Abstract: A method comprising: at an electronic device (100) having an array microphones (101) with a plurality of microphones and a processor (102): receiving a plurality of microphone signals (x1, x2, x3) from the plurality of microphones; generating a processed signal (XP) from the plurality of microphone signals using one or both of beamforming and deconvolution; generating a compensated processed signal (XO) by compensating the processed audio signal (XP) in accordance with compensation coefficients (Z). Generating the compensated processed signal comprises: generating first spectrum values (PXP) from the processed audio signal; generating reference spectrum values (<PX>) from multiple second spectrum values (PX1, PX2, PX3) generated from each of at least two of the microphone signals in the plurality of microphone signals (x1, x2, x3); and generating the compensation coefficients (Z) from the reference spectrum values (<PX>) and the first spectrum values (PXP).

Abstract: A microphone assembly includes an acoustic transducer configured to generate an analog signal in response to pressure changes sensed by the acoustic transducer. The analog signal includes frequency components below a threshold frequency. The microphone assembly also includes an integrated circuit electrically coupled to the acoustic transducer and configured to determine a characteristic of frequency components below the threshold frequency, determine whether the characteristic of the frequency components corresponds to a fall event, and generate an output signal in response to a determination that the characteristic of the frequency components corresponds to the fall event. The microphone assembly also includes a housing having an external device interface with electrical contacts. The acoustic transducer and the integrated circuit are disposed within the housing. The integrated circuit is electrically coupled to contacts of the external device interface.

Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by two or more network microphone devices include receiving an instruction to process one or more audio signals captured by a first network microphone device and after receiving the instruction (i) disabling at least a first microphone of a plurality of microphones of a second network microphone device, (ii) capturing a first audio signal via a second microphone of the plurality of microphones, (iii) receiving over a network interface of the second network microphone device a second audio signal captured via at least a third microphone of the first network microphone device, (iv) using estimated noise content to suppress first and second noise content in the first and second audio signals, (v) combining the suppressed first and second audio signals into a third audio signal, and (vi) determining that the third audio signal includes a voice input comprising a wake word.

Abstract: A method and apparatus for handling both echo cancellation and noise in a given space using a single adaptive filter. The proposed method utilizes just a single adaptive filter and without any control logic, the system is capable of handling both the AEC and the noise in a given space. The technology as proposed and claimed herein proposes using a single adaptive filter to cancel referenced noise AEC and unreferenced noise ANC in a given physical space using a beamformer. By adding the far end reference and a beam pointed dynamically on the noise source in the given physical space this can be achieved. This invention also reduces the processing load and memory.

Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by two or more network microphone devices include receiving an instruction to process one or more audio signals captured by a first network microphone device and after receiving the instruction (i) disabling at least a first microphone of a plurality of microphones of a second network microphone device, (ii) capturing a first audio signal via a second microphone of the plurality of microphones, (iii) receiving over a network interface of the second network microphone device a second audio signal captured via at least a third microphone of the first network microphone device, (iv) using estimated noise content to suppress first and second noise content in the first and second audio signals, (v) combining the suppressed first and second audio signals into a third audio signal, and (vi) determining that the third audio signal includes a voice input comprising a wake word.

Abstract: A system performs pole-zero or IIR modeling and estimation of an inter-microphone transfer function between first and second microphones that output respective first and second microphone signals. The system includes a first adaptive FIR filter to which the first microphone signal is provided, a delay element that delays the second microphone signal by a predetermined delay amount, and a second adaptive FIR filter to which the delayed second microphone signal is provided. A first coefficient of the second adaptive FIR filter is constrained to a fixed non-zero value. The filters are jointly adapted to minimize an error signal that is a difference of the two filters outputs. The delay is small: approximately the acoustic propagation delay between the two microphones and is not determined by the environmental reverberation characteristics. The error signal may serve as a noise reference in a noise canceller, for implementing far-field beamforming with low delay.

