187 results about "Microphone signal" patented technology

A hearing aid system comprises a hearing aid, and a portable auxiliary device’ adapted to establish a communication link between them. The hearing aid comprises a microphone providing an electric input signal, a signal processor, and an output unit. The auxiliary device comprises a microphone providing an auxiliary electric input signal, and a user control interface allowing a user to initiate a specific calibration mode of operation of the hearing aid system. The signal processor of the hearing aid is configured to receive corresponding time segments of said electric input signal and said auxiliary electric input signal to provide an estimate of an acoustic transfer function from said microphone of said auxiliary device to said microphone of said hearing aid. A method of operating a hearing aid system is further disclosed. The invention may e.g. be used in various applications related to own voice detection and estimation.

This disclosure provides methods, devices, and systems for audio signal processing. The present implementations more specifically relate to speech enhancement techniques for separating microphone signals into speech, echo, and noise signals. In some aspects, a speech enhancement system may include a delay estimator and an acoustic echo and noise (AEN) decoupling filter. The delay estimator receives a microphone signal via a microphone and a far-end audio signal for output via a speaker and estimates a reference audio signal based on a delay between the microphone signal and the far-end audio signal. In some aspects, the AEN decoupling filter may determine a speech mask, an echo mask, and a noise mask based on the microphone signal and the reference audio signal and may suppress an echo component and a noise component of the microphone signal based on the determined set of masks.

Technologies directed to providing event detection using Antennas as Sensors (A2S) and microphone signals are described. One method of operating a device includes receiving audio data corresponding to audio captured by at least one microphone of the device, and impedance data from an Antenna as Sensor (A2S) system of the device, the impedance data is digital data representing impedance changes of an antenna captured by the A2S system. The method determines, using the audio data and the impedance data and a machine learning (ML) model, a user input event representing a physical interaction event with the device. The method performs an action in response to the user input event.

Various implementations include approaches for device control and / or sound source selection in audio devices. In some implementations, an audio device includes: an electro-acoustic transducer for providing an audio output; a set of microphones for detecting ambient sounds; and a processor coupled with the electro-acoustic transducer and the set of microphones, the processor configured to: evaluate microphone signals from the set of microphones to identify classes of sound sources in the ambient sounds; and adjust output of at least one class of the ambient sounds relative to another class of ambient sounds based on a user input.

Various implementations include a method of training a road noise cancelation (RNC) system for a vehicle, including: providing inputs to RNC system, the inputs obtained from: a set of ear-mounted microphones on a user, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, the inputs from the set of ear-mounted microphones on the user approximating a signal detected by the ears of the user; adapting a set of parameters in the RNC system defining an estimated signal detected at respective ears of the user based on the inputs; and generating at least one of the following for input during an operating mode of the RNC system: estimated ear microphone signals based on the adapted set of parameters, or a set of projection filters for use in determining an estimated ear signal at the respective ears of the user.

Embodiments of the present invention relate to the technical field of vehicle noise reduction, and disclosed are a noise reduction method, an electronic device, and a storage medium. In the embodiments of the present invention, the noise reduction method comprises: determining an optimal compensation parameter from a preset compensation parameter set on the basis of a current engine rotation speed, compensation parameters including parameters used for compensating for at least one of the following pieces of information: a reference signal, a filter coefficient, a loudspeaker signal, and a microphone signal; and generating a cancellation signal on the basis of the determined compensation parameter, the cancellation signal being used for cancelling current engine noise. The present invention is at least conducive to improving the noise reduction effect.

Operating an electrostatic acoustic device simultaneously as a speaker and as a microphone. The electrostatic acoustic device includes a membrane and an electrode disposed proximate to the membrane. An input varying audio signal is input to the electrostatic acoustic device. The membrane is configured to respond mechanically to a varying electric field responsive to the varying audio signal input. A portion of the input varying audio signal is tapped to produce a reference signal. A signal is detected responsive to motion of the membrane, to convert the signal to an output varying voltage signal. The output varying voltage signal is compared to the reference signal to produce a microphone signal. The microphone signal is responsive to motion of the membrane induced by air pressure variations of ambient sound.

