391 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.

A method for generating broadcasts including receiving game state data and user data of players participating in a gaming session of a video game. A spectator zone-of-interest in the gaming session is identified having a scene of a virtual gaming world that is viewable from camera perspectives in the virtual gaming world. Statistics and facts are generated for the gaming session based on the game state data and the user data using a first AI model trained to isolate game state data and user data that are of interest by spectators. Narration is generated for the scene using a second AI model configured to select statistics and facts from the statistics and facts generated using the first AI model, the selected statistics and facts having a highest potential spectator interest as determined by the second AI model configured to generate the narration using the selected statistics and facts.

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 computer system is provided that enables players to play an online multiplayer game. When collisions are detected in the game, energy objects are created. These objects may be acquired by players during the game to increase a special ability meter. Activation of the special ability meter allows players to be provided with one or more benefits during the multiplayer video game. In some examples, the benefit may include moving a player object to a second track within the multiplayer racing game.

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 invention provides a method and a system for protecting a player from cheating by an automatic visual sighting device in a video game. The method comprises the following steps: acquiring each frame of the video game; superposing a pre-generated universal defense disturbance on each obtained frame, and presenting the frame superposed with the universal defense disturbance to a player of the video game; wherein the universal defense disturbance superimposed on each frame is visually invisible to a player of the video game, and an object detection model in a visual automatic sighting device during running of the video game cannot recognize a target object, so that the automatic sighting function of the visual automatic sighting device fails. According to the scheme, the automatic visual sighting device cannot accurately recognize the game target, so that the completeness of the game is ensured, legal game playing methods are not influenced, and the automatic visual sighting device can be effectively expanded in different game settings and player groups and can adapt to the dynamic characteristics of the game environment.

An intelligent personal computing and communications system including a system processor; a natural language processor operationally coupled to the system processor and implemented with software stored on a tangible medium and executed by said processor; and a user interface operationally coupled to the natural language processor for inputting requests to the natural language processor; whereby the natural language processor makes a video or a video game, activates a video game, purchases customized products, creates targeted advertisements or serves as a virtual companion.

A device may as implemented by an interactive computing system configured with specific computer-executable instructions, capturing one or more image frames of a video game, receiving, from one or more sensors, eye tracking information associated with a user playing the video game, associating the eye tracking information with the one or more image frames, identifying at least a first frame based at least in part on the eye tracking information, identifying at least one feature of interest within the first frame based on the eye tracking information, and outputting an indication associated with the at least one feature of interest.

Artificial intelligence (AI) models are disclosed to generate unique, personalized podcasts that include recommendations of other games that a particular gamer might want to play. The podcasts can present the recommendations in a voice of a video game character of a video game already played by the respective gamer.

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.

The invention relates to the technical field of video game decision making, and particularly discloses a video game decision making system based on auxiliary task learning. The method comprises the following steps: generating a structured game state vector by comprehensively collecting and fusing vision, numerical values, texts and interaction data in a game; a multi-element auxiliary task library is constructed, and an auxiliary task list with priority ranking is output after evaluation, ranking and scheduling; realizing collaborative learning of the main task and the auxiliary task through a shared-private double-branch network and a collaborative loss function, and outputting optimized decision model parameters; game operation is generated and executed based on the decision model parameters and the game state vector, and meanwhile continuous adjustment and optimization are conducted according to feedback data of the game environment. According to the method, the problem that a complex game state is difficult to comprehensively analyze in a traditional game intelligent decision is solved, the pertinence, the efficiency, the robustness and the generalization of the decision are improved, and comprehensive and powerful support is provided for video game decision.

Techniques for improving a user video game experience are described. In an example, a computer system receives event data from a plurality of user devices. Each event data includes an identifier of an activity in a video game and data indicating completion of the activity. The identifier can be predefined in program code of the video game. The identifier and completion data can be received based on an execution of the program code. The event data is processed to determine a video game mechanic suggestion to help a player complete the activity.

A system and method AI-enabled telematics and actuation for electronic entertainment, simulation, training, and remote operations systems. The system and method disclosed support neuro symbolic reasoning and generative AI enabled experience generation to allow a user or collection of users to experience a wide range of realistic scenarios where the user can pick and choose an experience that best fits their individual or collective preferences. Additionally, the system and method have wide applications to a variety of environments, including but not limited to, racing, sports, military training, vehicle and aircraft operation, and training simulations. The proposed system and method enable realistic, immersive video game, simulation, training, and remote operations environments which are applicable to a wide range of devices, platforms, and mediums for recreational, commercial, industrial, and security uses.

A vehicle gaming system for a vehicle includes one or more computing devices configured to obtain body gesture data indicative of one or more recognized poses of a user of a video game; obtain speech data indicative of one or more recognized words spoken by the user in a passenger cabin of the vehicle; generate a multimodal gaming input by combining the body gesture data and the speech data; identify one or more game commands for the video game being played from a game command datastore based on the multimodal gaming input; and transmit the one or more game commands to a remote gaming server to obtain gaming codes associated with the one or more game commands to cause the video game to perform an action associated with the one or more game commands.

Clustering models and other types of models may be used to match a first video game player that is proficient in a particular game task with a second video game player that is facing the same task. A secure communication channel between the two players may then be opened on the game network for the first player to coach the second player within the game environment.

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 spiral spring configured to bias the joystick to a neutral position; a detectable component coupled to the spiral spring; and a sensor configured to detect a position of the detectable component.

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.

Artificial intelligence (AI) models are disclosed to provide in-game AI assistants that can execute in-game tasks for human players in conformance with audible prompts from the human players during multi-player gameplay instances. The AI assistants can therefore report in-game events to help the human players and even act as additional players within the video game, controlling their own video game characters to establish virtual teammates to help the human players advance within the video game.

Artificial intelligence (AI) models are disclosed to provide in-game AI assistants that can execute in-game tasks for human players in conformance with audible prompts from the human players during single-player gameplay instances. The AI assistants can therefore report in-game events to help the human players and even act as additional players within the video game, controlling their own video game characters to establish virtual teammates to help the human players advance within the video game.

The patent discloses improved methods and systems for detecting a collision between a player controlled virtual character in a video game and an object positioned on a surface in a virtual environment of the video game. Two geometric models are defined, one of which is preferably a cylinder and the other of which is preferably a capsule. For a frame of the video game, data indicative of a position, velocity and direction of the virtual character is acquired and, in a subsequent frame, data indicative of another position of the virtual character is acquired. The first geometric model is moved vertically downward by a predefined distance to identify a level of the ground surface and the second geometric model is moved horizontally forward to detect a collision of the virtual character with the object.

Systems and methods for constructing an offline graph structure configured to enable controlled character motion synthesis in a multi-player online gaming include a graph structure that has a plurality of master nodes and edges such that each master node is representative of a set of similar dominant poses and edges are representative of plausible transitions between these dominant poses. Motion is generated at runtime by navigating through the graph structure and applying dominant poses from the plurality of master nodes. Since, an online game describes a desired motion of a character using a plurality of control parameters therefore, transitions that match the plurality of control parameters most closely are selected from the graph structure.

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 for providing a training option to improve input skills of the user include detecting selection of the training option for a video game. Responsive to the training option selection, a plurality of minigames are presented at a user interface for user selection. Each minigame is selected to include a portion of the video game that requires distinct set of input skills to progress in the video game. User selection of a minigame is detected and an executable code for the portion of the video game is instantiated for user practice of the distinct set of input skills. The input skills exhibited by the user during gameplay of the minigame is monitored to identify an amount of progress made in the portion of the video game. Updates are provided at the user interface for user interaction, based on the input skills exhibited by the user.

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.