Abstract: The present disclosure discloses a sound receiving that includes an air conduction sound receiving circuit, a bone conduction sound receiving circuit, an adaptive filter, a crossover frequency control circuit and a synthesis circuit. The air conduction sound receiving circuit generates an air conduction sound signal. The bone conduction sound receiving circuit generates a bone conduction sound signal. The adaptive filter performs calculation according to a minimum of an error function in real time to generate a transferring filter function to filter the bone conduction sound signal to generate a transferred bone conduction sound signal. The crossover frequency control circuit determines a crossover frequency according to a maximum energy frequency point of the transferring filter function on a frequency domain.

Abstract: 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.

Abstract: The present disclosure relates to a noise manageable electronic device and a control method thereof as the disclosure capable of operating even in the Internet of Things (IoT) environment through a 5G communication network, and the electronic device of the present disclosure may control the driving of the electronic device that generates noise when a voice command is generated by a user. The present disclosure may be configured to include a receiver configured to receive the voice command from the user and noise generated from a plurality of electronic devices arranged in the home, a noise extractor configured to extract the noise, and a processor configured to determine whether the received voice command is recognizable, and to reduce the noise by controlling driving of a first electronic device that has generated the noise among the plurality of electronic devices, when it is determined that the voice command is not recognizable.

Abstract: A sound control device includes: a first memory storing instructions; and a processor that implements the stored instructions to execute a plurality of instructions, including: a synthesizing task that synthesizes a synthesized sound signal from an input sound signal acquired from a sound input device and a reproducing sound signal acquired from a sound reproducing device; an outputting task that outputs alternately between the reproducing sound signal and the synthesized sound signal to a sound emitting device; a notification control task that outputs notifying information for causing a notifying device to notify for a notification period, which is an output period during which the outputting task is outputting the synthesized sound signal to the sound emitting device; and a registering task that registers, in a second memory, duration information specifying the notification period.

Abstract: A voice signal processing method includes acquiring a near-end noise signal and a near-end voice signal by using at least one microphone, acquiring a far-end voice signal according to an incoming call, determining a noise control parameter and a voice signal change parameter based on at least one of information about the near-end voice signal, information about the near-end noise signal, or information about the far-end voice signal, generating an anti-phase signal of the near-end noise signal based on the noise control parameter, changing the far-end voice signal to improve articulation of the far-end voice signal based on information related to at least one of the voice signal change parameter, the near-end noise signal, or the anti-phase signal, and outputting the anti-phase signal and the changed far-end voice signal.

Abstract: An audio enhancement method includes receiving a first input signal representative of audio captured using an array of two or more sensors, the first input signal characterized by a first signal-to-noise ratio (SNR), with the audio being the signal-of-interest. The method also includes receiving a second input signal representative of the audio, the second input signal characterized by a second SNR. The second SNR is higher than the first SNR. The method further includes computing a spectral mask based on a frequency domain representation of the second input signal, and processing a frequency domain representation of the first input signal based on the spectral mask to generate one or more driver signals. The method further includes driving one or more acoustic transducers using the generated driver signals.

Abstract: A speech enhancement method is provided. The speech enhancement method includes: estimating a direction of a speaker by using an input signal, generating direction information indicating the estimated direction, detecting speech of a speaker based on a result of the estimating the direction, and enhancing the speech of the speaker by using the direction information based on a result of the detecting the speech.

Abstract: Noise filtering for an incoming signal is provided. The noise filtering method includes executing a transformation operation on the incoming signal by distributing energy corresponding to each of a plurality of components of the incoming signal into a two-dimensional representation. The noise filtering method also includes executing a filtering operation on the plurality of components to determine real objects and remove noise within the incoming signal. The filtering operation utilizing at least one of a plurality of noise detection matrixes based on time, frequency, or direction.

