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    SYSTEMS AND METHODS FOR AUTOMATICALLY MEASURING A VIDEO GAME DIFFICULTY
    3.
    发明申请
    SYSTEMS AND METHODS FOR AUTOMATICALLY MEASURING A VIDEO GAME DIFFICULTY 有权

    公开(公告)号：US20210093974A1

    公开(公告)日：2021-04-01

    申请号：US17068315

    申请日：2020-10-12

    申请人： Electronic Arts Inc.

    发明人： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

    IPC分类号： A63F13/67 ,  A63F13/537 ,  A63F13/822

    摘要： Embodiments of the systems and methods described herein can automatically measure the difficulty metrics associated with various aspects of a video game using an artificial intelligence system. The artificial intelligence system may include multiple game agents. Telemetry data associated with the gameplay of each game agent may be recorded while the game application is automatically executed by the game agents. The telemetry data may be communicated to a data analysis system which can calculate game difficulty metrics for various aspects of the game. The data analysis system can determine game difficulty associated with the various aspects based on the game difficulty metrics. The results from the data analysis system may be visualized and communicated to a game developer for updating the operations of the video game.

    Custom voice control of video game character
    4.
    发明授权
    Custom voice control of video game character 有权

    公开(公告)号：US10926173B2

    公开(公告)日：2021-02-23

    申请号：US16436811

    申请日：2019-06-10

    申请人： Electronic Arts Inc.

    发明人： Dhaval Hemant Shah ,  Igor Borovikov ,  Mohsen Sardari ,  John Kolen ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman

    IPC分类号： A63F13/00 ,  A63F13/424 ,  A63F13/63 ,  A63F13/215

    摘要： Systems and methods are disclosed for enabling a player of a video game to designate custom voice utterances to control an in-game character. One or more machine learning models may learn in-game character actions associated with each of a number of player-defined utterances based on player demonstration of desired character actions. During execution of an instance of a video game, current game state information may be provided to the one or more trained machine learning models based on an indication that a given utterance was spoken by the player. A system may then cause one or more in-game actions to be performed by a non-player character in the instance of the video game based on output of the one or more machine learning models.

    Systems and methods for automatically measuring a video game difficulty
    5.
    发明授权
    Systems and methods for automatically measuring a video game difficulty 有权

    公开(公告)号：US10799798B2

    公开(公告)日：2020-10-13

    申请号：US16455448

    申请日：2019-06-27

    申请人： Electronic Arts Inc.

    发明人： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

    IPC分类号： A63F13/67 ,  A63F13/537 ,  A63F13/822

    摘要： Embodiments of the systems and methods described herein can automatically measure the difficulty metrics associated with various aspects of a video game using an artificial intelligence system. The artificial intelligence system may include multiple game agents. Telemetry data associated with the gameplay of each game agent may be recorded while the game application is automatically executed by the game agents. The telemetry data may be communicated to a data analysis system which can calculate game difficulty metrics for various aspects of the game. The data analysis system can determine game difficulty associated with the various aspects based on the game difficulty metrics. The results from the data analysis system may be visualized and communicated to a game developer for updating the operations of the video game.

    Real-time audio generation for electronic games based on personalized music preferences
    6.
    发明授权
    Real-time audio generation for electronic games based on personalized music preferences 有权

    公开(公告)号：US10799795B1

    公开(公告)日：2020-10-13

    申请号：US16365417

    申请日：2019-03-26

    申请人： Electronic Arts Inc.

    发明人： John Kolen ,  Harold Henry Chaput ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman ,  Kenneth Alan Moss

    IPC分类号： A63F13/67 ,  A63F13/79 ,  A63F13/54 ,  G06F16/635 ,  G06N3/08 ,  G06N3/04

    摘要： Systems and methods are provided for real-time audio generation for electronic games based on personalized music preferences. An example method includes requesting listening history information from one or more music streaming platforms, the listening history information indicating, at least, music playlists to which a user created or is subscribed. A style preference associated with the user is determined based on the listening history information. A musical cue associated with an electronic game is accessed, with the musical being associated with music to be output by the electronic game based on a game state of the electronic game. Personalized music is generated utilizing one or more machine learning models based on the musical cue and the style preference, wherein the system is configured to provide the personalized music for inclusion in the electronic game.

    PERSONALIZED REAL-TIME AUDIO GENERATION BASED ON USER PHYSIOLOGICAL RESPONSE
    7.
    发明申请
    PERSONALIZED REAL-TIME AUDIO GENERATION BASED ON USER PHYSIOLOGICAL RESPONSE 审中-公开

    公开(公告)号：US20200313782A1

    公开(公告)日：2020-10-01

    申请号：US16365499

    申请日：2019-03-26

    申请人： Electronic Arts Inc.

    发明人： John Kolen ,  Harold Henry Chaput ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman ,  Kenneth Alan Moss

    IPC分类号： H04H60/46 ,  G06F3/16 ,  G06N3/08

    摘要： Systems and methods are provided for personalized real-time audio generation based on user physiological response. An example method includes obtaining hearing information associated with a user's hearing capabilities, the hearing information indicating one or more constraints on the user's hearing, and the hearing information being determined based on one or more hearing tests performed by the user; requesting listening history information from one or more music streaming platforms, the listening history information indicating, at least, music playlists to which a user created or is subscribed; determining, based on the listening history information, a style preference associated with the user; generating, utilizing one or more machine learning models, personalized music based on the hearing information and the style preference, wherein the personalized music comports with the constraints, and wherein the system is configured to provide the personalized music for output via a user device of the user.

    TOXICITY-BASED CHAT PERSONALIZATION WITHIN VIDEO GAMES
    8.
    发明申请
    TOXICITY-BASED CHAT PERSONALIZATION WITHIN VIDEO GAMES 审中-公开

    公开(公告)号：US20200298131A1

    公开(公告)日：2020-09-24

    申请号：US16359812

    申请日：2019-03-20

    申请人： Electronic Arts Inc.

    发明人： Jervis Pinto ,  Polina Igorevna Gouskova ,  Chetan Nagaraja Rao ,  Farah Mariam Ali ,  Mohsen Sardari ,  John Kolen ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman

    IPC分类号： A63F13/87 ,  A63F13/79

    摘要： Using user-specific prediction models, it is possible to present an individualized view of messages generated by users playing a shared instance of a video game. Further, users with different subjective views of what is offensive may be presented with different forms or annotations of a message. By personalizing the views of messages generated by users, it is possible to reduce or eliminate the toxic environment that sometimes forms when players, who may be strangers to each other and may be located in disparate locations play a shared instance of a video game. Further, the user-specific prediction models may be adapted to filter or otherwise annotate other undesirable messages that may not be offensive, such as a message generated by one user in a video game that includes a solution to an in-game puzzle that another user may not desire to read as it may spoil the challenge for the user.