ARTIFICIAL INTELLIGENCE DETERMINED EMOTIONAL STATE WITH DYNAMIC MODIFICATION OF OUTPUT OF AN INTERACTION APPLICATION

    公开(公告)号:US20250010180A1

    公开(公告)日:2025-01-09

    申请号:US18591752

    申请日:2024-02-29

    Abstract: A method including receiving an input from a user for an interaction application that is executing. The method including receiving a first plurality of multimodal cues from a plurality of trackers, wherein each of the plurality of trackers is configured to track a corresponding cue using artificial intelligence. The method including providing the first plurality of multimodal cues to an artificial intelligence (AI) model configured to classify one or more emotions of a user, wherein the AI model generates a first predicted emotion based on the first plurality of multimodal cues. The method including determining a modification to content generated by the interaction application in response to the input, wherein the modification to the content is determined based on the predicted emotion. The method including providing the modification to the interaction application, wherein the interaction application is configured to generate modified content based on the modification.

    SYSTEMS AND METHODS FOR ENABLING COMMUNICATION BETWEEN USERS

    公开(公告)号:US20240367060A1

    公开(公告)日:2024-11-07

    申请号:US18593580

    申请日:2024-03-01

    Abstract: Systems and methods for enabling communication between users are described. One of the methods includes receiving, via a computer network, data regarding a plurality of real gestures made by a first user via a first user account. The data regarding the plurality of real gestures is received from a client device. The method further includes determining, from the data, whether a speed of occurrence of the plurality of real gestures is greater than a predetermined speed. After determining that the speed of occurrence of the plurality of real gestures is greater than the predetermined speed, the method includes determining one or more meanings of a combination of the plurality of real gestures. The method includes communicating the one or more meanings of the combination via a virtual avatar, controlled by the first user via the first user account, to a second user.

    CONTEXTUAL SCENE ENHANCEMENT
    35.
    发明公开

    公开(公告)号:US20240024783A1

    公开(公告)日:2024-01-25

    申请号:US17870546

    申请日:2022-07-21

    CPC classification number: A63F13/53 A63F13/69 A63F13/54

    Abstract: Certain aspects of the present disclosure include systems and techniques for generating content that indicates a sensation associated with audio. One example method generally includes monitoring audio to be played during display of an associated portion of an interactive content stream provided over a communication network to at least one viewing device during an interactive session, and analyzing, via a machine learning component, the audio to determine a sensation associated with at least a portion of the audio. The method may also include determining an effect indicating the sensation, wherein the effect is associated with one or more output devices associated with the at least one viewing device, and outputting an indication of the effect to the associated output devices, wherein the effect is configured to be output along with the audio in real-time with the display of the associated portion of the interactive content stream.

    Handwriting recognition using cardinal directions between sample points

    公开(公告)号:US11471765B2

    公开(公告)日:2022-10-18

    申请号:US17107202

    申请日:2020-11-30

    Abstract: A computer simulation controller such as a PlayStation® Dual Shock® computer game controller has a touchpad to input text with a “palm graffiti” or “unistrokes” type alphabet. As each letter is drawn, it is saved as a file such as a postscript file which is basically a story of the cursor coordinates (started at (1,1) move to (1,3) etc. From there, plural (e.g., fifteen (15)) coordinates (even distribution) are sampled across the set of coordinates to obtain the cardinal directions (N, NE, E, etc.) between them, which are encoded for data processing.

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