system

Abstract

An object of a system according to an embodiment is to enable a visually impaired person to obtain information on a public sign or a guide board by voice.SOLUTION: A system includes a QR code installation part, a recognition part, and a feedback part. The QR code installation unit installs a QR code on a public sign or a guide plate. The recognition unit reads the QR code installed by the QR code installation unit and recognizes an image or a character. The feedback unit feeds back the information recognized by the recognition unit by voice.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has limited the means by which visually impaired people can obtain information from public signs and guide boards, and has made it difficult to provide multilingual support.

[0005] The system according to the embodiment aims to enable visually impaired people to obtain information from public signs and guide boards by voice. [Means for solving the problem]

[0006] The system according to the embodiment includes a QR code installation unit, a recognition unit, and a feedback unit. The QR code installation unit installs a QR code on a public sign or information board. The recognition unit reads the QR code installed by the QR code installation unit and recognizes images and characters. The feedback unit provides audio feedback of the information recognized by the recognition unit. [Effects of the Invention]

[0007] The system according to the embodiment allows visually impaired people to obtain information from public signs and guide boards by voice. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also 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. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an 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 emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may 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 a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The system according to the embodiment of the present invention is a system that places QR codes on public signs and information boards for the visually impaired, recognizes images and text by reading the codes, and provides audio feedback. This system can solve the problems of infrastructure limitations such as Braille and the difficulty of supporting multiple languages.

[0029] A system according to an embodiment includes a QR code installation unit, a recognition unit, and a feedback unit. The QR code installation unit installs QR codes on public signs and information boards. For example, the QR code installation unit installs QR codes on station information boards, bus stop timetables, and information boards at public facilities. The QR code installation unit can also incorporate a system that dynamically changes the installation location of QR codes, allowing them to be placed in optimal locations based on user traffic flow. The QR code installation unit can also use NFC tags in addition to QR codes, allowing users to obtain information simply by holding a smartphone over the tag. The recognition unit reads the QR code installed by the QR code installation unit and recognizes images and text. For example, the recognition unit analyzes text and image information embedded in the QR code to identify information important to visually impaired users. The recognition unit can also customize the information recognized by the generation AI based on the user's past behavioral history and preferences to provide more appropriate information. The recognition unit can also update the information recognized by the generation AI in real time to provide the latest information. The feedback unit provides audio feedback of the information recognized by the recognition unit. For example, the feedback unit may provide audio feedback to a visually impaired person in the form of, "The station exit is on the right," or "The next bus will arrive in 10 minutes." The feedback unit may also provide audio feedback in a language that is appropriate for the visually impaired person. The feedback unit may also customize the content of the audio feedback based on the user's past feedback history to provide more appropriate information. This allows the system according to the embodiment to enable visually impaired people to obtain information about public signs and guide boards by audio. For example, visually impaired people may be able to receive smoother guidance at stations, bus stops, public facilities, etc., significantly improving their mobility and lifestyle.

[0030] The QR code installation unit can install QR codes on station information boards, bus stop timetables, and information boards at public facilities. The QR code installation unit installs QR codes on station information boards, for example. For example, the QR code installation unit can also install QR codes on bus stop timetables. The QR code installation unit can also install QR codes on information boards at public facilities. This allows visually impaired people to obtain information at various public facilities.

[0031] The recognition unit can analyze the text information and image information embedded in the QR code to identify information that is important to visually impaired people. For example, the recognition unit can analyze the text information embedded in the QR code to identify information that is important to visually impaired people. For example, the recognition unit can also analyze the image information embedded in the QR code to identify information that is important to visually impaired people. The recognition unit can also use an NFC tag in addition to the QR code, allowing information to be obtained simply by holding a smartphone over the tag. This makes it possible to identify information that is important to visually impaired people.

