Abstract: This specification describes a method for generating audio for a video game. The method is implemented by one or more processors. The method comprises: obtaining, by one or more of the processors, acoustic feature data comprising a value for one or more audio characteristics; selecting, by one or more of the processors, a first latent embedding from a codebook of latent embeddings based upon processing the acoustic feature data using an acoustic machine learning model; and generating, by one or more of the processors, an output audio sample based upon the selected first latent embedding.

Abstract: This specification relates to methods of compression that utilise machine-learning. According to a first aspect of this specification, there is described a computer implemented method comprising: receiving, at a decoder and via a network, a first encoded representation of a set of input data and processing, by the decoder, the first encoded representation using a machine-learning decoder model to generate a first set of decoded data corresponding to the set of input data. The method further comprises processing, at the decoder, the first set of decoded data using a machine-learning encoder model to generate a second encoded representation of the set of input data. The machine-learning encoder model corresponds to an encoder-side machine-learning encoder model that was used to generate the first encoded representation. The method further comprises processing, at the decoder, the second encoded representation using the machine-learning decoder model to generate a second set of decoded data.

Abstract: Facilitating communication between computing platforms, including establishing, via a game agnostic communication service (GACS), communication with a first and a second computing platform; receiving i) first game state data associated with a first video game application executing at the first computing platform and ii) second game state data associated with a second video game application executing at the second computing platform; receiving a request to display at the first computing platform a first communication interface of the GACS; generating content for the first communication interface based at least in part on the first or the second game state data; causing to display the generated content via the first communication interface; receiving selection of one of the communication messages to transmit to the second computing platform; transmitting the selected communication message to the second computing platform for display via a second communication interface of the GACS at the second computing platfo

Abstract: A collusion detection system may detect collusion between entities participating in online gaming. The collusion detection system may identify a plurality of entities associated with and opponents within an instance of an online game, determine social data associated with the plurality of entities, determine in-game behavior data associated with the plurality of entities, and determine, for one or more pairings of the plurality of entities, respective pairwise feature sets based at least in part on the social data and the in-game behavior data. The collusion detection system may then perform anomaly detection on the respective pairwise feature sets and, in response to the anomaly detection detecting one or more anomalous pairwise feature sets, output one or more suspect pairings of the plurality of entities corresponding to the one or more anomalous pairwise feature sets as suspected colluding pairings.

Abstract: A motion capture object that includes the use of two types of markers for tracking and identifying motion capture objects within a motion capture environment. The system includes belt markers and motion capture markers. The belt markers are configured to divide the object into separate hemispheres (e.g., a first and second hemisphere). The motion capture markers in each hemisphere are positioned in different patterns. The motion capture markers in the first hemisphere are positioned in a first pattern that is unique to the first hemisphere. The motion capture markers in the second hemisphere are positioned in a second pattern that is unique to the second hemisphere.

Abstract: The present invention provides a video game development platform. More specifically, aspects of the invention relate to components of applications such as video games including the source code, graphics, sounds, and animations as well as a market place where any of the above are traded for currency, tokens, credits, or given to other people. These components can then be combined, using game editing and creation tools, to make video games. Users can create and edit games, either of their own or based on other users' preexisting games, and can share their games with others. Game components may be bought, sold, traded, or otherwise distributed through an online marketplace.

Abstract: Systems and methods for constrained physically controlled animation selection and playback include a computing system configured to execute a game application configured generate a virtual game environment comprising first and second virtual character models. The game application may identify a collision event for a first frame, between the first virtual character model and the second virtual character model, where the character models are in locomotive states. The game application may determine first and second metric(s) of the character models, and apply the metrics to a model, to determine an outcome of the collision event for a second frame. The game application may identify an animation sequence having a type of animation sequence corresponding to the determined outcome, and generate the second frame according to the identified animation sequence.

Abstract: This specification describes a computer-implemented method of predicting the appearance of a deformable object in a video game. The method comprises determining a configuration of a moveable object underlying the deformable object. Input data is inputted into a machine-learning model. The input data comprises a representation of the configuration of the moveable object. A model output is generated as output of the machine-learning model for predicting the appearance of the deformable object. Mesh and texture data for the deformable object is determined from the model output. The deformable object is rendered using the generated mesh and texture data.

Abstract: The systems and methods described herein provide for an automated photosensitivity detection system (PDS) configured to automatically execute processes for flash detection and pattern detection of a video. PDS outputs an analysis result for each type of pattern detection analysis for the video. The PDS can execute each type of pattern detection analysis independently of the other pattern detection processes. Each pattern detection process is a distinct process that can be calculated without reference to the other processes. The final analysis result can aggregate the results of each detection process executed by the PDS.

