiving information related to that region. This allows the system to prioritize receiving highly relevant information by considering the user's geographical location.

[0083] The input unit can recognize user gestures and complete input during touchscreen input. For example, if the user performs a specific gesture, the input unit will automatically complete the corresponding input. Furthermore, if the user combines multiple gestures, the input unit can complete the input based on that combination. In addition, the input unit can consider the speed and direction of the user's gestures to complete the optimal input. This allows the input to be completed by recognizing the user's gestures.

[0084] The generation unit can estimate the user's emotions and adjust the way the response is expressed based on the estimated emotions. For example, if the user is stressed, the generation unit will generate a concise and easy-to-understand response. If the user is relaxed, the generation unit can also generate a response that includes detailed explanations. Furthermore, if the user is in a hurry, the generation unit can generate a response quickly. This allows for the provision of more appropriate responses by adjusting the way the response is expressed according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0085] The generation unit can improve the accuracy of its answers by referring to the user's past question history during the generation process. For example, the generation unit generates relevant answers based on the content of questions the user has asked in the past. Furthermore, the generation unit can identify specific patterns from the user's past question history and generate highly accurate answers. In addition, the generation unit can analyze the content of questions the user has asked in the past and generate the optimal answer. This allows for improved answer accuracy by referring to the user's past question history.

[0086] The generation unit can customize the response content based on the user's current interests during generation. For example, the generation unit generates relevant responses based on topics the user is currently interested in. It can also analyze the user's current interests and customize the response content accordingly. Furthermore, the generation unit can generate responses related to the user's interests based on their recent searches. This allows for the provision of more relevant responses by customizing the response content based on the user's current interests.

[0087] The generation unit can estimate the user's emotions and adjust the level of detail in the response based on the estimated emotions. For example, if the user is stressed, the generation unit will generate a concise and to-the-point response. If the user is relaxed, the generation unit can also generate a response with detailed explanations. Furthermore, if the user is in a hurry, the generation unit can generate a response quickly. This allows for the provision of more appropriate responses by adjusting the level of detail in the response according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0088] The generation unit can provide highly relevant information by considering the user's geographical location during generation. For example, if the user is in a specific location, the generation unit can provide information related to that location. Furthermore, if the user is on the move, the generation unit can provide relevant information based on their current location. Additionally, if the user is in a specific region, the generation unit can provide information related to that region. This allows the generation unit to provide highly relevant information by considering the user's geographical location.

[0089] The generation unit can analyze the user's social media activity during generation to supplement the response content. For example, the generation unit generates relevant responses based on information shared by the user on social media. It can also analyze the user's interests from their social media activity and supplement the response content accordingly. Furthermore, the generation unit can generate relevant responses based on information about accounts the user follows on social media. This allows for the supplementation of response content by analyzing the user's social media activity.

[0090] The display unit can estimate the user's emotions and adjust the display method based on the estimated emotions. For example, if the user is stressed, the display unit can provide a simple and highly visible display method. If the user is relaxed, the display unit can also provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the display unit can provide a concise display method. This allows for more appropriate display by adjusting the display method according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may include, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0091] The display unit can automatically adjust font size and color based on the user's visual characteristics during display. For example, if the user has poor eyesight, the display unit will display in a larger font size. Furthermore, if the user has color vision deficiency, the display unit can adjust the color contrast. In addition, the display unit can automatically adjust the optimal font size and color based on the user's visual characteristics. This automatic adjustment of font size and color based on the user's visual characteristics improves visibility.

[0092] The display unit can select the optimal display layout by referring to the user's past browsing history when displaying information. For example, the display unit can prioritize displaying relevant information based on the content the user has previously viewed. Furthermore, the display unit can select the optimal display layout from the user's past browsing history. In addition, the display unit can analyze the content the user has previously viewed and provide the optimal display method. This allows the display unit to select the optimal display layout by referring to the user's past browsing history.