Abstract: Systems and methods for suppressing noise and detecting voice input in a multi-channel audio signal captured by two or more network microphone devices include receiving an instruction to process one or more audio signals captured by a first network microphone device and after receiving the instruction (i) disabling at least a first microphone of a plurality of microphones of a second network microphone device, (ii) capturing a first audio signal via a second microphone of the plurality of microphones, (iii) receiving over a network interface of the second network microphone device a second audio signal captured via at least a third microphone of the first network microphone device, (iv) using estimated noise content to suppress first and second noise content in the first and second audio signals, (v) combining the suppressed first and second audio signals into a third audio signal, and (vi) determining that the third audio signal includes a voice input comprising a wake word.

Abstract: A method includes acquiring sound signals of a current frame using two microphones, calculating an interaural level difference between the two microphones based on the sound signals of the current frame according to a first preset algorithm, determining whether the interaural level difference satisfies a sound source direction determining condition, determining, based on the interaural level difference, whether the sound signals of the current frame include a backward sound signal if the determining condition is satisfied, filtering out the backward sound signal from the sound signals of the current frame.

Abstract: Provided herein are a multi-microphone system and method including a controller, a plurality of transducers each operable within a unique sensitivity range, and corresponding microphone units. The controller receives a sound signal output from a first microphone unit that corresponds to a microphone unit having a transducer with the highest sensitivity. The controller analyzes the sound signal output to identify a first parameter of the sound signal output and determines if the first parameter satisfies pre-defined criteria. In an instance in which the first parameter satisfies the pre-defined criteria, the controller outputs the sound signal output of the selected first microphone unit as the output of the multi-microphone system. Otherwise, the controller receives a sound signal output from a second microphone unit comprising a corresponding transducer with a sensitivity less than the first microphone unit but greater than remaining transducers.

Abstract: Emergency call processing in a helmet (100) with a rigid shell (101) that spatially divides a shell interior from a shell ambiance includes receiving an emergency indication signal, upon reception of the emergency indication signal establishing a speech link between a controllable transceiver and a counterpart transceiver via at least one wireless communication channel, and reproducing sound in the shell interior and picking up sound with a sensitivity that is higher in the shell interior than in the shell ambience. The sound reproduced in the shell is received from the counterpart transceiver and the sound picked-up in the shell interior is transmitted to the counterpart transceiver.

Abstract: The disclosure relates to a microphone arrangement comprising at least three groups of microphones that are mounted on a head-wearable support structure. The at least three groups of microphones comprising a first group of microphones with one or more microphones, a second group of microphones with one or more microphones, and a third group of microphones with one or more microphones, wherein the first group is mounted to a casing that accommodates signal transmission circuitry, the second group is mounted to slide with respect to the casing and the first group is mounted in a direction of a first axis.

Abstract: The techniques described herein improve methods to equip a computing device to conduct automatic speech recognition (“ASR”) in talker-independent multi-talker scenarios. In some examples, permutation invariant training of deep learning models can be used for talker-independent multi-talker scenarios. In some examples, the techniques can determine a permutation-considered assignment between a model's estimate of a source signal and the source signal. In some examples, the techniques can include training the model generating the estimate to minimize a deviation of the permutation-considered assignment. These techniques can be implemented into a neural network's structure itself, solving the label permutation problem that prevented making progress on deep learning based techniques for speech separation. The techniques discussed herein can also include source tracing to trace streams originating from a same source through the frames of a mixed signal.

Abstract: Disclosed is a wearable device for producing noise free communication. The wearable device includes a housing configured to wear by a user, an air conduction microphone configured in the housing to receive voice sound of the user, an accelerometer sensor configured in the housing to receive voice signature, a battery configured in the housing to power the air conduction microphone and the accelerometer sensor, a printed circuit board configured in the housing to receive power from the battery, a memory unit connected to the printed circuitry board to store plurality of instructions, and a digital signal processor connected to the printed circuit board to process the stored plurality of instructions. The instructions are programmed to achieve a noise free communication. The voice from both air conduction microphone and the accelerometer sensor are analyzed to filter out noise and resulting in generation of noise free communication.

