System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving input information generated from input means of a user; means for receiving video data of a game; means for analyzing the received input information and video data and specifying a progress status of the game and an action of the user; means for generating a play-by-play phrase based on the specified status of the game and action of the user; means for converting the generated play-by-play phrase into audio data; and means for distributing play-by-play data including the audio data to the user.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] In modern gaming, solo play is common, but the excitement and thrill that can be gained from this is limited. It is particularly difficult to recreate the tension and excitement of a tournament with commentators and an audience in a solo play environment. Furthermore, even participating in a tournament presents a psychological hurdle, making it intimidating for many users. Given these circumstances, there is a demand for new gaming experiences that can provide excitement and thrills even when playing alone. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means: A system including means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data and identifying the game progress status and the user's actions, means for generating commentary phrases based on the identified game status and user actions, means for converting the generated commentary phrases into audio data, and means for delivering the commentary data including the audio data to the user, allows a user to have an exciting and fulfilling gaming experience in real time, even when playing a game alone.

[0006] "User input means" refers to devices used by the user to operate the game, including keyboards, mice, controllers, etc.

[0007] "Game video data" refers to the graphics information of the game a user is playing, including the visual content displayed on the screen.

[0008] "Input information" refers to operations or commands that a user performs via an input means, such as pressing a button or moving a joystick.

[0009] "Means for receiving" refers to the equipment or software process for obtaining particular data or signals.

[0010] "Means for analyzing" means a method or device that processes received data to extract or understand specific information.

[0011] "Game progress" refers to the progress and current state within the game, including clearing a level, entering a boss battle, and character actions.

[0012] "User action" refers to an operation or movement performed by the user, such as attacking, jumping, or using an item.

[0013] "Commentary phrases" refer to comments and cheering phrases that are generated according to the game's progress and the user's actions.

[0014] "Audio data" refers to acoustic signals or audio files, and is used to output analysis results and commentary phrases as sound.

[0015] "Distribution means" refers to the process or tool used to transmit the generated data to the user's terminal.

[0016] A "display device" is a device used by a user to visually confirm information, and includes a monitor or screen.

[0017] "Real-time" refers to instant processing and communication with minimal delay, meaning immediate response to user operations and game progress. [Brief explanation of the drawings]

[0018] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

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

[0021] 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, a 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), and an APU (Accelerated Processing Unit).

[0022] 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.

[0023] 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.

[0024] 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), Bluetooth (registered trademark), etc.

[0025] 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."

[0026] [First embodiment]

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

[0028] 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.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. 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).

[0030] 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.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0033] 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.

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

[0035] 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.

[0036] 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.

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

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

[0039] The present invention is a system that provides real-time commentary based on user input and game video data while a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay.

[0040] System Overview

[0041] This system receives input information generated by the user's input means, acquires game video data, analyzes this data to generate commentary phrases, converts the generated commentary phrases into audio data, and executes a series of processes to distribute the audio data to the user's device.

[0042] Program processing

[0043] 1. Acquiring game data

[0044] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[0045] 2. Receiving Data

[0046] The device transmits the captured game video data and input information to the server in real time. This data is collected at regular intervals (e.g., several times per second) and sent to the server as packets.

[0047] 3. Data Analysis

[0048] The server analyzes the game footage and input information received from the device. Specifically, the server uses machine learning models to identify the game's progress and user actions, such as when a boss battle begins or when the user uses a special ability.

[0049] 4. Commentary Phrase Generation

[0050] The server generates commentary phrases based on the analysis results. These phrases will add excitement to the user's gameplay. For example, phrases such as "The user has entered a boss battle!" or "Amazing! The user is using a special ability!" are generated.

[0051] 5. Conversion to audio data

[0052] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[0053] 6. Live data distribution and display

[0054] The server sends the generated commentary phrase text and audio data to the device, which then displays the received data on the screen and plays the audio, allowing the user to enjoy real-time commentary related to the game's progress visually and aurally while playing.

[0055] Specific examples

[0056] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, which continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and detects the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the audio. The user can continue playing the game while experiencing the excitement of the boss battle thanks to this commentary.

[0057] In this way, the present invention provides a new gaming experience that allows users to feel excitement and excitement in real time even when playing a game alone.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] The user starts the game. The user launches the game application on their device to play the game.

[0061] Step 2:

[0062] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[0063] Step 3:

[0064] The game video data and input information captured by the device are sent to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent to the server as packets.

[0065] Step 4:

[0066] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0067] Step 5:

[0068] The server generates commentary phrases based on the analysis results, evaluates the analysis results using a machine learning model, and generates appropriate commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!").

[0069] Step 6:

[0070] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[0071] Step 7:

[0072] The server sends the text and audio data of the generated commentary phrase to the terminal, so that the commentary data arrives in real time at the user's terminal.

[0073] Step 8:

[0074] The terminal displays and plays the commentary data it receives. The text of the commentary phrases is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[0075] Step 9:

[0076] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more.

[0077] Example 1

[0078] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0079] When a user is playing a computer program alone, there is a demand for providing real-time commentary based on the game progress and the user's actions to make the user's playing experience more exciting and lively. However, conventional systems have difficulty analyzing game data and user operation information in real time, generating appropriate commentary phrases, and providing them as audio, which makes it difficult to improve the user experience.

[0080] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0081] In this invention, the server includes means for receiving operation information generated from a user's operation means, means for receiving video data of a computer program, means for analyzing the received operation information and video data and identifying the progress of the computer program and the user's actions, means for generating commentary phrases based on the identified status of the computer program and the user's actions, means for converting the generated commentary phrases into audio data, and means for delivering the commentary data including the audio data to the user. This makes it possible to generate appropriate commentary in real time and provide the commentary to the user as audio and text.

[0082] "User's operation means" is a general term for input devices that a user uses to operate a computer program.

[0083] "Operation information" refers to a series of data input by the user through the operating means, including pressing buttons on the controller and movements of the joystick.

[0084] "Video data of a computer program" refers to image information that is generated when a computer program is executed.

[0085] "Means for receiving" refers to methods and techniques for receiving data from the outside.

[0086] "Means of analysis" refers to the technology used to understand the received data and convert it into meaningful information.

[0087] "Progress" is information that indicates a user's progress within a computer program.

[0088] "User behavior" refers to the specific actions a user takes when operating a computer program.

[0089] A "commentary phrase" is a commentary sentence in the form of a sentence that is generated according to the progress of a computer program and the actions of a user.

[0090] "Generation means" refers to methods and technologies for creating new content from data and information.

[0091] "Audio data" refers to digital data in audio format.

[0092] "Means for converting into audio data" refers to technology for converting text data into audio format.

[0093] "Delivery means" refers to the methods and techniques used to deliver the generated data to users.

[0094] "Character data" means digital information expressed in text format.

[0095] "Display device" refers to a device for visually displaying information.

[0096] "Real-time" means processing or reacting immediately, without delay.

[0097] This invention is a system that provides real-time commentary on the game progress and user actions while a user is playing a computer program alone, with the aim of making the user's playing experience more exciting and lively.

[0098] The system mainly consists of the following components: terminals, servers, and communication means to link them together.

[0099] Device features and operations

[0100] A terminal is a device operated by a user that runs a computer program (e.g., game software). It includes an input device (e.g., a controller or keyboard), a display device (e.g., a monitor or display), and a network communication function. While the user is playing the game, the terminal captures operation information and game video data in real time and transmits them to a server at regular intervals.

[0101] Server Functions and Operations

[0102] The server's primary function is to receive and analyze the operation information and game video data sent from the device. The server uses machine learning models to identify the game's progress and user behavior, and generates commentary phrases based on that information. Machine learning models used for this include TensorFlow and PyTorch. The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google's Text-to-Speech API or Amazon Polly.

[0103] Live data distribution

[0104] The server transmits the generated voice and text data to the terminal, which receives it and displays the commentary phrases on the screen while playing the voice, allowing the user to enjoy the commentary visually and aurally in real time while playing the game.

[0105] Specific examples

[0106] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, and while this is happening, the device continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and identifies the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the voice. This allows the user to continue playing the game while experiencing the excitement of the boss battle in real time.

[0107] Prompt Sentence Examples

[0108] Here are some example prompts to input to the generative AI model:

[0109] The user is in a boss battle in an action game. Generate commentary phrases in real time based on the user's input data and game footage data. Then convert the generated phrases into text and audio data and send them to the device.

[0110] By inputting this prompt into a generative AI model, the model can generate specific commentary phrases to enrich the user's gaming experience, and then help translate them into the appropriate format for delivery.

[0111] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0112] Step 1:

[0113] When a user starts a game, the device captures the game's video data and operation information in real time. As input, it receives operation information from the user's operating means (button presses and joystick movements) and the video data displayed on the game screen. As output, it captures this data and converts it into a format for sending to the next process.

[0114] Specific operation: The terminal acquires user input through sensors and network interfaces, and prepares the captured video data and operation information as data packets.

[0115] Step 2:

[0116] The device sends the captured game video data and operation information to the server at regular intervals (e.g., 5 times per second). As input, the data captured in step 1 is used. As output, these data are sent to the server as data packets.

[0117] Specific operation: The terminal uses a data communication protocol to send captured data packets to the server, thereby transmitting data in real time.

[0118] Step 3:

[0119] The server receives and analyzes the data sent from the device. As input, it uses the game video data and operation information sent from the device. As output, it generates data to identify the game progress and user behavior.

[0120] Specific operation: The server uses a machine learning model (e.g., TensorFlow or PyTorch) to analyze the received game video data and operation information and detect the occurrence of specific events (e.g., the start of a boss battle, the use of a special ability).

[0121] Step 4:

[0122] The server generates commentary phrases based on the analysis results. As input, it uses the game progress and user behavior information generated in step 3. As output, it generates the generated commentary phrases.

[0123] Specific behavior: The server uses natural language generation technology to generate commentary phrases corresponding to specific events (e.g., "The user has entered a boss battle!", "Amazing! The user is using a special ability!").

[0124] Step 5:

[0125] The server converts the generated commentary phrases into audio data. As input, the commentary phrases generated in step 4 are used. As output, audio data is generated.

[0126] Specific operation: The server inputs the commentary phrase into a speech synthesis engine (e.g., Google's Text-to-Speech API or Amazon Polly) and generates voice data in real time.

[0127] Step 6:

[0128] The server sends the generated voice data and text data to the terminal. As input, the voice data generated in step 5 and the text data generated in step 4 are used. As output, these data are sent to the terminal.

[0129] Specific operation: The server uses a data communication protocol to send voice data and text data to the terminal.

[0130] Step 7:

[0131] The terminal plays and displays the received audio and text data. As input, the audio and text data sent from the server are used. As output, a live commentary is provided to the user in real time.

[0132] Specific operation: The device displays text data on the screen and plays audio data from the speaker, allowing users to enjoy the commentary visually and aurally while playing the game.

[0133] (Application example 1)

[0134] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0135] Conventional game systems have the problem of lacking excitement and excitement when users play alone. Real-time commentary is an effective way to make gameplay more engaging, but the systems that enable this are complex and difficult for average users to use. Furthermore, these systems require high computational resources, making them difficult to process on individual devices. Furthermore, the technology for analyzing video and input information and generating appropriate phrases is still immature, which can lead to a decline in the quality of the commentary.

[0136] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0137] In this invention, the server includes: means for receiving input information generated from a user's input means; means for receiving game video data; means for analyzing the received input information and video data to identify the game progress and the user's actions; means for generating commentary phrases based on the identified game progress and the user's actions; means for converting the generated commentary phrases into audio data; means for delivering the commentary data including the audio data to the user; means for analyzing data transmitted to the cloud server using a machine learning model; and means for receiving the generated commentary phrases from the cloud server and displaying them as text and playing them as audio. This allows users to enjoy a real-time commentary based on the progress of the game visually and audibly, improving the playing experience. Furthermore, processing on the cloud server reduces the load on the computing resources of the local terminal.

[0138] A "user input" is a device or interface that a user uses to operate a game.

[0139] "Input information" refers to data generated by the user when playing a game, and specifically includes information such as button presses, joystick movements, and touch operations.

[0140] "Game video data" is digital information corresponding to the screen display of the game the user is playing.

[0141] A "cloud server" is a remote server that processes, stores, and manages various data via the Internet.

[0142] A "machine learning model" is an algorithm or architecture that analyzes and parses large amounts of data to learn specific patterns and trends.

[0143] "Game progress" refers to the current point in time during gameplay, the progress of the scenario, the occurrence of events, etc.

[0144] "User actions" refer to various operations and movements performed by the user while playing the game.

[0145] "Commentary phrases" are commentary and commentary texts that are generated in accordance with the game progress and the user's actions.

[0146] "Voice data" refers to digital data generated by a voice synthesis engine that converts commentary phrases into voice.

[0147] "Commentary data" is digital information that includes text data of commentary phrases and audio data based on these phrases.

[0148] "Text display" refers to the visual presentation of textual information on a digital display.

[0149] "Audio playback" refers to outputting audio data on a digital device so that it can be audibly recognized.

[0150] The present invention is a system for providing real-time commentary while a user is playing a game alone. This system is designed to enhance the user's gameplay experience. Specific implementations of the system use various hardware and software, as described in detail below.

[0151] Main hardware and software used

[0152] 1. User Device

[0153] The user device is typically a smartphone. This device runs game applications and provides input means for users to control the game. It also has the ability to capture game video data and input information and send it to a cloud server.

[0154] 2. Cloud Server

[0155] The cloud server receives game video data and input information in real time and analyzes this data using machine learning models (e.g., TensorFlow or PyTorch). The cloud server identifies the game's progress and user actions and generates appropriate commentary phrases. These phrases are converted into audio data by a speech synthesis engine (e.g., Google Cloud Text-to-Speech).

[0156] 3. Generative AI Models

[0157] The system uses a generative AI model to analyze game footage and input information, which is then used to generate appropriate commentary phrases based on the user's gameplay situation.

[0158] Processing description

[0159] Acquiring and sending game data

[0160] When a user plays a game on a smartphone, the device captures game video data and input information in real time. For example, when a user jumps or attacks while playing an action game, the smartphone sends the operation data and video frames to a cloud server. The data is sent at regular intervals (e.g., several times per second) to maintain real-time performance.

[0161] Data analysis and commentary generation

[0162] On the cloud server, a machine learning model analyzes the received data and identifies the game's progress and the user's actions. For example, when the user enters a specific boss battle or uses a special ability. The server then generates commentary phrases based on the analysis results. The generated phrases add excitement to the gameplay, such as "The user has entered a boss battle!"

[0163] Conversion to audio data and distribution

[0164] The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech. The converted voice and text data are sent to the user's device, which displays them on the screen and plays the audio. In this way, users can enjoy the game commentary visually and aurally in real time.

[0165] Examples of specific examples and prompts

[0166] For example, if a user enters a boss battle in an action game, the following happens:

[0167] 1. The user's smartphone detects the start of a boss battle and sends the data to the cloud server.

[0168] 2. The cloud server analyzes the data and generates a commentary phrase such as, "The user has entered a boss battle!"

[0169] 3. The generated phrase is converted into audio data using Google Cloud Text-to-Speech.

[0170] 4. This voice data and the text of the phrase are sent to the user's smartphone, where the voice is played and the text is displayed.

[0171] An example of a prompt sentence when actually using a speech synthesis engine is as follows.

[0172] Example prompt sentence:

[0173] "Please convert the following text into natural, easy-to-listen speech: 'The user has entered a boss battle!'"

[0174] This system allows users to enjoy a fulfilling gaming experience even when playing alone. In addition, by using a cloud server, the load on the user's device can be reduced, and real-time and high-quality commentary can be maintained.

[0175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0176] Step 1: Capture the data

[0177] When a user plays a game on a smartphone, the device captures game video data and input information in real time. Specifically, it captures each frame of the screen and obtains data on the user's operations (button presses, touch operations, etc.). Input: user operations and game video, Output: captured operation data and video data.

[0178] Step 2: Sending data

[0179] The captured data is sent to the cloud server at regular intervals (e.g., several times per second). The device assembles the captured data into packets and sends them to the cloud server via the Internet. Input: Captured operation data and video data. Output: Packet data sent to the cloud server.

[0180] Step 3: Receiving and analyzing data

[0181] The cloud server analyzes the received data in real time. A machine learning model (e.g., TensorFlow, PyTorch) runs based on the received operation data and video data to identify the game progress and user actions. Input: Sent packet data, Output: Analysis results (game progress, user actions).

[0182] Step 4: Generate commentary phrases

[0183] The server generates commentary phrases based on the analysis results. Appropriate commentary phrases are generated in text format from the analysis results of the machine learning model. For example, if the user enters a specific boss battle, the phrase "The user has entered a boss battle!" is generated. Input: Analysis results, Output: Text data of the generated commentary phrases.

[0184] Step 5: Converting to audio data

[0185] The generated commentary phrase text data is converted into audio data using a speech synthesis engine (e.g., Google Cloud Text-to-Speech). Input: commentary phrase text data, output: audio data (audio file format such as MP3).

[0186] Step 6: Streaming live data

[0187] The cloud server sends the generated voice and text data to the device. The device receives this and displays the text on the user's screen and plays the voice, allowing the user to enjoy the commentary in real time. Input: Generated voice and text data, Output: Commentary data sent to the device.

[0188] Step 7: Display text and play audio

[0189] The device displays the received commentary phrase text data and plays the audio data. This allows the user to enjoy the commentary visually and aurally. Specifically, the commentary phrase is displayed on the user's game screen and the audio is played at the same time. Input: Commentary data sent to the device, Output: Text displayed on the screen, audio played.

