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Ulrik Kjems

Michael Syskind Pedersen

Jesper Bruun Jensen

Thomas Bo Elmedyb

Thomas Krogh Andersen

Richard Heusdens

Richard C Hendriks

Jesper Bünsow Boldt

Karsten Bo Rasmussen

Andreas Thelander Bertelsen

Thomas Kaulberg

Kim Spetzler Petersen

Thomas Behrens

Gudmundur Bogason

Søren Holdt Jensen

Mads Graesbøll Christensen

Cees H Taal

Richard Faculty Of Electrical Engineering Heusdens

Richard Faculty Of Electrical Engineering Hendriks

Mads Græsbøll Christensen

The present invention relates to a multi-band noise reduction system for digital audio signals producing a noise reduced digital audio output signal from a digital audio signal. The digital audio signal comprises a target signal and a noise signal, i.e. a noisy digital audio signal. The multi-band noise reduction system operates on a plurality of sub-band signals derived from the digital audio signal and comprises a second or adaptive signal-to-noise ratio estimator which is configured for filtering a plurality of first signal-to-noise ratio estimates of the plurality of sub-band signals with respective time-varying low-pass filters to produce respective second signal-to-noise ratio estimates of the plurality of sub-band signals. A low-pass cut-off frequency of each of the time-varying low-pass filters is adaptable in accordance with a first signal-to-noise ratio estimate determined by a first signal-to-noise ratio estimator and/or the second signal-to-noise ratio estimate of the sub-band signal.

Multi-band noise reduction system and methodology for digital audio signals

The present invention relates in one aspect to a microphone array signal processing system comprising a digital buffer coupled to a signal input and configured to store first and second digital audio signals. A beamformer analyzer is configured to, in response to a first voice trigger, determine noise statistics based on the first signal segment of the first digital audio signal and a first signal segment of the second digital audio signal. A coefficients calculator is configured to calculate a first set of fixed beamformer coefficients of a beamforming algorithm. The beamforming algorithm is configured for applying the first set of fixed beamformer coefficients to the first signal segments of the first and second digital audio signals retrieved from the digital buffer to produce a noise reduced digital audio signal.

Microphone array signal processing system

An audio processing device comprises a) at least one input unit for providing time-frequency representation Y(k,n) of an electric input signal representing sound consisting of target speech and noise signal components, where k and n are frequency band and time frame indices, respectively, b) a noise detection and/or reduction system configured to b1) determine an a posteriori signal to noise ratio estimate &#x3b3;(k,n) of said electric input signal, and to b2) determine an a priori target signal to noise signal ratio estimate &#x3b6;(k,n) of said electric input signal from said a posteriori signal to noise ratio estimate &#x3b3;(k,n) based on a recursive decision directed algorithm. The application further relates to a method of of estimating an a priori signal to noise ratio. The invention may e.g. be used for the hearing aids, headsets, ear phones, active ear protection systems, handsfree telephone systems, mobile telephones, etc.

Audio processing device and a method for estimating a signal-to-noise-ratio of a sound signal

A method comprises processing M subband communication signals and N target-cancelled signals in each subband with a set of beamformer coefficients to obtain an inverse target-cancelled covariance matrix of order N in each band; using a target absence signal to obtain an initial estimate of the noise power in a beamformer output signal averaged over recent frames with target absence in each subband; multiplying the initial noise estimate with a noise correction factor to obtain a refined estimate of the power of the beamformer output noise signal component in each subband; processing the refined estimate with the magnitude of the beamformer output to obtain a postfilter gain value in each subband; processing the beamformer output signal with the postfilter gain value to obtain a postfilter output signal in each subband; and processing the postfilter output subband signals to obtain an enhanced beamformed output signal.

Noise estimation for use with noise reduction and echo cancellation in personal communication

The application relates to a method of providing a speech intelligibility predictor value for estimating an average listener's ability to understand of a target speech signal when said target speech signal is subject to a processing algorithm and/or is received in a noisy environment. The application further relates to a method of improving a listener's understanding of a target speech signal in a noisy environment and to corresponding device units. The object of the present application is to provide an alternative objective intelligibility measure, e.g. a measure that is suitable for use in a time-frequency environment. The invention may e.g. be used in audio processing systems, e.g. listening systems, e.g. hearing aid systems.

