Interlink Electronics, Inc.

Dolby Laboratories Licensing Corporation

Doppler Labs, Inc.

Eargo, Inc.

Jeffrey R Baker

Richard Fritz Lanman, Iii

Carlos Solis Sanchez

Noah Kraft

Gints Valdis Klimanis

Matthew J Jaffe

Sal Gregory Garcia

Declan Christopher Flannery

Scott J Daly

Anthony Parks

Poppy Anne Carrie Crum

Edwin Keshesh Yousafian

Paul Anthony Long

Michael J Errico

Jonathan Sarjeant Aase

Beau Jay Polinske

Daniel C Wiggins

James Dexter Tickle

Matthew Sills

Matthew Fumio Yamamoto

Alex Brandmeyer

McGregor Steele Joyner

Andrea Fanelli

Ian Eric Esten

Jacob Meacham

Steve B Branton

Nicolas R Tsingos

Chee Wai Lu

Nils Jacob Palmborg

Patrick Harold Bair

Thomas Ezekiel Burgess

Daniel Paul Darcy

Satej Suresh Pankey

Vimal Puthanveed

Volodymyr Vlaskin

David Lee Stallard

Dustin J Luck

David J Arthur

Scott David Alhart

Shaohon Chen

Richard Fritz Lanman Iii

Embodiments are disclosed for hybrid near/far-field speaker virtualization. In an embodiment, a method comprises: receiving a source signal including channel-based audio or audio objects; generating near-field gain(s) and far-field gain(s) based on the source signal and a blending mode; generating a far-field signal based, at least in part, on the source signal and the far-field gain(s); rendering, using a speaker virtualizer, the far-field signal for playback of far-field acoustic audio through far-field speakers into an audio reproduction environment; generating a near-field signal based at least in part on the source signal and the near-field gain(s); prior to providing the far-field signal to the far-field speakers, sending the near-field signal to a near-field playback device or an intermediate device coupled to the near-field playback device; providing the far-field signal to the far-field speakers; and providing the near-field signal to the near-field speakers to synchronously overlay the far-field acoustic audio.

Method, systems and apparatus for hybrid near/far virtualization for enhanced consumer surround sound

An apparatus and method of generating personalized HRTFs. The system is prepared by calculating a model for HRTFs described as the relationship between a finite example set of input data, namely anthropometric measures and demographic information for a set of individuals, and a corresponding set of output data, namely HRTFs numerically simulated using a high-resolution database of 3D scans of the same set of individuals. At the time of use, the system queries the user for their demographic information, and then from a series of images of the user, the system detects and measures various anthropometric characteristics. The system then applies the prepared model to the anthropometric and demographic data as part of generating a personalized HRTF. In this manner, the personalized HRTF can be generated with more convenience than by performing a high-resolution scan or an acoustic measurement of the user, and with less computational complexity than by numerically simulating their HRTF.

Personalized HRTFs via optical capture

A hearing assistance device is discussed that has one or more accelerometers, a user interface, and optionally a left/right determination module is configured to receive input data from the one or more accelerometers from user actions causing control signals as sensed by the accelerometers to trigger a program change for an audio configuration for the device selected from a group consisting of a change in amplification/volume control, a change in a mute mode, a change of a hear loss profile loaded into that hearing assistance device, and a change in a play-pause mode.

Hearing assistance device with an accelerometer

One or more context aware processing parameters and an ambient audio stream are received. One or more sound characteristics associated with the ambient audio stream are identified using a machine learning model. One or more actions to perform are determined using the machine learning model and based on the one or more context aware processing parameters and the identified one or more sound characteristics. The one or more actions are performed.

Context aware hearing optimization engine

An apparatus may include a housing adapted for at least partial insertion into a concha bowl of a human ear, at least one speaker residing in or on the housing, a control system residing in or on the housing and a positioning element attached to the housing. The control system may be configured for controlling the speaker and configured for radio frequency (RF) communication. The positioning element may be configured to fit at least partially inside a concha of the human ear and may be configured to retain the housing at least partially within the concha bowl. The positioning element may include one or more wires Control System configured for communication with the control system. The one or more wires may be configured for at receiving and/or transmitting RF radiation. In some examples, the positioning element may be, or may include, a concha lock. The positioning element may include a loop antenna.

In-ear radio frequency antenna

A plurality of utterances of a first user from the language of the first user is translated into a language of a second user. The confidence scores associated with the translated utterances are compared with a confidence threshold. A predetermined utterance gap is adjusted based on the comparison. The predetermined utterance gap is a duration of time that occurs between utterances.

Translation techniques with adjustable utterance gaps

Personal audio systems and methods are disclosed. A personal audio system includes a voice activity detector to determine whether or not an ambient audio stream contains voice activity, a pitch estimator to determine a frequency of a fundamental component of an annoyance noise contained in the ambient audio stream, and a filter bank to attenuate the fundamental component and at least one harmonic component of the annoyance noise to generate a personal audio stream. The filter bank implements a first filter function when the ambient audio stream does not contain voice activity, or a second filter function when the ambient audio stream contains voice activity.

Annoyance noise suppression

Personal audio systems and methods are disclosed. The personal audio system includes a processor configured to generate a processed ambient audio stream by processing the ambient audio stream in accordance with a selected set of processing parameters selected from the plurality of processing parameter sets stored in the memory, a communications interface configured to receive a new set of processing parameters, selected by someone other than the user, and a controller configured to instruct the processor to begin generating the processed ambient audio stream by using the new set of processing parameters.

Sharing of custom audio processing parameters

A time heuristic audio control system, comprises a receiver for receiving time-based data from a personal computing device and a memory storing one or more sets processing parameters comprising instructions for processing the ambient sound based upon the time-based data. The system further includes a processor coupled to the memory and the receiver configured to adjust the ambient sound as directed by a selected set of processing parameters retrieved from the memory to create adjusted audio, the selected set of processing parameters retrieved based upon the time-based data and at least one speaker for outputting the adjusted audio.

Time heuristic audio control

A hearing assistance device is discussed that has one or more accelerometers, a user interface, and optionally a left/right determination module is configured to receive input data from the one or more accelerometers from user actions causing control signals as sensed by the accelerometers to trigger a program change for an audio configuration for the device selected from a group consisting of a change in amplification/volume control, a change in a mute mode, a change of a hearing loss profile loaded into that hearing assistance device, and a change in a play-pause mode.

Active acoustic filter systems and methods are disclosed. An active acoustic filter system includes a memory storing one or more stored sound profiles and a respective set of processing parameters associated with each of the one or more stored sound profiles. A processor coupled to the memory generates processed sound by processing ambient sound in accordance with a set of processing parameters retrieved from the memory based on results from comparing an ambient sound profile to at least one of the one or more stored sound profiles.

Active acoustic filter with automatic selection of filter parameters based on ambient sound

Translation with conversational overlap

Ambient sound is converted into digital signals. A processor performs active noise cancellation and/or a transformation operation that is distinct from the active noise cancellation on the digital signals. The active noise cancellation and the transformation operation transform the digital signals into modified digital signals. The modified digital signals are converted into modified analog signals. The modified analog signals are outputted as audio waves. An interior microphone is configured to output an output signal to the processor in response to receiving the modified analog signals. In response to receiving the output signal from the interior microphone, the processor is configured to determine whether the modified digital signals produce desired audio waves.

Real-time audio processing of ambient sound

Growing community of inventors

Thousan Oaks, CA, United States of America

Jeffrey R Baker