[0093] The display unit can estimate the user's emotions and determine the priority of the displayed content based on the estimated emotions. For example, if the user is feeling stressed, the display unit will prioritize displaying important information. Conversely, if the user is relaxed, the display unit can display all information equally. Furthermore, if the user is in a hurry, the display unit can prioritize displaying information of high urgency. This allows for the prioritization of important information by determining the priority of displayed content according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may include, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0094] The display unit can prioritize displaying highly relevant information by considering the user's geographical location. For example, if the user is in a specific location, the display unit will prioritize displaying information related to that location. Furthermore, if the user is on the move, the display unit can prioritize displaying relevant information based on their current location. Additionally, if the user is in a specific region, the display unit can prioritize displaying information related to that region. This allows the display to prioritize highly relevant information by considering the user's geographical location.

[0095] The display unit can select the optimal display method by considering the user's device information when displaying information. For example, if the user is using a smartphone, the display unit provides a display method that matches the screen size. Furthermore, if the user is using a tablet, the display unit can provide a display method optimized for a larger screen. In addition, if the user is using a smartwatch, the display unit can provide a concise and highly visible display method. This allows the optimal display method to be selected by considering the user's device information.

[0096] The voice output unit can estimate the user's emotions and adjust the tone and speed of the voice based on the estimated emotions. For example, if the user is stressed, the voice output unit will output the voice slowly in a calm tone. Conversely, if the user is relaxed, the voice output unit can output the voice in a bright tone. Furthermore, if the user is in a hurry, the voice output unit can output the voice quickly and concisely. This allows for more appropriate voice output by adjusting the tone and speed of the voice according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may include, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0097] The audio output unit can automatically adjust the volume and sound quality based on the user's hearing characteristics when outputting audio. For example, if the user has poor hearing, the audio output unit will automatically increase the volume. Furthermore, if the user has difficulty hearing high frequencies, the audio output unit can adjust the sound quality to emphasize those frequencies. In addition, the audio output unit can automatically adjust the optimal volume and sound quality based on the user's hearing characteristics. This allows for optimal audio output by automatically adjusting the volume and sound quality based on the user's hearing characteristics.

[0098] The audio output unit can provide optimal audio feedback by referring to the user's past listening history when outputting audio. For example, the audio output unit can provide optimal audio based on audio feedback that the user has previously enjoyed listening to. Furthermore, the audio output unit can identify specific patterns from the user's past listening history and provide optimal audio feedback. In addition, the audio output unit can analyze content the user has previously listened to and provide optimal audio feedback. This allows the system to provide optimal audio feedback by referring to the user's past listening history.

[0099] The voice output unit can estimate the user's emotions and prioritize the content of the voice output based on the estimated emotions. For example, if the user is stressed, the voice output unit will prioritize outputting important information. If the user is relaxed, the voice output unit can output all information equally. Furthermore, if the user is in a hurry, the voice output unit can prioritize outputting information of high urgency. In this way, by prioritizing the content of the voice output according to the user's emotions, important information can be output preferentially. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0100] The audio output unit can prioritize outputting highly relevant information by considering the user's geographical location. For example, if the user is in a specific location, the audio output unit will prioritize outputting information related to that location. Furthermore, if the user is on the move, the audio output unit can prioritize outputting relevant information based on their current location. Additionally, if the user is in a specific region, the audio output unit can prioritize outputting information related to that region. This allows for the prioritization of highly relevant information by considering the user's geographical location.

[0101] The audio output unit can select the optimal audio output method by considering the user's device information when outputting audio. For example, if the user is using a smartphone, the audio output unit can provide audio output optimized for the smartphone's speaker. Furthermore, if the user is using headphones, the audio output unit can provide audio output optimized for headphones. In addition, if the user is using an in-car system, the audio output unit can provide audio output optimized for the in-car speaker. This allows the system to select the optimal audio output method by considering the user's device information.

