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公开(公告)号：US12138543B1
公开(公告)日：2024-11-12
申请号：US17248336
申请日：2021-01-20
Applicant: Electronic Arts Inc.
Inventor： Wolfram Sebastian Starke , Yiwei Zhao , Mohsen Sardari , Harold Henry Chaput , Navid Aghdaie , Kazi Atif-Uz Zaman
Abstract: Systems and methods are provided for enhanced animation generation based on generative control models. An example method includes accessing an autoencoder trained based on character control information generated using motion capture data, the character control information indicating, at least, trajectory information associated with the motion capture data, and the autoencoder being trained to reconstruct, via a latent feature space, the character control information. First character control information associated with a trajectory of an in-game character of an electronic game is obtained. A latent feature representation is generated and the latent feature representation is modified. A control signal is output to a motion prediction network for use in updating a character pose of the in-game character.
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公开(公告)号：US11830121B1
公开(公告)日：2023-11-28
申请号：US17305214
申请日：2021-07-01
Applicant: Electronic Arts Inc.
Inventor： Wolfram Sebastian Starke , Yiwei Zhao , Mohsen Sardari , Harold Henry Chaput , Navid Aghdaie
IPC: G06T13/40 , G06T15/50 , G06T7/73 , G06N3/02 , A63F13/573
CPC classification number: G06T13/40 , A63F13/573 , G06N3/02 , G06T7/75 , G06T15/503 , A63F2250/1094 , A63F2300/646 , A63F2300/6607
Abstract: In some embodiments, the dynamic animation generation system can provide a deep learning framework to produce a large variety of martial arts movements in a controllable manner from unstructured motion capture data. The system can imitate animation layering using neural networks with the aim to overcome challenges when mixing, blending and editing movements from unaligned motion sources. The system can synthesize movements from given reference motions and simple user controls, and generate unseen sequences of locomotion, but also reconstruct signature motions of different fighters. For achieving this task, the dynamic animation generation system can adopt a modular framework that is composed of the motion generator, that maps the trajectories of a number of key joints and root trajectory to the full body motion, and a set of different control modules that map the user inputs to such trajectories.
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公开(公告)号：US20230061250A1
公开(公告)日：2023-03-02
申请号：US17463754
申请日：2021-09-01
Applicant: Electronic Arts Inc.
Inventor： Han Liu , Jingwen Liang , Schaefer Mitchell , Mohsen Sardari
Abstract: This specification describes a computer-implemented generative interior design method. The method comprises obtaining input data comprising boundary data. The boundary data defines a boundary of an interior region of a video game building. A floor plan for the interior region of the video game building is generated. This comprises processing the input data using a floor plan generator model. The floor plan divides the interior region into a plurality of interior spaces. A layout for at least one of the plurality of interior spaces defined by the floor plan is generated by a layout generator model comprising one or more graph neural networks. The layout represents a configuration of one or more objects to be placed in the interior region.
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公开(公告)号：US11521594B2
公开(公告)日：2022-12-06
申请号：US17094601
申请日：2020-11-10
Applicant: ELECTRONIC ARTS INC.
Inventor： Kilol Gupta , Tushar Agarwal , Zahra Shakeri , Mohsen Sardari , Harold Henry Chaput , Navid Aghdaie
IPC: G10L13/047 , G10L13/08
Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.
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公开(公告)号：US11413541B2
公开(公告)日：2022-08-16
申请号：US16891723
申请日：2020-06-03
Applicant: Electronic Arts Inc.
Inventor： Jesse Harder , Harold Chaput , Mohsen Sardari , Navid Aghdaie , Kazi Zaman
Abstract: According to an aspect of this specification, there is described a computer implemented method comprising: receiving input data, the input data comprising data relating to a user of a computer game; generating, based on the input data, one or more candidate challenges for the computer game; determining, using a machine-learned model, whether each of the one or more of the candidate challenges satisfies a threshold condition, wherein the threshold condition is based on a target challenge difficultly; in response to a positive determination, outputting the one or more candidate challenges that satisfy the threshold condition for use in the computer game by the user.
