Motorola Mobility LLC

Google Inc.

Google Technology Holdings LLC

Plamen A Ivanov

Joel A Clark

Robert A Zurek

Kevin J Bastyr

Jincheng Wu

Mark A Jasiuk

Adrian M Schuster

Snehitha Singaraju

Rivanaldo S Oliveira

Tenkasi Vaideeswaran Ramabadran

Giles T Davis

Pratik Kamdar

Malay Gupta

Roger William Ady

Dusan Macho Cierna

Rajib Acharya

Mark Frederick Valentine

Joseph C Dwyer

Sandeep Vuppu

Juan C Garcia

Daniel L Richards

Seungyoon Lee

John Ross Meloney

Kevin J Bastry

A disclosed method includes monitoring an audio signal energy level while having a noise suppressor deactivated to conserve battery power, buffering the audio signal in response to a detected increase in the audio energy level, activating and running a voice activity detector on the audio signal in response to the detected increase in the audio energy level and activating and running a noise estimator in response to voice being detected in the audio signal by the voice activity detector. The method may further include activating and running the noise suppressor only if the noise estimator determines that noise suppression is required. The method activates and runs a noise type classifier to determine the noise type based on information received from the noise estimator and selects a noise suppressor algorithm, from a group of available noise suppressor algorithms, where the selected noise suppressor algorithm is the most power consumption efficient.

Apparatus and method for power efficient signal conditioning for a voice recognition system

A disclosed method includes monitoring an audio signal energy level while having a plurality of signal processing components deactivated and activating at least one signal processing component in response to a detected change in the audio signal energy level. The method may include activating and running a voice activity detector on the audio signal in response to the detected change where the voice activity detector is the at least one signal processing component. The method may further include activating and running the noise suppressor only if a noise estimator determines that noise suppression is required. The method may activate and runs a noise type classifier to determine the noise type based on information received from the noise estimator and may select a noise suppressor algorithm, from a group of available noise suppressor algorithms, where the selected noise suppressor algorithm is the most power consumption efficient.

A method, a system, and a computer program product for detecting an audio trigger phrase at a particular audio input channel and initiating a voice recognition session. The method includes capturing audio content by a plurality of microphone pairs of an audio capturing device, wherein each microphone pair of the plurality of microphone pairs is associated with an audio input channel of a plurality of audio input channels of the audio capturing device. The method further includes simultaneously monitoring, by a processor of the audio capturing device, audio content on each of the audio input channels. The method further includes: independently detecting, by the processor, an audio trigger phrase on at least one audio input channel of the plurality of audio input channels; and in response to detecting the audio trigger phrase, commencing a voice recognition session using the at least one audio input channel as an audio source.

Detecting audio trigger phrases for a voice recognition session

A method, a system, and a computer program product reducing noise in audio received by at least one microphone. The method includes determining, from an audio signal received by at least one primary microphone of an electronic device, whether a user that is proximate to the electronic device is currently speaking. The method further includes, in response to determining that a user is not currently speaking, receiving a first audio using a first microphone subset from among a plurality of microphones and receiving at least one second audio using at least one second microphone subset from among the plurality of microphones. The method further includes generating a composite signal from the first audio and the second audio. The method further includes collectively processing the audio signal and the composite signal to generate a modified audio signal having a reduced level of noise.

Reducing noise in audio signals

A method includes obtaining, by a processor, an audio echo signal and an audio desired signal from an acoustic echo correction stage of an electronic device, and converting the echo signal and the desired signal to the frequency domain. The method further includes grouping, by the processor, frequency bin results of respective frequency domain converted echo and desired signals into respective echo and desired sub-bands. A sub-band suppressor gain is estimated based on an estimated sub-band energy for the echo and desired sub-bands. The method further includes modulating the frequency domain converted desired signal to compensate for residual echo, the modulating based, at least in part, on the estimated sub-band suppressor gain, and the modulating producing a compensated frequency domain converted echo signal. The method also includes converting the compensated frequency domain converted desired signal into time domain converted audio output signal.

Echo cancellation and suppression in electronic device

One method of operation includes beamforming a plurality of microphone outputs to obtain a plurality of virtual microphone audio channels. Each virtual microphone audio channel corresponds to a beamform. The virtual microphone audio channels include at least one voice channel and at least one noise channel. The method includes performing voice activity detection on the at least one voice channel and adjusting a corresponding voice beamform until voice activity detection indicates that voice is present on the at least one voice channel. Another method beamforms the plurality of microphone outputs to obtain a plurality of virtual microphone audio channels, where each virtual microphone audio channel corresponds to a beamform, and with at least one voice channel and at least one noise channel. The method performs voice recognition on the at least one voice channel and adjusts the corresponding voice beamform to improve a voice recognition confidence metric.

