Electronic Arts Inc.

Electronics Arts, Inc.

Kenneth Alan Moss

Navid Aghdaie

Kazi Atif-Uz Zaman

John Kolen

Harold Henry Chaput

Mohsen Sardari

Mohamed Marwan Mattar

Su Xue

Han Liu

Jesse Hans Stokes Harder

Thomas Murray Perlinski

Graham Francis Scott

Jijnes Jashbhai Patel

Daniel Valentine Gibson

Daniel Lee Kading

John Christopher Epler

Igor Borovikov

Yiwei Zhao

Kilol Gupta

Zahra Shakeri

Meng Wu

Jervis Pinto

Qilian Yu

Mathieu Guindon

Mohamed Marwan Abdel Magid Mattar

Bhargav Rajendra

A video game includes a single player mode where completion of storyline objectives advances the single player storyline. The video game also includes a multiplayer mode where a plurality of players can play on an instance of a multiplayer map. Storyline objectives from the single player mode are selected and made available for completion to players in the multiplayer mode, and the single player storylines can be advanced by players completing respective storyline objectives while playing in the multiplayer mode. Combinations of storyline objectives are selected from pending storyline objectives for players connecting to a multiplayer game for compatibility with multiplayer maps. Constraints can be used to determine compatibility.

Dynamic modifications of single player and multiplayer mode in a video game

Embodiments of the systems and methods disclosed herein provide a sponsor matching system in which players and sponsors can be matched. Upon a match based at least in part on stored sponsorship criteria and/or player preferences, a first sponsor can select a set of players to receive permission to select an advertisement associated with the first sponsor. Once a first player of the selected players selects an advertisement and an advertisement placement location associated with the first sponsor, the sponsor matching system can generate game rendering instructions for a first player system associated with the first player.

Automated player sponsorship system

A computer-implemented method of generating speech audio in a video game is provided. The method includes inputting, into a synthesizer module, input data that represents speech content. Source acoustic features for the speech content in the voice of a source speaker are generated and are input, along with a speaker embedding associated with a player of the video game into an acoustic feature encoder of a voice convertor. One or more acoustic feature encodings are generated as output of the acoustic feature encoder, which are inputted into an acoustic feature decoder of the voice convertor to generate target acoustic features. The target acoustic features are processed with one or more modules, to generate speech audio in the voice of the player.

Generating speech in the voice of a player of a video game

Embodiments of the systems and methods described herein provide a three dimensional reconstruction system that can receive an image from a camera, and then utilize machine learning algorithms to identify objects in the image. The three dimensional reconstruction system can identify a geolocation of a user, identify features of the surrounding area, such as structures or geographic features, and reconstruct the scene including the identified features. The three dimensional reconstruction system can generate three dimensional object data for the features and/or objects, modify the three dimensional objects, arrange the objects in a scene, and render a two dimensional view of the scene.

Three dimensional reconstruction of objects based on geolocation and image data

Various aspects of the subject technology relate to systems, methods, and machine-readable media for user matchmaking. The method includes training a quality model and an embedding model based on historical data and user control options. The method also includes receiving user control options and matchmaking requests from users. The method also includes embedding, through the embedding model, user data regarding the users into an embedded space based on the received user control options and the matchmaking requests. The method also includes determining, based on the embedded user data, that a distance between two users satisfies a distance threshold. The method also includes matching the two users when the determined distance satisfies the distance threshold.

User-controllable model-driven matchmaking

Systems described herein may automatically and dynamically adjust the amount and type of computing resources usable to execute, process, or perform various tasks associated with a video game. Using one or more machine learning algorithms, a prediction model can be generated that uses the historical and/or current user interaction data obtained by monitoring the users playing the video game. Based on the historical and/or current user interaction data, future user interactions likely to be performed in the future can be predicted. Using the predictions of the users' future interactions, the amount and type of computing resources maintained in the systems can be adjusted such that a proper balance between reducing the consumption of computing resources and reducing the latency experienced by the users of the video game is achieved and maintained.

Predictive execution of distributed game engines

Embodiments of the systems and methods disclosed herein provide a request distribution system in which a request for resources may be executed by a plurality of workers. Upon receiving a request for resources from a user computing system, the request distribution system may select a subset of workers from the plurality of workers to execute the request within a time limit. Once the workers generate a plurality of outputs, each output associated with a quality level, the request distribution system may transmit the output associated with the highest quality level to the user computing system.

Request distribution system

Embodiments of the systems and methods described herein provide a virtual object aging system. The virtual object aging system can utilize artificial intelligence to modify virtual objects within a video game to age and/or deteriorate for a certain time period. The virtual object aging system can be used to determine erosion, melting ice, and/or other environmental effects on virtual objects within the game. The virtual object aging system can apply aging, rust, weathering, and/or other effects that cause persistent change to object meshes and textures.

Artificial intelligence based virtual object aging

Systems and methods for generating a customized virtual character are disclosed. A system may obtain video data or other media depicting a real person, and then may provide the obtained media to one or more machine learning models configured to learn visual appearance and behavior information regarding the particular person depicted in the video or other media. The system may then generate a custom visual appearance model and a custom behavior model corresponding to the real person, which may subsequently be used to render, within a virtual environment of a video game, a virtual character that resembles the real person in appearance and in-game behavior.

Virtual character generation from image or video data

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.

Dynamic difficulty adjustment

Systems and methods for generating a customized virtual animal character are disclosed. A system may obtain video data or other media depicting a real animal, and then may provide the obtained media to one or more machine learning models configured to learn visual appearance and behavior information regarding the particular animal depicted in the video or other media. The system may then generate a custom visual appearance model and a custom behavior model corresponding to the real animal, which may subsequently be used to render, within a virtual environment of a video game, a virtual animal character that resembles the real animal in appearance and in-game behavior.

Virtual animal character generation from image or video data

Embodiments presented herein use an audio based authentication system for pairing a user account with an audio-based periphery computing system. The audio-based authentication system allows a user to interface with the periphery device through a user computing device. The user can utilize a previously authenticated user account on the user computing device in order to facilitate the pairing of the audio-based periphery computing system with the user account.

Growing community of inventors

Redwood City, CA, United States of America

Kenneth Alan Moss