The embodiment of the invention discloses a stereo echo cancellation method and terminal equipment. The method comprises the following steps: acquiring a plurality of first microphone signals and a plurality of loudspeaker signals; respectively carrying out time-frequency conversion, feature extraction, sub-band decomposition and feature fusion on the plurality of first microphone signals and the plurality of loudspeaker signals to obtain low sub-band combined features and high sub-band combined features; inputting the low sub-band combined features and the high sub-band combined features into a neural network model, and outputting a plurality of amplitude spectrum gain factors; a plurality of second microphone signals is generated based on the plurality of amplitude spectrum gain factors and the plurality of first microphone signals. According to the method and the device, the high-low sub-band combined features are obtained through feature fusion of the microphone signals and the loudspeaker signals, the echo-removed microphone signals are generated through the gain factors output by the neural network model, processing such as inter-channel decorrelation is not needed, the complexity of an algorithm is reduced, and the tone quality is improved.

The utility model relates to the technical field of microphones and loudspeakers, and discloses a wireless and wired microphone loudspeaker audio circuit which comprises a wired microphone module which comprises a wired signal input end, a first signal processing module and a wired signal output end. The first signal processing module is connected between the wired signal input end and the wired signal output end; the wireless microphone module comprises a wireless signal input end, a second signal processing module and a common signal output end, the second signal processing module comprises a first input end, a second input end and a first output end, the wireless signal input end is connected with the first input end, and the wired signal output end is connected with the second input end; the common signal output end is connected with the first output end. By designing the first signal processing module and the second signal processing module, the sound quality difference of wireless and wired microphone signals is effectively reduced, the phenomenon of serious signal attenuation can be avoided, and good sound quality is ensured.

The present invention improves the quality of signals of a virtual stereo microphone. This communication device comprises: a reception circuit that receives encoded information obtained by encoding signals of a stereo microphone; and a generation circuit that generates signals of a virtual stereo microphone configured from virtual microphones arranged on both sides of the stereo microphone through an extrapolation process performed on the phase spectrum of a decoded stereo signal obtained by decoding the encoded information in a frequency band in which the phase difference of signals between microphones constituting the stereo microphone is 2π or less.

An acoustic echo cancellation (AEC) system that dynamically controls an adaptation speed of an adaptive filter, enabling the adaptive filter to converge quickly while protecting near-end speech. For example, a device may control the adaptation speed of the adaptive filter to adapt quickly when near-end speech is not present and adapt slowly when near-end speech is present. The device controls the adaptation speed by dynamically determining step-size values and / or performing error normalization to limit the rate of adaptation. In some examples, the device determines the variable step-size parameter based on a relative strength of a microphone signal and a reference signal over time. For example, the device can compare current energy levels of the microphone signal and the reference signal to a range of energy levels to determine a microphone step-size value, a reference step-size value, and an AEC step-size value.

The invention discloses a hybrid echo cancellation method and system based on depth filtering and frequency band weighted loss, and the method comprises the steps: carrying out the preprocessing of a microphone signal and a reference signal through a low-complexity linear echo cancellation preprocessing module, and outputting an error signal; the three paths of input are sent to a hybrid conditional filter network (HHF-Net); complex domain time-frequency features are extracted through an encoder, and a complex time-frequency spectrum is recovered through a decoder after bottleneck layer modeling; a depth filtering module learns a complex filter coefficient for each time frequency unit, and suppresses echo through causal two-dimensional convolution; a mixed loss function training model of frequency band weighted amplitude loss and scale invariant signal-to-noise ratio (SI-SNR) loss is adopted. The problems of target voice information loss, poor output voice listening feeling and overlarge model parameter quantity in a double-talk scene are solved, an average opinion score (MOS) index is remarkably improved, and echo components are effectively inhibited while voice distortion is reduced.