[0032] The feedback unit can provide voice feedback to visually impaired people in the form of, for example, "The exit for this station is on the right," or "The next bus will arrive in 10 minutes." For example, the feedback unit can provide voice feedback to visually impaired people, such as, "The exit for this station is on the right." For example, the feedback unit can also provide voice feedback such as, "The next bus will arrive in 10 minutes." The feedback unit can also use an emotion estimation function to analyze the emotions felt by the user when scanning the QR code and identify installation locations that are less stressful. This allows visually impaired people to receive specific voice guidance.

[0033] The feedback unit can provide audio feedback in accordance with the language used by the visually impaired person. For example, the feedback unit can support multiple languages, such as Japanese, English, and Chinese. The feedback unit can also incorporate a QR code into the digital signage, allowing the display content to be dynamically changed. This allows the visually impaired person to obtain information in their own language.

[0034] The QR code installation unit introduces a system that can dynamically change the installation location of the QR code, allowing it to be placed in the optimal position according to the user's flow of movement. For example, the QR code installation unit can automatically adjust the position of the QR code to match the user's flow of movement, such as on a train platform or in a bus stop waiting area. This makes it easier for visually impaired people to find the QR code.

[0035] The QR code installation unit can use NFC tags in addition to QR codes, allowing information to be obtained by simply holding a smartphone over the tag. For example, the QR code installation unit can use NFC tags in addition to QR codes to introduce a system that allows information to be obtained by simply holding a smartphone over the tag. For example, the QR code installation unit can install NFC tags on station information boards and bus stop timetables, allowing visually impaired people to easily obtain information. This allows visually impaired people to obtain information more smoothly.

[0036] The QR code installation unit can incorporate QR codes into digital signage, allowing the display content to be changed dynamically. For example, the QR code installation unit will develop a system that can incorporate QR codes into digital signage and dynamically change the display content. For example, the QR code installation unit can install digital signage on station information boards or bus stop timetables, and update the QR code content in real time. This allows visually impaired people to obtain the latest information.

[0037] The QR code installation unit can combine QR codes with AR technology, so that 3D objects are displayed when a smartphone is held over the code. The QR code installation unit will develop a system that combines QR codes with AR technology, so that 3D objects are displayed when a smartphone is held over the code. For example, the QR code installation unit can install a QR code on a station information board, so that the station structure can be displayed in 3D when a smartphone is held over the code. This allows visually impaired people to obtain information through 3D objects.

[0038] The recognition unit can customize the information recognized by the generation AI based on the user's past behavioral history and preferences, providing more appropriate information. For example, the recognition unit will develop a system that customizes the information recognized by the generation AI based on the user's past behavioral history and preferences. For example, the recognition unit can prioritize providing information that is important to the user based on information about stations and bus stops that the user has used in the past. This allows for providing more appropriate information to visually impaired people.

[0039] The recognition unit can update the information recognized by the generation AI in real time and provide the latest information. For example, the recognition unit can develop a system that updates the information recognized by the generation AI in real time and provides the latest information. For example, the recognition unit can update bus operation status and station congestion status in real time and provide this to visually impaired people. This allows visually impaired people to obtain the latest information.

[0040] The recognition unit can provide feedback of the information recognized by the generation AI to not only the visually impaired but also the hearing impaired via text or vibration. For example, the recognition unit can display text on a smartphone screen and notify by vibration. This allows not only the visually impaired but also the hearing impaired to obtain information.

[0041] The recognition unit can display the information recognized by the generation AI on a wearable device such as smart glasses, allowing visually impaired people to access information without using their hands. For example, the recognition unit will develop a system that displays the information recognized by the generation AI on a wearable device such as smart glasses. For example, the recognition unit can notify visually impaired people by voice or vibration so that they can access information without using their hands. This allows visually impaired people to access information without using their hands.

[0042] The feedback unit can customize the content of the voice feedback based on the user's past feedback history and provide more appropriate information. The feedback unit develops a system that customizes the content of the voice feedback based on the user's past feedback history, for example. For example, the feedback unit can prioritize providing information that is important to the user based on information about stations and bus stops that the user has used in the past. This makes it possible to provide more appropriate voice feedback to visually impaired people.