Abstract: An active noise control apparatus (100) includes: a sound source signal generating unit (1) generating a sound source signal from a control frequency determined in accordance with a noise source (400); a control signal filter (2) generating an original control signal by filtering the sound source signal; a stabilization processing unit (5) generating a control signal by filtering the original control signal to allow a signal in a frequency band including the control frequency to pass through, and to block a signal in a frequency band including disturbance added to the noise; a reference signal filter (3) generating a reference signal by filtering the sound source signal. The apparatus further includes: a filter coefficient updating unit (4) updating a filter coefficient sequence of the control signal filter using an error signal being an interference between a secondary noise generated from the control signal and the noise, and the reference signal.

Abstract: An audio processing device includes a first anti-noise filter, an output circuit, and an equalizer circuit. The first anti-noise filter is configured to process a digital signal, in order to generate a noise cancellation signal. The output circuit is configured to mix the noise cancellation signal with an equalized signal to generate a mixed signal, and to generate a sound output signal based on the mixed signal, in which the digital signal is associated with the sound output signal. The equalizer circuit is configured to receive an input signal, and to adjust at least one parameter of the equalizer circuit according to the equalized signal and the digital signal, in order to process the input signal to generate the equalized signal.

Abstract: Embodiments disclosed herein may include determining a signal parameter of a first microphone and a second microphone associated with a computing device. Embodiments may include generating a reference parameter based upon at least one of the parameter of the first microphone and the parameter of the second microphone. Embodiments may include adjusting a tolerance of at least one of the first microphone and the second microphone, based upon the reference parameter. Embodiments may include receiving, at the first microphone, a first speech signal, the first speech signal having a first speech signal magnitude and receiving, at the second microphone, a second speech signal, the second speech signal having a second speech signal magnitude. Embodiments may include comparing at least one of the first speech signal magnitude and the second speech signal magnitude with a third speech signal magnitude and detecting an obstructed microphone based upon the comparison.

Abstract: The present invention relates to a desktop speakerphone array processor for microphones which produces high quality sound. The microphone array has a front direction defined by the line of sight from a microphone inlet of the second microphone towards a microphone inlet of the first microphone, the array processor being connected to receive a front microphone signal from the first microphone, a rear microphone signal from the second microphone and an audio output signal representing a speaker sound emitted from a sound driver arranged near the first and second microphones and in the rearwards hemisphere with respect to the front direction of the microphone array, the array processor being configured to provide a first array signal having a first directivity pattern with a main lobe oriented in the front direction of the microphone array in dependence on the front microphone signal, the rear microphone signal and the audio output signal.

Abstract: The present invention provides a system to create a quiet zone by suppressing background noise near a user's head. The present invention utilizes two microphones; one microphone receives environmental noise and the other one is located close to a person's head. A parabolic dish loudspeaker creates a uniform sound field near a user's head. A high performance frequency-domain filtered-x least mean square with band selection (FD-FX-LMS-BS) algorithm is utilized to generate the anti-phase noise signals. The algorithm has high noise reduction performance and also allows selection of specific frequency bands for noise reduction. The FD-FX-LMS-BS algorithm is performed by a field programmable gate array (FPGA) chip, which has minimal delay in algorithm processing.

Abstract: Techniques are provided for vector noise cancellation. Different value combinations for a plurality of weighting factors may be established for a plurality of selection regions. Each value combination for the plurality of weighting factors may correspond to a different combination of a set of input signals. One or more characteristics of input signals may be used to select a particular selection region. A particular value combination of the set of weighting factors may be chosen to attenuate or amplify the input signals to generate one or more output signals.

Abstract: This encoding device (100) is provided with: a CELP encoding unit (102) that decodes CELP encoded data resulting from CELP encoding an input signal, generating a CELP decoded signal; a transform encoding unit (106) that generates a decoded signal spectrum by decoding transform encoded data resulting from using the spectrum of the input signal and the suppression spectrum of suppressing using a first suppression factor to transform encode the amplitude of the spectrum of the CELP decoded signal, and that outputs an index of the transform encoded frequency component; a pulse index recording unit (107) that forms and records an array using the index; and a CELP component suppression unit (109) that uses a second suppression factor and the array to suppress the amplitude of the spectrum resulting from adding the decoded signal spectrum and the suppression spectrum.