[0190] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0191] The present invention is a system that provides real-time commentary based on user input and game video data when a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay. Furthermore, by incorporating an emotion engine, the present invention generates and adjusts commentary phrases to match the user's emotional state, providing a more personalized gaming experience.

[0192] System Overview

[0193] This system receives input information generated by the user's input means, acquires game video data, analyzes this data, and generates commentary phrases. It then executes a series of processes: converting the generated commentary phrases into audio data and distributing it to the user's device. It then uses an emotion engine to analyze the user's emotional state and adjust the commentary phrases.

[0194] Program processing

[0195] 1. Acquiring game data

[0196] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[0197] 2. Receiving Data

[0198] The device transmits the captured game video data and input information to the server in real time. This data is transmitted at regular intervals (for example, several times per second) and sent to the server as packets.

[0199] 3. Data Analysis

[0200] The server analyzes the game footage and input information received from the device. It uses machine learning models to analyze each frame of the game footage and identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0201] 4. Recognizing emotional states

[0202] The server uses an emotion engine to analyze the user's emotional state by capturing and analyzing the user's facial and voice data to identify the user's current emotional state (e.g., excitement, tension, joy).

[0203] 5. Commentary Phrase Generation

[0204] The server generates commentary phrases based on the game progress and the user's emotional state. Using the analysis results, it selects and adjusts commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!") that matches the user's emotions.

[0205] 6. Conversion to audio data

[0206] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[0207] 7. Live data distribution and display

[0208] The server transmits the text and audio data of the generated commentary phrases to the terminal, which then displays the received commentary data on the screen and plays the audio, allowing the user to enjoy the commentary visually and aurally while playing.

[0209] Specific examples

[0210] For example, consider the case where a user enters a boss battle in a particular action game. While the user is playing the game on their device, the device captures game footage and controller input data and sends it to the server. The server analyzes this data to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio. During gameplay, the user not only receives commentary, but also experiences commentary that is in tune with their emotions.

[0211] In this way, the present invention provides a new gaming experience that allows users to feel the excitement and excitement in real time even when playing alone. Furthermore, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, achieving an even deeper gaming experience.

[0212] The processing flow will be explained below.

[0213] Step 1:

[0214] The user starts the game. The user launches the game application on their device and begins playing.

[0215] Step 2:

[0216] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[0217] Step 3:

[0218] The device captures game video data and input information and sends it to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent as packets to the server.

[0219] Step 4:

[0220] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0221] Step 5:

[0222] The server uses an emotion engine to recognize the user's emotions based on the analysis results. It acquires facial expression and voice data from the user's device and analyzes them to identify the user's current emotional state (e.g., excitement, tension, joy).

[0223] Step 6:

[0224] The server generates commentary phrases based on the game progress and the user's emotional state. For example, if a boss battle is reached, the server generates a phrase such as "The user has reached the boss battle!", and if the user is excited, the server adds an add-on commentary phrase such as "This is an exciting moment!".

[0225] Step 7:

[0226] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[0227] Step 8:

[0228] The server transmits the text and audio data of the generated commentary phrases to the terminal, thereby distributing commentary data to the user's terminal in real time.

[0229] Step 9:

[0230] The terminal displays and plays the commentary data it receives. The commentary phrase text is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[0231] Step 10:

[0232] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more, and they can experience a commentary that is personalized to their own emotions.

[0233] Example 2

[0234] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0235] Conventional game systems have the problem that users have difficulty feeling the excitement and excitement of playing alone. Even if systems exist that provide real-time commentary, the commentary is not tailored to the user's emotional state. Therefore, a system that provides more personalized commentary that is in tune with the user's emotions during gameplay is needed.

[0236] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0237] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress and the user's actions, means for analyzing the user's facial expression data and voice data to identify the user's emotional state, means for generating commentary phrases based on the identified game situation and the user's emotional state, means for converting the generated commentary phrases into voice data, and means for delivering the commentary data including the voice data to the user. This allows a commentary that is in line with the user's emotional state in real time to be provided, allowing for greater excitement and thrills while playing.

[0238] "User input means" refers to the device or interface that the user uses to operate the game, and specifically refers to input devices such as a controller, keyboard, or mouse.

[0239] "Input information" refers to data relating to operations and instructions given to the game by the user via input means.

[0240] "Game visual data" refers to all visual information and screen frames displayed in the game a user is playing.

[0241] "Receive" refers to the act of obtaining data or information from another device.

[0242] "Analyzing" refers to the act of breaking down data, understanding its content and structure, and extracting specific information.

[0243] "Game progress" refers to the status of events and stages taking place within the game, as well as the degree of progress.

[0244] "User actions" refers to all operations and actions performed by a user within the game.

[0245] "Facial expression data" refers to image or video data relating to a user's facial expressions.

[0246] "Voice data" refers to data that includes voice information related to a user's speech.

[0247] "Emotional state" refers to the user's psychological state, such as excitement, tension, joy, etc.

[0248] "Commentary phrases" refer to sentences that explain and comment on the game situation and user actions.

[0249] "Converting to audio data" refers to the process of converting commentary phrases in text format into audio format.

[0250] "Distributing" refers to the act of transmitting the generated data to a user's device.

[0251] The term "system" refers to an overall device or program that is made up of the above means.

[0252] This invention relates to a system that provides real-time commentary when a user is playing a game alone. This system generates commentary that takes into account the emotional state of the user based on input information generated by the user's input means and video data of the game, and makes it possible to distribute this commentary in real time.

[0253] Overall structure

[0254] The system mainly consists of the following components:

[0255] 1. Terminal

[0256] 2. Server

[0257] 3. Users

[0258] The terminal is a device on which the user plays the game, captures the game video data and the user's input information, and transmits the captured data to the server.

[0259] The server analyzes the data received from the device, identifies the game progress and the user's emotional state, generates commentary phrases based on the analysis results, converts them into voice data, and distributes them to the device.

[0260] Hardware and software used

[0261] Terminal: Use a personal computer or game console capable of high-performance data processing. Open Broadcaster Software (OBS) is used as capture software. DirectInput or XInput API is used to obtain user input information.

[0262] Server: A cloud server or dedicated server capable of high-speed data analysis is used. TensorFlow or PyTorch is used to run the machine learning model. For emotion recognition, facial recognition software combining OpenCV and Dlib is used. For voice synthesis, Google Text-to-Speech API or Amazon Polly is used.

[0263] Data processing and calculation

[0264] Receive input information generated from a user's input method:

[0265] The device records user operations in real time during gameplay. For example, when a user presses a button on a controller, that information is acquired.

[0266] Receive game video data:

[0267] The device captures each frame of the game screen in real time and transmits it to the server.

[0268] Data analysis:

[0269] The server analyzes the received game footage and input information to determine the game's progress. For example, the server uses a machine learning model to identify scenes in which boss characters appear. It also determines whether the user is excited or not from facial expression and voice data.

[0270] Commentary generation:

[0271] The server generates commentary phrases based on the analysis results. It generates phrases using specific prompts from a generative AI model (e.g., GPT-3).

[0272] Conversion to audio data:

[0273] The generated commentary phrases are converted into voice data by a voice synthesis engine.

[0274] Live data distribution:

[0275] The server sends the generated voice and text data to the terminal, which displays the received data on the screen and plays the voice.

[0276] Specific examples

[0277] For example, consider the case where a user enters a boss battle in a particular action game. The user plays the game on the device, which captures game footage and controller input data and sends it to the server. The server analyzes this to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio at the same time. The user can experience this commentary in real time while playing the game.

[0278] Prompt Sentence Examples

[0279] Here are some example prompts for a generative AI model:

[0280] The user is in a boss battle in an action game. Generate a commentary phrase to describe this scene, keeping in mind that the user is very excited.

[0281] This system provides a new gaming experience that allows users to feel the excitement and excitement even when playing alone. In addition, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, creating a deeper gaming experience.

[0282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0283] Step 1:

[0284] The device captures game footage and controller input data in real time while the user is playing the game. Input includes game footage (each frame) and the user's controller input information (button presses and joystick movements). This data is acquired using Open Broadcaster Software (OBS) and the DirectInput or XInput API. Output includes the captured video data and controller input data stored in memory. For example, a video frame of the moment the user sees a "giant boss character appear" and input data that "the user presses the attack button" are captured.

[0285] Step 2:

[0286] The device sends captured game video data and input information to the server at regular intervals. Inputs include captured video data and controller input data. These data are sent in JSON format using WebSocket. Outputs include packets that are sent to the server periodically (several times per second). Specifically, the "current frame image" and "information about the button pressed by the user" are sent five times per second.

[0287] Step 3:

[0288] The server analyzes the game footage and input information received from the device. Inputs include video data and input information sent from the device. These data are analyzed using a machine learning model (e.g., TensorFlow or PyTorch) to identify the game's progress and the user's actions. Outputs include the game's progress (e.g., the start of a boss battle) and the user's actions (e.g., repeatedly pressing the attack button). Specifically, the machine learning model recognizes that "the user has entered a boss battle" and obtains the result that "the user is repeatedly pressing a specific button (attacking)."

[0289] Step 4:

[0290] The server analyzes the user's facial expression data and voice data to identify the user's emotional state. The inputs include the user's facial expression data (images captured from the webcam) and voice data (voice from the microphone). These data are analyzed using OpenCV and Dlib to identify the user's emotional state (e.g., excitement, tension, joy). The output is the identified user's emotional state. For example, the webcam captures the user's face, and the emotion recognition model determines that the user is excited. The tone of the user's voice can also be analyzed to indicate that the user is excited.

[0291] Step 5:

[0292] The server generates commentary phrases based on the game progress and the user's emotional state. The inputs include the identified game progress and the user's emotional state. These data are used to generate phrases using prompts from a generative AI model (e.g., GPT-3). The output is the generated commentary phrase. For example, the prompt "The user has entered a boss battle. Please generate a commentary phrase for this scene. Please also keep in mind that the user is very excited" is provided to the generative AI model, which generates the commentary phrase "The user has entered a boss battle! This is an exciting moment!"

[0293] Step 6:

[0294] The server converts the generated commentary phrases into voice data. The input is the generated commentary phrases. These data are converted into speech using a speech synthesis engine (e.g., Google Text-to-Speech API or Amazon Polly). The output is the voice data. Specifically, the commentary phrase "The user has entered a boss battle! This is an exciting moment!" is converted into voice data.

[0295] Step 7:

[0296] The server distributes the generated voice data and text data to the terminal. The input includes voice data and text data. These data are sent to the terminal via the network. The output includes commentary data sent to the terminal. Specifically, the text data and voice data saying "The user has entered a boss battle!" are sent to the terminal.

[0297] Step 8:

[0298] The device displays the commentary data received from the server on the screen and plays the audio. Inputs include text data and audio data sent from the server. These data are played on the device's display and speaker. Output allows the user to experience the commentary visually and audibly. Specifically, the device displays the text "The user has entered a boss battle!" on the screen and plays the audio at the same time. The user can enjoy the commentary in real time.

[0299] (Application example 2)

[0300] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0301] Conventional real-time commentary systems for gameplay provide fixed commentary phrases without considering the user's emotional state, making it difficult for users to achieve a personalized experience. It is also difficult to provide real-time commentary that responds to the game's progress and user actions. There is a need to solve these issues and provide a more engaging and personalized gaming experience.

[0302] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0303] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress status and the user's actions, means for generating commentary phrases based on the identified game status and user actions, means for converting the generated commentary phrases into voice data, means for delivering commentary data including the voice data to the user, means for recognizing the user's emotional state using the user's voice data and camera video, and means for adjusting the commentary phrases based on the recognized emotional state. This allows for personalized commentary to be provided in real time according to the user's emotional state, enabling a more engaging gameplay experience.

[0304] "User input means" refers to the devices or interfaces that a user uses to operate the game.

[0305] "Input information" is a series of data generated from the user's input means, and includes button press status, stick movement, and the like.

[0306] "Game video data" is a series of image data captured from the screen display content of the game being played by the user.

[0307] "Game progress" refers to events or states currently occurring within the game, including player progress and enemy appearances.

[0308] "User action" refers to a specific operation or movement that a user performs in the game, including attacking, moving, etc.

[0309] "Live commentary phrases" are comments and explanatory sentences that are generated based on the game progress and the user's actions.

[0310] "Voice data" refers to a series of data obtained by converting commentary phrases into voice format using voice synthesis.

[0311] "Reportage data" refers to information including text data and audio data of commentary phrases, and is provided to the user.

[0312] An "emotional state" is a user's psychological or emotional response or state, including excitement, tension, joy, and the like.

[0313] An "emotion engine" is software or algorithms that recognize a user's emotional state from voice data and camera footage.

[0314] "Analysis" is the process of processing and analyzing sets of data to extract specific information or patterns.

[0315] "Distribution" refers to the act of transferring live data, including audio data, from a server to a user's device.

[0316] MODE FOR CARRYING OUT THE INVENTION

[0317] This invention is a system that provides real-time commentary to users playing games alone to enhance their gaming experience. The system acquires and analyzes input information generated by the user's input means and game video data to generate commentary phrases that correspond to the user's actions and the game's progress. It also uses an emotion engine to recognize the user's emotional state and adjusts the commentary phrases based on that state, providing a personalized commentary experience.

[0318] Overview of program processing

[0319] 1. Acquiring and sending game data

[0320] A capture card is used to capture game footage and controller input data from the device on which the user is playing the game (e.g., game console or PC). For this purpose, a capture card such as the "Elgato HD60 S+" is used. Game footage is captured at a constant frame rate (e.g., 30 fps or more), and input data (button presses and stick movements) is captured in milliseconds. The captured data is sent to a server in real time.

[0321] 2. Data Analysis

[0322] The server analyzes the received video and input data to identify the game progress and user actions. For example, it uses the machine learning model "YOLOv4" and the image analysis library "OpenCV" to identify specific actions and events within the video data.

[0323] 3. Recognizing emotional states

[0324] The server uses the IBM Watson Tone Analyzer emotion engine to recognize the user's emotional state using the user's voice data and camera footage, making it possible to determine whether the user is excited, relaxed, or nervous.

[0325] 4. Creating and adjusting commentary phrases

[0326] The server generates commentary phrases based on the identified game progress and the user's emotional state, adjusting the phrases as needed. For example, if the user enters a boss battle, the server generates the phrase "The user has entered a boss battle!", and if the user is in an excited state, it adds a phrase such as "This is an exciting moment!".

[0327] 5. Conversion to audio data

[0328] The generated commentary phrases are converted into audio data in real time using the voice synthesis tool "Google Text-to-Speech API."

[0329] 6. Live data distribution and display

[0330] The server delivers the generated audio data and text data to the user's device, plays the audio data, and displays the text data, thereby providing the user with a commentary.

[0331] Specific examples

[0332] For example, consider a situation where a user is playing an action game and enters a boss battle. At this moment, the user's device sends game footage and input data to the server. The server uses the machine learning model YOLOv4 and the image analysis library OpenCV to analyze the boss battle. Furthermore, the IBM Watson Tone Analyzer detects excitement in the user's voice and generates commentary phrases such as the following:

[0333] "The viewer is now in a boss battle! This is an exciting moment!"

[0334] This commentary is converted into audio data using the Google Text-to-Speech API and sent to the user's device, allowing the user to experience the commentary in real time and enjoy more engaging gameplay.

[0335] Prompt Sentence Examples

[0336] "The user is about to enter the fight against Ornstein in Dark Souls. Please generate a commentary phrase to use when the user is excited."

[0337] This invention enables real-time personalized commentary during gameplay, making the user's gaming experience richer and more engaging.

[0338] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0339] Step 1:

[0340] When a user starts playing a game, the user's device (e.g., game console or PC) uses a capture card to capture game footage and controller input data. The input data includes the user's actions (button presses and stick movements), and the game footage data includes the game screen being played. This data is sent to the server in real time at regular intervals.

[0341] Input: User operation data and game video data

[0342] Output: Captured operation data and video data

[0343] Step 2:

[0344] The server analyzes the game video data and input information received in real time, and uses the image analysis library "OpenCV" and the machine learning model "YOLOv4" to identify the game progress and user actions. Specifically, it analyzes each frame of the game video and identifies important events and actions (e.g., entering a boss battle or using a special technique).

[0345] Input: Captured operational and video data

[0346] Output: Game progress and user actions

[0347] Step 3:

[0348] The server receives the user's voice data and camera footage and uses the emotion engine "IBM Watson Tone Analyzer" to recognize the user's emotional state, thereby identifying whether the user is excited or nervous.

[0349] Input: User's voice data and camera footage

[0350] Output: User's emotional state

[0351] Step 4:

[0352] Based on the analyzed game progress and user actions, the server uses a generative AI model to generate commentary phrases. Furthermore, the server adjusts the commentary phrases based on the recognized user's emotional state. For example, if the user is excited about a boss battle, the server generates a phrase such as, "The user has entered a boss battle! This is an exciting moment!"

[0353] Input: Game progress, user actions, and emotional state

[0354] Output: Adjusted commentary phrase

[0355] Step 5:

[0356] The server converts the generated commentary phrases into voice data using the speech synthesis tool "Google Text-to-Speech API." This phrase is converted into voice data in real time and prepared as voice output.

[0357] Input: Adjusted commentary phrase

[0358] Output: Live audio data

[0359] Step 6:

[0360] The server delivers the generated audio and text data to the user's device, which receives, displays, and plays it back, allowing the user to experience a real-time, personalized visual and audio commentary while playing.

[0361] Input: Live audio and text data

[0362] Output: Providing a live experience to the user

[0363] 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.

[0364] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0365] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0366] [Second embodiment]

[0367] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0368] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0369] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. 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).

