333 results about "Microphone signal" patented technology

The invention discloses a KTV intelligent light control method and device. The method comprises the following steps: S1, extracting song feature data from a song requesting system, wherein the song feature data comprises low-frequency energy EL, a rhythm feature Tbeat, an emotion label Cemtion and a refrain time point tcorus; s2, generating a light theme template based on the Cemtion and the Tbeat, and setting a switching time point; s3, separating the microphone signal X (t) into a human voice track V (t) and an accompaniment track A (t) through a pre-trained real-time source separation model; s4, adjusting spotlight parameters according to the volume VdB and pitch change rate # imgabs0 # of the human voice track V (t), and driving an atmosphere lamp according to the frequency spectrum of the accompaniment track A (t); s5, acquiring a personnel distribution thermodynamic diagram H (x, y) through an infrared thermal imaging sensor, and acquiring an action amplitude parameter Mlevel through a millimeter wave radar; and S6, fusing personnel distribution and motion amplitude data. According to the invention, KTV intelligent light control can be carried out more intelligently.

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.

Engine order cancellation (EOC) systems generate feedforward noise signals based on engine or other rotating shaft RPM and use those signals and an adaptively configured W filter to reduce SPL in the vehicle cabin by emitting anti-noise via speakers. An EOC system can include a signal analysis controller for detecting non-stationary events such as speech based on parameters sampled from a current frame of an error signal output from microphones positioned at various locations of a vehicle passenger cabin. Upon detection, the signal analysis controller can mitigate the effects of the non-stationary event to prevent the EOC system from increasing noise or causing a post-echo in the passenger cabin that sounds like speech. For example, if speech is detected in a frame, adaptation can be frozen during the frame. Alternatively, the signal analysis controller can adaptively subtract a speech signal from the error microphone signal.

Some methods may involve receiving a first content stream that includes first audio signals, rendering the first audio signals to produce first audio playback signals, generating first calibration signals, generating first modified audio playback signals by inserting the first calibration signals into the first audio playback signals, and causing a loudspeaker system to play back the first modified audio playback signals, to generate first audio device playback sound. The method(s) may involve receiving microphone signals corresponding to at least the first audio device playback sound and to second through Nth audio device playback sound corresponding to second through Nth modified audio playback signals (including second through Nth calibration signals) played back by second through Nth audio devices, extracting second through Nth calibration signals from the microphone signals and estimating at least one acoustic scene metric based, at least partly, on the second through Nth calibration signals.

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.

The invention relates to a video conference echo suppression method based on a low-delay adaptive learning model. The method comprises the following steps: acquiring acoustic scene noise features, and matching a lightweight LSTM neural network model by using the acoustic scene noise features; the method comprises the following steps: collecting real-time sound signals of a video conference, preprocessing and extracting multi-modal features of the real-time sound signals; performing adaptive filtering by using an NLMS algorithm to estimate an echo path between a near-end microphone signal and a far-end reference signal of the real-time sound signal, performing convolution on the echo path and the far-end reference signal to generate an echo estimation signal, and subtracting the echo estimation signal from the near-end microphone signal to obtain a preliminary residual signal; learning a gain by using the lightweight LSTM neural network model, and further suppressing the residual signal by using the gain to obtain a time domain enhanced signal; comfortable noise is introduced, and incremental learning is adaptively triggered. And efficient linear and nonlinear echo cancellation is supported.

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.

Methods and systems are disclosed for a vehicle audio system including, in one example, a method for noise cancellation in a vehicle having a reference sensor configured to acquire a reference signal, a plurality of speakers configured to emit a noise cancellation signal, and a plurality of error microphones configured to acquire a residual signal. The method processes the reference signal with a time domain adaptive weight filter to produce the noise cancellation signal, estimates a frequency domain filtered virtual microphone signal from the noise cancellation signal and the residual signal, and a frequency domain filtered reference signal from the reference signal. The method decomposes the frequency domain filtered virtual microphone signal and the frequency domain filtered reference signal into a plurality of frequency domain subband signals, and updates the time domain adaptive weight filter based on a weight transformation of a plurality of frequency domain subband adaptive filter weights.

