208 results about "Video game" patented technology

The disclosed concepts relate to training a machine learning model to provide help sessions during a video game. For instance, prior video game data from help sessions provided by human users can be filtered to obtain training data. Then, a machine learning model can be trained using approaches such as imitation learning, reinforcement learning, and / or tuning of a generative model to perform help sessions. Then, the trained machine learning model can be employed at inference time to provide help sessions to video game players.

The disclosed concepts relate to automatically identifying conditions in a video game to trigger a help session. When a help session is triggered, another video game player or machine learning model can temporarily take over for the current video game player until an ending condition is reached. Help session triggering can be designated by evaluation of prior gameplay data of other video game players to identify in-game conditions that may tend to cause user disengagement, such as in-game conditions that are associated with difficult in-game goals or negative in-game consequences.

The disclosed concepts relate to providing help sessions for video game players. For instance, a help session starting state can be obtained from a video game session by a particular video game player. The help session starting state can be loaded into a help session. During the help session, inputs received from a client device of a video game helper can be directed to the help session. After the help session, an updated help session state can be obtained. In some cases, the particular video game player can choose to accept the updated help session state and proceed with video game play from that state. In other cases, the particular video game player can choose to reject that state and return back to the help session starting state.

The disclosed concepts relate to managing help sessions within a video game based on age information associated with a video game player. For example, systems and associated methods scan perform age-based restriction of a help session using a variety of techniques. For instance, automated helpers can be selected for help sessions involving children, or messaging between a human helper and a child can be restricted using a range of communication techniques described herein.

The disclosed concepts relate to managing help sessions in video games. A system or method receives control inputs from a helper during a help session in a video game. The system or method obtains a game state of the video game and determines whether to provide the control inputs to the video game based on the game state. In at least one instance, the system or method at least temporarily prevents the video game from receiving a particular control input.

A technique for generating, from a video from a computer game, a three-dimensional (3D) representation of space in which Gaussians represent objects in the video. Metadata from the game can be used in creating the 3D representation. User-input content such as a hand-drawn game path is inserted into the 3D representation of space and aligned and scaled. The opacity of the Gaussians in the 3D representation of space is then set to zero such that Gaussians representing objects in the video are transparent and only one or more portions of the user-input content are not transparent. The 3D representation of space is then combined with the video so that the user-input content is presented with the video and animated according to the metadata.

The disclosed concepts relate to tracking and representing help sessions for video games where video game players are assisted by a helper, e.g., another video game player and / or a trained machine learning model. For instance, the disclosed implementations can graphically modify a controllable entity, such as a character or vehicle, to convey that the current video game player is being assisted by a helper. As another example, the disclosed implementations can graphically modify game achievements to indicate when a given achievement was earned with assistance from a helper.

This specification provides a computer-implemented method for generating facial animation data. The facial animation data animates a face in a video game in accordance with speech sounds and speech emotion of speech audio. Speech audio data representing the speech audio is processed using a machine-learned speech emotion recognition model. One or more emotion representations that represent the emotion of the speech audio are generated. For each of the one or more emotion representations, a respective conditioning input for a facial animation generative model is determined. Facial animation data for the speech audio data is generated, comprising processing, using the facial animation generative model: (i) input data derived from the speech audio data, and (ii) the one or more conditioning inputs.

Systems, devices, methods, and machine-readable media configured to provide voice synthetization in a multiplayer video game are provided. A system can include a multiplayer video game including a character selection interface through which a player selects a character to represent them in playing the video game, and a voice model trained to convert audio from the player directly into audio in a voice of the character and provide an output that includes the audio in the voice of the character.

A method includes accessing game state data for a game play of a video game. The method including executing an artificial intelligence (AI) model using the game state data to identify key events in the game play. The method including executing the AI model using the game state data to curate a storyline for a video recapping the game play for a selected duration. The method including executing the AI model using the game state data to select and arrange scenes from the game play following the storyline, wherein each scene includes video frames from the game play. The method including regenerating the scenes using the game state of the game play. The method including executing the AI model to generate the video recapping the game play including the scenes arranged to follow the storyline. The method including displaying the video recapping the game play in a user interface.

In an interactive media system, for example, in a video game or extended reality (XR) environment, interactive media event information may be received. An interactive media satisfaction value may be determined based on one or more interactive media events received. For example, the event may be scoring a point by the user. When the interactive media satisfaction value is determined to be high, supplemental content with more upbeat themes may be selected for display in the interactive media user interface, while supplemental content with more negative themes, or more comfort-oriented or escapist themes may be selected when the satisfaction value is low. A user engagement metric may also be determined and used for timing, locating, and selecting a mode for presenting the supplemental content.