A denoising method, an electronic device and a storage medium are provided. The denoising method includes: determining an optimal compensation parameter from a preset compensation parameter set according to a current engine speed; and generating a cancellation signal according to the determined compensation parameter. The compensation parameter includes a parameter configured to compensate for at least one of following information: a reference signal, a filter coefficient, a speaker signal, or a microphone signal. The cancellation signal is configured to cancel current engine noise. At least it is beneficial for improving the denoising effect.

The invention provides a howling suppression method and a howling suppression device. The howling suppression method comprises the following steps: executing a frequency domain transformation operation on a microphone signal to generate a frequency domain microphone signal corresponding to the microphone signal; dividing the frequency domain microphone signal into a plurality of sub-bands; detecting a first candidate howling frequency point where howling occurs by performing rough howling detection on the plurality of sub-bands; detecting a second candidate howling frequency point generating howling from a candidate howling band by executing fine howling detection on the candidate howling band comprising the first candidate howling frequency point; and performing howling suppression operation on the second candidate howling frequency point.

Audio systems, methods, and processor instructions are provided herein that detect voice activity of a user and provide an output voice signal. The systems, methods, and instructions receive a plurality of microphone signals and combine the plurality of microphone signals according to a first combination and a second combination. The first combination produces a primary signal having an enhanced response in a direction of a mouth of the user, and the second combination produces a reference signal having a reduced response in the direction of the mouth of the user. The primary signal and the reference signal are added and subtracted to produce a sum signal and a difference signal, respectively. The sum signal is compared to the difference signal and an output voice signal is provided based on the comparison.

The application discloses a directional sound pickup method and device and electronic equipment, and the method comprises the following steps: in step S1, a microphone frequency domain signal phase difference is calculated according to a target sound source azimuth angle, and the phase is compensated; in step S2, the compensated microphone signals are summed to obtain a first enhanced signal of a target signal. The application can break through the limitation of a sampling rate by linearly compensating the microphone phase in the frequency domain, so that the phases of the two microphone signals of the target direction are completely consistent, and the effect of a delay and sum algorithm is improved.

A system for acoustic echo cancellation comprising, obtaining on one or more near-end microphone signals and one or more playback signals, obtaining one or more subband signal sequences based on the one or more playback signals, processing the obtained one or more subband signal sequences with one or more subband adaptive filters, and reducing an echo in the obtained microphone signal via using outputs from the one or more subband adaptive filters.

The invention discloses an active sound production system and method for optimizing door closing sound quality, and relates to the field of simulation testing, a multi-dimensional sensing array module comprises a distance sensor, a three-axis acceleration sensor, a distributed microphone array and a temperature and humidity sensor, the sensors synchronously collect data, the data are transmitted through a CAN bus, and the timeliness and consistency of the data are ensured; the environmental acoustic modeling module is used for carrying out noise spectrum analysis on microphone signals, evaluating a vehicle door motion state, processing distance and acceleration data, calculating a temperature correction coefficient, dynamically adjusting sound pressure parameters, periodically updating an environmental parameter matrix and reflecting acoustic characteristics under different working conditions; and the PID-fuzzy hybrid algorithm module adopts a PID and fuzzy logic fusion framework, presets a target frequency, a maximum sound pressure level and a door closing speed threshold value, and calculates frequency, sound pressure and speed deviation, and the fuzzy logic module dynamically adjusts PID parameters according to the noise level, weights and superposes a proportional term, an integral term and a differential term, and is used for regulating and controlling the door closing sound quality.

Method in an electrical audio signaling circuit comprising a feedback loop (280) with a digital filter (285) coupled to a current-to-digital-to-analog converter (240, 320), the method comprising: providing (560, 625) an output signal from the current-to-digital-to-analog converter (240, 320) to analog elements of the electrical audio signaling circuit, wherein the output signal from the current-to-digital-to-analog converter (240, 320) is based on a reference signal input to the current-to-digital-to-analog converter (240, 320) while no output from the digital filter (285) is input to the current-to-digital-to-analog converter (240, 320); comparing (565, 630) an output signal of the electrical audio signaling circuit with a reference; and calibrating (570, 635) the electrical audio signal circuit, such that the output signal of the electrical audio signal circuit corresponds to the reference,wherein the calibration of the electrical audio signal circuit enables more precise control of a cutoff frequency of a microphone signal, while the output of the digital filter (285) is input into the current-to-digital-to-analog converter (240, 320).