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Patent Agency Ranking
公开(公告)号：US11161044B2
公开(公告)日：2021-11-02
申请号：US16404563
申请日：2019-05-06
Applicant: Electronic Arts Inc.
Inventor： Navid Aghdaie , John Kolen , Mohamed Marwan Mattar , Mohsen Sardari , Su Xue , Kazi Atif-Uz Zaman
IPC: A63F13/67 , A63F13/5375 , A63F13/285
Abstract: Embodiments of the present disclosure provide a tutorial system that can aid a user in performing various game commands in response to different game states in a virtual game environment. As the user plays the game, various game states may be encountered. A tutorial engine may, based on a current game state, determine one or more game commands to be recommended to the user, based on historical information of the user and a game state model, wherein the game state model maintains associations between game states and different segments of users. The user is recommended relevant game commands during the normal course of gameplay, based on their own gameplay history and on game commands commonly performed by other users of the game application.
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7.发明授权公开(公告)号：US11110353B2
公开(公告)日：2021-09-07
申请号：US16507864
申请日：2019-07-10
Applicant: Electronic Arts Inc.
Inventor： Caedmon Somers , Jason Rupert , Igor Borovikov , Ahmad Beirami , Yunqi Zhao , Mohsen Sardari , John Kolen , Navid Aghdaie , Kazi Atif-Uz Zaman
Abstract: System and methods for utilizing a video game console to monitor the player's video game, detect when a particular gameplay situation occurs during the player's video game experience, and collect game state data corresponding to how the player reacts to the particular gameplay situation or an effect of the reaction. In some cases, the video game console can receive an exploratory rule set to apply during the particular gameplay situation. In some cases, the video game console can trigger the particular gameplay situation. A system can receive the game state data from many video game consoles and train a rule set based on the game state data. Advantageously, the system can save computational resources by utilizing the players' video game experience to train the rule set.
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公开(公告)号：US20210086083A1
公开(公告)日：2021-03-25
申请号：US17064040
申请日：2020-10-06
Applicant: Electronic Arts Inc.
Inventor： Navid Aghdaie , John Kolen , Mohamed Marwan Mattar , Mohsen Sardari , Su Xue , Kazi Atif-Uz Zaman , Kenneth Alan Moss
Abstract: Embodiments of systems presented herein may perform automatic granular difficulty adjustment. In some embodiments, the difficulty adjustment is undetectable by a user. Further, embodiments of systems disclosed herein can review historical user activity data with respect to one or more video games to generate a game retention prediction model that predicts an indication of an expected duration of game play. The game retention prediction model may be applied to a user's activity data to determine an indication of the user's expected duration of game play. Based on the determined expected duration of game play, the difficulty level of the video game may be automatically adjusted.
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公开(公告)号：US10940396B2
公开(公告)日：2021-03-09
申请号：US16359812
申请日：2019-03-20
Applicant: Electronic Arts Inc.
Inventor： Jervis Pinto , Polina Igorevna Gouskova , Chetan Nagaraja Rao , Farah Mariam Ali , Mohsen Sardari , John Kolen , Navid Aghdaie , Kazi Atif-Uz Zaman
Abstract: 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.
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公开(公告)号：US10940393B2
公开(公告)日：2021-03-09
申请号：US16460871
申请日：2019-07-02
Applicant: Electronic Arts Inc.
Inventor： Caedmon Somers , Jason Rupert , Igor Borovikov , Ahmad Beirami , Yunqi Zhao , Mohsen Sardari , Harold Henry Chaput , Navid Aghdaie , Kazi Atif-Uz Zaman
Abstract: Systems and methods are disclosed for training a machine learning model to control an in-game character or other entity in a video game in a manner that aims to imitate how a particular player would control the character or entity. A generic behavior model that is trained without respect to the particular player may be obtained and then customized based on observed gameplay of the particular player. The customization training process may include freezing at least a subset of layers or levels in the generic model, then generating one or more additional layers or levels that are trained using gameplay data for the particular player.
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