Yahoo! Inc.

Interval Research Corporation

Google Inc.

Interval Licensing LLC

Microsoft Technology Licensing, LLC

Vulcan Patents LLC

Yahoo Assets LLC

Excalibur Ip, LLC

Apple Inc.

X Development LLC

Oath Inc.

Iyo Inc.

Malcolm G Slaney

Michele Mae Covell

Steven E Saunders

William MacDonald White

Richard Francis Lyon

Ricardo Antonio Garcia

Kilian Quirin Weinberger

Bonnie M Johnson

J Thomas Ngo

Annarosa Tomasi

Brian Kemler

Justin Wooyoung Lee

Arun Ramanujapuram

Paul A Freiberger

Arthur Rothstein

Gavin Miller

Marc Eliot Davis

Dilek Zeynep Hakkani-Tur

Larry Paul Heck

Todd Beaupre

Andreas Stolcke

Jason Rugolo

Steven Horowitz

Fethiye Asli Celikyilmaz

William Woods

Eric M Gottschalk

Anna Prokofieva

Deepak Agarwal

Philippe P Piernot

Lyndon Kennedy

Geoffrey G Zweig

Michael Spiegelman

Bee-Chung Chen

Ian C Rogers

Srinivasan H Sengamedu

Aren Jansen

Satish Menon

Sriram Jayaprakash Sathish

Marcos R Vescovi

Robert L Adams

Dennis M DeCoste

Andres Hernandez Schafhauser

Annarosa Tomasai

Killian Quirin Weinberger

Matthew B Humphries

Gavin S P Miller

Eric D Scheirer

Christopher Pal

Marc Aurelio Ranzato

Daniel Naar

Eva Hoerster

Kaushal Kurapati

Polly Ng

Sree Harsha Yella

A method of generating congruous metadata is provided. The method includes receiving a similarity measure between at least two multimedia objects. Each multimedia object has associated metadata. If the at least two multimedia objects are similar based on the similarity measure and a similarity threshold, the associated metadata of each of the multimedia objects are compared. Then, based on the comparison of the associated metadata of each of the at least two multimedia objects, the method further includes generating congruous metadata. Metadata may be tags, for example.

Generating congruous metadata for multimedia

A method includes providing, for each respective audio channel of a plurality of audio channels provided by an operating system of a computing device, a set of successive audio processing stages to apply to the respective audio channel. The method also includes providing, by the operating system, an application programming interface (API) configured to set a plurality of parameters for adjusting the set of successive audio processing stages for each respective audio channel. The method additionally includes receiving, via the API and from an application running on the computing device, one or more values for one or more parameters of the plurality of parameters. The method further includes adjusting, by the operating system, the plurality of audio channels based on the received one or more values for the one or more parameters.

Dynamics processing effect architecture

Generally, the present disclosure is directed to systems and methods that train machine-learned models (e.g., artificial neural networks) to perform perceptual or cognitive task(s) based on biometric data (e.g., brain wave recordings) collected from living organism(s) while the living organism(s) are performing the perceptual or cognitive task(s). In particular, aspects of the present disclosure are directed to a new supervision paradigm, by which machine-learned feature extraction models are trained using example stimuli paired with companion biometric data such as neural activity recordings (e g electroencephalogram data, electrocorticography data, functional near-infrared spectroscopy, and/or magnetoencephalography data) collected from a living organism (e.g., human being) while the organism perceived those examples (e.g., viewing the image, listening to the speech, etc.).

Training machine-learned models for perceptual tasks using biometric data

In some embodiments, an ear-mounted sound reproduction system is provided. The system includes an ear-mountable housing that sits within the pinna of the ear and occludes the ear canal. In some embodiments, the ear-mountable housing includes a plurality of external-facing microphones. Because the external-facing microphones may be situated within the pinna of the ear but outside of the ear canal, the microphones will experience some, but not all, of the three-dimensional acoustic effects of the pinna. In some embodiments, sound is reproduced by an internal-facing driver element of the housing using a plurality of filters applied to the signals received by the plurality of external-facing microphones to preserve three-dimensional localization cues that would be present at the eardrum in the absence of the housing, such that the housing is essentially transparent to the user. In some embodiments, techniques are provided for deriving the plurality of filters.

Partial HRTF compensation or prediction for in-ear microphone arrays

Embodiments of the invention are directed to using image data and contextual data to determine information about a scene, based on one or more previously obtained images. Contextual data, such location of image capture, can be used to determine previously obtained images related to the contextual data and other location-related information, such as billboard locations. With even low resolution devices, such as cell phone, image attributes, such as a histogram or optically recognized characters, can be compared between the previously obtained images and the newly captured image. Attributes matching within a predefined threshold indicated matching images. Information on the content of matching previously obtained images can be provided back to a user who captured the new image. User profile data can refine the content information. The content information can also be used as search terms for additional searching or other processing.

Data access based on con lent of image recorded by a mobile device

Improving accuracy in understanding and/or resolving references to visual elements in a visual context associated with a computerized conversational system is described. Techniques described herein leverage gaze input with gestures and/or speech input to improve spoken language understanding in computerized conversational systems. Leveraging gaze input and speech input improves spoken language understanding in conversational systems by improving the accuracy by which the system can resolve references&#x2014;or interpret a user's intent&#x2014;with respect to visual elements in a visual context. In at least one example, the techniques herein describe tracking gaze to generate gaze input, recognizing speech input, and extracting gaze features and lexical features from the user input. Based at least in part on the gaze features and lexical features, user utterances directed to visual elements in a visual context can be resolved.

Eye gaze for spoken language understanding in multi-modal conversational interactions

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an augmented environmental awareness system to present new and important sounds to a user in an enhanced auditory experience. In one aspect, a method includes detecting a new sound that was not present in a current auditory environment before the detection, adjusting electrical input signals that are determined to be characteristic of the new sound to generated adjusted electrical signals, generating electrical output signals from the adjusted electrical signals and from the electrical input signals that are not determined to be characteristic of the new sounds, and providing the electrical output signals to audio output transducers.

Augmented environmental awareness system

The systems and methods described create a mathematical representation of each of the media objects for which user ratings are known. The mathematical representations take into account the subjective rating value assigned by a user to the respective media object and the user that assigned the rating value. The media object with the mathematical representation closest to that of the seed media object is then selected as the most similar media object to the seed media object. In an embodiment, the mathematical representation is a vector representation in which each user is a different dimension and each user's rating value is the magnitude of the vector in that dimension. Similarity between two songs is determined by identifying the closest vectors to that of the seed song. Closeness may be determined by subtracting or by calculating the dot product of each of the vectors with that of the seed media object.

System and method for identifying similar media objects

Growing community of inventors

Palo Alto, CA, United States of America

Malcolm G Slaney