[0102] The mobile information access support function can estimate the user's emotions and adjust the way information is delivered based on those emotions. For example, if the user is stressed, the mobile information access support function will select a concise and easy-to-understand method of information delivery. If the user is relaxed, it can also select a method of information delivery that includes detailed information. Furthermore, if the user is in a hurry, it can select a method of delivering information quickly. By adjusting the way information is delivered during travel according to the user's emotions, more appropriate information can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0103] The mobile information access support function can optimize the timing of information delivery by detecting the user's current speed and direction of movement. For example, if the user is moving at high speed, the mobile information access support function will speed up the timing of information delivery. Conversely, if the user is moving at low speed, the mobile information access support function can delay the timing of information delivery. Furthermore, the mobile information access support function can select the optimal timing of information delivery based on the user's direction of movement. In this way, the timing of information delivery can be optimized by detecting the user's current speed and direction of movement.

[0104] The on-the-go information access support function can select the optimal information delivery method by referring to the user's past travel history while they are on the move. For example, the on-the-go information access support function can select the optimal information delivery method based on the travel routes the user has used in the past. It can also identify specific patterns from the user's past travel history and select the optimal information delivery method. Furthermore, the on-the-go information access support function can analyze information the user has received while traveling in the past and select the optimal information delivery method. In this way, the optimal information delivery method can be selected by referring to the user's past travel history.

[0105] The mobile information access support function can estimate the user's emotions and prioritize the information provided during travel based on those emotions. For example, if the user is stressed, the mobile information access support function will prioritize providing important information. Conversely, if the user is relaxed, it can provide all information equally. Furthermore, if the user is in a hurry, the mobile information access support function can prioritize providing highly urgent information. In this way, by prioritizing the information provided during travel according to the user's emotions, important information can be provided preferentially. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0106] The mobile information access support feature prioritizes providing relevant information while the user is on the move, taking into account their geographical location. For example, if the user is in a specific location, the mobile information access support feature prioritizes information related to that location. Furthermore, if the user is in a specific region, the mobile information access support feature can prioritize information related to that region. This allows for the prioritization of highly relevant information by considering the user's geographical location.

[0107] The mobile information access support function can select the optimal information delivery method while the user is on the move, taking into account the user's device information. For example, if the user is using a smartphone, the mobile information access support function will select an information delivery method optimized for smartphones. It can also select an information delivery method optimized for tablets if the user is using a tablet, and even for smartwatches if the user is using a smartwatch. This allows the system to select the most suitable information delivery method by considering the user's device information.

[0108] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0109] The reception system can analyze the tone and speed of the user's voice when receiving voice input, and estimate the user's emotions. For example, if a user is in a hurry, their voice tone is often high and their speed is fast. In this case, the reception system estimates that the user is in a hurry and receives the information quickly. Conversely, if a user is relaxed, their voice tone is often low and their speed is slow. In this case, the reception system estimates that the user is relaxed and can receive the information slowly. Furthermore, if a user is stressed, their voice tone is often unstable and their speed fluctuates. In this case, the reception system estimates that the user is stressed and can receive the information at an appropriate time. By adjusting the information reception method according to the user's emotions, it becomes possible to provide more appropriate information.

[0110] The generator can refer to the user's past question history to generate answers based on the user's interests. For example, if a user has frequently asked questions about the weather in the past, the generator will determine that the user is interested in the weather and provide detailed information about it. Similarly, if a user has asked questions about news in the past, the generator will determine that the user is interested in news and can provide the latest news. Furthermore, if a user has asked questions about a specific topic in the past, the generator can prioritize providing information related to that topic. In this way, by referring to the user's past question history, more relevant information can be provided.

[0111] The display unit can automatically adjust the font size and color of the displayed content based on the user's visual characteristics. For example, if the user has poor eyesight, the display unit will increase the font size. If the user has color vision deficiency, the display unit can adjust the color contrast. Furthermore, if the user is using the device at night, the display unit can automatically adjust the screen brightness to provide a more eye-friendly display. In this way, visibility can be improved by adjusting the displayed content based on the user's visual characteristics.