[0043] The feedback unit may add a function that allows the speed and tone of the voice feedback to be adjusted to suit the user's preferences. For example, the feedback unit may develop a system that adds a function that allows the speed and tone of the voice feedback to be adjusted to suit the user's preferences. For example, the feedback unit may allow the user to adjust the voice speed and tone on a settings screen. This allows visually impaired people to receive voice feedback that suits their preferences.

[0044] The feedback unit can provide voice feedback as text or vibration to not only the visually impaired but also the hearing impaired. The feedback unit will develop a system that provides voice feedback as text or vibration to not only the visually impaired but also the hearing impaired. For example, the feedback unit can display text on a smartphone screen and notify by vibration. This allows not only the visually impaired but also the hearing impaired to obtain information.

[0045] The feedback unit can make the voice feedback compatible with devices such as smart speakers and earphones, allowing users to obtain information without using their hands. The feedback unit, for example, develops a system that makes the voice feedback compatible with devices such as smart speakers and earphones. For example, the feedback unit can utilize a voice assistant function to enable visually impaired people to obtain information without using their hands. This allows visually impaired people to obtain information without using their hands.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The QR code installation unit may also provide tactile feedback to make it easier for visually impaired people to find the QR code. For example, the QR code installation unit may install a device that provides tactile feedback around the QR code, allowing visually impaired people to identify the location of the QR code by touching it with their hands. The QR code installation unit may also place a tactile marker at the location where the QR code is installed, allowing visually impaired people to confirm the location of the QR code by touch. Furthermore, the QR code installation unit may install a device that provides vibration feedback at the location where the QR code is installed, allowing visually impaired people to identify the location of the QR code by feeling the vibrations.

[0048] The recognition unit can also analyze the ambient sounds when a visually impaired person reads a QR code and provide appropriate audio feedback. For example, the recognition unit can detect the ambient noise level and automatically adjust the volume of the audio feedback. The recognition unit can also analyze the ambient sounds and provide audio feedback that is easy for visually impaired people to hear. Furthermore, the recognition unit can record the ambient sounds when a visually impaired person reads a QR code and play them back later so that the visually impaired person can confirm the information.

[0049] The feedback unit may also simplify the content of the audio feedback to reduce the physical burden on the visually impaired person when obtaining information. For example, the feedback unit may provide only the minimum amount of information required by the visually impaired person by audio. The feedback unit may also adjust the speed of the audio feedback to reduce the physical burden on the visually impaired person when obtaining information. Furthermore, the feedback unit may provide the content of the audio feedback in stages to reduce the physical burden on the visually impaired person when obtaining information.

[0050] The QR code installation unit can also install safety guides at the location where the QR code is installed to ensure safety for visually impaired people when reading the QR code. For example, the QR code installation unit can install handrails or guidelines at the location where the QR code is installed, allowing visually impaired people to read the QR code safely. The QR code installation unit can also display safety warnings at the location where the QR code is installed, allowing visually impaired people to read the QR code safely. Furthermore, the QR code installation unit can install safety sensors at the location where the QR code is installed, allowing visually impaired people to read the QR code safely.

[0051] The processing flow of the first embodiment will be briefly explained below.

[0052] Step 1: The QR code installation unit installs QR codes on public signs and information boards. For example, QR codes are installed on station information boards, bus stop timetables, and information boards at public facilities. The QR code installation unit can also introduce a system that can dynamically change the location of QR codes, allowing them to be placed in the optimal location according to the user's flow of traffic. Furthermore, the QR code installation unit can also use NFC tags in addition to QR codes, allowing information to be obtained simply by holding a smartphone over them. Step 2: The recognition unit reads the QR code placed by the QR code placement unit and recognizes the images and text. For example, it analyzes the text and image information embedded in the QR code to identify information that is important to visually impaired people. The recognition unit can also customize the information recognized by the generation AI based on the user's past behavioral history and preferences to provide more appropriate information. Furthermore, the recognition unit can update the information recognized by the generation AI in real time to provide the latest information. Step 3: The feedback unit provides the information recognized by the recognition unit as audio feedback. For example, audio feedback such as "The exit for this station is on the right" or "The next bus will arrive in 10 minutes" is given to a visually impaired person. The feedback unit can also provide audio feedback in a language that is appropriate for the visually impaired person. Furthermore, the feedback unit can customize the content of the audio feedback based on the user's past feedback history to provide more appropriate information.