Apparatus and method for beamforming to obtain voice and noise signals

A portable device performs echo cancellation and echo suppression. An audio echo signal and an audio desired signal are obtained from an acoustic echo correction stage of the portable device. The echo and desired signals are converted to the frequency domain. Frequency bin results of the respective frequency domain converted echo and desired signals are grouped into echo and desired sub-bands. A sub-band suppressor gain is estimated based on the estimated sub-band energy for the echo and desired sub-bands. The frequency domain converted echo signal is modulated based at least in part on the estimated sub-band suppressor gain to compensate for residual echo. The compensated frequency domain converted echo signal is time domain converted into an audio output signal. The audio output signal is processed by a selected one of a voice recognition engine and a communication module transmitter.

Systems and methods for controlling a portable electronic communication device use device operational context to provide user trigger or command input. When user input is received from a user of the device, a set of user input options is selected based on an operational context of the device, including an identification of at least one running application. Each user input option is associated with a device action, and the received user input is mapped to a matching user input option within the selected set of user input options. The device action associated with the matching user input option is then executed.

Device control based on its operational context

A method of operation beamforms a plurality of microphone outputs to obtain a plurality of virtual microphone audio channels with at least one audio output channel and at least one audio control channel. The method performs voice recognition on the audio control channel to detect voice commands for controlling audio output channel attributes, and adjusts an audio channel attribute in response to detecting a voice command. Adjusting an attribute of the audio channel may be accomplished by, for example, controlling one or more parameters of an adjustable beamformer. The detected voice commands for controlling audio channel attributes may include voice commands for controlling audio sensitivity zooming, panning in a specified direction, focusing on a specified direction, blocking a specified direction, mixing a narrator's voice, blocking a narrator's voice, or reducing background noise. An apparatus that performs the method of operation is also disclosed.

Voice controlled audio recording system with adjustable beamforming

A portable electronic communication device includes a user input receiver, one or more user outputs, and a processor programmed to receive user input from the user input receiver and to determine based on the user input whether the user desires the device to enter a private mode. The device alters communications from the device via the one or more user outputs while in the private mode, and enters the private mode if the user input indicates that the user desires the device to enter the private mode. While in the private mode, the device may alter the manner in which it communicates to the user.

Privacy mode detection and response over voice activated interface

Configuring an adaptive microphone array to gather signals from a main lobe of the array, and configuring the array to reduce side interference gathered from sources that are not situated within the main lobe. A memory stores test signals gathered by the array in an anechoic chamber, a free-field environment, or other echo, interference and noise-minimized acoustic environment. Signals gathered in real time are processed to provide a preliminary output and preliminary weights. The test signals are retrieved from memory. The preliminary weights are applied to the test signals to provide equalizer weights. The equalizer weights and the preliminary output generate an equalized output that minimizes degradations resulting from side interference reduction.

Methods and apparatuses for performing adaptive equalization of microphone arrays

A method and apparatus to reduce acoustic feedback from a speaker to a microphone in a communication device. An audio signal can be reproduced by an apparatus. An audible signal of at least one near-end user can be voice activity detected at the apparatus. At least one audio output channel of multiple audio output channels can be operated on to attenuate acoustic pressure representative of the audio signal near at least one microphone aperture location when the audible signal of the at least one near-end user is detected at the apparatus.

Method and apparatus for reducing acoustic feedback from a speaker to a microphone in a communication device

A method and apparatus for voice recognition performed in a voice recognition block comprising a plurality of voice recognition stages. The method includes receiving a first plurality of voice inputs, corresponding to a first phrase, into a first voice recognition stage of the plurality of voice recognition stages, wherein multiple ones of the voice recognition stages includes a plurality of voice recognition modules and multiples ones of the voice recognition stages perform a different type of voice recognition processing, wherein the first voice recognition stage processes the first plurality of voice inputs to generate a first plurality of outputs for receipt by a subsequent voice recognition stage. The method further includes, receiving by each subsequent voice recognition stage a plurality of outputs from a preceding voice recognition stage, wherein a plurality of final outputs is generated by a final voice recognition stage from which to approximate the first phrase.

Method and apparatus including parallell processes for voice recognition

Configuring an adaptive microphone array to gather signals from a main lobe of the array, and configuring the array to reduce side interference gathered from sources that are not situated within the main lobe. A memory stores test signals gathered by the array at a plurality of predetermined angular bearings with reference to the array in an anechoic chamber. Signals gathered in real time are processed to provide a preliminary output and preliminary weights. The test signals are retrieved from memory. The preliminary weights are applied to the test signals to provide null steering weights. The null steering weights and the preliminary output are processed to reduce or minimize the amplitude response of the array at the angular orientation.

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Schaumburg, IL, United States of America

Plamen A Ivanov