A voice activity detection method and system and a voice enhancement method and system are provided. A voice presence probability of a target voice signal present in microphone signals may be determined by calculating a linear correlation between a signal subspace where the microphone signals are located and a target subspace where the target voice signal is located. The voice enhancement method and system may be used to calculate filter coefficients based on the voice presence probability, so as to perform voice enhancement on the microphone signals. The calculation accuracy of the voice presence probability is improved, and the voice enhancement effect is also improved.

The invention relates to the technical field of acoustic signal processing, and discloses a motion state detection method and device based on a multi-sensor fusion signal and application, and the method comprises the steps: collecting an environment sound signal and a user motion vibration signal through at least two sound sensors disposed at different positions; carrying out signal preprocessing on the environment sound signal and the motion vibration signal respectively and then carrying out feature extraction; and performing motion mode classification based on a feature extraction result and outputting a motion state detection result. According to the invention, through a dual-microphone signal fusion technology, various motion states can be accurately identified, and motion speed estimation and environment safety early warning functions are realized. The technical problems that a traditional single sensor scheme is single in function and prone to noise interference are solved.

A method performed by a first device, which includes performing an audio call with a second device by transmitting a microphone signal as an uplink signal and receiving a downlink signal for driving a first speaker and while performing the audio call, performing a joint media playback session in which both devices independently stream a piece of media content for synchronous playback such that both devices receive an audio signal of the piece of media content for driving respective speakers at the same time, determining that a voice activity detection (VAD) signal indicates that the downlink signal includes speech, in response to determining that the VAD signal indicates that the downlink signal includes speech, processing the audio signal of the piece of media content by applying a scalar gain, and driving the first speaker with a mix of the downlink signal and the audio signal.

The invention relates to a vehicle system (7) for detecting relevant vehicles with right of way, as well as a corresponding method and a correspondingly equipped motor vehicle (1). The vehicle system (7) comprises a plurality of microphone devices (4) which, due to differently shaped receiving cones (6), have different frequency- and direction-dependent sensitivities (S). The vehicle system (7) is configured, upon receiving a signal tone sequence (18) emitted by a foreign vehicle, to determine a position and / or a speed vector of the foreign vehicle by evaluating corresponding different microphone signals from the microphone devices (4), and to determine a relevance of the foreign vehicle for the motor vehicle (1) based on the position and / or the speed vector, and optionally to output a corresponding control signal for controlling at least one device (3, 17) of the motor vehicle (1).

The invention provides a full-automatic wall surface acquisition device and a wall surface hollowing intelligent detection method, the device comprises a support structure for providing stable structure support and a control module, the support structure is provided with a traction and knocking module, a fan and a microphone, the traction and knocking module is used for knocking a wall surface, the fan is used for driving the microphone to rotate, and the microphone is used for driving the fan to rotate. The draught fan is used for providing negative pressure wind power so that the supporting structure can be tightly attached to the surface of the outer wall of a building, the microphone is used for recording wall surface knocking signals, and the control module is in signal connection with the traction and knocking module, the draught fan and the microphone, controls the traction and knocking module, the draught fan and the microphone and obtains collected signals of the microphone. According to the device, standardized and automatic knocking and signal acquisition can be realized, and the consistency and comparability of data are ensured.

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.