Abstract: An acoustic device captures sound using two or more microphones and filters the sound into a plurality of sub-bands. For each of the plurality of sub-bands, the device identifies sound captured by the microphones from at least two directions and attenuates the sound captured by the microphones, within each of the sub-bands, in substantially one of the directions.

Abstract: In one embodiment, a process for suppressing reverberation begins with a device of a user obtaining a reverberant speech signal from a voice of the user. The device determines a first estimated reverberation component of the reverberant speech signal. The device generates a first de-reverberated output signal with a first reverberation suppression based on the reverberant speech signal and the first estimated reverberation component. Then, the device generates a second improved reverberation component using the first de-reverberated output signal. The device generates a second de-reverberated output signal with a second reverberation suppression based on the reverberant speech signal and the second improved reverberation component.

Abstract: A method of operating a speaker system including a speaker coupled to an amplifier, and a dedicated digital speaker protection circuit includes turning on the amplifier in a mute mode, after a first delay period, issuing a play command to the amplifier to place the amplifier in a play mode, but without an input signal during a second delay period, and performing a speaker offset detection during the second delay period, wherein, if there is an offset, then the amplifier is forced back into the mute mode, and if there is no offset, then the amplifier is allowed to continue to operate in the play mode. The method also includes issuing a speaker protection control signal or command if an offset is detected.

Abstract: When a first noise and second noise to be generated after the first noise are generated within a predetermined period, a noise reduction unit is controlled so as to execute a first noise reduction process for an audio signal in a period including the first noise and not to execute the first noise reduction process for an audio signal in a period including the second noise.

Abstract: Electronic circuitry is described. The electronic circuitry includes a first microelectromechanical system (MEMS) structure that exhibits a first frequency response in a voice frequency range and that captures a first signal. The electronic circuitry also includes a second MEMS structure coupled to the first MEMS structure. The second MEMS structure exhibits a second frequency response in an ultrasound frequency range and captures a second signal. A combination of the first frequency response and the second frequency response achieves a target frequency response in a combined frequency range.

Abstract: A system performs residual echo suppression on a microphone signal that receives, e.g., voice commands, and that is exposed to echo from multiple speakers. An example is a smartphone that receives voice commands while the smartphone is playing music through stereo speakers. The system estimates residual echo level in different ways, and determines which estimate to use. The technique responds well to the difficult to handle scenario of a spatially quiescent image suddenly transitioning to a spatially rich image. Even in the face of such difficult scenarios, the system detects and removes residual echo from the microphone signal, instead of allowing the undesired residual echo to pass through.

Abstract: According to an embodiment, a signal processing apparatus includes an estimation unit and an updating unit. The estimation unit is configured to estimate an auxiliary variable of a target section including first and second sections of input signals by using an approximating auxiliary function for approximating an auxiliary function having an auxiliary variable as an argument. The auxiliary function is determined according to an objective function that outputs a function value that is smaller as a statistical independence of separated signals into which input signals in time-series are separated by a demixing matrix is higher. The estimation unit is configured to estimate a value of the auxiliary variable of the target section based on the estimated auxiliary variable. The updating unit is configured to update the demixing matrix such that a function value of the approximating auxiliary function is minimized.

Abstract: A noise reduction audio reproducing method includes the steps of: generating, from an audio signal of collected and obtained noise, an audio signal for noise cancellation to cancel the noise by synthesizing the audio signal for noise cancellation and the noise in an acoustic manner, reproducing the audio signal for noise cancellation acoustically to synthesize this with the noise in an acoustic manner; emphasizing an audio component to be listened to, of collected audio; synthesizing an audio signal with the audio component to be listened to being emphasized, and the audio signal for noise cancellation to supply the synthesized signal thereof to an electro-acoustic converting unit; and controlling so as to supply an audio signal, with the audio component to be listened to having been emphasized, to a synthesizing unit, regarding only a section based on a control signal.

