279 results about "Residual noise" patented technology

An active noise cancellation system includes a series of features for more effective cancellation, greater reliability, and improved stability. A particular feature adapted for headset systems includes locating a residual microphone radially offset from the center of a sound generator to detect a signal more similar to that incident upon the eardrum of the user. In addition, an open back headset design includes perforations on the side of the headset instead of the back, so that the perforations are less susceptible to inadvertent blockage. The system also includes a mechanism for detecting changes in the acoustic characteristics of the environment that may be caused, for example, by pressure exerted upon the earpieces, and that may destabilize the cancellation system. The system automatically responds to such changes, for example, by reducing the gain or the frequency response of the system to preserve stability. The system further includes other methods for detecting imminent instability and compensating, such as detecting the onset of signals within enhancement frequencies characteristic of the onset of instability, and adjusting the gain or frequency response of the system or suppressing the enhanced signals. The system further includes a mechanism for conserving battery life by turning the system off when sound levels are low, or adjusting the power supply to the system to correspond to the current power requirements of the system.

An adaptive signal processing system eliminates noise from input signals while retaining desired signal content, such as speech. The resulting low noise output signal delivers improved clarity and intelligibility. The low noise output signal also improves the performance of subsequent signal processing systems, including speech recognition systems. An adaptive beamformer in the signal processing system consistently updates beamforming signal weights in response to changing microphone signal conditions. The adaptive weights emphasize the contribution of high energy microphone signals to the beamformed output signal. In addition, adaptive noise cancellation logic removes residual noise from the beamformed output signal based on a noise estimate derived from the microphone input signals.

A subtractor subtracts an echo canceling signal Ĉ·yl(n−1) from a canceling error signal e(n) to estimate a residual noise to be silenced at the position of a microphone, and outputs a first basic signal x1(n) representing the residual noise. A first control circuit section generates a first control signal y1(n) based on the first basic signal x1(n) and a second basic signal x2(n) that is generated by delaying the first basic signal x1(n) by a time Z⁻ⁿ. A second circuit section generates a second control signal y2(n) based on the first basic signal x1(n) and an engine rotation signal.

The present technology provides adaptive noise reduction of an acoustic signal using a sophisticated level of control to balance the tradeoff between speech loss distortion and noise reduction. The energy level of a noise component in a sub-band signal of the acoustic signal is reduced based on an estimated signal-to-noise ratio of the sub-band signal, and further on an estimated threshold level of speech distortion in the sub-band signal. In embodiments, the energy level of the noise component in the sub-band signal may be reduced to no less than a residual noise target level. Such a target level may be defined as a level at which the noise component ceases to be perceptible.

The invention relates to: A method for estimating residual noise in the frequency range (271) of a desired part (240) of a signal to a corresponding apparatus and to a mobile telephone utilizing the method.

The object of the present invention is to generate a measure for the residual noise in a signal.

The problem is solved in that the amplitude of the signal (114) comprising the noise is modified, and the signal (114) is combined with the modified signal (115) to create a noise estimation measure (116).

The invention may e.g. be used in digital radio communications systems to contribute to the monitoring of link quality and therefore to improve payload throughput. One of the advantages of the invention is that an indication of link quality at an early stage in the receiver is provided.

A three dimensional area of quiet is created by an active noise cancellation system comprising a reference microphone receiving background noise and sending the noise signal to an adaptive active noise canceller. An adaptive filter system using weights updated by a least mean squares method or other method generates an anti-phase signal which is broadcasted to counteract the background noise. The resulting residual noise or residual signal is sent back to the adaptive active noise canceller to reset the weights of the adaptive filter.

A system is provided to automatically estimate performance of a receiver for receiving input signals, the input signals having a carrier frequency and a baud rate, from a channel in a communication system and the effect of highly correlated noise cancellation on performance of the receiver, while no active transmission is occurring on the channel, comprising: a digital front end in the receiver for receiving samples of the input signals; a predictor coupled to the digital front end for predicting highly correlated noise in a second sample of the input signal; and a subtraction unit coupled to the predictor for subtracting the predictor output from the second sample to determine residual noise in the second sample. Other systems and methods are disclosed.

A time-space domain video denoising method is provided which reduces video noise of different types. Noise is assumed to be real-world camera noise such as white Gaussian noise (signal-independent), mixed Poissonian-Gaussian (signal-dependent) noise, or processed (non-white) signal-dependent noise. This method comprises the following processing steps: 1) time-domain filtering on current frame using motion-compensated previous and subsequent frames; 2) restoration of possibly blurred contents due to faulty motion compensation and noise estimation; 3) spatial filtering to remove residual noise left from temporal filtering. To reduce the blocking effect, a method is applied to detect and remove blocking in the motion compensated frames. To perform time-domain filtering weighted motion-compensated frame averaging is used. To decrease the chance of blurring, two levels of reliability are used to accurately estimate the weights.