Provided in the present application are a deep learning-based echo cancellation method, a device and a readable storage medium. A specific implementation solution comprises: acquiring a far-end microphone signal corresponding to a far-end room, and acquiring a near-end microphone signal corresponding to a near-end room; using the far-end microphone signal as a reference signal, acquiring a first compressed complex spectrum corresponding to the reference signal, and acquiring a second compressed complex spectrum corresponding to the near-end microphone signal; inputting the first compressed complex spectrum and the second compressed complex spectrum into a trained neural network model for echo cancellation processing, to output a near-end speech compressed complex spectrum; and performing an inverse short-time Fourier transform on the near-end speech compressed complex spectrum to obtain a pure near-end speech signal. In the implementation of the present application, the microphone signal of each far-end room serves as neural network reference information to restore the near-end pure speech signal, effectively suppressing echo components and thus implementing echo suppression of virtual spatial sound systems.

The present application relates to the technical field of attention mechanism, and discloses an interrogation psychological sensitive point detection method based on a timing attention mechanism, wherein a microphone signal is processed in a local time window through a short-time Fourier transform to generate a spatial covariance matrix time sequence under a symmetric positive definite manifold, and a relative displacement weighted kernel reflecting inter-frame time lag correlation is extracted from a timing attention model output; then, based on an affine invariant metric, a bisection vector is constructed to calculate a bisection cross-sectional curvature density to quantize the geometric inconsistency of the two; subsequently, the weighted kernel is adjusted by the index gate, the geometric aligned predicted spatial covariance matrix is obtained through cut space summation and exponential mapping, the actual and predicted matrix residuals are calculated by measuring the distance of the affine invariant metric, a single time sequence score is generated by energy proportion weighting, and finally, an adaptive threshold is constructed by using the median absolute deviation of the score and a threshold coefficient to screen sensitive moments that meet the conditions, thereby effectively improving the detection accuracy and scene adaptability.

A voice capture system is provided that includes a first voice beamformer and a second voice beamformer, a voice mixer, a voice-rejecting noise beamformer, a noise beamformer adjuster, an interference suppressor, and a speech enhancer. The first voice beamformer and the second voice beamformer and the voice mixer generate a voice-enhanced reference signal based on a first frequency-domain microphone signal and a second frequency-domain microphone signal. The voice-rejecting noise beamformer includes filter weights and generates a noise reference signal based on the first frequency-domain microphone signal and the second frequency-domain microphone signal. The noise beamformer adjuster adjusts one or more filter weights of the voice-rejecting noise beamformer to account for fit variation. The interference suppressor generates an interference-suppressed signal based on the voice-enhanced reference signal and the noise reference signal. The speech enhancer dynamically generates an output voice signal by applying a dynamic noise suppression signal to each frequency bin of the interference-suppressed signal.

This invention relates to the field of microphone technology, specifically to a method and system for suppressing echo and howling using a combination of bone conduction and air conduction microphones, applied to a closed-loop audio device including a combination microphone, a loudspeaker, and a feedback path estimation filter. The method involves acquiring a bone conduction signal as a target sound reference through a bone conduction acquisition channel, and acquiring a microphone signal containing target sound components and echo feedback components through an air conduction acquisition channel. The feedback path estimation filter is used to estimate the feedback path of the loudspeaker signal, generating a feedback estimation signal which is subtracted from the microphone signal to obtain an error signal. The error signal is then soft-limited to obtain a soft-limiting error signal, which forms the updated loudspeaker signal. A pre-whitening filter is established based on the soft-limiting error signal to obtain a pre-whitened microphone signal, a pre-whitened loudspeaker signal, and a pre-whitening prediction error signal. A stability detection signal is generated based on the difference between the error signal and the soft-limiting error signal. In a stable state, a normalized minimum mean square branch is used for updating; in a howling-prone state, an affine projection branch is used for updating, to track feedback path changes and suppress echo and howling.