A device may access a feature vector generated based on interactions by a user with a video game. The device may access a cluster map comprising a mapping of user clusters, wherein each location within the cluster map is associated with a set of users whose feature vectors are within a threshold degree of similarity of each other. The cluster map may be generated using a plurality of extracted feature vectors obtained from interaction information. A device may determine a map location within the cluster map associated with the user based at least in part on the feature vector. A device may determine a target map location within the cluster map. A device may determine a guidance action based at least in part on the target map location and the map location associated with the user. A device may execute the guidance action.

Methods and systems are provided for generating chat communication in a video game. One method includes accessing a gameplay database that includes dialog scripts from player interactions occurring during interactive scenarios of a cooperative video game. The method includes processing the dialog scripts to extract chat words between real players during the cooperative video game and labeling the chat words to correlate the chat words to one or more interactive scenarios and correlate the chat words to a game context, wherein over time an artificial intelligence (AI) model is trained using the chat words that are labeled to learn contextually relevant chat words for the cooperative video game. The method includes identifying a non-player character (NPC), during an instance of gameplay of the cooperative video game, the NPC is present in the cooperative video game while an avatar of a real player is present in a scene of the cooperative video game. The method includes generating one or more NPC chat words for the NPC using the AI model, the NPC chat words being audible to the real player.

Systems and methods for customizing a video game to a player defined time period include content units of the video game that are selected based on at least one of multiple pre-defined criteria. Content units are then edited to fit into the player defined time period. Game gear required for playing the selected content units is determined. The edited content units and the selected game gear are provided to the player to play within the player defined time period.

Systems and techniques are described herein for a human-machine interface. For instance, an apparatus for a human-machine interface is provided. The apparatus may include a body and a joystick coupled to the body, the joystick comprising: a planar spring configured to bias the joystick to a neutral position; a detectable component coupled to the planar spring; and a sensor configured to detect a position of the detectable component.

Methods and systems are provided for providing assistance for players during game amusement of a video game. The method includes executing a video game for a game session. The player controls a player character during the game session. The method includes detecting a selection of ghost assistance for the game session. The method includes linking or connecting the game session with an Assisted Artificial Intelligence (AI) engine. The assist AI engine operates to provide ghost assist to the player according to a mode setting. The ghost assistance is provided via a ghost role. The method includes rendering the ghost role during the game session to perform an interactive action in the game. The interactive action is generated in response to a control input generated by the secondary AI engine. The interactive action of the ghost role is configured to cause the ghost role to progress along an interactive path of the game.

A computer-implemented method for generating a machine-learned inverse rig model. The machine-learned inverse rig model outputs rig parameters for a facial animation rig used to generate animations of facial expressions in video games. The method comprises receiving one or more training examples. Each training example comprises target mesh data for a face portraying a particular facial expression. For each training example, predicted rig parameters are generated using an inverse rig model, comprising processing the target mesh data of the training example. Predicted mesh data is generated, comprising processing the predicted rig parameters using a forward rig model. A loss is determined, comprising performing a comparison between the predicted mesh data and the target mesh data. The inverse rig model is trained, comprising updating parameters of the inverse rig model based on the losses of one or more training examples.

Aspects of the subject disclosure may include, for example: obtaining training data associated with a video game player, where the training data is indicative of control inputs provided by the video game player during a course of playing a plurality of video games; receiving, via a communications network from a user device of the video game player, current data indicative of current control inputs being provided by the video game player during a course of playing a current video game; determining, based at least in part upon the training data and the current data, that the video game player is currently behaving irregularly as compared to behavior indicated by the training data; and responsive to the determination being that the video game player is currently behaving irregularly as compared to the behavior indicated by the training data, initiating a communication to a third-party requesting intervention. Other embodiments are disclosed.

Methods, systems, and devices that support a dynamic screen refresh rate are described. An electronic device may dynamically (e.g., autonomously, while operating) adjust the rate at which a screen is refreshed, such as to balance considerations such as user experience and power consumption by the electronic device. For example, the electronic device may use an increased refresh rate when executing applications for which user experience is enhanced by a higher refresh rate and may use a decreased refresh rate when executing other applications. As another example, the electronic device may use different refresh rates while executing different portions of the same application, as some aspects of an application (e.g., more intense portions of a video game) may benefit more than others from a higher refresh rate. The electronic device may also account of rother factors, such as battery level, when setting or adjusting the refresh rate of the screen.

1. Name of this design product: Racing game simulator stand body. 2. Purpose of this design: A bracket for the cockpit of video games and racing simulators. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1. 5. Other situations requiring explanation: The part covered by the red semi-transparent layer in the picture is not part of the part claimed for protection in this design.