[0112] The voice output unit can estimate the user's emotions and adjust the tone and speed of the voice based on those estimates. For example, if the user is stressed, the voice output unit will output the voice slowly in a calm tone. If the user is relaxed, the voice output unit can output the voice in a bright tone. Furthermore, if the user is in a hurry, the voice output unit can output the voice quickly and concisely. By adjusting the tone and speed of the voice according to the user's emotions, more appropriate voice output becomes possible.

[0113] The reception desk can prioritize receiving highly relevant information by considering the user's geographical location. For example, if the user is in a specific location, it will prioritize receiving information related to that location. Furthermore, if the user is on the move, it can prioritize receiving relevant information based on their current location. Additionally, if the user is in a specific region, it can prioritize receiving information related to that region. In this way, by considering the user's geographical location, it can prioritize receiving highly relevant information.

[0114] The generation unit can estimate the user's emotions and adjust the way the response is expressed based on those emotions. For example, if the user is stressed, it can generate a concise and easy-to-understand response. If the user is relaxed, it can generate a response that includes detailed explanations. Furthermore, if the user is in a hurry, it can generate a response quickly. In this way, by adjusting the way the response is expressed according to the user's emotions, it can provide a more appropriate response.

[0115] The display unit can select the optimal display layout by referring to the user's past browsing history. For example, it can prioritize displaying relevant information based on the content the user has previously viewed. It can also select the optimal display layout from the user's past browsing history. Furthermore, it can analyze the content the user has previously viewed and provide the optimal display method. In this way, the optimal display layout can be selected by referring to the user's past browsing history.

[0116] The audio output unit can estimate the user's emotions and prioritize the audio output content based on those emotions. For example, if the user is stressed, important information will be prioritized in the audio output. If the user is relaxed, all information can be output equally. Furthermore, if the user is in a hurry, highly urgent information can be prioritized in the audio output. In this way, by prioritizing the audio output content according to the user's emotions, important information can be prioritized in the audio output.

[0117] The on-the-go information access support function can estimate the user's emotions and adjust the way information is delivered based on those emotions. For example, if the user is stressed, it can select a concise and easy-to-understand information delivery method. If the user is relaxed, it can select an information delivery method that includes detailed information. Furthermore, if the user is in a hurry, it can select a method that delivers information quickly. By adjusting the information delivery method during travel according to the user's emotions, it becomes possible to provide more appropriate information.

[0118] The information access support function while on the move can select the optimal information delivery method by referring to the user's past travel history. For example, it can select the optimal information delivery method based on the travel routes the user has used in the past. It can also identify specific patterns from the user's past travel history and select the optimal information delivery method. Furthermore, it can analyze information the user has received while traveling in the past and select the optimal information delivery method. In this way, the optimal information delivery method can be selected by referring to the user's past travel history.

[0119] The following briefly describes the processing flow for example form 2.

[0120] Step 1: The reception desk accepts information input. This includes voice input, touchscreen input, image input, and text input. For example, if a user asks "What's the weather like today?" by voice, the reception desk will accept that voice input. Alternatively, if a user enters a question using a touchscreen, the reception desk can also accept that touch input. Step 2: The generation unit analyzes the information received by the reception unit and generates a response. The generation unit uses a generation AI to generate an appropriate response to the user's question. For example, if the user asks "What's the weather like today?", it will generate a response such as "The weather today is sunny." Step 3: The display unit displays the answer generated by the generation unit. The display unit displays the information on a small display built into the chest of the robot-shaped smartphone. For example, it displays an answer such as "Today's weather is sunny." Step 4: The audio output unit provides the answer generated by the generation unit as audio. The audio output unit outputs the generated answer as audio using a speaker. For example, it provides an answer such as "The weather today is sunny" as audio.

