Abstract:
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 γ(k,n) of said electric input signal, and to b2) determine an a priori target signal to noise signal ratio estimate ζ(k,n) of said electric input signal from said a posteriori signal to noise ratio estimate γ(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.(Fig. 1A should be published)
Abstract:
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 γ(k,n) of said electric input signal, and to b2) determine an a priori target signal to noise signal ratio estimate ζ(k,n) of said electric input signal from said a posteriori signal to noise ratio estimate γ(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.(Fig. 1A should be published)
Abstract:
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.