Implementations disclosed herein are directed to a method for predicting motion capture data implemented by a video game development system including one or more processors. The method can include: obtaining, by one or more of the processors of the video game development system, motion capture data; the motion capture data can include 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 can include processing the motion capture data using one or more machine learning models to determine the predicted value.

Techniques disclosed herein pertain to improving end user video game console experiences. Particularly, techniques are disclosed herein for controller-driven video game console login. In some examples, operating a video game controller includes receiving a first notification from a video game console. The first notification can indicate that a login event has occurred at the video game console. Based on the first notification, it can be detected that an electronic device is within a predetermined distance from the video game controller and a signal can be emitted from the video game controller. A second notification can be received from the electronic device, where the second notification indicates that the signal was received by the electronic device. Based on the second notification, a login credential for a video game player can be obtained and transmitted from the video game controller to the video game console.

A method and system for improving a resolution of an image frame is described. The image frame is part of a data stream. The data stream may be a video game, for example. The method comprising the following steps. Sending an encoded version of the image frame from a server to a client device via a first communication channel between the server and the client device. Detecting a reduced bandwidth of the first communication channel. In response to detecting the reduced bandwidth, determining data to be sent to the client device via a second communication channel. The second communication channel is separate to the first communication channel and the data relates to the image frame. The determined data is sent via the second communication channel.

A system for managing the execution of a plurality of video game instances at a server in response to inputs from a single client device, the system comprising an input receiving unit which receives a

Systems and methods are described for imparting dynamic, non-linear and realistic movement and look and feel to a player's / virtual character's first-person limbs and hand-held object model, and procedurally animating a first-person virtual camera such that it simulates the movement of a camera handheld by the player / virtual character. To impart chaotic or random motion to the first-person limbs and hand-held object model a first module defines and implements first and second two dimensional mass-spring-damper systems, each of which is linked to the player's / virtual vector's view vector. Procedural animation or rotational shake is implemented by a second module by applying a coherent noise function to each of the six axes of the first-person virtual camera.

The present application relates to a kind of cognitive function evaluation and intervention method based on spatial navigation video game, the method includes: obtaining user identity information to establish file;Present three-dimensional virtual environment with first person view, execute route repetition and backtracking task and record direction selection accuracy;According to weighted formula, calculate comprehensive score, compare with preset threshold and output cognitive state discrimination result;According to the real-time performance of user, dynamically adjust path complexity and moving speed, form personalized training;After completing training, evaluate again, generate post-intervention discrimination result;Record and show score change trend and difficulty progression trajectory.The present application integrates screening and intervention, through objective behavior data and adaptive algorithm, can effectively distinguish healthy elderly people and mild cognitive impairment elderly people, and improve cognitive function through personalized training, provides efficient digital solution for elderly cognitive health management.

Methods are provided for automatically generating filler content for a video game. A first collection of game play state data of a video game is accessed. A first video game output corresponding to the first collection of game play state data is also accessed. A second collection of game play state data of the video game is also accessed. A second video game output corresponding to the second collection of game play state data is also accessed. An artificial intelligence (AI) system is executed to automatically generate video game filler content that fills a content gap between the first video game output and the second video game output in accordance with a target filler content specification. The AI system is configured to use the first collection of game play state data and the second collection of game play state data as inputs for generation of the video game filler content.

Systems, devices, methods, and machine-readable media configured to provide voice inference in a video game are provided. A video game system can include an encoder configured to generate a first encoding representative of physical characteristics of a specified entity, a similarity operator configured to determine similarity values between (i) corresponding stored encodings of multiple characters, the stored encodings representative of physical characteristics of respective characters of the multiple characters and (ii) the first encoding, identify a selected character from the multiple characters based on the similarity values, and provide an identifier of the selected character, a voice database configured to provide audio or a spectrogram of the selected character, and a video game configured to provide the audio of a player-selected character in a voice of the selected character.

A data processing apparatus comprising circuitry configured to: execute a machine learning, ML, model configured to receive, as an input, a game state of a video game and first virtual physiological data indicative of a first virtual physiological state of an agent of the video game, and generate, as an output, a probability of each of a plurality of actions of the agent and second virtual physiological data indicative of a second, subsequent, virtual physiological state of the agent; and perform reinforcement learning to generate a policy for completion of a task by the agent, the reinforcement learning comprising, for each of a plurality of attempts at the task by the agent, executing one or more successive iterations of the ML model and, for each attempt, controlling the agent to perform a different respective set of actions based on the output probability of each of the plurality of actions at each of the one or more successive iterations.