[0053] (Example 2) The system according to the embodiment of the present invention is a system that places QR codes on public signs and information boards for the visually impaired, recognizes images and text by reading the codes, and provides audio feedback. This system can solve the problems of infrastructure limitations such as Braille and the difficulty of supporting multiple languages.

[0054] A system according to an embodiment includes a QR code installation unit, a recognition unit, and a feedback unit. The QR code installation unit installs QR codes on public signs and information boards. For example, the QR code installation unit installs QR codes on station information boards, bus stop timetables, and information boards at public facilities. The QR code installation unit can also incorporate a system that dynamically changes the installation location of QR codes, allowing them to be placed in optimal locations based on user traffic flow. The QR code installation unit can also use NFC tags in addition to QR codes, allowing users to obtain information simply by holding a smartphone over the tag. The recognition unit reads the QR code installed by the QR code installation unit and recognizes images and text. For example, the recognition unit analyzes text and image information embedded in the QR code to identify information important to visually impaired users. The recognition unit can also customize the information recognized by the generation AI based on the user's past behavioral history and preferences to provide more appropriate information. The recognition unit can also update the information recognized by the generation AI in real time to provide the latest information. The feedback unit provides audio feedback of the information recognized by the recognition unit. For example, the feedback unit may provide audio feedback to a visually impaired person in the form of, "The station exit is on the right," or "The next bus will arrive in 10 minutes." The feedback unit may also provide audio feedback in a language that is appropriate for the visually impaired person. The feedback unit may also customize the content of the audio feedback based on the user's past feedback history to provide more appropriate information. This allows the system according to the embodiment to enable visually impaired people to obtain information about public signs and guide boards by audio. For example, visually impaired people may be able to receive smoother guidance at stations, bus stops, public facilities, etc., significantly improving their mobility and lifestyle.

[0055] The QR code installation unit can install QR codes on station information boards, bus stop timetables, and information boards at public facilities. The QR code installation unit installs QR codes on station information boards, for example. For example, the QR code installation unit can also install QR codes on bus stop timetables. The QR code installation unit can also install QR codes on information boards at public facilities. This allows visually impaired people to obtain information at various public facilities.

[0056] The recognition unit can analyze the text information and image information embedded in the QR code to identify information that is important to visually impaired people. For example, the recognition unit can analyze the text information embedded in the QR code to identify information that is important to visually impaired people. For example, the recognition unit can also analyze the image information embedded in the QR code to identify information that is important to visually impaired people. The recognition unit can also use an NFC tag in addition to the QR code, allowing information to be obtained simply by holding a smartphone over the tag. This makes it possible to identify information that is important to visually impaired people.

[0057] The feedback unit can provide voice feedback to visually impaired people in the form of, for example, "The exit for this station is on the right," or "The next bus will arrive in 10 minutes." For example, the feedback unit can provide voice feedback to visually impaired people, such as, "The exit for this station is on the right." For example, the feedback unit can also provide voice feedback such as, "The next bus will arrive in 10 minutes." The feedback unit can also use an emotion estimation function to analyze the emotions felt by the user when scanning the QR code and identify installation locations that are less stressful. This allows visually impaired people to receive specific voice guidance.

[0058] The feedback unit can provide audio feedback in accordance with the language used by the visually impaired person. For example, the feedback unit can support multiple languages, such as Japanese, English, and Chinese. The feedback unit can also incorporate a QR code into the digital signage, allowing the display content to be dynamically changed. This allows the visually impaired person to obtain information in their own language.

