Apple Inc.

Vasu Iyengar

Aram M Lindahl

Sorin V Dusan

Yang Lu

Nicholas J Bryan

Fatos Myftari

Sean Anthony Ramprashad

Vladan Bajic

Lalin S Theverapperuma

Martin E Johnson

Joshua D Atkins

Andrew P Bright

John Woodruff

Tarun Pruthi

Tom-Davy W Saux

Ronald Nadim Isaac

Tyrone T Chen

Andrew E Greenwood

Jakub Mazur

Ashrith Deshpande

Tony S Verma

Esge Brandt Andersen

Ruchir M Dave

Hanchi Chen

Thomas M Jensen

Qing Yang

Alexander Kanaris

Sarmad Aziz Malik

Sarthak Khanal

Raghavendra S Prabhu

Hannes Breitschaedel

Navneet Gandhi

Aspects of the subject technology provide for generation of a self-voice signal by an electronic device that is operating in an active noise cancellation mode. In this way, during a phone call, a video conference, or while listening to audio content, a user of the electronic device may benefit from active cancellation of ambient noise while still being able to hear their own voice when they speak. In various implementations described herein, the concurrent self-voice and automatic noise cancellation features are facilitated by accelerometer-based control of sidetone and/or active noise cancellation operations.

Adaptive noise cancellation and speech filtering for electronic devices

Aspects of the subject technology relate to a device including a microphone, a filter and a processor. The filter receives an audio signal including ambient noise and a voice of a user of the device from the microphone. At least a portion of ambient noise is filtered from the audio signal. The processor determines a level of the ambient noise in the received audio signal and dynamically adjusts a gain applied to the filtered audio signal based on the level of the ambient noise.

Self-voice adaptation

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

A method performed by an audio system that includes a headset with a left headset housing and a right headset housing. The method includes driving a speaker of the left headset housing with an audio signal, determining whether audio howl is present within the left headset housing by comparing spectral content from a first error microphone signal produced by a first error microphone of the left headset housing and spectral content from a second error microphone signal produced by a second error microphone of the right headset housing, and, in response to determining that audio howl is present, filtering the audio signal to mitigate the audio howl.

Method and system for detecting and mitigating audio howl in headsets

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

A device implementing a system for mitigating noise includes at least one processor configured to receive a first audio signal corresponding to a first microphone, and determine whether wind noise is present based at least in part on the first audio signal. The processor is configured to select, based on the determining, a second audio signal from between second and third microphones. The second microphone is disposed at a location that experiences less echo coupling when the device is in a particular orientation with respect to a user. The third microphone is disposed at another location that experiences less wind noise. The processor is configured to determine voice and noise reference values based on the first and the selected second audio signals, and perform noise suppression with respect to at least one of the first or the selected second audio signal, based on the voice or the noise reference value.

Mitigating noise in audio signals

A method for controlling a speech enhancement process in a far-end device, while engaged in a voice or video telephony communication session over a communication link with a near-end device. A near-end user speech signal is produced, using a microphone to pick up speech of a near-end user, and is analyzed by an automatic speech recognizer (ASR) without being triggered by an ASR trigger phrase or button. The recognized words are compared to a library of phrases to select a matching phrase, where each phrase is associated with a message that represents an audio signal processing operation. The message associated with the matching phrase is sent to the far-end device, which is used to configure the far-end device to adjust the speech enhancement process that produces the far-end speech signal. Other embodiments are also described.

Transparent near-end user control over far-end speech enhancement processing

Signals are received from audio pickup channels that contain signals from multiple sound sources. The audio pickup channels may include one or more microphones and one or more accelerometers. Signals representative of multiple sound sources are generated using a blind source separation algorithm. It is then determined which of those signals is deemed to be a voice signal and which is deemed to be a noise signal. The output noise signal may be scaled to match a level of the output voice signal, and a clean speech signal is generated based on the output voice signal and the scaled noise signal. Other aspects are described.