[0370] 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.

[0371] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0372] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0373] 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.

[0374] 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.

[0375] 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 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.

[0376] 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.

[0377] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0378] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0379] The present invention is a system that provides real-time commentary based on user input and game video data while a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay.

[0380] System Overview

[0381] This system receives input information generated by the user's input means, acquires game video data, analyzes this data to generate commentary phrases, converts the generated commentary phrases into audio data, and executes a series of processes to distribute the audio data to the user's device.

[0382] Program processing

[0383] 1. Acquiring game data

[0384] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[0385] 2. Receiving Data

[0386] The device transmits the captured game video data and input information to the server in real time. This data is collected at regular intervals (e.g., several times per second) and sent to the server as packets.

[0387] 3. Data Analysis

[0388] The server analyzes the game footage and input information received from the device. Specifically, the server uses machine learning models to identify the game's progress and user actions, such as when a boss battle begins or when the user uses a special ability.

[0389] 4. Commentary Phrase Generation

[0390] The server generates commentary phrases based on the analysis results. These phrases will add excitement to the user's gameplay. For example, phrases such as "The user has entered a boss battle!" or "Amazing! The user is using a special ability!" are generated.

[0391] 5. Conversion to audio data

[0392] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[0393] 6. Live data distribution and display

[0394] The server sends the generated commentary phrase text and audio data to the device, which then displays the received data on the screen and plays the audio, allowing the user to enjoy real-time commentary related to the game's progress visually and aurally while playing.

[0395] Specific examples

[0396] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, which continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and detects the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the audio. The user can continue playing the game while experiencing the excitement of the boss battle thanks to this commentary.

[0397] In this way, the present invention provides a new gaming experience that allows users to feel excitement and excitement in real time even when playing a game alone.

[0398] The processing flow will be explained below.

[0399] Step 1:

[0400] The user starts the game. The user launches the game application on their device to play the game.

[0401] Step 2:

[0402] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[0403] Step 3:

[0404] The game video data and input information captured by the device are sent to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent to the server as packets.

[0405] Step 4:

[0406] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0407] Step 5:

[0408] The server generates commentary phrases based on the analysis results, evaluates the analysis results using a machine learning model, and generates appropriate commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!").

[0409] Step 6:

[0410] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[0411] Step 7:

[0412] The server sends the text and audio data of the generated commentary phrase to the terminal, so that the commentary data arrives in real time at the user's terminal.

[0413] Step 8:

[0414] The terminal displays and plays the commentary data it receives. The text of the commentary phrases is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[0415] Step 9:

[0416] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more.

[0417] Example 1

[0418] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0419] When a user is playing a computer program alone, there is a demand for providing real-time commentary based on the game progress and the user's actions to make the user's playing experience more exciting and lively. However, conventional systems have difficulty analyzing game data and user operation information in real time, generating appropriate commentary phrases, and providing them as audio, which makes it difficult to improve the user experience.

[0420] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0421] In this invention, the server includes means for receiving operation information generated from a user's operation means, means for receiving video data of a computer program, means for analyzing the received operation information and video data and identifying the progress of the computer program and the user's actions, means for generating commentary phrases based on the identified status of the computer program and the user's actions, means for converting the generated commentary phrases into audio data, and means for delivering the commentary data including the audio data to the user. This makes it possible to generate appropriate commentary in real time and provide the commentary to the user as audio and text.

[0422] "User's operation means" is a general term for input devices that a user uses to operate a computer program.

[0423] "Operation information" refers to a series of data input by the user through the operating means, including pressing buttons on the controller and movements of the joystick.

[0424] "Video data of a computer program" refers to image information that is generated when a computer program is executed.

[0425] "Means for receiving" refers to methods and techniques for receiving data from the outside.

[0426] "Means of analysis" refers to the technology used to understand the received data and convert it into meaningful information.

[0427] "Progress" is information that indicates a user's progress within a computer program.

[0428] "User behavior" refers to the specific actions a user takes when operating a computer program.

[0429] A "commentary phrase" is a commentary sentence in the form of a sentence that is generated according to the progress of a computer program and the actions of a user.

[0430] "Generation means" refers to methods and technologies for creating new content from data and information.

[0431] "Audio data" refers to digital data in audio format.

[0432] "Means for converting into audio data" refers to technology for converting text data into audio format.

[0433] "Delivery means" refers to the methods and techniques used to deliver the generated data to users.

[0434] "Character data" means digital information expressed in text format.

[0435] "Display device" refers to a device for visually displaying information.

[0436] "Real-time" means processing or reacting immediately, without delay.

[0437] This invention is a system that provides real-time commentary on the game progress and user actions while a user is playing a computer program alone, with the aim of making the user's playing experience more exciting and lively.

[0438] The system mainly consists of the following components: terminals, servers, and communication means to link them together.

[0439] Device features and operations

[0440] A terminal is a device operated by a user that runs a computer program (e.g., game software). It includes an input device (e.g., a controller or keyboard), a display device (e.g., a monitor or display), and a network communication function. While the user is playing the game, the terminal captures operation information and game video data in real time and transmits them to a server at regular intervals.

[0441] Server Functions and Operations

[0442] The server's primary function is to receive and analyze the operation information and game video data sent from the device. The server uses machine learning models to identify the game's progress and user behavior, and generates commentary phrases based on that information. Machine learning models used for this include TensorFlow and PyTorch. The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google's Text-to-Speech API or Amazon Polly.

[0443] Live data distribution

[0444] The server transmits the generated voice and text data to the terminal, which receives it and displays the commentary phrases on the screen while playing the voice, allowing the user to enjoy the commentary visually and aurally in real time while playing the game.

[0445] Specific examples

[0446] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, and while this is happening, the device continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and identifies the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the voice. This allows the user to continue playing the game while experiencing the excitement of the boss battle in real time.

[0447] Prompt Sentence Examples

[0448] Here are some example prompts to input to the generative AI model:

[0449] The user is in a boss battle in an action game. Generate commentary phrases in real time based on the user's input data and game footage data. Then convert the generated phrases into text and audio data and send them to the device.

[0450] By inputting this prompt into a generative AI model, the model can generate specific commentary phrases to enrich the user's gaming experience, and then help translate them into the appropriate format for delivery.

[0451] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0452] Step 1:

[0453] When a user starts a game, the device captures the game's video data and operation information in real time. As input, it receives operation information from the user's operating means (button presses and joystick movements) and the video data displayed on the game screen. As output, it captures this data and converts it into a format for sending to the next process.

[0454] Specific operation: The terminal acquires user input through sensors and network interfaces, and prepares the captured video data and operation information as data packets.

[0455] Step 2:

[0456] The device sends the captured game video data and operation information to the server at regular intervals (e.g., 5 times per second). As input, the data captured in step 1 is used. As output, these data are sent to the server as data packets.

[0457] Specific operation: The terminal uses a data communication protocol to send captured data packets to the server, thereby transmitting data in real time.

[0458] Step 3:

[0459] The server receives and analyzes the data sent from the device. As input, it uses the game video data and operation information sent from the device. As output, it generates data to identify the game progress and user behavior.

[0460] Specific operation: The server uses a machine learning model (e.g., TensorFlow or PyTorch) to analyze the received game video data and operation information and detect the occurrence of specific events (e.g., the start of a boss battle, the use of a special ability).

[0461] Step 4:

[0462] The server generates commentary phrases based on the analysis results. As input, it uses the game progress and user behavior information generated in step 3. As output, it generates the generated commentary phrases.

[0463] Specific behavior: The server uses natural language generation technology to generate commentary phrases corresponding to specific events (e.g., "The user has entered a boss battle!", "Amazing! The user is using a special ability!").

[0464] Step 5:

[0465] The server converts the generated commentary phrases into audio data. As input, the commentary phrases generated in step 4 are used. As output, audio data is generated.

[0466] Specific operation: The server inputs the commentary phrase into a speech synthesis engine (e.g., Google's Text-to-Speech API or Amazon Polly) and generates voice data in real time.

[0467] Step 6:

[0468] The server sends the generated voice data and text data to the terminal. As input, the voice data generated in step 5 and the text data generated in step 4 are used. As output, these data are sent to the terminal.

[0469] Specific operation: The server uses a data communication protocol to send voice data and text data to the terminal.

[0470] Step 7:

[0471] The terminal plays and displays the received audio and text data. As input, the audio and text data sent from the server are used. As output, a live commentary is provided to the user in real time.

[0472] Specific operation: The device displays text data on the screen and plays audio data from the speaker, allowing users to enjoy the commentary visually and aurally while playing the game.

[0473] (Application example 1)

[0474] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0475] Conventional game systems have the problem of lacking excitement and excitement when users play alone. Real-time commentary is an effective way to make gameplay more engaging, but the systems that enable this are complex and difficult for average users to use. Furthermore, these systems require high computational resources, making them difficult to process on individual devices. Furthermore, the technology for analyzing video and input information and generating appropriate phrases is still immature, which can lead to a decline in the quality of the commentary.

[0476] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0477] In this invention, the server includes: means for receiving input information generated from a user's input means; means for receiving game video data; means for analyzing the received input information and video data to identify the game progress and the user's actions; means for generating commentary phrases based on the identified game progress and the user's actions; means for converting the generated commentary phrases into audio data; means for delivering the commentary data including the audio data to the user; means for analyzing data transmitted to the cloud server using a machine learning model; and means for receiving the generated commentary phrases from the cloud server and displaying them as text and playing them as audio. This allows users to enjoy a real-time commentary based on the progress of the game visually and audibly, improving the playing experience. Furthermore, processing on the cloud server reduces the load on the computing resources of the local terminal.

[0478] A "user input" is a device or interface that a user uses to operate a game.

[0479] "Input information" refers to data generated by the user when playing a game, and specifically includes information such as button presses, joystick movements, and touch operations.

[0480] "Game video data" is digital information corresponding to the screen display of the game the user is playing.

[0481] A "cloud server" is a remote server that processes, stores, and manages various data via the Internet.

[0482] A "machine learning model" is an algorithm or architecture that analyzes and parses large amounts of data to learn specific patterns and trends.

[0483] "Game progress" refers to the current point in time during gameplay, the progress of the scenario, the occurrence of events, etc.

[0484] "User actions" refer to various operations and movements performed by the user while playing the game.

[0485] "Commentary phrases" are commentary and commentary texts that are generated in accordance with the game progress and the user's actions.

[0486] "Voice data" refers to digital data generated by a voice synthesis engine that converts commentary phrases into voice.

[0487] "Commentary data" is digital information that includes text data of commentary phrases and audio data based on these phrases.

[0488] "Text display" refers to the visual presentation of textual information on a digital display.

[0489] "Audio playback" refers to outputting audio data on a digital device so that it can be audibly recognized.

[0490] The present invention is a system for providing real-time commentary while a user is playing a game alone. This system is designed to enhance the user's gameplay experience. Specific implementations of the system use various hardware and software, as described in detail below.

[0491] Main hardware and software used

[0492] 1. User Device

[0493] The user device is typically a smartphone. This device runs game applications and provides input means for users to control the game. It also has the ability to capture game video data and input information and send it to a cloud server.

[0494] 2. Cloud Server

[0495] The cloud server receives game video data and input information in real time and analyzes this data using machine learning models (e.g., TensorFlow or PyTorch). The cloud server identifies the game's progress and user actions and generates appropriate commentary phrases. These phrases are converted into audio data by a speech synthesis engine (e.g., Google Cloud Text-to-Speech).

[0496] 3. Generative AI Models

[0497] The system uses a generative AI model to analyze game footage and input information, which is then used to generate appropriate commentary phrases based on the user's gameplay situation.

[0498] Processing description

[0499] Acquiring and sending game data

[0500] When a user plays a game on a smartphone, the device captures game video data and input information in real time. For example, when a user jumps or attacks while playing an action game, the smartphone sends the operation data and video frames to a cloud server. The data is sent at regular intervals (e.g., several times per second) to maintain real-time performance.

[0501] Data analysis and commentary generation

[0502] On the cloud server, a machine learning model analyzes the received data and identifies the game's progress and the user's actions. For example, when the user enters a specific boss battle or uses a special ability. The server then generates commentary phrases based on the analysis results. The generated phrases add excitement to the gameplay, such as "The user has entered a boss battle!"

[0503] Conversion to audio data and distribution

[0504] The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech. The converted voice and text data are sent to the user's device, which displays them on the screen and plays the audio. In this way, users can enjoy the game commentary visually and aurally in real time.

[0505] Examples of specific examples and prompts

[0506] For example, if a user enters a boss battle in an action game, the following happens:

[0507] 1. The user's smartphone detects the start of a boss battle and sends the data to the cloud server.

[0508] 2. The cloud server analyzes the data and generates a commentary phrase such as, "The user has entered a boss battle!"

[0509] 3. The generated phrase is converted into audio data using Google Cloud Text-to-Speech.

[0510] 4. This voice data and the text of the phrase are sent to the user's smartphone, where the voice is played and the text is displayed.

[0511] An example of a prompt sentence when actually using a speech synthesis engine is as follows.

[0512] Example prompt sentence:

[0513] "Please convert the following text into natural, easy-to-listen speech: 'The user has entered a boss battle!'"

[0514] This system allows users to enjoy a fulfilling gaming experience even when playing alone. In addition, by using a cloud server, the load on the user's device can be reduced, and real-time and high-quality commentary can be maintained.

[0515] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0516] Step 1: Capture the data

[0517] When a user plays a game on a smartphone, the device captures game video data and input information in real time. Specifically, it captures each frame of the screen and obtains data on the user's operations (button presses, touch operations, etc.). Input: user operations and game video, Output: captured operation data and video data.

[0518] Step 2: Sending data

[0519] The captured data is sent to the cloud server at regular intervals (e.g., several times per second). The device assembles the captured data into packets and sends them to the cloud server via the Internet. Input: Captured operation data and video data. Output: Packet data sent to the cloud server.

[0520] Step 3: Receiving and analyzing data

[0521] The cloud server analyzes the received data in real time. A machine learning model (e.g., TensorFlow, PyTorch) runs based on the received operation data and video data to identify the game progress and user actions. Input: Sent packet data, Output: Analysis results (game progress, user actions).

[0522] Step 4: Generate commentary phrases

[0523] The server generates commentary phrases based on the analysis results. Appropriate commentary phrases are generated in text format from the analysis results of the machine learning model. For example, if the user enters a specific boss battle, the phrase "The user has entered a boss battle!" is generated. Input: Analysis results, Output: Text data of the generated commentary phrases.

[0524] Step 5: Converting to audio data

[0525] The generated commentary phrase text data is converted into audio data using a speech synthesis engine (e.g., Google Cloud Text-to-Speech). Input: commentary phrase text data, output: audio data (audio file format such as MP3).

[0526] Step 6: Streaming live data

[0527] The cloud server sends the generated voice and text data to the device. The device receives this and displays the text on the user's screen and plays the voice, allowing the user to enjoy the commentary in real time. Input: Generated voice and text data, Output: Commentary data sent to the device.

[0528] Step 7: Display text and play audio

[0529] The device displays the received commentary phrase text data and plays the audio data. This allows the user to enjoy the commentary visually and aurally. Specifically, the commentary phrase is displayed on the user's game screen and the audio is played at the same time. Input: Commentary data sent to the device, Output: Text displayed on the screen, audio played.

[0530] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0531] The present invention is a system that provides real-time commentary based on user input and game video data when a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay. Furthermore, by incorporating an emotion engine, the present invention generates and adjusts commentary phrases to match the user's emotional state, providing a more personalized gaming experience.

[0532] System Overview

[0533] This system receives input information generated by the user's input means, acquires game video data, analyzes this data, and generates commentary phrases. It then executes a series of processes: converting the generated commentary phrases into audio data and distributing it to the user's device. It then uses an emotion engine to analyze the user's emotional state and adjust the commentary phrases.

[0534] Program processing

[0535] 1. Acquiring game data

[0536] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[0537] 2. Receiving Data

[0538] The device transmits the captured game video data and input information to the server in real time. This data is transmitted at regular intervals (for example, several times per second) and sent to the server as packets.

[0539] 3. Data Analysis

[0540] The server analyzes the game footage and input information received from the device. It uses machine learning models to analyze each frame of the game footage and identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0541] 4. Recognizing emotional states

[0542] The server uses an emotion engine to analyze the user's emotional state by capturing and analyzing the user's facial and voice data to identify the user's current emotional state (e.g., excitement, tension, joy).

[0543] 5. Commentary Phrase Generation

[0544] The server generates commentary phrases based on the game progress and the user's emotional state. Using the analysis results, it selects and adjusts commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!") that matches the user's emotions.

[0545] 6. Conversion to audio data

[0546] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[0547] 7. Live data distribution and display

[0548] The server transmits the text and audio data of the generated commentary phrases to the terminal, which then displays the received commentary data on the screen and plays the audio, allowing the user to enjoy the commentary visually and aurally while playing.

[0549] Specific examples

[0550] For example, consider the case where a user enters a boss battle in a particular action game. While the user is playing the game on their device, the device captures game footage and controller input data and sends it to the server. The server analyzes this data to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio. During gameplay, the user not only receives commentary, but also experiences commentary that is in tune with their emotions.

[0551] In this way, the present invention provides a new gaming experience that allows users to feel the excitement and excitement in real time even when playing alone. Furthermore, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, achieving an even deeper gaming experience.

[0552] The processing flow will be explained below.

[0553] Step 1:

[0554] The user starts the game. The user launches the game application on their device and begins playing.

[0555] Step 2:

[0556] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[0557] Step 3:

[0558] The device captures game video data and input information and sends it to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent as packets to the server.