[0121] 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.

[0122] Data generation model 58 is a form of 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> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0123] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0124] Each of the multiple elements described above, including the reception unit, generation unit, display unit, and voice output unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the reception unit is implemented by the touch panel 38A and microphone 38B of the smart device 14 and receives the user's voice or touch input. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates an appropriate answer to the user's question using a generation AI. The display unit is implemented by the display 40A of the smart device 14 and visually displays the generated answer. The voice output unit is implemented by the speaker 40B of the smart device 14 and provides the generated answer by voice. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0125] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0126] 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.

[0127] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0128] 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.

[0129] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0130] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0131] 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.

[0132] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0133] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0134] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0135] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0136] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0137] 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.

[0138] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0139] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0140] Each of the multiple elements described above, including the reception unit, generation unit, display unit, and audio output unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the microphone 238 of the smart glasses 214 and receives voice input from the user. The generation unit is implemented by the identification processing unit 290 of the data processing unit 12 and generates an appropriate answer to the user's question using generation AI. The display unit is implemented by the display of the smart glasses 214 and visually displays the generated answer. The audio output unit is implemented by the speaker 240 of the smart glasses 214 and provides the generated answer by voice. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0141] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0142] 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.

[0143] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0144] 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.

[0145] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0146] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0147] 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.

[0148] 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.

[0149] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0150] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0151] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0152] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0153] 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.

[0154] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0155] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0156] Each of the multiple elements described above, including the reception unit, generation unit, display unit, and audio output unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the microphone 238 of the headset terminal 314 and receives voice input from the user. The generation unit is implemented by the identification processing unit 290 of the data processing unit 12 and generates an appropriate answer to the user's question using a generation AI. The display unit is implemented by the display 343 of the headset terminal 314 and visually displays the generated answer. The audio output unit is implemented by the speaker 240 of the headset terminal 314 and provides the generated answer by voice. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0157] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0158] 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.

[0159] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0160] 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.

[0161] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0162] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0163] 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.

[0164] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0165] 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.

[0166] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0167] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0168] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0169] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0170] 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.

[0171] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0172] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0173] Each of the multiple elements described above, including the reception unit, generation unit, display unit, and voice output unit, is implemented in, for example, at least one of the robot 414 and the data processing unit 12. For example, the reception unit is implemented by the microphone 238 of the robot 414 and receives voice input from the user. The generation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12 and generates an appropriate answer to the user's question using a generation AI. The display unit is implemented by, for example, the display of the robot 414 and visually displays the generated answer. The voice output unit is implemented by, for example, the speaker 240 of the robot 414 and provides the generated answer in voice. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0174] 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.

[0175] Figure 9 shows the 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.

[0176] 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.

[0177] 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.

[0178] 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, and motorcycles, 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 based, for example, 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.

[0179] 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."

[0180] 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.

[0181] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0190] 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 other things 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.

[0191] 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.