[0059] The QR code installation unit introduces a system that can dynamically change the installation location of the QR code, allowing it to be placed in the optimal position according to the user's flow of movement. For example, the QR code installation unit can automatically adjust the position of the QR code to match the user's flow of movement, such as on a train platform or in a bus stop waiting area. This makes it easier for visually impaired people to find the QR code.

[0060] The QR code installation unit can use NFC tags in addition to QR codes, allowing information to be obtained by simply holding a smartphone over the tag. For example, the QR code installation unit can use NFC tags in addition to QR codes to introduce a system that allows information to be obtained by simply holding a smartphone over the tag. For example, the QR code installation unit can install NFC tags on station information boards and bus stop timetables, allowing visually impaired people to easily obtain information. This allows visually impaired people to obtain information more smoothly.

[0061] The QR code installation unit uses the emotion estimation function to analyze the emotion a user feels when scanning a QR code and can identify a location where the QR code will be installed that is less stressful. For example, the QR code installation unit develops a system that uses the emotion estimation function to analyze the emotion a user feels when scanning a QR code in real time. For example, the QR code installation unit can use a camera or sensor to analyze the user's facial expressions and movements and identify a location where the QR code will be installed that is less stressful. This allows visually impaired people to scan QR codes in a location where they will be less stressed.

[0062] The QR code installation unit can incorporate QR codes into digital signage, allowing the display content to be changed dynamically. For example, the QR code installation unit will develop a system that can incorporate QR codes into digital signage and dynamically change the display content. For example, the QR code installation unit can install digital signage on station information boards or bus stop timetables, and update the QR code content in real time. This allows visually impaired people to obtain the latest information.

[0063] The QR code installation unit can combine QR codes with AR technology, so that 3D objects are displayed when a smartphone is held over the code. The QR code installation unit will develop a system that combines QR codes with AR technology, so that 3D objects are displayed when a smartphone is held over the code. For example, the QR code installation unit can install a QR code on a station information board, so that the station structure can be displayed in 3D when a smartphone is held over the code. This allows visually impaired people to obtain information through 3D objects.

[0064] The QR code installation unit can use the emotion estimation function to monitor the emotions of users when they scan a QR code in real time and suggest installation methods that elicit positive emotions.The QR code installation unit can, for example, use the emotion estimation function to develop a system that monitors the emotions of users when they scan a QR code in real time.For example, the QR code installation unit can analyze the user's facial expressions and movements using a camera or sensor and suggest installation methods that elicit positive emotions.This allows visually impaired people to use QR codes while feeling positive emotions.

[0065] The recognition unit can customize the information recognized by the generation AI based on the user's past behavioral history and preferences, providing more appropriate information. For example, the recognition unit will develop a system that customizes the information recognized by the generation AI based on the user's past behavioral history and preferences. For example, the recognition unit can prioritize providing information that is important to the user based on information about stations and bus stops that the user has used in the past. This allows for providing more appropriate information to visually impaired people.

[0066] The recognition unit can update the information recognized by the generation AI in real time and provide the latest information. For example, the recognition unit can develop a system that updates the information recognized by the generation AI in real time and provides the latest information. For example, the recognition unit can update bus operation status and station congestion status in real time and provide this to visually impaired people. This allows visually impaired people to obtain the latest information.

[0067] The recognition unit can use the emotion estimation function to analyze what emotions a user has in response to the recognized information and provide additional information to alleviate negative emotions. For example, the recognition unit can use the emotion estimation function to develop a system that analyzes in real time what emotions a user has in response to the recognized information. For example, the recognition unit can analyze the user's facial expressions and voice to detect negative emotions. This allows visually impaired people to alleviate negative emotions.

