Sony Interactive Entertainment Inc.

Masanori Omote

Justice Adams

Arindam Jati

Sudha Krishnamurthy

Naveen Kumar

Ashish Singh

Erik Beran

Saket Kumar

Lakshmish Kaushik

Zhenhao Ge

Marie Kitajima

Michael G Taylor

Michael Taylor

Jian Zheng

A method for building an artificial intelligence (AI) model. The method includes accessing data related to monitored behavior of a user. The data is classified, wherein the classes include an objective data class identifying data relevant to a group of users including the user, and a subjective data class identifying data that is specific to the user. Objective data is accessed and relates to monitored behavior of a plurality of users including the user. The method includes providing as a first set of inputs into a deep learning engine performing AI the objective data and the subjective data of the user, and a plurality of objective data of the plurality of users. The method includes determining a plurality of learned patterns predicting user behavior when responding to the first set of inputs. The method includes building a local AI model of the user including the plurality of learned patterns.

Private artificial intelligence (AI) model of a user for use by an autonomous personal companion

Techniques are described for training neural networks on variable length datasets. The numeric representation of the length of each training sample is randomly perturbed to yield a pseudo-length, and the samples sorted by pseudo-length to achieve lower zero padding rate (ZPR) than completely randomized batching (thus saving computation time) yet higher randomness than strictly sorted batching (thus achieving better model performance than strictly sorted batching).

Semi-sorted batching with variable length input for efficient training

Mobile and autonomous personal companion based on an artificial intelligence (AI) model for a user

A system enhances existing audio-visual content with audio describing the setting of the visual content. A scene annotation module classifies scene elements from an image frame received from a host system and generates a caption describing the scene elements. A text to speech synthesis module may then convert the caption to synthesized speech data describing the scene elements within the image frame

Scene annotation using machine learning

Graphical style modification may be implemented using machine learning. A color accommodation module receives an image frame from a host system and generates a color-adapted version of the image frame. A Graphical Style Modification module generates a style adapted video stream by applying a style adapted from a target image frame to each image frame in a buffered video stream.

Graphical style modification for video games using machine learning

Methods and systems are provided for displaying voice input of a spectator in a video game. The method includes receiving, by a server, the voice input produced by the spectator while viewing video game video of the video game. The method includes examining, by the server, the voice input to identify speech characteristics associated with the voice input of the spectator. The method includes processing, by the server, the voice input to generate a spectator video that includes text images representing the voice input of the spectator. In one embodiment, the text images are configured to be adjusted in visual appearance based on the speech characteristics of the voice input, wherein the text images are directed in a field of view of an avatar of the spectator. The method includes combining, by the server, video game video with the spectator video to produce an overlay of the text images graphically moving in toward a game scene provided by the video game video. The method includes sending, to a client device, a spectator video stream that includes the overlay of the text images.

In-game visualization of spectator feedback

Accommodation for color or visual impairments may be implemented by selective color substitution. A color accommodation module receives an image frame from a host system and generates a color-adapted version of the image frame. The color accommodation module may include a rule based filter that substitutes one or more colors within the image frame with one or more corresponding alternative colors.

Textual annotation of acoustic effects

A chatbot learns a person's related 'intents' when asking for information and thereafter, in response to an initial query, which the chatbot answers, the chatbot generates a secondary dialogue, either providing the person with additional information or inquiring as to whether the person wishes to know more about a subject. The chatbot may use an external trigger such as time, event, etc. and automatically generate a query or give information to the person without any initial query from the person.

Automatic dialogue design

Graphical style modification may be implemented using machine learning. A color accommodation module receives an image frame from a host system and generates a color-adapted version of the image frame. A Graphical Style Modification module receives a first image frame from a host system and applies a style adapted from a second image frame to the first image frame to generate a style adapted first image frame.

Color accommodation for on-demand accessibility

A head mounted display (HMD) including a lens of optics configured for viewing virtual reality (VR) content. The HMD includes a display screen disposed behind the lens of optics such that the lens of optics is between the display screen and an eye of a user when the HMD is worn by the user, wherein the display screen is configured for rendering the VR content. The HMD includes a support structure configured to fit around a head of the user when worn, wherein the lens of optics and display screen is disposed within the support structure such that the display screen is located in front of the eye when the HMD is worn. The HMD includes a heating component disposed in the support structure, wherein the heating component is controllable to provide heat in response to an environmental cue in the VR content displayed on the display screen.

Growing community of inventors

Half Moon Bay, CA, United States of America

Masanori Omote