[0559] Step 4:

[0560] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0561] Step 5:

[0562] The server uses an emotion engine to recognize the user's emotions based on the analysis results. It acquires facial expression and voice data from the user's device and analyzes them to identify the user's current emotional state (e.g., excitement, tension, joy).

[0563] Step 6:

[0564] The server generates commentary phrases based on the game progress and the user's emotional state. For example, if a boss battle is reached, the server generates a phrase such as "The user has reached the boss battle!", and if the user is excited, the server adds an add-on commentary phrase such as "This is an exciting moment!".

[0565] Step 7:

[0566] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[0567] Step 8:

[0568] The server transmits the text and audio data of the generated commentary phrases to the terminal, thereby distributing commentary data to the user's terminal in real time.

[0569] Step 9:

[0570] The terminal displays and plays the commentary data it receives. The commentary phrase text is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[0571] Step 10:

[0572] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more, and they can experience a commentary that is personalized to their own emotions.

[0573] Example 2

[0574] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0575] Conventional game systems have the problem that users have difficulty feeling the excitement and excitement of playing alone. Even if systems exist that provide real-time commentary, the commentary is not tailored to the user's emotional state. Therefore, a system that provides more personalized commentary that is in tune with the user's emotions during gameplay is needed.

[0576] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0577] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress and the user's actions, means for analyzing the user's facial expression data and voice data to identify the user's emotional state, means for generating commentary phrases based on the identified game situation and the user's emotional state, means for converting the generated commentary phrases into voice data, and means for delivering the commentary data including the voice data to the user. This allows a commentary that is in line with the user's emotional state in real time to be provided, allowing for greater excitement and thrills while playing.

[0578] "User input means" refers to the device or interface that the user uses to operate the game, and specifically refers to input devices such as a controller, keyboard, or mouse.

[0579] "Input information" refers to data relating to operations and instructions given to the game by the user via input means.

[0580] "Game visual data" refers to all visual information and screen frames displayed in the game a user is playing.

[0581] "Receive" refers to the act of obtaining data or information from another device.

[0582] "Analyzing" refers to the act of breaking down data, understanding its content and structure, and extracting specific information.

[0583] "Game progress" refers to the status of events and stages taking place within the game, as well as the degree of progress.

[0584] "User actions" refers to all operations and actions performed by a user within the game.

[0585] "Facial expression data" refers to image or video data relating to a user's facial expressions.

[0586] "Voice data" refers to data that includes voice information related to a user's speech.

[0587] "Emotional state" refers to the user's psychological state, such as excitement, tension, joy, etc.

[0588] "Commentary phrases" refer to sentences that explain and comment on the game situation and user actions.

[0589] "Converting to audio data" refers to the process of converting commentary phrases in text format into audio format.

[0590] "Distributing" refers to the act of transmitting the generated data to a user's device.

[0591] The term "system" refers to an overall device or program that is made up of the above means.

[0592] This invention relates to a system that provides real-time commentary when a user is playing a game alone. This system generates commentary that takes into account the emotional state of the user based on input information generated by the user's input means and video data of the game, and makes it possible to distribute this commentary in real time.

[0593] Overall structure

[0594] The system mainly consists of the following components:

[0595] 1. Terminal

[0596] 2. Server

[0597] 3. Users

[0598] The terminal is a device on which the user plays the game, captures the game video data and the user's input information, and transmits the captured data to the server.

[0599] The server analyzes the data received from the device, identifies the game progress and the user's emotional state, generates commentary phrases based on the analysis results, converts them into voice data, and distributes them to the device.

[0600] Hardware and software used

[0601] Terminal: Use a personal computer or game console capable of high-performance data processing. Open Broadcaster Software (OBS) is used as capture software. DirectInput or XInput API is used to obtain user input information.

[0602] Server: A cloud server or dedicated server capable of high-speed data analysis is used. TensorFlow or PyTorch is used to run the machine learning model. For emotion recognition, facial recognition software combining OpenCV and Dlib is used. For voice synthesis, Google Text-to-Speech API or Amazon Polly is used.

[0603] Data processing and calculation

[0604] Receive input information generated from a user's input method:

[0605] The device records user operations in real time during gameplay. For example, when a user presses a button on a controller, that information is acquired.

[0606] Receive game video data:

[0607] The device captures each frame of the game screen in real time and transmits it to the server.

[0608] Data analysis:

[0609] The server analyzes the received game footage and input information to determine the game's progress. For example, the server uses a machine learning model to identify scenes in which boss characters appear. It also determines whether the user is excited or not from facial expression and voice data.

[0610] Commentary generation:

[0611] The server generates commentary phrases based on the analysis results. It generates phrases using specific prompts from a generative AI model (e.g., GPT-3).

[0612] Conversion to audio data:

[0613] The generated commentary phrases are converted into voice data by a voice synthesis engine.

[0614] Live data distribution:

[0615] The server sends the generated voice and text data to the terminal, which displays the received data on the screen and plays the voice.

[0616] Specific examples

[0617] For example, consider the case where a user enters a boss battle in a particular action game. The user plays the game on the device, which captures game footage and controller input data and sends it to the server. The server analyzes this to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio at the same time. The user can experience this commentary in real time while playing the game.

[0618] Prompt Sentence Examples

[0619] Here are some example prompts for a generative AI model:

[0620] The user is in a boss battle in an action game. Generate a commentary phrase to describe this scene, keeping in mind that the user is very excited.

[0621] This system provides a new gaming experience that allows users to feel the excitement and excitement even when playing alone. In addition, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, creating a deeper gaming experience.

[0622] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0623] Step 1:

[0624] The device captures game footage and controller input data in real time while the user is playing the game. Input includes game footage (each frame) and the user's controller input information (button presses and joystick movements). This data is acquired using Open Broadcaster Software (OBS) and the DirectInput or XInput API. Output includes the captured video data and controller input data stored in memory. For example, a video frame of the moment the user sees a "giant boss character appear" and input data that "the user presses the attack button" are captured.

[0625] Step 2:

[0626] The device sends captured game video data and input information to the server at regular intervals. Inputs include captured video data and controller input data. These data are sent in JSON format using WebSocket. Outputs include packets that are sent to the server periodically (several times per second). Specifically, the "current frame image" and "information about the button pressed by the user" are sent five times per second.

[0627] Step 3:

[0628] The server analyzes the game footage and input information received from the device. Inputs include video data and input information sent from the device. These data are analyzed using a machine learning model (e.g., TensorFlow or PyTorch) to identify the game's progress and the user's actions. Outputs include the game's progress (e.g., the start of a boss battle) and the user's actions (e.g., repeatedly pressing the attack button). Specifically, the machine learning model recognizes that "the user has entered a boss battle" and obtains the result that "the user is repeatedly pressing a specific button (attacking)."

[0629] Step 4:

[0630] The server analyzes the user's facial expression data and voice data to identify the user's emotional state. The inputs include the user's facial expression data (images captured from the webcam) and voice data (voice from the microphone). These data are analyzed using OpenCV and Dlib to identify the user's emotional state (e.g., excitement, tension, joy). The output is the identified user's emotional state. For example, the webcam captures the user's face, and the emotion recognition model determines that the user is excited. The tone of the user's voice can also be analyzed to indicate that the user is excited.

[0631] Step 5:

[0632] The server generates commentary phrases based on the game progress and the user's emotional state. The inputs include the identified game progress and the user's emotional state. These data are used to generate phrases using prompts from a generative AI model (e.g., GPT-3). The output is the generated commentary phrase. For example, the prompt "The user has entered a boss battle. Please generate a commentary phrase for this scene. Please also keep in mind that the user is very excited" is provided to the generative AI model, which generates the commentary phrase "The user has entered a boss battle! This is an exciting moment!"

[0633] Step 6:

[0634] The server converts the generated commentary phrases into voice data. The input is the generated commentary phrases. These data are converted into speech using a speech synthesis engine (e.g., Google Text-to-Speech API or Amazon Polly). The output is the voice data. Specifically, the commentary phrase "The user has entered a boss battle! This is an exciting moment!" is converted into voice data.

[0635] Step 7:

[0636] The server distributes the generated voice data and text data to the terminal. The input includes voice data and text data. These data are sent to the terminal via the network. The output includes commentary data sent to the terminal. Specifically, the text data and voice data saying "The user has entered a boss battle!" are sent to the terminal.

[0637] Step 8:

[0638] The device displays the commentary data received from the server on the screen and plays the audio. Inputs include text data and audio data sent from the server. These data are played on the device's display and speaker. Output allows the user to experience the commentary visually and audibly. Specifically, the device displays the text "The user has entered a boss battle!" on the screen and plays the audio at the same time. The user can enjoy the commentary in real time.

[0639] (Application example 2)

[0640] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0641] Conventional real-time commentary systems for gameplay provide fixed commentary phrases without considering the user's emotional state, making it difficult for users to achieve a personalized experience. It is also difficult to provide real-time commentary that responds to the game's progress and user actions. There is a need to solve these issues and provide a more engaging and personalized gaming experience.

[0642] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0643] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress status and the user's actions, means for generating commentary phrases based on the identified game status and user actions, means for converting the generated commentary phrases into voice data, means for delivering commentary data including the voice data to the user, means for recognizing the user's emotional state using the user's voice data and camera video, and means for adjusting the commentary phrases based on the recognized emotional state. This allows for personalized commentary to be provided in real time according to the user's emotional state, enabling a more engaging gameplay experience.

[0644] "User input means" refers to the devices or interfaces that a user uses to operate the game.

[0645] "Input information" is a series of data generated from the user's input means, and includes button press status, stick movement, and the like.

[0646] "Game video data" is a series of image data captured from the screen display content of the game being played by the user.

[0647] "Game progress" refers to events or states currently occurring within the game, including player progress and enemy appearances.

[0648] "User action" refers to a specific operation or movement that a user performs in the game, including attacking, moving, etc.

[0649] "Live commentary phrases" are comments and explanatory sentences that are generated based on the game progress and the user's actions.

[0650] "Voice data" refers to a series of data obtained by converting commentary phrases into voice format using voice synthesis.

[0651] "Reportage data" refers to information including text data and audio data of commentary phrases, and is provided to the user.

[0652] An "emotional state" is a user's psychological or emotional response or state, including excitement, tension, joy, and the like.

[0653] An "emotion engine" is software or algorithms that recognize a user's emotional state from voice data and camera footage.

[0654] "Analysis" is the process of processing and analyzing sets of data to extract specific information or patterns.

[0655] "Distribution" refers to the act of transferring live data, including audio data, from a server to a user's device.

[0656] MODE FOR CARRYING OUT THE INVENTION

[0657] This invention is a system that provides real-time commentary to users playing games alone to enhance their gaming experience. The system acquires and analyzes input information generated by the user's input means and game video data to generate commentary phrases that correspond to the user's actions and the game's progress. It also uses an emotion engine to recognize the user's emotional state and adjusts the commentary phrases based on that state, providing a personalized commentary experience.

[0658] Overview of program processing

[0659] 1. Acquiring and sending game data

[0660] A capture card is used to capture game footage and controller input data from the device on which the user is playing the game (e.g., game console or PC). For this purpose, a capture card such as the "Elgato HD60 S+" is used. Game footage is captured at a constant frame rate (e.g., 30 fps or more), and input data (button presses and stick movements) is captured in milliseconds. The captured data is sent to a server in real time.

[0661] 2. Data Analysis

[0662] The server analyzes the received video and input data to identify the game progress and user actions. For example, it uses the machine learning model "YOLOv4" and the image analysis library "OpenCV" to identify specific actions and events within the video data.

[0663] 3. Recognizing emotional states

[0664] The server uses the IBM Watson Tone Analyzer emotion engine to recognize the user's emotional state using the user's voice data and camera footage, making it possible to determine whether the user is excited, relaxed, or nervous.

[0665] 4. Creating and adjusting commentary phrases

[0666] The server generates commentary phrases based on the identified game progress and the user's emotional state, adjusting the phrases as needed. For example, if the user enters a boss battle, the server generates the phrase "The user has entered a boss battle!", and if the user is in an excited state, it adds a phrase such as "This is an exciting moment!".

[0667] 5. Conversion to audio data

[0668] The generated commentary phrases are converted into audio data in real time using the voice synthesis tool "Google Text-to-Speech API."

[0669] 6. Live data distribution and display

[0670] The server delivers the generated audio data and text data to the user's device, plays the audio data, and displays the text data, thereby providing the user with a commentary.

[0671] Specific examples

[0672] For example, consider a situation where a user is playing an action game and enters a boss battle. At this moment, the user's device sends game footage and input data to the server. The server uses the machine learning model YOLOv4 and the image analysis library OpenCV to analyze the boss battle. Furthermore, the IBM Watson Tone Analyzer detects excitement in the user's voice and generates commentary phrases such as the following:

[0673] "The viewer is now in a boss battle! This is an exciting moment!"

[0674] This commentary is converted into audio data using the Google Text-to-Speech API and sent to the user's device, allowing the user to experience the commentary in real time and enjoy more engaging gameplay.

[0675] Prompt Sentence Examples

[0676] "The user is about to enter the fight against Ornstein in Dark Souls. Please generate a commentary phrase to use when the user is excited."

[0677] This invention enables real-time personalized commentary during gameplay, making the user's gaming experience richer and more engaging.

[0678] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0679] Step 1:

[0680] When a user starts playing a game, the user's device (e.g., game console or PC) uses a capture card to capture game footage and controller input data. The input data includes the user's actions (button presses and stick movements), and the game footage data includes the game screen being played. This data is sent to the server in real time at regular intervals.

[0681] Input: User operation data and game video data

[0682] Output: Captured operation data and video data

[0683] Step 2:

[0684] The server analyzes the game video data and input information received in real time, and uses the image analysis library "OpenCV" and the machine learning model "YOLOv4" to identify the game progress and user actions. Specifically, it analyzes each frame of the game video and identifies important events and actions (e.g., entering a boss battle or using a special technique).

[0685] Input: Captured operational and video data

[0686] Output: Game progress and user actions

[0687] Step 3:

[0688] The server receives the user's voice data and camera footage and uses the emotion engine "IBM Watson Tone Analyzer" to recognize the user's emotional state, thereby identifying whether the user is excited or nervous.

[0689] Input: User's voice data and camera footage

[0690] Output: User's emotional state

[0691] Step 4:

[0692] Based on the analyzed game progress and user actions, the server uses a generative AI model to generate commentary phrases. Furthermore, the server adjusts the commentary phrases based on the recognized user's emotional state. For example, if the user is excited about a boss battle, the server generates a phrase such as, "The user has entered a boss battle! This is an exciting moment!"

[0693] Input: Game progress, user actions, and emotional state

[0694] Output: Adjusted commentary phrase

[0695] Step 5:

[0696] The server converts the generated commentary phrases into voice data using the speech synthesis tool "Google Text-to-Speech API." This phrase is converted into voice data in real time and prepared as voice output.

[0697] Input: Adjusted commentary phrase

[0698] Output: Live audio data

[0699] Step 6:

[0700] The server delivers the generated audio and text data to the user's device, which receives, displays, and plays it back, allowing the user to experience a real-time, personalized visual and audio commentary while playing.

[0701] Input: Live audio and text data

[0702] Output: Providing a live experience to the user

[0703] 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.

[0704] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0705] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0706] [Third embodiment]

[0707] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0708] 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.

[0709] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. 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).

[0710] 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.

[0711] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0712] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0713] 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.

[0714] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type 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.

[0715] 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 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.

[0716] 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.

[0717] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0718] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0719] The present invention is a system that provides real-time commentary based on user input and game video data while a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay.

[0720] System Overview

[0721] This system receives input information generated by the user's input means, acquires game video data, analyzes this data to generate commentary phrases, converts the generated commentary phrases into audio data, and executes a series of processes to distribute the audio data to the user's device.

[0722] Program processing

[0723] 1. Acquiring game data

[0724] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[0725] 2. Receiving Data

[0726] The device transmits the captured game video data and input information to the server in real time. This data is collected at regular intervals (e.g., several times per second) and sent to the server as packets.

[0727] 3. Data Analysis

[0728] The server analyzes the game footage and input information received from the device. Specifically, the server uses machine learning models to identify the game's progress and user actions, such as when a boss battle begins or when the user uses a special ability.

[0729] 4. Commentary Phrase Generation

[0730] The server generates commentary phrases based on the analysis results. These phrases will add excitement to the user's gameplay. For example, phrases such as "The user has entered a boss battle!" or "Amazing! The user is using a special ability!" are generated.

[0731] 5. Conversion to audio data

[0732] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[0733] 6. Live data distribution and display

[0734] The server sends the generated commentary phrase text and audio data to the device, which then displays the received data on the screen and plays the audio, allowing the user to enjoy real-time commentary related to the game's progress visually and aurally while playing.

[0735] Specific examples

[0736] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, which continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and detects the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the audio. The user can continue playing the game while experiencing the excitement of the boss battle thanks to this commentary.

[0737] In this way, the present invention provides a new gaming experience that allows users to feel excitement and excitement in real time even when playing a game alone.

[0738] The processing flow will be explained below.

[0739] Step 1:

[0740] The user starts the game. The user launches the game application on their device to play the game.

[0741] Step 2:

[0742] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[0743] Step 3:

[0744] The game video data and input information captured by the device are sent to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent to the server as packets.

[0745] Step 4:

[0746] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0747] Step 5:

[0748] The server generates commentary phrases based on the analysis results, evaluates the analysis results using a machine learning model, and generates appropriate commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!").