Abstract: A voice detection system and method for automatic volume controls and voice sensors is disclosed. More specifically, the invention addresses a situation where the user's own voice undesirably affects the functionality of an automatic volume control for a two-way communication device, such as a cellular telephone. In addition, the invention proposes solutions wherein one (voice) microphone is employed and also, when two (voice and noise) microphones are employed. Further, an algorithm is disclosed that addresses the issue concerning the user's own voice in an AVC pertaining to the two microphone solution. Yet further, a method herein is disclosed that detects the presence of voice in a single non-selective (noise) microphone.

Abstract: Adaptive noise control for reducing power of an acoustic noise signal radiated from a noise source to a listening position comprises providing an electrical reference signal correlated with the acoustic noise signal; filtering the electrical reference signal with an adaptive filter to provide an electrical output signal; multiplying the electrical output signal of the adaptive filter by a gain factor to provide a first electrical compensation signal; filtering and multiplying the electrical output signal of the adaptive filter by the inverse of the gain factor to provide a second electrical compensation signal, the second gain factor being equal to 1 subtracted by the first gain factor; radiating the first electrical compensation signal to the listening position with an acoustic transducer; sensing a residual electrical error signal at the listening position; adding the second electrical compensation signal to the electrical error signal to provide a compensated error signal; and adapting filter coefficients

Abstract: A personal audio device, such as a headphone, includes an adaptive noise canceling (ANC) circuit that adaptively generates an anti-noise signal from a reference microphone signal that measures the ambient audio, and the anti-noise signal is combined with source audio to provide an output for a speaker. The anti-noise signal causes cancellation of ambient audio sounds that appear at the reference microphone. A processing circuit uses the reference microphone to generate the anti-noise signal, which can be generated by an adaptive filter. The processing circuit also models an acoustic leakage path from the transducer to the reference microphone and removes elements of the source audio appearing at the reference microphone signal due to the acoustic output of the speaker. Another adaptive filter can be used to model the acoustic leakage path.

Abstract: There is provided a noise suppressing device, for suppressing a noise component contained in a sound, including: at least two sound receiving parts receiving sounds from a plurality of directions containing a sound from a direction of a given sound source and converting the sounds to digital sound signals in a time domain, respectively; an estimating part acquiring both direction information on a direction of the given sound source and distance information on a distance from the given sound source based upon the digital sound signals converted by the sound receiving parts, and estimating a component value of a noise component contained in the signal by use of the direction information and the distance information; and a controlling part acquiring a control value of a suppression amount for controlling a range of a direction of the digital sound signals.

Abstract: The active noise control device for canceling out a target sound to be controlled in a target area for sound control includes: control sound output units each of which produces a control sound based on a wavefront control signal; and a wavefront control unit which provides the wavefront control signal to the corresponding one of the control sound output units, and the wavefront control unit generates the wavefront control signal to emit a synthesized sound from a virtual sound source toward the target area for sound control and cancel out the target sound in the target area for sound control, the synthesized sound being a sound synthesized from control sounds produced by the respective control sound output units, and the virtual sound source being located at a predetermined position.

Abstract: The present invention relates to adaptive beamforming in audio systems. More specifically, aspects of the invention relate to a method for adaptively estimating a target sound signal by establishing a simulation model simulating an audio environment comprising: a plurality of spatially separated microphones, a target sound source, and a number of audio noise sources.

Abstract: A purpose of the invention is to provide a noise gate that can output an audio signal in which only a stationary noise is removed, without degrading an utterance voice of a speaking person. A sound collection device 1 includes an FFT processing unit 11, the noise gate 12, and an IFFT processing unit 13. The sound collection device 1 transforms a collected audio signal NET into a frequency spectrum NE?N by using the FFT processing unit 11. The noise gate 12 estimates a noise spectrum N?N of a stationary noise based on the frequency spectrum NE?N of the audio signal. The noise gate 12 decreases a signal level (a gain) of the audio signal in a case where a signal level ratio of the frequency spectrum NE?N of the audio signal to the noise spectrum N?N is less than a threshold value, and outputs the audio signal.

