Apple Inc.

Knowles Electronics, Inc.

Maxim Integrated Products, Inc.

Tony S Verma

John Woodruff

Tyrone T Chen

Vasu Iyengar

Tom-Davy W Saux

Vladan Bajic

Andrew E Greenwood

Jakub Mazur

Shailesh Sakri

Jonathon Ray

Jae Woo Chang

Martin E Johnson

Sean Boland Kelly

Christopher M Garrido

Sean Anthony Ramprashad

Sorin V Dusan

Joseph M Williams

Daniel K Boothe

Mitchell R Lerner

Patrick Miauton

Charles C Hoyt

Sridhar Krishna Nemala

Peter D Callaway

Darius A Satongar

Per Håkan Linus Persson

Frederic Caldwell

Sharon Gadonniex

Juan C Martinez Nieto

A computer system outputs audio content via one or more audio output devices. If the audio content includes information that enables spatialization of the audio content, the system outputs the audio content in a simulated three-dimensional environment, including, if the audio content corresponds to a first category of content, causing the one or more audio output devices to simulate production of the audio content in a first virtual space, and if the audio content corresponds to a second category of content, causing the one or more audio output devices to simulate production of the audio content in a second virtual space that has different simulated acoustic properties than simulated acoustic properties of the first virtual space.

Systems, methods, and graphical user interfaces for using spatialized audio during communication sessions

A method performed by an audio source device. The method obtains an input audio signal and determines a sound output level of a headset based on the input audio signal, a user volume setting, and a sound output sensitivity of the headset. The method determines whether the sound output level is above a threshold. In response to determining that the sound output level is above the threshold, a scalar gain is applied upon the input audio signal to produce an output audio signal for output by the headset.

Method and system for adaptive volume control

A method performed by a near-end headphone device, while the device is engaged in a voice communication session with a far-end device. The method receives a downlink audio signal from the far-end device and drives a speaker with the downlink audio signal. The method receives an accelerometer signal from an accelerometer of the near-end device and performs echo cancellation and residual echo suppression. The method generates a combined SNR-RES signal based on a SNR of the echo cancelled the accelerometer signal and the residual echo suppression signal. The method determines whether the combined SNR-RES signal is below a threshold. In response to being below the threshold, the method gates the echo cancelled accelerometer signal, generates an uplink audio signal by blending the gated signal with a microphone signal and transmits the uplink audio signal to the far-end device.

Accelerometer echo suppression and echo gating during a voice communication session on a headphone device

An audio system has an ambient sound enhancement function, in which an against-the-ear audio device having a speaker converts a digitally processed version of an input audio signal into sound. The audio system also has an acoustic noise cancellation (ANC) function that may be combined in various ways with the sound enhancement function, and that may be responsive to voice activity detection. Other aspects are also described and claimed.

Ambient sound enhancement and acoustic noise cancellation based on context

An audio system has an ambient sound enhancement function, in which an against-the-ear audio device having a speaker converts a digitally processed version of an input audio signal into sound. The input audio signal may be amplified where the amplification may be in accordance with a stored hearing profile of the user (personalized ambient sound enhancement.) The audio system also has an acoustic noise cancellation (ANC) function that may be combined in various ways with the sound enhancement function, and that may be responsive to voice activity detection. Other aspects are also described and claimed.

Ambient sound enhancement based on hearing profile and acoustic noise cancellation

Systems and methods for stereo separation and directional suppression are provided. An example method includes receiving a first audio signal, representing sound captured by a first microphone associated with a first location, and a second audio signal, representing sound captured by a second microphone associated with a second location. The microphones comprise omni-directional microphones. The distance between the first and second microphones is limited by the size of a mobile device. A first channel signal of a stereo signal is generated by forming, based on the first and second audio signals, a first beam at the first location. A second channel signal of the stereo signal is generated by forming, based on the first and second audio signals, a second beam at the second location. First and second directions, associated respectively with the first and second beams, are fixed relative to a line between the first and second locations.

Stereo separation and directional suppression with omni-directional microphones

Systems and methods for multi-sourced noise suppression are provided. An example system may receive streams of audio data including a voice signal and noise, the voice signal including a spoken word. The streams of audio data are provided by distributed audio devices. The system can assign weights to the audio streams based at least partially on quality of the audio streams. The weights of audio streams can be determined based on signal-to-noise ratios (SNRs). The system may further process, based on the weights, the audio stream to generate cleaned speech. Each audio device comprises microphone(s) and can be associated with the Internet of Things (IoT), such that the audio devices are Internet of Things devices. The processing can include noise suppression and reduction and echo cancellation. The cleaned speech can be provided to a remote device for further processing which may include Automatic Speech Recognition (ASR).

Multi-sourced noise suppression

Systems and methods for active noise reduction and occlusion reduction based on seal quality of an in-the-ear (ITE) module inserted into a user's ear canal are provided. An example method includes receiving one or more acoustic signals. Each of the acoustic signals represents at least one captured sound having at least one of a voice component and an unwanted noise. The voice component may include the user's own voice. A quality of a seal of an ear canal is determined based at least partially on the acoustic signals. If the quality of the seal exceeds a predetermined threshold value, an occlusion reduction is performed on the acoustic signals to improve the voice component. If the quality of the seal is below a predetermined threshold value, active noise reduction is performed on the acoustic signals to reduce the unwanted noise.

Occlusion reduction and active noise reduction based on seal quality

A system and method are provided for use in an electronic device configured to process data to perform a method of generating a fixed point approximation of a number x by first locating the most significant bit of a given number, then retrieving predetermined values from electronic data storage, where the first value is based on a first index value generated from the most significant bit and contains fixed-point representation located in a table in storage. Then, output values are generated from look-up tables that correspond to index values generated from a number of bits that immediately following the most significant bit. Finally, the final mathematic result is computed using fixed-point arithmetic logic to generate a fixed point approximation.

System and method for generating a fixed point approximation to nonlinear functions

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San Francisco, CA, United States of America

Tony S Verma