[0749] Step 6:

[0750] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[0751] Step 7:

[0752] The server sends the text and audio data of the generated commentary phrase to the terminal, so that the commentary data arrives in real time at the user's terminal.

[0753] Step 8:

[0754] The terminal displays and plays the commentary data it receives. The text of the commentary phrases is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[0755] Step 9:

[0756] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more.

[0757] Example 1

[0758] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0759] When a user is playing a computer program alone, there is a demand for providing real-time commentary based on the game progress and the user's actions to make the user's playing experience more exciting and lively. However, conventional systems have difficulty analyzing game data and user operation information in real time, generating appropriate commentary phrases, and providing them as audio, which makes it difficult to improve the user experience.

[0760] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0761] In this invention, the server includes means for receiving operation information generated from a user's operation means, means for receiving video data of a computer program, means for analyzing the received operation information and video data and identifying the progress of the computer program and the user's actions, means for generating commentary phrases based on the identified status of the computer program and the user's actions, means for converting the generated commentary phrases into audio data, and means for delivering the commentary data including the audio data to the user. This makes it possible to generate appropriate commentary in real time and provide the commentary to the user as audio and text.

[0762] "User's operation means" is a general term for input devices that a user uses to operate a computer program.

[0763] "Operation information" refers to a series of data input by the user through the operating means, including pressing buttons on the controller and movements of the joystick.

[0764] "Video data of a computer program" refers to image information that is generated when a computer program is executed.

[0765] "Means for receiving" refers to methods and techniques for receiving data from the outside.

[0766] "Means of analysis" refers to the technology used to understand the received data and convert it into meaningful information.

[0767] "Progress" is information that indicates a user's progress within a computer program.

[0768] "User behavior" refers to the specific actions a user takes when operating a computer program.

[0769] A "commentary phrase" is a commentary sentence in the form of a sentence that is generated according to the progress of a computer program and the actions of a user.

[0770] "Generation means" refers to methods and technologies for creating new content from data and information.

[0771] "Audio data" refers to digital data in audio format.

[0772] "Means for converting into audio data" refers to technology for converting text data into audio format.

[0773] "Delivery means" refers to the methods and techniques used to deliver the generated data to users.

[0774] "Character data" means digital information expressed in text format.

[0775] "Display device" refers to a device for visually displaying information.

[0776] "Real-time" means processing or reacting immediately, without delay.

[0777] This invention is a system that provides real-time commentary on the game progress and user actions while a user is playing a computer program alone, with the aim of making the user's playing experience more exciting and lively.

[0778] The system mainly consists of the following components: terminals, servers, and communication means to link them together.

[0779] Device features and operations

[0780] A terminal is a device operated by a user that runs a computer program (e.g., game software). It includes an input device (e.g., a controller or keyboard), a display device (e.g., a monitor or display), and a network communication function. While the user is playing the game, the terminal captures operation information and game video data in real time and transmits them to a server at regular intervals.

[0781] Server Functions and Operations

[0782] The server's primary function is to receive and analyze the operation information and game video data sent from the device. The server uses machine learning models to identify the game's progress and user behavior, and generates commentary phrases based on that information. Machine learning models used for this include TensorFlow and PyTorch. The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google's Text-to-Speech API or Amazon Polly.

[0783] Live data distribution

[0784] The server transmits the generated voice and text data to the terminal, which receives it and displays the commentary phrases on the screen while playing the voice, allowing the user to enjoy the commentary visually and aurally in real time while playing the game.

[0785] Specific examples

[0786] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, and while this is happening, the device continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and identifies the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the voice. This allows the user to continue playing the game while experiencing the excitement of the boss battle in real time.

[0787] Prompt Sentence Examples

[0788] Here are some example prompts to input to the generative AI model:

[0789] The user is in a boss battle in an action game. Generate commentary phrases in real time based on the user's input data and game footage data. Then convert the generated phrases into text and audio data and send them to the device.

[0790] By inputting this prompt into a generative AI model, the model can generate specific commentary phrases to enrich the user's gaming experience, and then help translate them into the appropriate format for delivery.

[0791] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0792] Step 1:

[0793] When a user starts a game, the device captures the game's video data and operation information in real time. As input, it receives operation information from the user's operating means (button presses and joystick movements) and the video data displayed on the game screen. As output, it captures this data and converts it into a format for sending to the next process.

[0794] Specific operation: The terminal acquires user input through sensors and network interfaces, and prepares the captured video data and operation information as data packets.

[0795] Step 2:

[0796] The device sends the captured game video data and operation information to the server at regular intervals (e.g., 5 times per second). As input, the data captured in step 1 is used. As output, these data are sent to the server as data packets.

[0797] Specific operation: The terminal uses a data communication protocol to send captured data packets to the server, thereby transmitting data in real time.

[0798] Step 3:

[0799] The server receives and analyzes the data sent from the device. As input, it uses the game video data and operation information sent from the device. As output, it generates data to identify the game progress and user behavior.

[0800] Specific operation: The server uses a machine learning model (e.g., TensorFlow or PyTorch) to analyze the received game video data and operation information and detect the occurrence of specific events (e.g., the start of a boss battle, the use of a special ability).

[0801] Step 4:

[0802] The server generates commentary phrases based on the analysis results. As input, it uses the game progress and user behavior information generated in step 3. As output, it generates the generated commentary phrases.

[0803] Specific behavior: The server uses natural language generation technology to generate commentary phrases corresponding to specific events (e.g., "The user has entered a boss battle!", "Amazing! The user is using a special ability!").

[0804] Step 5:

[0805] The server converts the generated commentary phrases into audio data. As input, the commentary phrases generated in step 4 are used. As output, audio data is generated.

[0806] Specific operation: The server inputs the commentary phrase into a speech synthesis engine (e.g., Google's Text-to-Speech API or Amazon Polly) and generates voice data in real time.

[0807] Step 6:

[0808] The server sends the generated voice data and text data to the terminal. As input, the voice data generated in step 5 and the text data generated in step 4 are used. As output, these data are sent to the terminal.

[0809] Specific operation: The server uses a data communication protocol to send voice data and text data to the terminal.

[0810] Step 7:

[0811] The terminal plays and displays the received audio and text data. As input, the audio and text data sent from the server are used. As output, a live commentary is provided to the user in real time.

[0812] Specific operation: The device displays text data on the screen and plays audio data from the speaker, allowing users to enjoy the commentary visually and aurally while playing the game.

[0813] (Application example 1)

[0814] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0815] Conventional game systems have the problem of lacking excitement and excitement when users play alone. Real-time commentary is an effective way to make gameplay more engaging, but the systems that enable this are complex and difficult for average users to use. Furthermore, these systems require high computational resources, making them difficult to process on individual devices. Furthermore, the technology for analyzing video and input information and generating appropriate phrases is still immature, which can lead to a decline in the quality of the commentary.

[0816] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0817] In this invention, the server includes: means for receiving input information generated from a user's input means; means for receiving game video data; means for analyzing the received input information and video data to identify the game progress and the user's actions; means for generating commentary phrases based on the identified game progress and the user's actions; means for converting the generated commentary phrases into audio data; means for delivering the commentary data including the audio data to the user; means for analyzing data transmitted to the cloud server using a machine learning model; and means for receiving the generated commentary phrases from the cloud server and displaying them as text and playing them as audio. This allows users to enjoy a real-time commentary based on the progress of the game visually and audibly, improving the playing experience. Furthermore, processing on the cloud server reduces the load on the computing resources of the local terminal.

[0818] A "user input" is a device or interface that a user uses to operate a game.

[0819] "Input information" refers to data generated by the user when playing a game, and specifically includes information such as button presses, joystick movements, and touch operations.

[0820] "Game video data" is digital information corresponding to the screen display of the game the user is playing.

[0821] A "cloud server" is a remote server that processes, stores, and manages various data via the Internet.

[0822] A "machine learning model" is an algorithm or architecture that analyzes and parses large amounts of data to learn specific patterns and trends.

[0823] "Game progress" refers to the current point in time during gameplay, the progress of the scenario, the occurrence of events, etc.

[0824] "User actions" refer to various operations and movements performed by the user while playing the game.

[0825] "Commentary phrases" are commentary and commentary texts that are generated in accordance with the game progress and the user's actions.

[0826] "Voice data" refers to digital data generated by a voice synthesis engine that converts commentary phrases into voice.

[0827] "Commentary data" is digital information that includes text data of commentary phrases and audio data based on these phrases.

[0828] "Text display" refers to the visual presentation of textual information on a digital display.

[0829] "Audio playback" refers to outputting audio data on a digital device so that it can be audibly recognized.

[0830] The present invention is a system for providing real-time commentary while a user is playing a game alone. This system is designed to enhance the user's gameplay experience. Specific implementations of the system use various hardware and software, as described in detail below.

[0831] Main hardware and software used

[0832] 1. User Device

[0833] The user device is typically a smartphone. This device runs game applications and provides input means for users to control the game. It also has the ability to capture game video data and input information and send it to a cloud server.

[0834] 2. Cloud Server

[0835] The cloud server receives game video data and input information in real time and analyzes this data using machine learning models (e.g., TensorFlow or PyTorch). The cloud server identifies the game's progress and user actions and generates appropriate commentary phrases. These phrases are converted into audio data by a speech synthesis engine (e.g., Google Cloud Text-to-Speech).

[0836] 3. Generative AI Models

[0837] The system uses a generative AI model to analyze game footage and input information, which is then used to generate appropriate commentary phrases based on the user's gameplay situation.

[0838] Processing description

[0839] Acquiring and sending game data

[0840] When a user plays a game on a smartphone, the device captures game video data and input information in real time. For example, when a user jumps or attacks while playing an action game, the smartphone sends the operation data and video frames to a cloud server. The data is sent at regular intervals (e.g., several times per second) to maintain real-time performance.

[0841] Data analysis and commentary generation

[0842] On the cloud server, a machine learning model analyzes the received data and identifies the game's progress and the user's actions. For example, when the user enters a specific boss battle or uses a special ability. The server then generates commentary phrases based on the analysis results. The generated phrases add excitement to the gameplay, such as "The user has entered a boss battle!"

[0843] Conversion to audio data and distribution

[0844] The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech. The converted voice and text data are sent to the user's device, which displays them on the screen and plays the audio. In this way, users can enjoy the game commentary visually and aurally in real time.

[0845] Examples of specific examples and prompts

[0846] For example, if a user enters a boss battle in an action game, the following happens:

[0847] 1. The user's smartphone detects the start of a boss battle and sends the data to the cloud server.

[0848] 2. The cloud server analyzes the data and generates a commentary phrase such as, "The user has entered a boss battle!"

[0849] 3. The generated phrase is converted into audio data using Google Cloud Text-to-Speech.

[0850] 4. This voice data and the text of the phrase are sent to the user's smartphone, where the voice is played and the text is displayed.

[0851] An example of a prompt sentence when actually using a speech synthesis engine is as follows.

[0852] Example prompt sentence:

[0853] "Please convert the following text into natural, easy-to-listen speech: 'The user has entered a boss battle!'"

[0854] This system allows users to enjoy a fulfilling gaming experience even when playing alone. In addition, by using a cloud server, the load on the user's device can be reduced, and real-time and high-quality commentary can be maintained.

[0855] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0856] Step 1: Capture the data

[0857] When a user plays a game on a smartphone, the device captures game video data and input information in real time. Specifically, it captures each frame of the screen and obtains data on the user's operations (button presses, touch operations, etc.). Input: user operations and game video, Output: captured operation data and video data.

[0858] Step 2: Sending data

[0859] The captured data is sent to the cloud server at regular intervals (e.g., several times per second). The device assembles the captured data into packets and sends them to the cloud server via the Internet. Input: Captured operation data and video data. Output: Packet data sent to the cloud server.

[0860] Step 3: Receiving and analyzing data

[0861] The cloud server analyzes the received data in real time. A machine learning model (e.g., TensorFlow, PyTorch) runs based on the received operation data and video data to identify the game progress and user actions. Input: Sent packet data, Output: Analysis results (game progress, user actions).

[0862] Step 4: Generate commentary phrases

[0863] The server generates commentary phrases based on the analysis results. Appropriate commentary phrases are generated in text format from the analysis results of the machine learning model. For example, if the user enters a specific boss battle, the phrase "The user has entered a boss battle!" is generated. Input: Analysis results, Output: Text data of the generated commentary phrases.

[0864] Step 5: Converting to audio data

[0865] The generated commentary phrase text data is converted into audio data using a speech synthesis engine (e.g., Google Cloud Text-to-Speech). Input: commentary phrase text data, output: audio data (audio file format such as MP3).

[0866] Step 6: Streaming live data

[0867] The cloud server sends the generated voice and text data to the device. The device receives this and displays the text on the user's screen and plays the voice, allowing the user to enjoy the commentary in real time. Input: Generated voice and text data, Output: Commentary data sent to the device.

[0868] Step 7: Display text and play audio

[0869] The device displays the received commentary phrase text data and plays the audio data. This allows the user to enjoy the commentary visually and aurally. Specifically, the commentary phrase is displayed on the user's game screen and the audio is played at the same time. Input: Commentary data sent to the device, Output: Text displayed on the screen, audio played.

[0870] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0871] The present invention is a system that provides real-time commentary based on user input and game video data when a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay. Furthermore, by incorporating an emotion engine, the present invention generates and adjusts commentary phrases to match the user's emotional state, providing a more personalized gaming experience.

[0872] System Overview

[0873] This system receives input information generated by the user's input means, acquires game video data, analyzes this data, and generates commentary phrases. It then executes a series of processes: converting the generated commentary phrases into audio data and distributing it to the user's device. It then uses an emotion engine to analyze the user's emotional state and adjust the commentary phrases.

[0874] Program processing

[0875] 1. Acquiring game data

[0876] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[0877] 2. Receiving Data

[0878] The device transmits the captured game video data and input information to the server in real time. This data is transmitted at regular intervals (for example, several times per second) and sent to the server as packets.

[0879] 3. Data Analysis

[0880] The server analyzes the game footage and input information received from the device. It uses machine learning models to analyze each frame of the game footage and identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0881] 4. Recognizing emotional states

[0882] The server uses an emotion engine to analyze the user's emotional state by capturing and analyzing the user's facial and voice data to identify the user's current emotional state (e.g., excitement, tension, joy).

[0883] 5. Commentary Phrase Generation

[0884] The server generates commentary phrases based on the game progress and the user's emotional state. Using the analysis results, it selects and adjusts commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!") that matches the user's emotions.

[0885] 6. Conversion to audio data

[0886] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[0887] 7. Live data distribution and display

[0888] The server transmits the text and audio data of the generated commentary phrases to the terminal, which then displays the received commentary data on the screen and plays the audio, allowing the user to enjoy the commentary visually and aurally while playing.

[0889] Specific examples

[0890] For example, consider the case where a user enters a boss battle in a particular action game. While the user is playing the game on their device, the device captures game footage and controller input data and sends it to the server. The server analyzes this data to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio. During gameplay, the user not only receives commentary, but also experiences commentary that is in tune with their emotions.

[0891] In this way, the present invention provides a new gaming experience that allows users to feel the excitement and excitement in real time even when playing alone. Furthermore, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, achieving an even deeper gaming experience.

[0892] The processing flow will be explained below.

[0893] Step 1:

[0894] The user starts the game. The user launches the game application on their device and begins playing.

[0895] Step 2:

[0896] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[0897] Step 3:

[0898] The device captures game video data and input information and sends it to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent as packets to the server.

[0899] Step 4:

[0900] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[0901] Step 5:

[0902] The server uses an emotion engine to recognize the user's emotions based on the analysis results. It acquires facial expression and voice data from the user's device and analyzes them to identify the user's current emotional state (e.g., excitement, tension, joy).

[0903] Step 6:

[0904] The server generates commentary phrases based on the game progress and the user's emotional state. For example, if a boss battle is reached, the server generates a phrase such as "The user has reached the boss battle!", and if the user is excited, the server adds an add-on commentary phrase such as "This is an exciting moment!".

[0905] Step 7:

[0906] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[0907] Step 8:

[0908] The server transmits the text and audio data of the generated commentary phrases to the terminal, thereby distributing commentary data to the user's terminal in real time.

[0909] Step 9:

[0910] The terminal displays and plays the commentary data it receives. The commentary phrase text is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[0911] Step 10:

[0912] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more, and they can experience a commentary that is personalized to their own emotions.

[0913] Example 2

[0914] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0915] Conventional game systems have the problem that users have difficulty feeling the excitement and excitement of playing alone. Even if systems exist that provide real-time commentary, the commentary is not tailored to the user's emotional state. Therefore, a system that provides more personalized commentary that is in tune with the user's emotions during gameplay is needed.

[0916] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0917] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress and the user's actions, means for analyzing the user's facial expression data and voice data to identify the user's emotional state, means for generating commentary phrases based on the identified game situation and the user's emotional state, means for converting the generated commentary phrases into voice data, and means for delivering the commentary data including the voice data to the user. This allows a commentary that is in line with the user's emotional state in real time to be provided, allowing for greater excitement and thrills while playing.

[0918] "User input means" refers to the device or interface that the user uses to operate the game, and specifically refers to input devices such as a controller, keyboard, or mouse.

[0919] "Input information" refers to data relating to operations and instructions given to the game by the user via input means.

[0920] "Game visual data" refers to all visual information and screen frames displayed in the game a user is playing.

[0921] "Receive" refers to the act of obtaining data or information from another device.

[0922] "Analyzing" refers to the act of breaking down data, understanding its content and structure, and extracting specific information.

[0923] "Game progress" refers to the status of events and stages taking place within the game, as well as the degree of progress.

[0924] "User actions" refers to all operations and actions performed by a user within the game.