Speech enhancement for an electronic device

Systems and methods are described for storing and reusing previously generated/calculated acoustic environment data. By reusing acoustic environment data, the systems and methods described herein may avoid the increased overhead in generating/calculating acoustic environment data for a location when this data has already been generated and is likely accurate. In particular, the time and complexity involved in determining reverberation/echo levels, noise levels, and noise types may be avoided when this information is available in storage. This previously stored acoustic environment data may not be limited to data generated/calculated by the same audio device. Instead, in some embodiments an audio device may access a centralized repository to leverage acoustic environment data generated/calculated by other audio devices.

Location based storage and upload of acoustic environment related information

An audio system has a housing in which are integrated a number of microphones. A programmed processor accesses the microphone signals and produces a number of acoustic pick up beams based groups of microphones, an estimation of voice activity and an estimation of noise characteristics on each beam. Two or more beams including a voice beam that is used to pick up a desired voice and a noise beam that is used to provide information to estimate ambient noise are adaptively selected from among the plurality of beams, based on thresholds for voice separation and thresholds for noise-matching. Other embodiments are also described and claimed.

Coordination of beamformers for noise estimation and noise suppression

Systems and methods for reducing effects of time-division multiplexing noise in mobile communications devices. When cellular communication with time-division multiplexing is detected, such as Global System for Mobiles (GSM) communication with Time Division Multiple Access (TDMA) protocol, total energy and energy at a repetition frequency of the time division multiplexing is measured in audio signals received from several microphones located in the device. A control signal indicating microphones affected by TDMA noise is provided to signal processing subsystems that receive audio signals from the microphones. A beam former circuit may combine two or more audio signals to produce beam formed signals. The control signal may further indicate beam formed signals affected by TDMA noise based on a ratio of the energy from the repetition frequency to the total energy in the beam formed signals.

System and method for reducing noise from time division multiplexing of a cellular communications transmitter

An audio electronics system operates on audio data. A low-pass or bandpass filter produces first data from audio data. A level detector produces a time-varying first gain. The first gain is based on a time-varying level of the first data. A harmonics generator receives, as input, the first data adjusted by an inverse of the first gain. The harmonics generator produces second data, as harmonics of the input. A multiplier outputs the second data adjusted by the first gain. Other aspects are also described and claimed.

Automatic level control for psychoacoustic bass enhancement

System of noise reduction for mobile devices includes blind source separator (BSS) and noise suppressor. BSS receives signals from at least two audio pickup channels. BSS includes sound source separator, voice source detector, equalizer, and auto-disabler. Sound source separator generates signals representing first sound source and second sound source based on signals from the first and the second channels. Voice source detector determines whether the signals representing the first and second sound sources are voice signal or noise signal, respectively. Equalizer scales noise signal to match a level of the voice signal, and generates scaled noise signal. Auto-disabler determines whether to disable BSS. Auto-disabler outputs signals from the at least two audio pickup channels when the BSS is disabled and outputs the voice signal and the scaled noise signal when the BSS is not disabled. Noise suppressor generates clean signal based on outputs from auto-disabler. Other embodiments are also described.

System and method of noise reduction for a mobile device

Electronic system for audio noise processing and noise reduction comprises: first and second noise estimators, selector and attenuator. First noise estimator processes first audio signal from voice beamformer (VB) and generate first noise estimate. VB generates first audio signal by beamforming audio signals from first and second audio pick-up channels. Second noise estimator processes first and second audio signal from noise beamformer (NB), in parallel with first noise estimator and generates second noise estimate. NB generates second audio signal by beamforming audio signals from first and second audio pick-up channels. First and second audio signals include frequencies in first and second frequency regions. Selector's output noise estimate may be a) second noise estimate in the first frequency region, and b) first noise estimate in the second frequency region. Attenuator attenuates first audio signal in accordance with output noise estimate. Other embodiments are also described.

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Pleasanton, CA, United States of America

Vasu Iyengar