[0192] (Note 1) The reception area accepts information input, A generation unit analyzes the information received by the reception unit and generates a response, A display unit that displays the answer generated by the generation unit, The system includes an audio output unit that provides the response generated by the generation unit as audio. A system characterized by the following features. (Note 2) The aforementioned reception unit is Supports voice input and touchscreen input. The system described in Appendix 1, characterized by the features described herein. (Note 3) The generating unit is Provide information based on what the user says. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned display unit is Information is displayed on a small screen built into the chest. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned audio output unit is Provides the generated response in audio. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned system, It features functions that support information access even while on the go. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned reception unit is The system estimates the user's emotions and adjusts the timing of input acceptance based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is It analyzes the user's past input history and suggests the optimal input method. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is When voice input is used, the system detects the ambient noise level and automatically adjusts noise cancellation. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is It estimates the user's emotions and prioritizes input content based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is When using voice input, the system prioritizes receiving highly relevant information by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is During touchscreen input, the system recognizes user gestures to complete the input. The system described in Appendix 1, characterized by the features described herein. (Note 13) The generating unit is It estimates the user's emotions and adjusts the way responses are expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The generating unit is During generation, the system improves the accuracy of the answers by referencing the user's past question history. The system described in Appendix 1, characterized by the features described herein. (Note 15) The generating unit is During generation, the responses are customized based on the user's current interests. The system described in Appendix 1, characterized by the features described herein. (Note 16) The generating unit is The system estimates the user's emotions and adjusts the level of detail in the responses based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The generating unit is When generating data, the system considers the user's geographical location to provide highly relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 18) The generating unit is During generation, the system analyzes the user's social media activity to supplement the response content. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned display unit is It estimates the user's emotions and adjusts the display method based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned display unit is When displayed, the font size and color are automatically adjusted based on the user's visual characteristics. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned display unit is When displaying content, the system selects the optimal display layout by referring to the user's past browsing history. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned display unit is It estimates the user's emotions and determines the priority of displayed content based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned display unit is When displaying information, the system prioritizes showing more relevant information, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned display unit is When displaying content, the system selects the optimal display method by considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned audio output unit is It estimates the user's emotions and adjusts the tone and speed of the voice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned audio output unit is When outputting audio, the volume and sound quality are automatically adjusted based on the user's hearing characteristics. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned audio output unit is When outputting audio, the system provides optimal audio feedback by referencing the user's past listening history. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned audio output unit is It estimates the user's emotions and prioritizes the content of the voice output based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned audio output unit is When outputting audio, the system prioritizes outputting highly relevant information, taking into account the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned audio output unit is When outputting audio, the system selects the optimal audio output method by considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned information access support function during transit is, The system estimates the user's emotions and adjusts the way information is provided while the user is on the move based on those estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 32) The aforementioned information access support function during transit is, While the user is moving, the system detects their current speed and direction to optimize the timing of information delivery. The system described in Appendix 2, characterized by the features described herein. (Note 33) The aforementioned information access support function during transit is, While the user is in transit, the system will refer to their past travel history to select the most appropriate method for providing information. The system described in Appendix 2, characterized by the features described herein. (Note 34) The aforementioned information access support function during transit is, The system estimates the user's emotions and prioritizes the information provided during travel based on those estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 35) The aforementioned information access support function during transit is, While the user is on the move, the system prioritizes providing relevant information by taking into account the user's geographical location. The system described in Appendix 2, characterized by the features described herein. (Note 36) The aforementioned information access support function during transit is, While the user is on the move, the system selects the optimal method for providing information, taking into account the user's device information. The system described in Appendix 2, characterized by the features described herein. [Explanation of symbols]

[0193] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The reception area accepts information input, A generation unit analyzes the information received by the reception unit and generates a response, A display unit that displays the answer generated by the generation unit, The system includes an audio output unit that provides the response generated by the generation unit as audio. A system characterized by the following features.

2. The aforementioned reception unit is Supports voice input and touchscreen input. The system according to feature 1.

3. The generating unit is Provide information based on what the user says. The system according to feature 1.

4. The aforementioned display unit is Information is displayed on a small screen built into the chest. The system according to feature 1.

5. The aforementioned audio output unit is Provides the generated response in audio. The system according to feature 1.

6. The aforementioned system, It features functions that support information access even while on the go. The system according to feature 1.

7. The aforementioned reception unit is The system estimates the user's emotions and adjusts the timing of input acceptance based on the estimated emotions. The system according to feature 1.

8. The aforementioned reception unit is It analyzes the user's past input history and suggests the optimal input method. The system according to feature 1.

9. The aforementioned reception unit is When voice input is used, the system detects the ambient noise level and automatically adjusts noise cancellation. The system according to feature 1.

10. The aforementioned reception unit is It estimates the user's emotions and prioritizes input content based on those estimated emotions. The system according to feature 1.

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