[0068] The recognition unit can provide feedback of the information recognized by the generation AI to not only the visually impaired but also the hearing impaired via text or vibration. For example, the recognition unit can display text on a smartphone screen and notify by vibration. This allows not only the visually impaired but also the hearing impaired to obtain information.

[0069] The recognition unit can display the information recognized by the generation AI on a wearable device such as smart glasses, allowing visually impaired people to access information without using their hands. For example, the recognition unit will develop a system that displays the information recognized by the generation AI on a wearable device such as smart glasses. For example, the recognition unit can notify visually impaired people by voice or vibration so that they can access information without using their hands. This allows visually impaired people to access information without using their hands.

[0070] The recognition unit can use the emotion estimation function to provide real-time feedback on the user's emotions regarding the information recognized by the recognition unit, and provide information that elicits positive emotions. For example, the recognition unit can use the emotion estimation function to develop a system that provides real-time feedback on the user's emotions regarding the information recognized by the recognition unit. For example, the recognition unit can analyze the user's facial expressions and voice and provide information that elicits positive emotions. This allows visually impaired people to obtain information while having positive emotions.

[0071] The feedback unit can customize the content of the voice feedback based on the user's past feedback history and provide more appropriate information. The feedback unit develops a system that customizes the content of the voice feedback based on the user's past feedback history, for example. For example, the feedback unit can prioritize providing information that is important to the user based on information about stations and bus stops that the user has used in the past. This makes it possible to provide more appropriate voice feedback to visually impaired people.

[0072] The feedback unit may add a function that allows the speed and tone of the voice feedback to be adjusted to suit the user's preferences. For example, the feedback unit may develop a system that adds a function that allows the speed and tone of the voice feedback to be adjusted to suit the user's preferences. For example, the feedback unit may allow the user to adjust the voice speed and tone on a settings screen. This allows visually impaired people to receive voice feedback that suits their preferences.

[0073] The feedback unit can use the emotion estimation function to analyze the emotions of a user when receiving voice feedback and provide voice feedback that elicits positive emotions. The feedback unit, for example, uses the emotion estimation function to develop a system that analyzes the emotions of a user when receiving voice feedback in real time. For example, the feedback unit can analyze the user's facial expressions and voice and provide voice feedback that elicits positive emotions. This allows visually impaired people to receive voice feedback with positive emotions.

[0074] The feedback unit can provide voice feedback as text or vibration to not only the visually impaired but also the hearing impaired. The feedback unit will develop a system that provides voice feedback as text or vibration to not only the visually impaired but also the hearing impaired. For example, the feedback unit can display text on a smartphone screen and notify by vibration. This allows not only the visually impaired but also the hearing impaired to obtain information.

[0075] The feedback unit can make the voice feedback compatible with devices such as smart speakers and earphones, allowing users to obtain information without using their hands. The feedback unit, for example, develops a system that makes the voice feedback compatible with devices such as smart speakers and earphones. For example, the feedback unit can utilize a voice assistant function to enable visually impaired people to obtain information without using their hands. This allows visually impaired people to obtain information without using their hands.

[0076] The feedback unit can use the emotion estimation function to monitor the emotions of a user when receiving voice feedback in real time and provide voice feedback that elicits positive emotions. The feedback unit, for example, uses the emotion estimation function to develop a system that monitors the emotions of a user when receiving voice feedback in real time. For example, the feedback unit can analyze the user's facial expressions and voice and provide voice feedback that elicits positive emotions. This allows visually impaired people to receive voice feedback while feeling positive emotions.

[0077] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0078] The QR code installation unit may also provide tactile feedback to make it easier for visually impaired people to find the QR code. For example, the QR code installation unit may install a device that provides tactile feedback around the QR code, allowing visually impaired people to identify the location of the QR code by touching it with their hands. The QR code installation unit may also place a tactile marker at the location where the QR code is installed, allowing visually impaired people to confirm the location of the QR code by touch. Furthermore, the QR code installation unit may install a device that provides vibration feedback at the location where the QR code is installed, allowing visually impaired people to identify the location of the QR code by feeling the vibrations.

