419 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 method that includes determining a set of one or more reverberation parameters of an extended reality (XR) environment in which a user is to participate, determining whether an audio source device is wirelessly communicatively coupled to send audio to an audio output device, in response to determining that the audio source device is not wirelessly communicatively coupled to the audio output device obtaining a microphone signal produced by a microphone of the audio source device, producing a reverberant audio signal from the microphone signal according to the set of one or more reverberation parameters, and sending the reverberant audio signal to drive a speaker driver of the audio source device.

The invention discloses a phase synchronization compensation algorithm for a bone conduction-air conduction mixed sound field of an earphone, and the algorithm comprises the steps: enabling a bone conduction vibration sensor signal # imgabs0 # and an air conduction microphone signal # imgabs1 # to pass through a wavelet packet decomposition module, obtaining a multi-resolution sub-band coefficient group # imgabs2 # and a multi-resolution sub-band coefficient group # imgabs3 #, and enabling the # imgabs4 # to be a sub-band index;

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.

The invention discloses a self-adaptive dual-microphone noise reduction method, which comprises the following steps of S10, detecting a stable noise segment, and calculating a characteristic value of a current frame of a main microphone signal m1; stable noise segment detection is carried out based on a characteristic value mode, and a characteristic value baseline value and a characteristic value threshold value are dynamically updated; s20, performing noise tracking on the stable noise segment based on the minimum differential microphone array output power, and performing real-time updating on the delay d of the auxiliary microphone signal m2 to obtain a delay gradual change result Dsm; s30, performing primary noise reduction and secondary noise reduction on the basis of the delay gradual change result Dsm, and outputting the result; according to the adaptive dual-microphone noise reduction method provided by the invention, real-time computing resource consumption is reduced, and meanwhile, instant, efficient and deep noise reduction can be realized.

The invention discloses an artificial cochlea self-sound restoration method and an artificial cochlea sound processor. The artificial cochlea self-sound restoration method comprises the following steps: dividing digital signals acquired by a bone conduction microphone and an air conduction microphone into signal frames; converting the signal frame from an initial time domain signal to an initial frequency domain signal; judging whether the microphone signal is self sound or not; when the signals collected by the bone conduction microphone and the air conduction microphone are self-sound, after the frequency domain signal frame of the bone conduction microphone and the frequency domain signal frame of the air conduction microphone are superposed, a new frequency domain signal is converted into a new time domain signal, and a signal frame after self-sound restoration is obtained; the sound of an implanter is collected from two channels of air conduction and bone conduction and is mixed and output, so that the accuracy of sound collection is improved.

In certain aspects, an active noise control (ANC) method and system for a headphone are disclosed. It is determined whether a music signal is played by a speaker of the headphone. Responsive to the music signal not being played by the speaker and a noise level of an ambient noise signal being greater than a noise threshold, a set of noise feedforward (FF) signals is obtained based on a set of FF microphone signals acquired by a set of FF microphones of the headphone. A noise feedback (FB) signal is obtained based on a first FB microphone signal acquired by a FB microphone of the headphone. A set of leakage monitoring parameters is obtained based on the set of noise FF signals and the noise FB signal. A set of FF filter parameters for a set of FF filters is adjusted based on the set of leakage monitoring parameters.

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.

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 direct sequence spread spectrum (DSSS) signals, generating first modified audio playback signals by inserting the first DSSS 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 DSSS signals) played back by second through Nth audio devices, extracting second through Nth DSSS signals from the microphone signals and estimating at least one acoustic scene metric based, at least partly, on the second through Nth DSSS signals.

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 method performed by a programmed processor of an electronic device. The device obtains an audio signal, obtains, using one or more microphones, a microphone signal that includes audio of an environment in which the electronic device is located. The device determines a context of the device, and selects a volume compensation model from several models based on the determined context. The device processes the audio signal according to the selected volume compensation model and the microphone signal, and uses the processed audio signal to drive one or more speakers of the device.

Disclosed in embodiments of the present application are a post-filtering method and system for a speech enhancement network. The technical solution provided in the embodiments of the present application comprises: acquiring a first speech masking value of a microphone signal output by an ENC module, wherein the first speech masking value is generated on the basis of the microphone signal and a loudspeaker signal to be played, and the microphone signal is aligned with the loudspeaker signal to be played; determining a first residual echo masking value of the microphone signal, calculating a noise masking value of the microphone signal on the basis of the first speech masking value and the first residual echo masking value, and performing overestimation on the first residual echo masking value to obtain a second residual echo masking value; and outputting a second speech masking value on the basis of the noise masking value and the second residual echo masking value, to synthesize a speech enhancement signal of the microphone signal on the basis of the second speech masking value. By using the foregoing technical means, echo residuals in a speech signal can be filtered out, reliability of the speech enhancement network is improved, the speech enhancement effect is improved, and voice call experience of users is optimized.

A system configured to perform neural sidelobe cancelling to achieve enhanced target speech separation. A device improves target speech separation by combining a fixed directional beamformer with a deep neural network (DNN) configured to (i) selectively enhance speech in one target direction, (ii) cancel speech from non-target directions, and (iii) cancel non-speech interference from all directions. By combining the directional output from the beamformer with raw microphone signals as input signals to the DNN, the DNN is given a directional cue with which to select the target speech. The DNN generates mask data representing the target speech using a combination of temporal convolutional blocks and causal self-attention blocks. For example, the DNN achieves low latency by processing a large number of short frames, while the causal self-attention blocks smooth the output and reinforce local consistency of speech.

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.

The invention provides a signal data synchronization method for a multi-microphone array, and the method comprises the steps: generating a digital synchronization signal through a main control processing unit, generating an analog synchronization signal through a digital-to-analog converter, and transmitting the analog synchronization signal to each microphone array unit; each microphone array unit obtains a respective synchronizing signal and transmits the synchronizing signal to the main control processing unit; the re-sampler adjusts the sampling interval of the synchronizing signal, and the phase discriminator detects the phase difference between the re-sampled synchronizing signal and the local high-frequency synchronizing signal and feeds back the phase difference to the re-sampler until the re-sampled synchronizing signal and the local high-frequency synchronizing signal have the same frequency and keep a stable phase difference; and performing mobile cross-correlation on the resampled synchronizing signal and a local high-frequency synchronizing signal in the delay estimator, and compensating delay deviation through a delayer. And the main control processing unit performs synchronization processing by using the local synchronization signal and the received return synchronization signal, and further adjusts the microphone signal of the array unit to achieve strict sample synchronization.

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.

A device may include a plurality of microphones, and a processor configured to extract a sound and a sound field from microphone signals of the plurality of microphones. The sound may be treated as near-field sound and the sound field may be treated as far-field sound. The device may adjust a strength of the sound based on a strength of the sound field and apply near-field head related transfer functions (HRTFs) to the sound. The device may apply far-field HRTFs to the sound field. The device may combine the near-field applied sound with the far-field applied sound field to generate spatial audio for playback through a plurality of speakers.

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.

A method performed by an audio system comprising a headset. The method sends a playback signal containing user-desired audio content to drive a speaker of the headset that is being worn by a user, receives a microphone signal from a microphone that is arranged to capture sounds within an ambient environment in which the user is located, performs a speech detection algorithm upon the microphone signal to detect speech contained therein, in response to a detection of speech, determines that the user intends to engage in a conversation with a person who is located within the ambient environment, and, in response to determining that the user intends to engage in the conversation, adjusts the playback signal based on the user-desired audio content.

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.