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    AI MODELING FOR VIDEO GAME COACHING AND MATCHMAKING
    122.
    发明申请
    AI MODELING FOR VIDEO GAME COACHING AND MATCHMAKING 有权

    公开(公告)号：US20240424408A1

    公开(公告)日：2024-12-26

    申请号：US18819278

    申请日：2024-08-29

    Applicant: Sony Interactive Entertainment Inc.

    Inventor： Javier Fernandez Rico ,  Michael Taylor ,  Glenn Black

    IPC: A63F13/67 ,  A63F13/798 ,  G06F18/214 ,  G06F18/24 ,  G06N3/08

    Abstract: A method is provided, including: recording gameplay data from one or more sessions of a video game, the one or more sessions defined for interactive gameplay of a user; training a machine learning model using the gameplay data, wherein the training configures the machine learning model to imitate the interactive gameplay of the user; after the training, exposing the machine learning model to one or more scenarios of the video game, such that the machine learning model generates gameplay decisions in response to the one or more scenarios; evaluating the gameplay decisions of the machine learning model in response to the one or more scenarios to determine one or more descriptive features of the user's gameplay; using the determined descriptive features of the user's gameplay to provide a recommendation to the user.

    TRANSFORMING COMPUTER GAME AUDIO USING IMPULSE RESPONSE OF A VIRTUAL 3D SPACE GENERATED BY NERF INPUT TO A CONVOLUTIONAL REVERBERATION ENGINE
    124.
    发明公开
    TRANSFORMING COMPUTER GAME AUDIO USING IMPULSE RESPONSE OF A VIRTUAL 3D SPACE GENERATED BY NERF INPUT TO A CONVOLUTIONAL REVERBERATION ENGINE 审中-公开

    公开(公告)号：US20240236608A1

    公开(公告)日：2024-07-11

    申请号：US18151430

    申请日：2023-01-07

    Applicant: Sony Interactive Entertainment Inc.

    Inventor： Michael Taylor

    IPC: H04S7/00 ,  G06T15/20

    CPC classification number: H04S7/305 ,  G06T15/205

    Abstract: A 3D neural radiance field (NeRF) is used to generate an impulse response (IR) characterization, which can then be input to a convolutional reverberation engine to create an audio experience that reflects the in-game world on a 2.0 stereo speaker system. The NeRF recreates a background geometry and the impulse response of a virtual 3D space generated using NeRF is input to the convolutional reverberation engine to transform game sounds/music to appear as though they are occurring inside the 3D space of the game. The same may be done for the player's real-world space in which the virtual IR and real IR are blended together in real-time, and the real-life player tracked as he moves around the room to create audio as it would sound were the player moving through the virtual space while adjusting for the acoustics of the real space.

    AVATAR GENERATION AND AUGMENTATION WITH AUTO-ADJUSTED PHYSICS FOR AVATAR MOTION
    125.
    发明公开
    AVATAR GENERATION AND AUGMENTATION WITH AUTO-ADJUSTED PHYSICS FOR AVATAR MOTION 审中-公开

    公开(公告)号：US20240233231A1

    公开(公告)日：2024-07-11

    申请号：US18095501

    申请日：2023-01-10

    Applicant: Sony Interactive Entertainment Inc.

    Inventor： Michael Taylor

    IPC: G06T13/40 ,  A63F13/57 ,  A63F13/63 ,  G06F3/04845

    CPC classification number: G06T13/40 ,  A63F13/57 ,  A63F13/63 ,  G06F3/04845 ,  G06T2200/24

    Abstract: A method including accessing an avatar including a plurality of physiological characteristics, wherein the avatar includes a plurality of motion profiles. The method including receiving editing of a motion profile of the avatar via a user interface. The method including modifying each of the plurality of motion profiles to be consistent with the motion profile that edited. The method including automatically generating a prompt to apply the motion profile that is edited to the avatar, wherein the prompt is provided as input for an image generation artificial intelligence system configured to implement latent diffusion. The method including generating a sequence of video frames using the image generation artificial intelligence system showing the avatar in motion based on the motion profile that is edited. The method including presenting the sequence of video frames in the user interface.

    USE OF MACHINE LEARNING TO TRANSFORM SCREEN RENDERS FROM THE PLAYER VIEWPOINT
    128.
    发明公开
    USE OF MACHINE LEARNING TO TRANSFORM SCREEN RENDERS FROM THE PLAYER VIEWPOINT 审中-公开

    公开(公告)号：US20240001239A1

    公开(公告)日：2024-01-04

    申请号：US17810556

    申请日：2022-07-01

    Applicant: Sony Interactive Entertainment Inc.

    Inventor： Michael Taylor ,  Glenn Black ,  Celeste Bean ,  Sergey Bashkirov

    IPC: A63F13/57 ,  G06N20/00 ,  G06T15/20

    CPC classification number: A63F13/57 ,  G06N20/00 ,  G06T15/20

    Abstract: Machine learning is used to transform screen renders from the viewpoint of the player's character to be from the viewpoint of other non-player characters (NPC) in the room. One or more neural networks are trained using game images captured during a human play session, and then subsequently the neural networks are used to create realistic video from the NPC viewpoints. To avoid rendering multiple viewpoints simultaneously, a single viewpoint is rendered, and neural networks are used to transform it for the viewpoints of other NPCs in the area. A group of NPCs may be treated as a batch and a single viewpoint transformed to multiple viewpoints in a single inference pass. For cloud gaming the game video can be rendered/sent immediately for the player but the actions of the NPCs are delayed for a frame while the neural network generates the behavior.

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