Abstract: A state system providing version agnostic centralized state management can use node graphs corresponding to virtual entities to maintain a world state among any version of a video game. As states to virtual entities change, corresponding nodes of the node graph are updated in response to the state change to account for and store the state change. As a data structure referencing, associating, and/or corresponding to virtual entities themselves, the node graph can facilitate centralized state management for a video game in a version agnostic manner. Additionally, the state system is also configured to validate node dependencies of a node graph when a corresponding change in state of a corresponding virtual entity occurs during gameplay, to avoid and/or prevent game state errors.

Abstract: The systems and methods described herein provide for an automated photosensitivity detection system (PDS) configured to automatically execute processes for flash detection and pattern detection of a video. PDS outputs an analysis result for each type of pattern detection analysis for the video. The PDS can execute each type of pattern detection analysis independently of the other pattern detection processes. Each pattern detection process is a distinct process that can be calculated without reference to the other processes. The final analysis result can aggregate the results of each detection process executed by the PDS.

Abstract: A visual anomaly detection system can test a video game under test. The testing can involve applying captured video frames to a large language model using dynamically generated prompts. The captured video frames can be obtained directly from an output port of a user computing system enabling the video frames to be applied to the machine learning model without modification and with minimal to no user intervention. Additionally, the systems disclosed herein can control the user computing system hosting the video game under test enabling the test system to react to test results in real-time or near real-time (e.g., within milliseconds, while the video game is executing, before a next action is performed with respect to the video game, and the like) and to modify the testing process as tests are being performed.

Abstract: A gaming system may provide for interactable environment geometry (IEG) detection. The gaming system may determine a sensory perspective of a sense of a non-player character (NPC) in a virtual environment of a game simulation, generate perception data of the NPC from the sensory perspective of the sense, input the perception data of the NPC into a detection model associated with the sense and receive, from the detection model, detection data for a detected item. The gaming system may then generate an awareness-based character decision for the NPC based on the detection data of the detected item.

Abstract: A method of generating a three-dimensional (3D) model includes obtaining a set of two-dimensional (2D) images of a scene acquired by one or more cameras from a set of camera angles and camera positions, obtaining the set of camera angles and camera positions based on obtaining, for each 2D image in the set of 2D images, a respective camera angle and a respective camera position for the 2D image, training a neural radiance field (NeRF) model, using the set of 2D images and the set of camera angles and camera positions as a training dataset, to obtain a trained NeRF model, generating a set of 2D depth maps based on the trained NeRF model, and generating a 3D polygonal mesh representing at least one object of one or more objects in the scene based on the set of 2D depth maps.

Abstract: A spectator system may provide for spectating in online gaming. The spectator system may receive, at a spectator server, game state data from a game simulation server hosting an online game for one or more players, generate one or more spectator game state data corresponding to one or more spectator devices and output the one or more spectator game state data to the spectator devices. The spectator server may further output the game state data to another spectator server.

Abstract: Systems and methods are provided for enhanced face shape generation for archetypes of virtual entities based on generative modeling techniques. An example method includes training models based on synthetically generated faces and information associated with an authoring system. The modeling system being trained to reconstruct face shapes for virtual entities based on a latent space embedding of a face identity associated with specific archetypes.

Abstract: A quality analysis tool for visual-programming scripting languages uses machine learning to process changes from visual-programming environments. The quality analysis tool can receive data associated with a code submission via a visual-programming scripting language, process the data to identify features in the data that correspond to previously identified defects, apply a pattern matching algorithm to the identified features, determine a risk prediction based on a learned pattern recognition model associated with a pattern in the features, and transmit a notice of predicted risk. The quality analysis tool can train models for use with visual-programming scripting languages and visual-programming environments.

Abstract: This specification describes a computer-implemented method of generating expressive speech audio for use in a video game. The method comprises receiving user-input text data and receiving prosody data obtained from user-input speech style data. The user-input text data is processed by a text encoder to generate a text feature embedding. A speech feature embedding is generated by an embedding converter based upon the text feature embedding. The prosody data is processing by a prosody encoder to generate a prosody feature embedding. A speech signal is generated by a speech decoder based upon the speech feature embedding and the prosody feature embedding.

Abstract: Implementations described herein relate to a method for predicting motion capture data implemented by a video game development system comprising one or more processors, the method including: obtaining, by one or more of the processors of the video game development system, motion capture data; the motion capture data including one or more missing values; generating, by one or more of the processors of the video game development system, a predicted value for the one or more missing values, generating a predicted value includes processing the motion capture data using one or more machine learning models to determine the predicted value.

Abstract: A party system of a gaming environment provides to users of the gaming environment parties of sizes that extend beyond the party size limitations of a video game. An extendable party can dynamically create subset parties of users for gameplay as needed, without requiring the party to be ceased. Therefore, an extendable party allows a subset of users, or multiples thereof, to enter into gameplay while maintaining the party as a whole. A party system, video game, or gaming environment can be configured to apply one or more rules or policies to a party that limit or alter a feature or function of an extended party, such as to prevent players among extended parties from providing or receiving competitive advantages.