Abstract: A device and method are disclosed for testing the intelligibility of audio announcement systems. The device may include a microphone, a translation engine, a processor, a memory associated with the processor, and a display. The microphone of the analyzer may be coupled to the translation engine, which in-turn may be coupled to the processor, which is in-turn may be coupled to the memory and the display. The translation engine can convert audio speech input from the microphone into data output. The processor can receive the data output and can apply a scoring algorithm thereto. The algorithm can compare the received data against data that is stored in the memory of the analyzer and calculates the accuracy of the received data. The algorithm may translate the calculated accuracy into a standardized STI intelligibility score that is then presented on the display of the analyzer.

Abstract: A system is provided for enhancing a sound signal produced by an audio system in a listening environment by compensating for ambient noise in the listening environment. The system receives an electrical sound signal and generates a sound output therefrom. A total sound signal is sensed representative of the total sound level in the environment, where the total sound level includes the sound output and the ambient noise. The system extracts an ambient noise signal representative of the ambient noise from the total sound signal, using an adaptive filter with an adaptive step size, in response to the total sound signal and to a reference signal derived from the electrical sound signal. The system generates a control signal in response to the ambient noise signal and adjusts the sound output of the audio system to compensate for the ambient noise level in response to the control signal.

Abstract: Provided are methods and systems for noise suppression within multiple time-frequency points of spectral representations. A multi-feature cluster tracker is used to track signal and noise sources and to predict signal versus noise dominance at each time-frequency point. Multiple features, such as binaural and monaural features, may be used for these purposes. A Gaussian mixture model (GMM) is developed and, in some embodiments, dynamically updated for distinguishing signal from noise and performing mask-based noise reduction. Each frequency band may use a different GMM or share a GMM with other frequency bands. A GMM may be combined from two models, with one trained to model time-frequency points in which the target dominates and another trained to model time-frequency points in which the noise dominates. Dynamic updates of a GMM may be performed using an expectation-maximization algorithm in an unsupervised fashion.

Abstract: A microphone system has a base coupled with first and second microphone apparatuses. The first microphone apparatus is capable of producing a first output signal having a noise component, while the second microphone apparatus is capable of producing a second output signal. The first microphone apparatus may have a first back-side cavity and the second microphone may have a second back-side cavity. The first and second back-side cavities may be fluidly unconnected. The system also has combining logic operatively coupled with the first microphone apparatus and the second microphone apparatus. The combining logic uses the second output signal to remove at least a portion of the noise component from the first output signal.

Abstract: Techniques are described herein that use sensors (e.g., microphones) for noise reduction in a mobile communication device. For example, one technique enables a first sensor that is initially configured to be a speech sensor to be used as a noise reference sensor. This technique also enables a second sensor that is initially configured to be a noise reference sensor to be used as a speech sensor. Another technique enables a primary sensor and/or a secondary sensor in a handset of a mobile communication device to be used as a speech sensor while a sensor in a headset of the mobile communication device is used as a noise reference sensor, or vice versa. In yet another technique, a secondary sensor in a mobile communication device is configured to be a directional sensor.

Abstract: Described herein are multi-channel noise suppression systems and methods that are configured to detect and suppress wind and background noise using at least two spatially separated microphones: at least one primary speech microphone and at least one noise reference microphone. The multi-channel noise suppression systems and methods are configured, in at least one example, to first detect and suppress wind noise in the input speech signal picked up by the primary speech microphone and, potentially, the input speech signal picked up by the noise reference microphone. Following wind noise detection and suppression, the multi-channel noise suppression systems and methods are configured to perform further noise suppression in two stages: a first linear processing stage that includes a blocking matrix and an adaptive noise canceler, followed by a second non-linear processing stage.

Abstract: Ambient sound is masked by receiving an audio signal, monitoring an acoustic signal that includes components of both the ambient sound the audio signal, determining a sound level sufficient to at least partially mask the ambient sound, and reproducing the received audio signal to produce an output acoustic signal at the determined sound level.