Disclosed is a 3D face capturing apparatus, method and computer-readable medium. As an example, the 3D face capturing method includes obtaining a face color image, obtaining a face depth image, aligning, by a computer, the face color image and the face depth image, obtaining, by the computer, a 3D face model by 2D modeling of the face color image and covering a modeled 2D face area on an image output by an image alignment module, removing by the computer, depth noise of the 3D face model, and obtaining, by the computer, an accurate 3D face model by aligning the 3D face model and a 3D face template, and removing residual noise based on a registration between the 3D face model and the 3D face template.

The invention discloses a voice denoising method and system based on L1/2 sparse constraint convolution non-negative matrix decomposition. In single-channel voice enhancement, it is assumed that noised voice signals v(i) are additively relevant to noise signals n(i) and voice signals s(i), i.e., v(i)=n(i)+s(i), and noise-base information is obtained by training specific noise by use of a CNMF method; and then by taking a noise base as prior information, a voice base is obtained by decomposing noised voice by use of a CNMF_L1/2 method, and finally, voice after denoising is synthesized. According to the method, correlation of voice between frames can be better described; and strong-sparse constraining is performed on a voice-base coefficient matrix by use of L1/2 regular item, and the voice after separation comprises less residual noise. Compared to conventional methods such as a spectral subtraction method, a wiener filtering method and a minimum mean square deviation logarithm domain spectrum estimation method and the like, the voice after enhancement can be understood more easily.

The invention discloses a device for eliminating echoes of mobile terminals, which comprises an echo canceller, an automatic gain controller and a noise suppression module, wherein the echo canceller is used for eliminating part of echo signals thereof according to the correlation between upstream signals and downstream signals and then sending output signals to the noise suppression module; the noise suppression module is used for receiving the output signals sent by the echo canceller, filtering noises of environment and residual noises not eliminated by the echo canceller and sending the output signals to the automatic gain controller; the automatic gain controller is used for comparing the downstream signals with the output signals sent by the noise suppression module in real time to conclude a decrement and adding the decrement to the upstream signals to eliminate the residual echoes thereof. The device for eliminating echoes of mobile terminals of the invention solves the problem of destroying normal voice signals when eliminating echoes, such as too great voice attenuation, changes of operation mode into simplex, discontinuous voices, distortion and so on.

The invention discloses an automobile active noise reduction method. The method comprises steps: a reference microphone is arranged in an engine compartment, and the reference microphone is used for acquiring engine compartment noise x(n); a loudspeaker is arranged in a driving compartment, and the loudspeaker is used for producing a sound signal y(n) for cancelling the engine compartment noise x(n); an error microphone is arranged in the driving compartment, and the error microphone is used for acquiring residual noise e(n); the engine compartment noise x(n) acquired by the reference microphone serves as an input signal, the residual noise e(n) acquired by the error microphone serves as an error signal, the signals are transmitted to an adaptive filter, a characteristic matrix W of the adaptive filter is updated according to an LMS algorithm, the sound signal y(n) produced by the loudspeaker is continuously adjusted, and the residual noise e(n) is made to be minimum. When the acoustic environment in the driving compartment changes, good noise reduction can still achieved, and thus, the method is not limited to specific automobile models, and the application range is large.

The invention relates to the field of digital image processing and can find use in suppression of noise in digital images, formed by high-energy radiation, including X-ray radiation. Specifically, the invention relates to a method for suppression of noise in digital x-ray images. The objective of the invention is to provide a method for noise suppression in digital X-ray images that has extended functionality, specifically, a method that makes it possible to reduce residual noise level and amount of artifacts in the form of discontinuities, directed along local orientation of object borders in textured image areas, to reduce residual LF noise level, and to eliminate over-smoothing (excessive filtering) of fine details. The technical innovation achieved is the improvement of digital image processing quality.

The invention discloses a single-channel monitor-free voice and noise separating method based on low-rank and sparse matrix decomposition. The method includes the steps of converting a time domain waveform of noise-contained voice to a time frequency domain via short-time Fourier transform to obtain a magnitude spectra with noises; decomposing the magnitude spectra with the noises into a sum of a noise magnitude spectra, a voice magnitude spectra and a residual noise magnitude spectra by a low-rank and sparse matrix decomposition algorithm; and finally reconstructing a voice time-domain waveform from the voice magnitude spectra via short-time Fourier transform. Without any priori information about voice and noise, the method is the single-channel monitor-free voice and noise separating method, pure voice can be separated from noise-contained voice by the aid of an algorithm, and the single-channel monitor-free voice and noise separating method is simple, effective, and particularly suitable for voice extraction in strong-noise environment.