[0925] "Facial expression data" refers to image or video data relating to a user's facial expressions.

[0926] "Voice data" refers to data that includes voice information related to a user's speech.

[0927] "Emotional state" refers to the user's psychological state, such as excitement, tension, joy, etc.

[0928] "Commentary phrases" refer to sentences that explain and comment on the game situation and user actions.

[0929] "Converting to audio data" refers to the process of converting commentary phrases in text format into audio format.

[0930] "Distributing" refers to the act of transmitting the generated data to a user's device.

[0931] The term "system" refers to an overall device or program that is made up of the above means.

[0932] This invention relates to a system that provides real-time commentary when a user is playing a game alone. This system generates commentary that takes into account the emotional state of the user based on input information generated by the user's input means and video data of the game, and makes it possible to distribute this commentary in real time.

[0933] Overall structure

[0934] The system mainly consists of the following components:

[0935] 1. Terminal

[0936] 2. Server

[0937] 3. Users

[0938] The terminal is a device on which the user plays the game, captures the game video data and the user's input information, and transmits the captured data to the server.

[0939] The server analyzes the data received from the device, identifies the game progress and the user's emotional state, generates commentary phrases based on the analysis results, converts them into voice data, and distributes them to the device.

[0940] Hardware and software used

[0941] Terminal: Use a personal computer or game console capable of high-performance data processing. Open Broadcaster Software (OBS) is used as capture software. DirectInput or XInput API is used to obtain user input information.

[0942] Server: A cloud server or dedicated server capable of high-speed data analysis is used. TensorFlow or PyTorch is used to run the machine learning model. For emotion recognition, facial recognition software combining OpenCV and Dlib is used. For voice synthesis, Google Text-to-Speech API or Amazon Polly is used.

[0943] Data processing and calculation

[0944] Receive input information generated from a user's input method:

[0945] The device records user operations in real time during gameplay. For example, when a user presses a button on a controller, that information is acquired.

[0946] Receive game video data:

[0947] The device captures each frame of the game screen in real time and transmits it to the server.

[0948] Data analysis:

[0949] The server analyzes the received game footage and input information to determine the game's progress. For example, the server uses a machine learning model to identify scenes in which boss characters appear. It also determines whether the user is excited or not from facial expression and voice data.

[0950] Commentary generation:

[0951] The server generates commentary phrases based on the analysis results. It generates phrases using specific prompts from a generative AI model (e.g., GPT-3).

[0952] Conversion to audio data:

[0953] The generated commentary phrases are converted into voice data by a voice synthesis engine.

[0954] Live data distribution:

[0955] The server sends the generated voice and text data to the terminal, which displays the received data on the screen and plays the voice.

[0956] Specific examples

[0957] For example, consider the case where a user enters a boss battle in a particular action game. The user plays the game on the device, which captures game footage and controller input data and sends it to the server. The server analyzes this to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio at the same time. The user can experience this commentary in real time while playing the game.

[0958] Prompt Sentence Examples

[0959] Here are some example prompts for a generative AI model:

[0960] The user is in a boss battle in an action game. Generate a commentary phrase to describe this scene, keeping in mind that the user is very excited.

[0961] This system provides a new gaming experience that allows users to feel the excitement and excitement even when playing alone. In addition, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, creating a deeper gaming experience.

[0962] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0963] Step 1:

[0964] The device captures game footage and controller input data in real time while the user is playing the game. Input includes game footage (each frame) and the user's controller input information (button presses and joystick movements). This data is acquired using Open Broadcaster Software (OBS) and the DirectInput or XInput API. Output includes the captured video data and controller input data stored in memory. For example, a video frame of the moment the user sees a "giant boss character appear" and input data that "the user presses the attack button" are captured.

[0965] Step 2:

[0966] The device sends captured game video data and input information to the server at regular intervals. Inputs include captured video data and controller input data. These data are sent in JSON format using WebSocket. Outputs include packets that are sent to the server periodically (several times per second). Specifically, the "current frame image" and "information about the button pressed by the user" are sent five times per second.

[0967] Step 3:

[0968] The server analyzes the game footage and input information received from the device. Inputs include video data and input information sent from the device. These data are analyzed using a machine learning model (e.g., TensorFlow or PyTorch) to identify the game's progress and the user's actions. Outputs include the game's progress (e.g., the start of a boss battle) and the user's actions (e.g., repeatedly pressing the attack button). Specifically, the machine learning model recognizes that "the user has entered a boss battle" and obtains the result that "the user is repeatedly pressing a specific button (attacking)."

[0969] Step 4:

[0970] The server analyzes the user's facial expression data and voice data to identify the user's emotional state. The inputs include the user's facial expression data (images captured from the webcam) and voice data (voice from the microphone). These data are analyzed using OpenCV and Dlib to identify the user's emotional state (e.g., excitement, tension, joy). The output is the identified user's emotional state. For example, the webcam captures the user's face, and the emotion recognition model determines that the user is excited. The tone of the user's voice can also be analyzed to indicate that the user is excited.

[0971] Step 5:

[0972] The server generates commentary phrases based on the game progress and the user's emotional state. The inputs include the identified game progress and the user's emotional state. These data are used to generate phrases using prompts from a generative AI model (e.g., GPT-3). The output is the generated commentary phrase. For example, the prompt "The user has entered a boss battle. Please generate a commentary phrase for this scene. Please also keep in mind that the user is very excited" is provided to the generative AI model, which generates the commentary phrase "The user has entered a boss battle! This is an exciting moment!"

[0973] Step 6:

[0974] The server converts the generated commentary phrases into voice data. The input is the generated commentary phrases. These data are converted into speech using a speech synthesis engine (e.g., Google Text-to-Speech API or Amazon Polly). The output is the voice data. Specifically, the commentary phrase "The user has entered a boss battle! This is an exciting moment!" is converted into voice data.

[0975] Step 7:

[0976] The server distributes the generated voice data and text data to the terminal. The input includes voice data and text data. These data are sent to the terminal via the network. The output includes commentary data sent to the terminal. Specifically, the text data and voice data saying "The user has entered a boss battle!" are sent to the terminal.

[0977] Step 8:

[0978] The device displays the commentary data received from the server on the screen and plays the audio. Inputs include text data and audio data sent from the server. These data are played on the device's display and speaker. Output allows the user to experience the commentary visually and audibly. Specifically, the device displays the text "The user has entered a boss battle!" on the screen and plays the audio at the same time. The user can enjoy the commentary in real time.

[0979] (Application example 2)

[0980] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0981] Conventional real-time commentary systems for gameplay provide fixed commentary phrases without considering the user's emotional state, making it difficult for users to achieve a personalized experience. It is also difficult to provide real-time commentary that responds to the game's progress and user actions. There is a need to solve these issues and provide a more engaging and personalized gaming experience.

[0982] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0983] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress status and the user's actions, means for generating commentary phrases based on the identified game status and user actions, means for converting the generated commentary phrases into voice data, means for delivering commentary data including the voice data to the user, means for recognizing the user's emotional state using the user's voice data and camera video, and means for adjusting the commentary phrases based on the recognized emotional state. This allows for personalized commentary to be provided in real time according to the user's emotional state, enabling a more engaging gameplay experience.

[0984] "User input means" refers to the devices or interfaces that a user uses to operate the game.

[0985] "Input information" is a series of data generated from the user's input means, and includes button press status, stick movement, and the like.

[0986] "Game video data" is a series of image data captured from the screen display content of the game being played by the user.

[0987] "Game progress" refers to events or states currently occurring within the game, including player progress and enemy appearances.

[0988] "User action" refers to a specific operation or movement that a user performs in the game, including attacking, moving, etc.

[0989] "Live commentary phrases" are comments and explanatory sentences that are generated based on the game progress and the user's actions.

[0990] "Voice data" refers to a series of data obtained by converting commentary phrases into voice format using voice synthesis.

[0991] "Reportage data" refers to information including text data and audio data of commentary phrases, and is provided to the user.

[0992] An "emotional state" is a user's psychological or emotional response or state, including excitement, tension, joy, and the like.

[0993] An "emotion engine" is software or algorithms that recognize a user's emotional state from voice data and camera footage.

[0994] "Analysis" is the process of processing and analyzing sets of data to extract specific information or patterns.

[0995] "Distribution" refers to the act of transferring live data, including audio data, from a server to a user's device.

[0996] MODE FOR CARRYING OUT THE INVENTION

[0997] This invention is a system that provides real-time commentary to users playing games alone to enhance their gaming experience. The system acquires and analyzes input information generated by the user's input means and game video data to generate commentary phrases that correspond to the user's actions and the game's progress. It also uses an emotion engine to recognize the user's emotional state and adjusts the commentary phrases based on that state, providing a personalized commentary experience.

[0998] Overview of program processing

[0999] 1. Acquiring and sending game data

[1000] A capture card is used to capture game footage and controller input data from the device on which the user is playing the game (e.g., game console or PC). For this purpose, a capture card such as the "Elgato HD60 S+" is used. Game footage is captured at a constant frame rate (e.g., 30 fps or more), and input data (button presses and stick movements) is captured in milliseconds. The captured data is sent to a server in real time.

[1001] 2. Data Analysis

[1002] The server analyzes the received video and input data to identify the game progress and user actions. For example, it uses the machine learning model "YOLOv4" and the image analysis library "OpenCV" to identify specific actions and events within the video data.

[1003] 3. Recognizing emotional states

[1004] The server uses the IBM Watson Tone Analyzer emotion engine to recognize the user's emotional state using the user's voice data and camera footage, making it possible to determine whether the user is excited, relaxed, or nervous.

[1005] 4. Creating and adjusting commentary phrases

[1006] The server generates commentary phrases based on the identified game progress and the user's emotional state, adjusting the phrases as needed. For example, if the user enters a boss battle, the server generates the phrase "The user has entered a boss battle!", and if the user is in an excited state, it adds a phrase such as "This is an exciting moment!".

[1007] 5. Conversion to audio data

[1008] The generated commentary phrases are converted into audio data in real time using the voice synthesis tool "Google Text-to-Speech API."

[1009] 6. Live data distribution and display

[1010] The server delivers the generated audio data and text data to the user's device, plays the audio data, and displays the text data, thereby providing the user with a commentary.

[1011] Specific examples

[1012] For example, consider a situation where a user is playing an action game and enters a boss battle. At this moment, the user's device sends game footage and input data to the server. The server uses the machine learning model YOLOv4 and the image analysis library OpenCV to analyze the boss battle. Furthermore, the IBM Watson Tone Analyzer detects excitement in the user's voice and generates commentary phrases such as the following:

[1013] "The viewer is now in a boss battle! This is an exciting moment!"

[1014] This commentary is converted into audio data using the Google Text-to-Speech API and sent to the user's device, allowing the user to experience the commentary in real time and enjoy more engaging gameplay.

[1015] Prompt Sentence Examples

[1016] "The user is about to enter the fight against Ornstein in Dark Souls. Please generate a commentary phrase to use when the user is excited."

[1017] This invention enables real-time personalized commentary during gameplay, making the user's gaming experience richer and more engaging.

[1018] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1019] Step 1:

[1020] When a user starts playing a game, the user's device (e.g., game console or PC) uses a capture card to capture game footage and controller input data. The input data includes the user's actions (button presses and stick movements), and the game footage data includes the game screen being played. This data is sent to the server in real time at regular intervals.

[1021] Input: User operation data and game video data

[1022] Output: Captured operation data and video data

[1023] Step 2:

[1024] The server analyzes the game video data and input information received in real time, and uses the image analysis library "OpenCV" and the machine learning model "YOLOv4" to identify the game progress and user actions. Specifically, it analyzes each frame of the game video and identifies important events and actions (e.g., entering a boss battle or using a special technique).

[1025] Input: Captured operational and video data

[1026] Output: Game progress and user actions

[1027] Step 3:

[1028] The server receives the user's voice data and camera footage and uses the emotion engine "IBM Watson Tone Analyzer" to recognize the user's emotional state, thereby identifying whether the user is excited or nervous.

[1029] Input: User's voice data and camera footage

[1030] Output: User's emotional state

[1031] Step 4:

[1032] Based on the analyzed game progress and user actions, the server uses a generative AI model to generate commentary phrases. Furthermore, the server adjusts the commentary phrases based on the recognized user's emotional state. For example, if the user is excited about a boss battle, the server generates a phrase such as, "The user has entered a boss battle! This is an exciting moment!"

[1033] Input: Game progress, user actions, and emotional state

[1034] Output: Adjusted commentary phrase

[1035] Step 5:

[1036] The server converts the generated commentary phrases into voice data using the speech synthesis tool "Google Text-to-Speech API." This phrase is converted into voice data in real time and prepared as voice output.

[1037] Input: Adjusted commentary phrase

[1038] Output: Live audio data

[1039] Step 6:

[1040] The server delivers the generated audio and text data to the user's device, which receives, displays, and plays it back, allowing the user to experience a real-time, personalized visual and audio commentary while playing.

[1041] Input: Live audio and text data

[1042] Output: Providing a live experience to the user

[1043] 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.

[1044] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1045] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1046] [Fourth embodiment]

[1047] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1048] 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.

[1049] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. 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).

[1050] 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.

[1051] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1052] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1053] 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.

[1054] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1055] 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.

[1056] 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 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.

[1057] 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.

[1058] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1059] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1060] The present invention is a system that provides real-time commentary based on user input and game video data while a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay.

[1061] System Overview

[1062] This system receives input information generated by the user's input means, acquires game video data, analyzes this data to generate commentary phrases, converts the generated commentary phrases into audio data, and executes a series of processes to distribute the audio data to the user's device.

[1063] Program processing

[1064] 1. Acquiring game data

[1065] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[1066] 2. Receiving Data

[1067] The device transmits the captured game video data and input information to the server in real time. This data is collected at regular intervals (e.g., several times per second) and sent to the server as packets.

[1068] 3. Data Analysis

[1069] The server analyzes the game footage and input information received from the device. Specifically, the server uses machine learning models to identify the game's progress and user actions, such as when a boss battle begins or when the user uses a special ability.

[1070] 4. Commentary Phrase Generation

[1071] The server generates commentary phrases based on the analysis results. These phrases will add excitement to the user's gameplay. For example, phrases such as "The user has entered a boss battle!" or "Amazing! The user is using a special ability!" are generated.

[1072] 5. Conversion to audio data

[1073] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[1074] 6. Live data distribution and display

[1075] The server sends the generated commentary phrase text and audio data to the device, which then displays the received data on the screen and plays the audio, allowing the user to enjoy real-time commentary related to the game's progress visually and aurally while playing.

[1076] Specific examples

[1077] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, which continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and detects the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the audio. The user can continue playing the game while experiencing the excitement of the boss battle thanks to this commentary.

[1078] In this way, the present invention provides a new gaming experience that allows users to feel excitement and excitement in real time even when playing a game alone.

[1079] The processing flow will be explained below.

[1080] Step 1:

[1081] The user starts the game. The user launches the game application on their device to play the game.

[1082] Step 2:

[1083] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[1084] Step 3:

[1085] The game video data and input information captured by the device are sent to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent to the server as packets.

[1086] Step 4:

[1087] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[1088] Step 5:

[1089] The server generates commentary phrases based on the analysis results, evaluates the analysis results using a machine learning model, and generates appropriate commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!").

[1090] Step 6:

[1091] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[1092] Step 7:

[1093] The server sends the text and audio data of the generated commentary phrase to the terminal, so that the commentary data arrives in real time at the user's terminal.

[1094] Step 8:

[1095] The terminal displays and plays the commentary data it receives. The text of the commentary phrases is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[1096] Step 9:

[1097] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more.

[1098] Example 1

[1099] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1100] When a user is playing a computer program alone, there is a demand for providing real-time commentary based on the game progress and the user's actions to make the user's playing experience more exciting and lively. However, conventional systems have difficulty analyzing game data and user operation information in real time, generating appropriate commentary phrases, and providing them as audio, which makes it difficult to improve the user experience.

[1101] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1102] In this invention, the server includes means for receiving operation information generated from a user's operation means, means for receiving video data of a computer program, means for analyzing the received operation information and video data and identifying the progress of the computer program and the user's actions, means for generating commentary phrases based on the identified status of the computer program and the user's actions, means for converting the generated commentary phrases into audio data, and means for delivering the commentary data including the audio data to the user. This makes it possible to generate appropriate commentary in real time and provide the commentary to the user as audio and text.

[1103] "User's operation means" is a general term for input devices that a user uses to operate a computer program.

[1104] "Operation information" refers to a series of data input by the user through the operating means, including pressing buttons on the controller and movements of the joystick.

[1105] "Video data of a computer program" refers to image information that is generated when a computer program is executed.

[1106] "Means for receiving" refers to methods and techniques for receiving data from the outside.

[1107] "Means of analysis" refers to the technology used to understand the received data and convert it into meaningful information.

[1108] "Progress" is information that indicates a user's progress within a computer program.

[1109] "User behavior" refers to the specific actions a user takes when operating a computer program.

[1110] A "commentary phrase" is a commentary sentence in the form of a sentence that is generated according to the progress of a computer program and the actions of a user.

[1111] "Generation means" refers to methods and technologies for creating new content from data and information.

[1112] "Audio data" refers to digital data in audio format.

[1113] "Means for converting into audio data" refers to technology for converting text data into audio format.

[1114] "Delivery means" refers to the methods and techniques used to deliver the generated data to users.

[1115] "Character data" means digital information expressed in text format.

[1116] "Display device" refers to a device for visually displaying information.

[1117] "Real-time" means processing or reacting immediately, without delay.