The invention discloses a multi-channel active noise control method capable of reducing the calculated amount. The method comprises the following steps: (1) building a multi-channel ANC system, wherein the system comprises M (Mgt; 1) the number of the microphones; (2) measuring a secondary channel transfer function; (3) selecting Q (Qlt; m) microphones, calculating a weighting matrix by using the latest T signals collected by the microphone system, and weighting the signals of the selected Q microphones to obtain a signal of a Q channel for controlling the updating of a filter; (4) updating a control filter; and (5) calculating the output of the control filter, and inputting the output into the secondary sound source for playing. According to the method, the Q microphones are randomly selected in each period of time, and the Q microphone signals are weighted to obtain the update signal of the control filter, so that the calculation amount can be greatly reduced, and the global noise reduction effect can be obtained.

A sound source separation system is configured to perform blind source separation of individual sound source signals by an independent component analysis (ICA) method from a plurality of mixed signals in which two or more sound source signals are mixed. The sound source separation system includes an n number of microphones, where n≥2; a virtual microphone signal generator configured to generate, from output signals of the n number of the microphones, an m number of the virtual microphone signals that are output signals of the m number of virtual unidirectional microphones having directivities in different directions, where m>n; and an ICA processor configured to separate an L number of the sound source signals that are signals of the L number of different sound sources, by the ICA method, from the m number of the virtual microphone signals that are the plurality of the mixed signals, where L>n and L≤m.

A voice capture system including a first and second voice beamformer, a voice mixer, a voice rejected noise beamformer, a noise beamformer adjustor, a jammer suppressor, and a speech enhancer is provided. The first and second voice beamformer and the voice mixer generate a voice enhanced reference signal based on a first and second frequency domain microphone signal. The voice rejected noise beamformer includes filter weights and generates a noise reference signal based on the first and second frequency domain microphone signal. The noise beamformer adjustor adjusts the one or more filter weights of the voice rejected noise beamformer to account for fit variation. The jammer suppressor generates a jammer suppressed signal based on the voice enhanced reference signal and the noise reference signal. The speech enhancer dynamically generates an output voice signal by applying a dynamic noise suppression signal to each frequency bin of the jammer suppressed signal.

Some disclosed methods involve causing one or more loudspeakers in an audio environment to emit sound and receiving microphone signals from one or more microphones in the audio environment corresponding to an acoustic response of the audio environment to the emitted sound. Some disclosed methods involve detecting, by the control system, a change of the acoustic response of the audio environment. Some disclosed methods involve changing one or more aspects of media processing for media played back by one or more devices in the audio environment based, at least in part, on the change of the acoustic response of the audio environment. Alternatively, or additionally, some disclosed methods may involve changing the lighting in the environment, changing a gain of one or more microphone signals, locking or unlocking one or more devices, or combinations thereof, based at least in part on the change of the acoustic response.

A processor is configured to determine, using an adaptive filter algorithm, an adaptive feedforward acoustic noise cancellation, ANC, filter, filter a headphone internal microphone signal using a feedback filter to produce a feedback audio signal, drive a headphone speaker with the feedback audio signal, and modify the feedback filter based on a characteristic of the adaptive feedforward ANC filter. Other embodiments are also described.

An analysis system has at least one monitoring assembly that includes at least one microphone to monitor an acoustic field proximate the monitoring assembly. The at least one microphone produces at least one microphone signal responsive to the acoustic field. The analysis system further includes a data storage device configured to buffer the at least one microphone signal and an audio analysis system configured to analyze a content of the data storage device where the audio analysis system is configured to analyze the content of the buffer to process at least a sound into a response or action.