The embodiment of the invention discloses an audio signal processing method and system, an audio interaction device and computer equipment. The method includes the following steps: performing echo cancellation on an echo signal in an acquired audio input signal to obtain an audio residual error signal of the audio input signal; performing noise cancellation on a noise signal in the audio residual error signal to obtain an audio enhancing signal after noise cancellation; and performing residual noise signal detection on the audio enhancing signal, and if a residual noise signal exists in the audio enhancing signal, filtering out the residual noise signal. By utilization of the method, the echo signal and the environmental noise signal in the audio input signal during audio interaction can be removed, detection and filtering of residual noise are realized at the same time, influence of environmental noise on an audio interaction process is effectively suppressed, and an effect of cancelling echoes and noise in the audio interaction process is improved, thereby improving the performance of an audio interaction device in cancelling echoes and noise.

The invention belongs to the field of active noise control and discloses a feedforward narrow band active noise control system with online secondary path identification. The feedforward narrow band active noise control system aims to solve the problem that system residual noise inhibition performance is seriously affected by auxiliary noise introduced into online secondary path identification in the feedforward narrow band active noise control system. The feedforward narrow band active noise control system comprises a signal synthesis subsystem, an online secondary path identification subsystem and a residual noise separation subsystem. The signal synthesis subsystem is used for generating secondary noise source signals with same frequency as sound signals in target noise. The online secondary path identification subsystem is capable of completing online secondary path identification in real time along with running of the narrow band active noise control system and used for inhibiting the target noise. The residual noise separation subsystem is capable of separating sound signals with frequencies in limited quantity from the residual noise. Energy of the introduced auxiliary noise is regulated by the separated residual sound signals, and consequently precision and quickness in online secondary path identification are improved, and influences of the introduced auxiliary noise on the residual noise are remarkably reduced.

The invention relates to an improved GSC self-adaptive speech enhancement method. An improved GSC self-adaptive speech enhancement system is used, a weight coefficient of a post filter is estimated based on the signal received by a microphone, incoherent noises in the signal are removed by using the post wiener filter, a self-adaptive blocking matrix is used for replacing a fixed blocking matrix in a conventional GSC structure so as to better block target signals and reduce cancellation of the target signals, the iterative mode of a self-adaptive algorithm is improved, the convergence rate and steady-state misadjustment signals and filter noise interference signals are balanced, and based on the characteristics of easy noise removal, small amount of calculation and the like of a spectral subtraction method, the possible residual noise signals can be further removed by using an improved spectral subtraction method. According to the invention, the method is capable of self-adaptive speech enhancement of signals at any angle and has a certain robustness for speech signal enhancement under a random environment, and the subsequent spectral subtraction method can be used for further removing the residual noises and improving the denoising capability of the entire system.

The invention discloses a speech enhancement processing method. The method comprises the steps that a training sample is formed based on speech data and noise data; the training sample is preprocessedto obtain a processed denoising sample; the denoising sample is divided into multiple batches of denoising samples, a WGAN model is trained by adopting each batch of the denoising sample until training of multiple batches of the denoising samples is completed, and a final WGAN-MBGD model is obtained; an enhanced speech signal is output by adopting the final WGAN-MBGD model. The speech enhancementprocessing method has the advantages that the unstable adversarial network gradient is generated, the rate of convergence is quicker, the small-batch calculation is applied, the calculated amount isalso reduced, spectral subtraction factors and spectral lower limit factors are introduced, and the residual noise is reduced by reducing the error among frequency spectrums.

Method for recovering target speech by extracting signal components falling in a speech segment, which is determined based on separated signals obtained through the Independent Component Analysis, thereby minimizing the residual noise in the recovered target speech. The present method comprises: the first step of receiving target speech emitted from a sound source and a noise emitted from another sound source and extracting estimated spectra Y* corresponding to the target speech by use of the Independent Component Analysis; the second step of separating from the estimated spectra Y* an estimated spectrum series group y* in which the noise is removed by applying separation judgment criteria based on the kurtosis of the amplitude distribution of each of estimated spectrum series in Y*; the third step of detecting a speech segment and a noise segment of the total sum F of all the estimated spectrum series in y* by applying detection judgment criteria based on a predetermined threshold value T that is determined by the maximum value of F; and the fourth step of extracting components falling in the speech segment from the estimated spectra Y* to generate a recovered spectrum group of the target speech for recovering the target speech.