[1118] This invention is a system that provides real-time commentary on the game progress and user actions while a user is playing a computer program alone, with the aim of making the user's playing experience more exciting and lively.

[1119] The system mainly consists of the following components: terminals, servers, and communication means to link them together.

[1120] Device features and operations

[1121] A terminal is a device operated by a user that runs a computer program (e.g., game software). It includes an input device (e.g., a controller or keyboard), a display device (e.g., a monitor or display), and a network communication function. While the user is playing the game, the terminal captures operation information and game video data in real time and transmits them to a server at regular intervals.

[1122] Server Functions and Operations

[1123] The server's primary function is to receive and analyze the operation information and game video data sent from the device. The server uses machine learning models to identify the game's progress and user behavior, and generates commentary phrases based on that information. Machine learning models used for this include TensorFlow and PyTorch. The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google's Text-to-Speech API or Amazon Polly.

[1124] Live data distribution

[1125] The server transmits the generated voice and text data to the terminal, which receives it and displays the commentary phrases on the screen while playing the voice, allowing the user to enjoy the commentary visually and aurally in real time while playing the game.

[1126] Specific examples

[1127] For example, consider the case where a user enters a boss battle in a particular action game. The user is playing the game on the device, and while this is happening, the device continues to capture game footage and controller input data. The captured data is sent to the server, which analyzes it and identifies the start of the boss battle. The server generates a commentary phrase, "The user has entered a boss battle!" and converts it into voice data using a speech synthesis engine. Finally, the server sends this commentary data to the device, which displays the text on the screen and plays the voice. This allows the user to continue playing the game while experiencing the excitement of the boss battle in real time.

[1128] Prompt Sentence Examples

[1129] Here are some example prompts to input to the generative AI model:

[1130] The user is in a boss battle in an action game. Generate commentary phrases in real time based on the user's input data and game footage data. Then convert the generated phrases into text and audio data and send them to the device.

[1131] By inputting this prompt into a generative AI model, the model can generate specific commentary phrases to enrich the user's gaming experience, and then help translate them into the appropriate format for delivery.

[1132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1133] Step 1:

[1134] When a user starts a game, the device captures the game's video data and operation information in real time. As input, it receives operation information from the user's operating means (button presses and joystick movements) and the video data displayed on the game screen. As output, it captures this data and converts it into a format for sending to the next process.

[1135] Specific operation: The terminal acquires user input through sensors and network interfaces, and prepares the captured video data and operation information as data packets.

[1136] Step 2:

[1137] The device sends the captured game video data and operation information to the server at regular intervals (e.g., 5 times per second). As input, the data captured in step 1 is used. As output, these data are sent to the server as data packets.

[1138] Specific operation: The terminal uses a data communication protocol to send captured data packets to the server, thereby transmitting data in real time.

[1139] Step 3:

[1140] The server receives and analyzes the data sent from the device. As input, it uses the game video data and operation information sent from the device. As output, it generates data to identify the game progress and user behavior.

[1141] Specific operation: The server uses a machine learning model (e.g., TensorFlow or PyTorch) to analyze the received game video data and operation information and detect the occurrence of specific events (e.g., the start of a boss battle, the use of a special ability).

[1142] Step 4:

[1143] The server generates commentary phrases based on the analysis results. As input, it uses the game progress and user behavior information generated in step 3. As output, it generates the generated commentary phrases.

[1144] Specific behavior: The server uses natural language generation technology to generate commentary phrases corresponding to specific events (e.g., "The user has entered a boss battle!", "Amazing! The user is using a special ability!").

[1145] Step 5:

[1146] The server converts the generated commentary phrases into audio data. As input, the commentary phrases generated in step 4 are used. As output, audio data is generated.

[1147] Specific operation: The server inputs the commentary phrase into a speech synthesis engine (e.g., Google's Text-to-Speech API or Amazon Polly) and generates voice data in real time.

[1148] Step 6:

[1149] The server sends the generated voice data and text data to the terminal. As input, the voice data generated in step 5 and the text data generated in step 4 are used. As output, these data are sent to the terminal.

[1150] Specific operation: The server uses a data communication protocol to send voice data and text data to the terminal.

[1151] Step 7:

[1152] The terminal plays and displays the received audio and text data. As input, the audio and text data sent from the server are used. As output, a live commentary is provided to the user in real time.

[1153] Specific operation: The device displays text data on the screen and plays audio data from the speaker, allowing users to enjoy the commentary visually and aurally while playing the game.

[1154] (Application example 1)

[1155] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1156] Conventional game systems have the problem of lacking excitement and excitement when users play alone. Real-time commentary is an effective way to make gameplay more engaging, but the systems that enable this are complex and difficult for average users to use. Furthermore, these systems require high computational resources, making them difficult to process on individual devices. Furthermore, the technology for analyzing video and input information and generating appropriate phrases is still immature, which can lead to a decline in the quality of the commentary.

[1157] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1158] In this invention, the server includes: means for receiving input information generated from a user's input means; means for receiving game video data; means for analyzing the received input information and video data to identify the game progress and the user's actions; means for generating commentary phrases based on the identified game progress and the user's actions; means for converting the generated commentary phrases into audio data; means for delivering the commentary data including the audio data to the user; means for analyzing data transmitted to the cloud server using a machine learning model; and means for receiving the generated commentary phrases from the cloud server and displaying them as text and playing them as audio. This allows users to enjoy a real-time commentary based on the progress of the game visually and audibly, improving the playing experience. Furthermore, processing on the cloud server reduces the load on the computing resources of the local terminal.

[1159] A "user input" is a device or interface that a user uses to operate a game.

[1160] "Input information" refers to data generated by the user when playing a game, and specifically includes information such as button presses, joystick movements, and touch operations.

[1161] "Game video data" is digital information corresponding to the screen display of the game the user is playing.

[1162] A "cloud server" is a remote server that processes, stores, and manages various data via the Internet.

[1163] A "machine learning model" is an algorithm or architecture that analyzes and parses large amounts of data to learn specific patterns and trends.

[1164] "Game progress" refers to the current point in time during gameplay, the progress of the scenario, the occurrence of events, etc.

[1165] "User actions" refer to various operations and movements performed by the user while playing the game.

[1166] "Commentary phrases" are commentary and commentary texts that are generated in accordance with the game progress and the user's actions.

[1167] "Voice data" refers to digital data generated by a voice synthesis engine that converts commentary phrases into voice.

[1168] "Commentary data" is digital information that includes text data of commentary phrases and audio data based on these phrases.

[1169] "Text display" refers to the visual presentation of textual information on a digital display.

[1170] "Audio playback" refers to outputting audio data on a digital device so that it can be audibly recognized.

[1171] The present invention is a system for providing real-time commentary while a user is playing a game alone. This system is designed to enhance the user's gameplay experience. Specific implementations of the system use various hardware and software, as described in detail below.

[1172] Main hardware and software used

[1173] 1. User Device

[1174] The user device is typically a smartphone. This device runs game applications and provides input means for users to control the game. It also has the ability to capture game video data and input information and send it to a cloud server.

[1175] 2. Cloud Server

[1176] The cloud server receives game video data and input information in real time and analyzes this data using machine learning models (e.g., TensorFlow or PyTorch). The cloud server identifies the game's progress and user actions and generates appropriate commentary phrases. These phrases are converted into audio data by a speech synthesis engine (e.g., Google Cloud Text-to-Speech).

[1177] 3. Generative AI Models

[1178] The system uses a generative AI model to analyze game footage and input information, which is then used to generate appropriate commentary phrases based on the user's gameplay situation.

[1179] Processing description

[1180] Acquiring and sending game data

[1181] When a user plays a game on a smartphone, the device captures game video data and input information in real time. For example, when a user jumps or attacks while playing an action game, the smartphone sends the operation data and video frames to a cloud server. The data is sent at regular intervals (e.g., several times per second) to maintain real-time performance.

[1182] Data analysis and commentary generation

[1183] On the cloud server, a machine learning model analyzes the received data and identifies the game's progress and the user's actions. For example, when the user enters a specific boss battle or uses a special ability. The server then generates commentary phrases based on the analysis results. The generated phrases add excitement to the gameplay, such as "The user has entered a boss battle!"

[1184] Conversion to audio data and distribution

[1185] The generated commentary phrases are converted into voice data using a speech synthesis engine such as Google Cloud Text-to-Speech. The converted voice and text data are sent to the user's device, which displays them on the screen and plays the audio. In this way, users can enjoy the game commentary visually and aurally in real time.

[1186] Examples of specific examples and prompts

[1187] For example, if a user enters a boss battle in an action game, the following happens:

[1188] 1. The user's smartphone detects the start of a boss battle and sends the data to the cloud server.

[1189] 2. The cloud server analyzes the data and generates a commentary phrase such as, "The user has entered a boss battle!"

[1190] 3. The generated phrase is converted into audio data using Google Cloud Text-to-Speech.

[1191] 4. This voice data and the text of the phrase are sent to the user's smartphone, where the voice is played and the text is displayed.

[1192] An example of a prompt sentence when actually using a speech synthesis engine is as follows.

[1193] Example prompt sentence:

[1194] "Please convert the following text into natural, easy-to-listen speech: 'The user has entered a boss battle!'"

[1195] This system allows users to enjoy a fulfilling gaming experience even when playing alone. In addition, by using a cloud server, the load on the user's device can be reduced, and real-time and high-quality commentary can be maintained.

[1196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1197] Step 1: Capture the data

[1198] When a user plays a game on a smartphone, the device captures game video data and input information in real time. Specifically, it captures each frame of the screen and obtains data on the user's operations (button presses, touch operations, etc.). Input: user operations and game video, Output: captured operation data and video data.

[1199] Step 2: Sending data

[1200] The captured data is sent to the cloud server at regular intervals (e.g., several times per second). The device assembles the captured data into packets and sends them to the cloud server via the Internet. Input: Captured operation data and video data. Output: Packet data sent to the cloud server.

[1201] Step 3: Receiving and analyzing data

[1202] The cloud server analyzes the received data in real time. A machine learning model (e.g., TensorFlow, PyTorch) runs based on the received operation data and video data to identify the game progress and user actions. Input: Sent packet data, Output: Analysis results (game progress, user actions).

[1203] Step 4: Generate commentary phrases

[1204] The server generates commentary phrases based on the analysis results. Appropriate commentary phrases are generated in text format from the analysis results of the machine learning model. For example, if the user enters a specific boss battle, the phrase "The user has entered a boss battle!" is generated. Input: Analysis results, Output: Text data of the generated commentary phrases.

[1205] Step 5: Converting to audio data

[1206] The generated commentary phrase text data is converted into audio data using a speech synthesis engine (e.g., Google Cloud Text-to-Speech). Input: commentary phrase text data, output: audio data (audio file format such as MP3).

[1207] Step 6: Streaming live data

[1208] The cloud server sends the generated voice and text data to the device. The device receives this and displays the text on the user's screen and plays the voice, allowing the user to enjoy the commentary in real time. Input: Generated voice and text data, Output: Commentary data sent to the device.

[1209] Step 7: Display text and play audio

[1210] The device displays the received commentary phrase text data and plays the audio data. This allows the user to enjoy the commentary visually and aurally. Specifically, the commentary phrase is displayed on the user's game screen and the audio is played at the same time. Input: Commentary data sent to the device, Output: Text displayed on the screen, audio played.

[1211] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1212] The present invention is a system that provides real-time commentary based on user input and game video data when a user is playing a game alone. The system of the present invention aims to add excitement and excitement to the user's gameplay. Furthermore, by incorporating an emotion engine, the present invention generates and adjusts commentary phrases to match the user's emotional state, providing a more personalized gaming experience.

[1213] System Overview

[1214] This system receives input information generated by the user's input means, acquires game video data, analyzes this data, and generates commentary phrases. It then executes a series of processes: converting the generated commentary phrases into audio data and distributing it to the user's device. It then uses an emotion engine to analyze the user's emotional state and adjust the commentary phrases.

[1215] Program processing

[1216] 1. Acquiring game data

[1217] The device captures game footage and controller input data in real time while the user is playing a game. For example, if the user is playing an action game, the device captures each frame of the screen and the user's actions (each button press and joystick movement).

[1218] 2. Receiving Data

[1219] The device transmits the captured game video data and input information to the server in real time. This data is transmitted at regular intervals (for example, several times per second) and sent to the server as packets.

[1220] 3. Data Analysis

[1221] The server analyzes the game footage and input information received from the device. It uses machine learning models to analyze each frame of the game footage and identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[1222] 4. Recognizing emotional states

[1223] The server uses an emotion engine to analyze the user's emotional state by capturing and analyzing the user's facial and voice data to identify the user's current emotional state (e.g., excitement, tension, joy).

[1224] 5. Commentary Phrase Generation

[1225] The server generates commentary phrases based on the game progress and the user's emotional state. Using the analysis results, it selects and adjusts commentary text (e.g., "The user has entered a boss battle!" or "Amazing! The user is using a special ability!") that matches the user's emotions.

[1226] 6. Conversion to audio data

[1227] The server converts the generated commentary phrases into voice data using a voice synthesis engine to generate commentary voice in real time.

[1228] 7. Live data distribution and display

[1229] The server transmits the text and audio data of the generated commentary phrases to the terminal, which then displays the received commentary data on the screen and plays the audio, allowing the user to enjoy the commentary visually and aurally while playing.

[1230] Specific examples

[1231] For example, consider the case where a user enters a boss battle in a particular action game. While the user is playing the game on their device, the device captures game footage and controller input data and sends it to the server. The server analyzes this data to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio. During gameplay, the user not only receives commentary, but also experiences commentary that is in tune with their emotions.

[1232] In this way, the present invention provides a new gaming experience that allows users to feel the excitement and excitement in real time even when playing alone. Furthermore, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, achieving an even deeper gaming experience.

[1233] The processing flow will be explained below.

[1234] Step 1:

[1235] The user starts the game. The user launches the game application on their device and begins playing.

[1236] Step 2:

[1237] The device captures game footage and controller input data. Game footage is captured as each frame of the screen, and controller input data includes button presses, joystick movements, etc.

[1238] Step 3:

[1239] The device captures game video data and input information and sends it to the server in real time. This data is collected at regular intervals (e.g., 10 times per second) and sent as packets to the server.

[1240] Step 4:

[1241] The server analyzes the data received from the device, processing the game video data frame by frame and analyzing the user's input information to identify the game's progress and the user's actions (e.g., entering a boss battle or using a special ability).

[1242] Step 5:

[1243] The server uses an emotion engine to recognize the user's emotions based on the analysis results. It acquires facial expression and voice data from the user's device and analyzes them to identify the user's current emotional state (e.g., excitement, tension, joy).

[1244] Step 6:

[1245] The server generates commentary phrases based on the game progress and the user's emotional state. For example, if a boss battle is reached, the server generates a phrase such as "The user has reached the boss battle!", and if the user is excited, the server adds an add-on commentary phrase such as "This is an exciting moment!".

[1246] Step 7:

[1247] The server converts the generated commentary phrases into audio data, and uses a speech synthesis engine to generate the commentary text as an audio file and convert it into a playable format.

[1248] Step 8:

[1249] The server transmits the text and audio data of the generated commentary phrases to the terminal, thereby distributing commentary data to the user's terminal in real time.

[1250] Step 9:

[1251] The terminal displays and plays the commentary data it receives. The commentary phrase text is displayed on the screen and the audio data is played back at the same time. This allows the user to enjoy the commentary visually and audibly.

[1252] Step 10:

[1253] Users can continue playing the game while watching and listening to the commentary. The commentary provided in real time allows users to feel the excitement and thrill of the gameplay even more, and they can experience a commentary that is personalized to their own emotions.

[1254] Example 2

[1255] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1256] Conventional game systems have the problem that users have difficulty feeling the excitement and excitement of playing alone. Even if systems exist that provide real-time commentary, the commentary is not tailored to the user's emotional state. Therefore, a system that provides more personalized commentary that is in tune with the user's emotions during gameplay is needed.

[1257] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1258] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress and the user's actions, means for analyzing the user's facial expression data and voice data to identify the user's emotional state, means for generating commentary phrases based on the identified game situation and the user's emotional state, means for converting the generated commentary phrases into voice data, and means for delivering the commentary data including the voice data to the user. This allows a commentary that is in line with the user's emotional state in real time to be provided, allowing for greater excitement and thrills while playing.

[1259] "User input means" refers to the device or interface that the user uses to operate the game, and specifically refers to input devices such as a controller, keyboard, or mouse.

[1260] "Input information" refers to data relating to operations and instructions given to the game by the user via input means.

[1261] "Game visual data" refers to all visual information and screen frames displayed in the game a user is playing.

[1262] "Receive" refers to the act of obtaining data or information from another device.

[1263] "Analyzing" refers to the act of breaking down data, understanding its content and structure, and extracting specific information.

[1264] "Game progress" refers to the status of events and stages taking place within the game, as well as the degree of progress.

[1265] "User actions" refers to all operations and actions performed by a user within the game.

[1266] "Facial expression data" refers to image or video data relating to a user's facial expressions.

[1267] "Voice data" refers to data that includes voice information related to a user's speech.

[1268] "Emotional state" refers to the user's psychological state, such as excitement, tension, joy, etc.

[1269] "Commentary phrases" refer to sentences that explain and comment on the game situation and user actions.

[1270] "Converting to audio data" refers to the process of converting commentary phrases in text format into audio format.

[1271] "Distributing" refers to the act of transmitting the generated data to a user's device.

[1272] The term "system" refers to an overall device or program that is made up of the above means.

[1273] This invention relates to a system that provides real-time commentary when a user is playing a game alone. This system generates commentary that takes into account the emotional state of the user based on input information generated by the user's input means and video data of the game, and makes it possible to distribute this commentary in real time.