[0079] The recognition unit can also analyze the ambient sounds when a visually impaired person reads a QR code and provide appropriate audio feedback. For example, the recognition unit can detect the ambient noise level and automatically adjust the volume of the audio feedback. The recognition unit can also analyze the ambient sounds and provide audio feedback that is easy for visually impaired people to hear. Furthermore, the recognition unit can record the ambient sounds when a visually impaired person reads a QR code and play them back later so that the visually impaired person can confirm the information.

[0080] The feedback unit may also simplify the content of the audio feedback to reduce the physical burden on the visually impaired person when obtaining information. For example, the feedback unit may provide only the minimum amount of information required by the visually impaired person by audio. The feedback unit may also adjust the speed of the audio feedback to reduce the physical burden on the visually impaired person when obtaining information. Furthermore, the feedback unit may provide the content of the audio feedback in stages to reduce the physical burden on the visually impaired person when obtaining information.

[0081] The QR code installation unit can also install safety guides at the location where the QR code is installed to ensure safety for visually impaired people when reading the QR code. For example, the QR code installation unit can install handrails or guidelines at the location where the QR code is installed, allowing visually impaired people to read the QR code safely. The QR code installation unit can also display safety warnings at the location where the QR code is installed, allowing visually impaired people to read the QR code safely. Furthermore, the QR code installation unit can install safety sensors at the location where the QR code is installed, allowing visually impaired people to read the QR code safely.

[0082] The recognition unit can also estimate the emotions of visually impaired people when they read a QR code and provide information to reduce stress. For example, the recognition unit can analyze the facial expressions and voice of visually impaired people when they read a QR code and provide information to help them relax if they are feeling stressed. The recognition unit can also estimate the emotions of visually impaired people when they read a QR code and provide information to elicit positive emotions. The recognition unit can also estimate the emotions of visually impaired people when they read a QR code and provide information to reduce negative emotions.

[0083] The feedback unit can also estimate the emotions of the visually impaired person when acquiring information and provide audio feedback to elicit positive emotions. For example, the feedback unit can analyze the facial expressions and voice of the visually impaired person when acquiring information and provide audio feedback to elicit positive emotions. The feedback unit can also estimate the emotions of the visually impaired person when acquiring information and provide audio feedback to reduce negative emotions. Furthermore, the feedback unit can estimate the emotions of the visually impaired person when acquiring information and provide audio feedback to reduce stress.

[0084] The QR code installation unit can also estimate the emotions of visually impaired people when they read a QR code and suggest installation locations that will elicit positive emotions. For example, the QR code installation unit can analyze the facial expressions and voice of visually impaired people when they read a QR code and suggest installation locations that will elicit positive emotions. The QR code installation unit can also estimate the emotions of visually impaired people when they read a QR code and suggest installation locations that will reduce negative emotions. Furthermore, the QR code installation unit can estimate the emotions of visually impaired people when they read a QR code and suggest installation locations that will reduce stress.

[0085] The recognition unit can also estimate the emotions of visually impaired people when they read a QR code and provide information to elicit positive emotions. For example, the recognition unit can analyze the facial expressions and voices of visually impaired people when they read a QR code and provide information to elicit positive emotions. The recognition unit can also estimate the emotions of visually impaired people when they read a QR code and provide information to reduce negative emotions. Furthermore, the recognition unit can estimate the emotions of visually impaired people when they read a QR code and provide information to reduce stress.

[0086] The feedback unit can also estimate the emotions of the visually impaired person when acquiring information and provide audio feedback to elicit positive emotions. For example, the feedback unit can analyze the facial expressions and voice of the visually impaired person when acquiring information and provide audio feedback to elicit positive emotions. The feedback unit can also estimate the emotions of the visually impaired person when acquiring information and provide audio feedback to reduce negative emotions. Furthermore, the feedback unit can estimate the emotions of the visually impaired person when acquiring information and provide audio feedback to reduce stress.