The invention discloses a signal processing method and device, a storage medium and electronic equipment, and relates to the technical field of audio processing. The method comprises the following steps: receiving a target audio signal; dividing the target audio signal into N sub-signals based on the signal type of the target audio signal; when the target audio signal is a microphone signal, respectively inputting S sub-signals greater than the first frequency division point in the N sub-signals into S loudspeakers for output, and inputting N-S sub-signals into the same loudspeaker for output; and when the target audio signal is a music signal, respectively inputting T sub-signals greater than the second frequency division point in the N sub-signals into T loudspeakers for output, and inputting N-T sub-signals into the same loudspeaker for output. The karaoke sound box solves the technical problem that when an existing karaoke sound box uses a single type of high-pitch loudspeaker, large dynamic human voice output during karaoke and high-frequency detail reduction during music playing cannot be met at the same time.

Microphone assembly (1) comprising at least one microphone capsule (2), preferably a MEMS microphone capsule, wherein the microphone assembly (1) comprises at least one electrical contacting means (3) for supplying voltage and / or for providing microphone signals, wherein the microphone assembly (1) comprises a first printed circuit board (4), on the upper side (5) of which the microphone capsule (2) is arranged, preferably fastened, wherein the first printed circuit board (4) comprises through-openings (6, 6a), characterized in that a bottom side (7) of the first circuit board (4) is connected to a second circuit board (9) comprising through-openings (8, 8a) in such a way that through-openings (6, 6a) of the first circuit board (4) and through-openings (8, 8a) of the second circuit board (9) form channels (10, 10a) designed for the passage of sound waves, and Channels (10, 10a) are formed which are spatially separated from one another by a web (11) arranged in the first circuit board (4) and a web (12) arranged in the second circuit board (9).

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.

Methods and systems for a vehicle audio system are disclosed. In one example, there is provided a method for noise cancellation in a vehicle having a physical microphone configured to acquire a physical microphone signal and a plurality of virtual microphones configured to acquire a residual signal, the plurality of virtual microphones configured to acquire the physical microphone signal, and the plurality of virtual microphones configured to acquire the residual signal. The method includes processing the physical microphone signal with an adaptive weight filter to estimate a virtual auxiliary path from the physical microphone to the plurality of virtual microphones, decomposing the residual signal and the physical microphone signal into a plurality of sub-band signals, determining a sub-band gradient for each sub-band, the method further includes determining a sub-band virtual path convergence rate based on a normalized step size for each sub-band, determining a sub-band virtual path for each sub-band based on the normalized step size and the sub-band gradient, and applying a weight transformation process to each sub-band virtual path to update the adaptive weight filter and validate the sub-band virtual path.

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.

A noise cancellation system for a vehicle takes microphone signals AS-n, generates a frequency domain representation of them and receives an operating signal OS-n which indicates an operating state of

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.

The invention provides a sound source positioning method and device, equipment and a medium, and the method comprises the steps: carrying out the sound collection of a detected sound source, and obtaining a multi-channel microphone signal; according to the multi-channel microphone signal, determining a predicted positioning feature, the predicted positioning feature representing a time difference of arrival (TDOA) of direct path propagation between the detected sound source and different microphones; determining a reference positioning feature corresponding to each candidate direction; and determining a target prediction feature from the plurality of reference positioning features according to the prediction positioning feature, and taking a candidate direction corresponding to the target prediction feature as a positioning result of the detected sound source, thereby solving the technical problem of inaccurate sound source positioning in the prior art.

A method including receiving a microphone signal from a microphone, receiving a speaker signal from a speaker associated with the microphone, generating a speaker response relationship based on the microphone signal and the speaker signal, and generating an enhanced audio signal by modifying an echo associated with the microphone signal using a machine learning model and the speaker response relationship, the machine learning model being configured to differentiate between a first sound pattern and a second sound pattern.

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.

Some noise compensation methods involve: receiving a microphone signal corresponding to ambient noise from a noise source location in or near an audio environment; determining or estimating a listener position in the audio environment; and estimating at least one critical distance, the critical distance being a distance from the noise source location at which the directly propagated sound pressure equals the diffuse-field sound pressure. Some examples involve estimating whether the listener position is within the at least one critical distance, and performing the noise compensation method for the ambient noise based at least in part on the estimation of whether the listener position is within the critical distance.