[1274] Overall structure

[1275] The system mainly consists of the following components:

[1276] 1. Terminal

[1277] 2. Server

[1278] 3. Users

[1279] The terminal is a device on which the user plays the game, captures the game video data and the user's input information, and transmits the captured data to the server.

[1280] The server analyzes the data received from the device, identifies the game progress and the user's emotional state, generates commentary phrases based on the analysis results, converts them into voice data, and distributes them to the device.

[1281] Hardware and software used

[1282] Terminal: Use a personal computer or game console capable of high-performance data processing. Open Broadcaster Software (OBS) is used as capture software. DirectInput or XInput API is used to obtain user input information.

[1283] Server: A cloud server or dedicated server capable of high-speed data analysis is used. TensorFlow or PyTorch is used to run the machine learning model. For emotion recognition, facial recognition software combining OpenCV and Dlib is used. For voice synthesis, Google Text-to-Speech API or Amazon Polly is used.

[1284] Data processing and calculation

[1285] Receive input information generated from a user's input method:

[1286] The device records user operations in real time during gameplay. For example, when a user presses a button on a controller, that information is acquired.

[1287] Receive game video data:

[1288] The device captures each frame of the game screen in real time and transmits it to the server.

[1289] Data analysis:

[1290] The server analyzes the received game footage and input information to determine the game's progress. For example, the server uses a machine learning model to identify scenes in which boss characters appear. It also determines whether the user is excited or not from facial expression and voice data.

[1291] Commentary generation:

[1292] The server generates commentary phrases based on the analysis results. It generates phrases using specific prompts from a generative AI model (e.g., GPT-3).

[1293] Conversion to audio data:

[1294] The generated commentary phrases are converted into voice data by a voice synthesis engine.

[1295] Live data distribution:

[1296] The server sends the generated voice and text data to the terminal, which displays the received data on the screen and plays the voice.

[1297] Specific examples

[1298] For example, consider the case where a user enters a boss battle in a particular action game. The user plays the game on the device, which captures game footage and controller input data and sends it to the server. The server analyzes this to detect the start of the boss battle and generates a commentary phrase such as "The user has entered a boss battle!" If the emotion engine determines that the user is excited at this time, it adds a phrase such as "This is an exciting moment!" The server converts this commentary phrase into audio and sends it to the device. The device displays the commentary phrase on the screen and plays the audio at the same time. The user can experience this commentary in real time while playing the game.

[1299] Prompt Sentence Examples

[1300] Here are some example prompts for a generative AI model:

[1301] The user is in a boss battle in an action game. Generate a commentary phrase to describe this scene, keeping in mind that the user is very excited.

[1302] This system provides a new gaming experience that allows users to feel the excitement and excitement even when playing alone. In addition, by combining it with an emotion engine, it provides personalized commentary according to the user's emotional state, creating a deeper gaming experience.

[1303] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1304] Step 1:

[1305] The device captures game footage and controller input data in real time while the user is playing the game. Input includes game footage (each frame) and the user's controller input information (button presses and joystick movements). This data is acquired using Open Broadcaster Software (OBS) and the DirectInput or XInput API. Output includes the captured video data and controller input data stored in memory. For example, a video frame of the moment the user sees a "giant boss character appear" and input data that "the user presses the attack button" are captured.

[1306] Step 2:

[1307] The device sends captured game video data and input information to the server at regular intervals. Inputs include captured video data and controller input data. These data are sent in JSON format using WebSocket. Outputs include packets that are sent to the server periodically (several times per second). Specifically, the "current frame image" and "information about the button pressed by the user" are sent five times per second.

[1308] Step 3:

[1309] The server analyzes the game footage and input information received from the device. Inputs include video data and input information sent from the device. These data are analyzed using a machine learning model (e.g., TensorFlow or PyTorch) to identify the game's progress and the user's actions. Outputs include the game's progress (e.g., the start of a boss battle) and the user's actions (e.g., repeatedly pressing the attack button). Specifically, the machine learning model recognizes that "the user has entered a boss battle" and obtains the result that "the user is repeatedly pressing a specific button (attacking)."

[1310] Step 4:

[1311] The server analyzes the user's facial expression data and voice data to identify the user's emotional state. The inputs include the user's facial expression data (images captured from the webcam) and voice data (voice from the microphone). These data are analyzed using OpenCV and Dlib to identify the user's emotional state (e.g., excitement, tension, joy). The output is the identified user's emotional state. For example, the webcam captures the user's face, and the emotion recognition model determines that the user is excited. The tone of the user's voice can also be analyzed to indicate that the user is excited.

[1312] Step 5:

[1313] The server generates commentary phrases based on the game progress and the user's emotional state. The inputs include the identified game progress and the user's emotional state. These data are used to generate phrases using prompts from a generative AI model (e.g., GPT-3). The output is the generated commentary phrase. For example, the prompt "The user has entered a boss battle. Please generate a commentary phrase for this scene. Please also keep in mind that the user is very excited" is provided to the generative AI model, which generates the commentary phrase "The user has entered a boss battle! This is an exciting moment!"

[1314] Step 6:

[1315] The server converts the generated commentary phrases into voice data. The input is the generated commentary phrases. These data are converted into speech using a speech synthesis engine (e.g., Google Text-to-Speech API or Amazon Polly). The output is the voice data. Specifically, the commentary phrase "The user has entered a boss battle! This is an exciting moment!" is converted into voice data.

[1316] Step 7:

[1317] The server distributes the generated voice data and text data to the terminal. The input includes voice data and text data. These data are sent to the terminal via the network. The output includes commentary data sent to the terminal. Specifically, the text data and voice data saying "The user has entered a boss battle!" are sent to the terminal.

[1318] Step 8:

[1319] The device displays the commentary data received from the server on the screen and plays the audio. Inputs include text data and audio data sent from the server. These data are played on the device's display and speaker. Output allows the user to experience the commentary visually and audibly. Specifically, the device displays the text "The user has entered a boss battle!" on the screen and plays the audio at the same time. The user can enjoy the commentary in real time.

[1320] (Application example 2)

[1321] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1322] Conventional real-time commentary systems for gameplay provide fixed commentary phrases without considering the user's emotional state, making it difficult for users to achieve a personalized experience. It is also difficult to provide real-time commentary that responds to the game's progress and user actions. There is a need to solve these issues and provide a more engaging and personalized gaming experience.

[1323] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1324] In this invention, the server includes means for receiving input information generated from a user's input means, means for receiving game video data, means for analyzing the received input information and video data to identify the game progress status and the user's actions, means for generating commentary phrases based on the identified game status and user actions, means for converting the generated commentary phrases into voice data, means for delivering commentary data including the voice data to the user, means for recognizing the user's emotional state using the user's voice data and camera video, and means for adjusting the commentary phrases based on the recognized emotional state. This allows for personalized commentary to be provided in real time according to the user's emotional state, enabling a more engaging gameplay experience.

[1325] "User input means" refers to the devices or interfaces that a user uses to operate the game.

[1326] "Input information" is a series of data generated from the user's input means, and includes button press status, stick movement, and the like.

[1327] "Game video data" is a series of image data captured from the screen display content of the game being played by the user.

[1328] "Game progress" refers to events or states currently occurring within the game, including player progress and enemy appearances.

[1329] "User action" refers to a specific operation or movement that a user performs in the game, including attacking, moving, etc.

[1330] "Live commentary phrases" are comments and explanatory sentences that are generated based on the game progress and the user's actions.

[1331] "Voice data" refers to a series of data obtained by converting commentary phrases into voice format using voice synthesis.

[1332] "Reportage data" refers to information including text data and audio data of commentary phrases, and is provided to the user.

[1333] An "emotional state" is a user's psychological or emotional response or state, including excitement, tension, joy, and the like.

[1334] An "emotion engine" is software or algorithms that recognize a user's emotional state from voice data and camera footage.

[1335] "Analysis" is the process of processing and analyzing sets of data to extract specific information or patterns.

[1336] "Distribution" refers to the act of transferring live data, including audio data, from a server to a user's device.

[1337] MODE FOR CARRYING OUT THE INVENTION

[1338] This invention is a system that provides real-time commentary to users playing games alone to enhance their gaming experience. The system acquires and analyzes input information generated by the user's input means and game video data to generate commentary phrases that correspond to the user's actions and the game's progress. It also uses an emotion engine to recognize the user's emotional state and adjusts the commentary phrases based on that state, providing a personalized commentary experience.

[1339] Overview of program processing

[1340] 1. Acquiring and sending game data

[1341] A capture card is used to capture game footage and controller input data from the device on which the user is playing the game (e.g., game console or PC). For this purpose, a capture card such as the "Elgato HD60 S+" is used. Game footage is captured at a constant frame rate (e.g., 30 fps or more), and input data (button presses and stick movements) is captured in milliseconds. The captured data is sent to a server in real time.

[1342] 2. Data Analysis

[1343] The server analyzes the received video and input data to identify the game progress and user actions. For example, it uses the machine learning model "YOLOv4" and the image analysis library "OpenCV" to identify specific actions and events within the video data.

[1344] 3. Recognizing emotional states

[1345] The server uses the IBM Watson Tone Analyzer emotion engine to recognize the user's emotional state using the user's voice data and camera footage, making it possible to determine whether the user is excited, relaxed, or nervous.

[1346] 4. Creating and adjusting commentary phrases

[1347] The server generates commentary phrases based on the identified game progress and the user's emotional state, adjusting the phrases as needed. For example, if the user enters a boss battle, the server generates the phrase "The user has entered a boss battle!", and if the user is in an excited state, it adds a phrase such as "This is an exciting moment!".

[1348] 5. Conversion to audio data

[1349] The generated commentary phrases are converted into audio data in real time using the voice synthesis tool "Google Text-to-Speech API."

[1350] 6. Live data distribution and display

[1351] The server delivers the generated audio data and text data to the user's device, plays the audio data, and displays the text data, thereby providing the user with a commentary.

[1352] Specific examples

[1353] For example, consider a situation where a user is playing an action game and enters a boss battle. At this moment, the user's device sends game footage and input data to the server. The server uses the machine learning model YOLOv4 and the image analysis library OpenCV to analyze the boss battle. Furthermore, the IBM Watson Tone Analyzer detects excitement in the user's voice and generates commentary phrases such as the following:

[1354] "The viewer is now in a boss battle! This is an exciting moment!"

[1355] This commentary is converted into audio data using the Google Text-to-Speech API and sent to the user's device, allowing the user to experience the commentary in real time and enjoy more engaging gameplay.

[1356] Prompt Sentence Examples

[1357] "The user is about to enter the fight against Ornstein in Dark Souls. Please generate a commentary phrase to use when the user is excited."

[1358] This invention enables real-time personalized commentary during gameplay, making the user's gaming experience richer and more engaging.

[1359] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1360] Step 1:

[1361] When a user starts playing a game, the user's device (e.g., game console or PC) uses a capture card to capture game footage and controller input data. The input data includes the user's actions (button presses and stick movements), and the game footage data includes the game screen being played. This data is sent to the server in real time at regular intervals.

[1362] Input: User operation data and game video data

[1363] Output: Captured operation data and video data

[1364] Step 2:

[1365] The server analyzes the game video data and input information received in real time, and uses the image analysis library "OpenCV" and the machine learning model "YOLOv4" to identify the game progress and user actions. Specifically, it analyzes each frame of the game video and identifies important events and actions (e.g., entering a boss battle or using a special technique).

[1366] Input: Captured operational and video data

[1367] Output: Game progress and user actions

[1368] Step 3:

[1369] The server receives the user's voice data and camera footage and uses the emotion engine "IBM Watson Tone Analyzer" to recognize the user's emotional state, thereby identifying whether the user is excited or nervous.

[1370] Input: User's voice data and camera footage

[1371] Output: User's emotional state

[1372] Step 4:

[1373] Based on the analyzed game progress and user actions, the server uses a generative AI model to generate commentary phrases. Furthermore, the server adjusts the commentary phrases based on the recognized user's emotional state. For example, if the user is excited about a boss battle, the server generates a phrase such as, "The user has entered a boss battle! This is an exciting moment!"

[1374] Input: Game progress, user actions, and emotional state

[1375] Output: Adjusted commentary phrase

[1376] Step 5:

[1377] The server converts the generated commentary phrases into voice data using the speech synthesis tool "Google Text-to-Speech API." This phrase is converted into voice data in real time and prepared as voice output.

[1378] Input: Adjusted commentary phrase

[1379] Output: Live audio data

[1380] Step 6:

[1381] The server delivers the generated audio and text data to the user's device, which receives, displays, and plays it back, allowing the user to experience a real-time, personalized visual and audio commentary while playing.

[1382] Input: Live audio and text data

[1383] Output: Providing a live experience to the user

[1384] 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.

[1385] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1386] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1387] 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.

[1388] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[1389] 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.

[1390] 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).

[1391] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, 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.

[1392] 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."

[1393] 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.

[1394] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1395] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1396] 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.

[1397] 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.

[1398] 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.

[1399] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[1400] The hardware resource that executes the specific processing 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 processing may be a single processor.

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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.

[1405] The following is further disclosed regarding the above embodiment.

[1406] (Claim 1)

[1407] means for receiving input information generated from a user's input means;

[1408] means for receiving game video data;

[1409] means for analyzing the received input information and video data to identify the game progress and user actions;

[1410] means for generating commentary phrases based on the identified game situation and user actions;

[1411] A means for converting the generated commentary phrases into audio data;

[1412] means for distributing live data including audio data to a user;

[1413] A system including:

[1414] (Claim 2)

[1415] 2. The system according to claim 1, further comprising means for generating commentary phrases as text data and displaying the text data on a display device of the user.

[1416] (Claim 3)

[1417] 10. The system of claim 1, further comprising means for receiving and analyzing game video data and user input information in real time.

[1418] "Example 1"

[1419] (Claim 1)

[1420] means for receiving operation information generated by a user's operation means;

[1421] means for receiving video data of a computer program;

[1422] means for analyzing the received operation information and video data to identify the progress of the computer program and the user's actions;

[1423] means for generating commentary phrases based on the identified computer program status and user actions;

[1424] A means for converting the generated commentary phrases into audio data;

[1425] means for distributing live data including audio data to a user;

[1426] A system including:

[1427] (Claim 2)

[1428] 2. The system according to claim 1, further comprising means for generating commentary phrases as character data and displaying the character data on a display device of the user.

[1429] (Claim 3)

[1430] 10. The system according to claim 1, further comprising means for receiving and analyzing video data of the computer program and user operation information in real time.

[1431] "Application Example 1"

[1432] (Claim 1)

[1433] means for receiving input information generated from a user's input means;

[1434] means for receiving game video data;

[1435] means for analyzing the received input information and video data to identify the game progress and user actions;

[1436] means for generating commentary phrases based on the identified game situation and user actions;

[1437] A means for converting the generated commentary phrases into audio data;

[1438] means for distributing live data including audio data to a user;

[1439] means for analyzing the data transmitted to the cloud server using a machine learning model;

[1440] a means for receiving the commentary phrases generated from the cloud server and displaying the commentary phrases as text and playing them back as audio;

[1441] A system including:

[1442] (Claim 2)

[1443] 2. The system according to claim 1, further comprising means for generating commentary phrases as text data and displaying the text data on a display device of the user.

[1444] (Claim 3)

[1445] 10. The system of claim 1, further comprising means for receiving and analyzing game video data and user input information in real time.

[1446] "Example 2: Combining Emotion Engines"

[1447] (Claim 1)

[1448] means for receiving input information generated from a user's input means;

[1449] means for receiving game video data;

[1450] means for analyzing the received input information and video data to identify the game progress and user actions;

[1451] means for analyzing the user's facial expression data and voice data to identify the user's emotional state;

[1452] means for generating commentary phrases based on the identified game situation and the user's emotional state;

[1453] A means for converting the generated commentary phrases into audio data;

[1454] means for distributing live data including audio data to a user;

[1455] A system including:

[1456] (Claim 2)

[1457] 2. The system according to claim 1, further comprising means for generating commentary phrases as text data and displaying the text data on a display device of the user.

[1458] (Claim 3)

[1459] 10. The system of claim 1, further comprising means for receiving and analyzing game video data and user input information in real time.

[1460] "Application example 2 when combining emotion engines"

[1461] (Claim 1)

[1462] means for receiving input information generated from a user's input means;

[1463] means for receiving game video data;

[1464] means for analyzing the received input information and video data to identify the game progress and user actions;

[1465] means for generating commentary phrases based on the identified game situation and user actions;

[1466] A means for converting the generated commentary phrases into audio data;

[1467] means for distributing live data including audio data to a user;

[1468] means for recognizing an emotional state of a user using voice data and camera footage;

[1469] means for adjusting commentary phrases based on the recognized emotional state;

[1470] A system including:

[1471] (Claim 2)

[1472] 2. The system according to claim 1, further comprising means for generating commentary phrases as text data and displaying the text data on a display device of the user.

[1473] (Claim 3)

[1474] 10. The system of claim 1, further comprising means for receiving and analyzing game video data and user input information in real time. [Explanation of symbols]

[1475] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving input information generated from a user's input means; means for receiving game video data; means for analyzing the received input information and video data to identify the game progress and user actions; means for generating commentary phrases based on the identified game situation and user actions; A means for converting the generated commentary phrases into audio data; means for distributing live data including audio data to a user; A system including:

2. 2. The system according to claim 1, further comprising means for generating commentary phrases as text data and displaying the text data on a display device of the user.

3. 10. The system of claim 1, further comprising means for receiving and analyzing game video data and user input information in real time.

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