[0087] The QR code installation unit can also estimate the emotions of visually impaired people when they read a QR code and suggest installation locations that will elicit positive emotions. For example, the QR code installation unit can analyze the facial expressions and voice of visually impaired people when they read a QR code and suggest installation locations that will elicit positive emotions. The QR code installation unit can also estimate the emotions of visually impaired people when they read a QR code and suggest installation locations that will reduce negative emotions. Furthermore, the QR code installation unit can estimate the emotions of visually impaired people when they read a QR code and suggest installation locations that will reduce stress.

[0088] The processing flow of the second embodiment will be briefly explained below.

[0089] Step 1: The QR code installation unit installs QR codes on public signs and information boards. For example, QR codes are installed on station information boards, bus stop timetables, and information boards at public facilities. The QR code installation unit can also introduce a system that can dynamically change the location of QR codes, allowing them to be placed in the optimal location according to the user's flow of traffic. Furthermore, the QR code installation unit can also use NFC tags in addition to QR codes, allowing information to be obtained simply by holding a smartphone over them. Step 2: The recognition unit reads the QR code placed by the QR code placement unit and recognizes the images and text. For example, it analyzes the text and image information embedded in the QR code to identify information that is important to visually impaired people. The recognition unit can also customize the information recognized by the generation AI based on the user's past behavioral history and preferences to provide more appropriate information. Furthermore, the recognition unit can update the information recognized by the generation AI in real time to provide the latest information. Step 3: The feedback unit provides the information recognized by the recognition unit as audio feedback. For example, audio feedback such as "The exit for this station is on the right" or "The next bus will arrive in 10 minutes" is given to a visually impaired person. The feedback unit can also provide audio feedback in a language that is appropriate for the visually impaired person. Furthermore, the feedback unit can customize the content of the audio feedback based on the user's past feedback history to provide more appropriate information.

[0090] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0091] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0092] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, 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.

[0093] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0094] 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.

[0095] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0096] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, 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. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0097] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0098] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0099] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0100] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0101] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0102] The storage 32 stores a data generation model 58 and an 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 emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0103] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0104] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0105] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0106] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0108] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0109] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0110] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0111] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. 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. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0112] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0113] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0114] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0115] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0116] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0117] The storage 32 stores a data generation model 58 and an 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 emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0118] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0119] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0120] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0121] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0123] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0124] 7, a 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.

[0125] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0126] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. 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. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0127] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0128] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0129] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0130] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0131] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0132] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0133] The storage 32 stores a data generation model 58 and an 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 emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0134] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0135] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0136] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0137] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0138] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0139] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0140] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0141] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0142] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0143] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0144] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0145] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0146] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0147] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0148] 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.

[0149] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0150] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0151] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0152] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0153] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0154] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0155] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0156] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0157] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. QR code installation department that installs QR codes on public signs and information boards; a recognition unit that reads the QR code placed by the QR code placement unit and recognizes images and characters; a feedback unit that provides audio feedback of the information recognized by the recognition unit. A system characterized by:

2. The QR code setting unit QR codes will be placed on station information boards, bus stop timetables, and information boards at public facilities.

2. The system of claim 1.

3. The recognition unit Analyze the text and image information embedded in the QR code to identify information that is important to visually impaired people.

2. The system of claim 1.

4. The feedback unit Providing audio feedback tailored to the language used by the visually impaired 2. The system of claim 1.

5. The recognition unit The information recognized by the generative AI is customized based on the user's past behavioral history and preferences to provide more appropriate information.

2. The system of claim 1.

6. The feedback unit Customize voice feedback based on the user's past feedback history to provide more relevant information 2. The system of claim 1.

7. The QR code setting unit Analyze the emotions felt by users when scanning the QR code and identify installation locations that are less likely to cause stress.

2. The system of claim 1.

8. The recognition unit Analyze how users feel about the information they perceive and provide additional information to alleviate negative emotions.

2. The system of claim 1.

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