Speech intelligibility predictor and applications thereof

A method estimates noise power spectral density (PSD) in an input sound signal to generate an output for noise reduction of the input sound signal. The method includes storing frames of a digitized version of the input signal, each frame having a predefined number N2 of samples corresponding to a frame length in time of L=N/sampling frequency. It further includes performing a time to frequency transformation, deriving a periodogram comprising an energy content |Y|from the corresponding spectrum Y, applying a gain function G(k,m)=f(&#x3c3;(km),&#x3c3;), |Y(k,m)|), to estimate a noise energy level |&#x174;|in each frequency sample, where &#x3c3;is the speech PSD and &#x3c3;the noise PSD. It further includes dividing spectra into a number of sub-bands, and providing a first estimate |{circumflex over (N)}|of the noise PSD level in a sub-band and a second, improved estimate |{circumflex over (N)}|of the noise PSD level in a subband by applying a bias compensation factor B to the first estimate.

Noise spectrum tracking in noisy acoustical signals

Disclosed is a method of reducing feedback in a hearing aid adapted to be worn by a user, the method comprising the step of: receiving an audio input signal in an input transducer in the hearing aid; wherein the method further comprises the steps of: transforming the input signal into the frequency domain; dividing the audio signal into a plurality of frequency bands; determining a threshold frequency over which a plurality of upper frequency bands lies; multiplying each of the plurality of upper frequency bands by a random phase, thereby obtaining a plurality of phase randomized upper frequency bands; synthesizing the plurality of phase randomized upper frequency bands and the lower frequency bands to an output signal; transforming the output signal into the time-domain; and transmitting the output signal to an output transducer of the hearing aid.

Method to reduce feedback in hearing aids

The invention relates to a method of identifying and correcting errors in a noisy binary mask. An object of the present invention is to provide a scheme for improving a binary mask representing speech. The problem is solved in that the method comprises a) providing a noisy binary mask comprising a binary representation of the power density of an acoustic signal comprising a target signal and a noise signal at a predefined number of discrete frequencies and a number of discrete time instances; b) providing a statistical model of a clean binary mask representing the power density of the target signal; and c) using the statistical model to detect and correct errors in the noisy binary mask. This has the advantage of providing an alternative and relatively simple way of improving an estimate of a binary mask representing a speech signal. The invention may e.g. be used for speech processing, e.g. in a hearing instrument.

Method of correcting errors in binary masks

This invention relates to a system () for determining directionality of a sound. The system () comprises a first audio device () placed on one side of a user's head () and having a first microphone unit () for converting said sound to a first electric signal, a second audio device () placed on the other side of the user's head () and having a second microphone unit () for converting said sound to a second electric signal, and comprises a transceiver unit () for interconnecting the first and second audio device and communicating the second electric signal to the first audio device (). The first audio device () further comprises a first comparator () for comparing the first and second electric signals and generating a first directionality signal from the comparison.

System and method for determining directionality of sound detected by as hearing aid

Disclosed is method of generating an audible signal in a hearing aid by estimating a weighting function of received audio signals, the hearing aid is adapted to be worn by a user; the method comprises the steps of:

Method of estimating weighting function of audio signals in a hearing aid

A digital filter includes at least a first and a second delayed summation line. One of the delay lines includes a warped finite impulse response (FIR) filter and the other line is a FIR filter. Midpoint elements from the first delayed summation line are used as input to the second delayed summation line. Output from the first delayed summation line is delayed with a delay corresponding to the total delay of the second delayed summation line and the delayed output from the first delayed summation line is added to output from the second delayed summation line to faun a new output.

Digital filter having a fir filter and a warped fir filter, and a listening device including such a digital filter

System and method for determining directionality of sound detected by a hearing aid

A device for detecting the presence of wind noise in an array of microphones including two or more separate sound inlet openings, and a sound to electrical converting element or microphone in relation to each sound inlet opening. The microphones each generate time dependent signals which are fed to a signal processing device that provides one or more output signals. The signal processing device has means for generating a time dependent cross correlation function between a first and a second microphone signal, and means for generating a signal corresponding to a time dependent auto correlation function of either the first or the second of the microphone signals. Further, the signal processing device has means for comparing the values of the auto correlation function and the cross correlation function and the means for comparing are arranged to detect the condition that the auto correlation function is substantially higher than the cross correlation function, whereby the condition is indicative of the presence of wind noise.

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Smørum, Denmark

Ulrik Kjems