초록 ▼

A method determines a bias reduced noise and interference estimation in a binaural microphone configuration with a right and a left microphone signal at a time-frame with a target speaker active. The method includes a determination of the auto power spectral density estimate of the common noise form

A method determines a bias reduced noise and interference estimation in a binaural microphone configuration with a right and a left microphone signal at a time-frame with a target speaker active. The method includes a determination of the auto power spectral density estimate of the common noise formed of noise and interference components of the right and left microphone signals and a modification of the auto power spectral density estimate of the common noise by using an estimate of the magnitude squared coherence of the noise and interference components contained in the right and left microphone signals determined at a time frame without a target speaker active. An acoustic signal processing system and a hearing aid implement the method for determining the bias reduced noise and interference estimation. The noise reduction performance of speech enhancement algorithms is improved by the invention. Further, distortions of the target speech signal and residual noise and interference components are reduced.

대표청구항 ▼

1. A method for determining a bias reduced noise and interference estimation in a binaural microphone configuration, the method which comprises: receiving with the binaural microphone configuration a right microphone signal and a left microphone signal during a time-frame with a target speaker activ

1. A method for determining a bias reduced noise and interference estimation in a binaural microphone configuration, the method which comprises: receiving with the binaural microphone configuration a right microphone signal and a left microphone signal during a time-frame with a target speaker active;determining an auto power spectral density estimate of a common noise containing noise components and interference components of the right and left microphone signals; andmodifying the auto power spectral density estimate of the common noise by using an estimate of a magnitude squared coherence of the noise components and interference components contained in the right and left microphone signals determined during a time frame without a target speaker active. 2. The method according to claim 1, which comprises calculating the magnitude squared coherence estimate MSC as MSC=|S^v,n1⁢v,n2⁢|2S^v,n1⁢v,n1⁢S^v,n2⁢v,n2,where:Ŝv,n1v,n2 is a cross power spectral density of the estimated noise and interference components computed by a blocking matrix from filtered noise and interference components contained in the right and left microphone signals;Ŝv,n1v,n1 is the auto power spectral density of the noise and interference components contained in the right microphone signal filtered by the blocking matrix; andŜv,n2v,n2 is the auto power spectral density of the noise and interference components contained in the left microphone signal filtered by the blocking matrix. 3. The method according to claim 1, which comprises calculating the bias reduced auto power spectral density estimate Ŝññ of the common noise as Ŝññ=MSC·(Ŝv,n1v,n1+Ŝv,n2v,n2)+(1−MSC)·Ŝññ,where Ŝññ is the auto power spectral density estimate of the common noise. 4. A method for a bias reduced noise and interference estimation in a binaural microphone configuration with a right microphone signal and a left microphone signal, the method which comprises: at time frames with a target speaker inactive, calculating the bias reduced auto power spectral density estimate Ŝññ as Ŝññ=Ŝv,n1v,n1+Ŝv,n2v,n2 whereŜv,n1v,n1 is the auto power spectral density of the noise and interference components contained in the right microphone signal filtered by the blocking matrix; andŜv,n2v,n2 is the auto power spectral density of the noise and interference components contained in the left microphone signal filtered by the blocking matrix; andat time frames with the target speaker active, carrying out the method according to claim 1 to determine the bias reduced auto power spectral density estimate Ŝññ. 5. The method according to claim 4, which comprises determining the bias reduced auto power spectral density estimate in different frequency bands. 6. The method according to claim 1, which comprises determining the bias reduced auto power spectral density estimate in different frequency bands. 7. A speech enhancement method, which comprises: providing a speech enhancement filter; andperforming the method according to claim 1 for determining a bias reduced auto power spectral density estimate; andutilizing the bias reduced auto power spectral density estimate for calculating filter weights of the speech enhancement filter. 8. A speech enhancement method, which comprises: providing a speech enhancement filter; andperforming the method according to claim 4 for determining a bias reduced auto power spectral density estimate; andutilizing the bias reduced auto power spectral density estimate for calculating filter weights of the speech enhancement filter. 9. An acoustic signal processing system for a bias reduced noise and interference estimation at a timeframe with a target speaker active, comprising: a binaural microphone configuration including a right microphone and a left microphone respectively outputting a right microphone signal and a left microphone signal;a power spectral density estimation unit connected to receive the right and left microphone signals from said binaural microphone configuration and configured for determining an auto power spectral density estimate of a common noise containing noise and interference components of the right and left microphone signals; anda bias reduction unit connected to said power spectral density estimation unit and configured for modifying the auto power spectral density estimate of the common noise by using an estimate of a magnitude squared coherence of the noise and interference components contained in the right and left microphone signals determined at a time frame without a target speaker active. 10. The acoustic signal processing system according to claim 9, wherein the bias reduced auto power spectral density estimate Ŝññ of the common noise is calculated as Ŝññ=MSC·(Ŝv,n1v,n1+Ŝv,n2v,n2)+(1−MSC)·Ŝññ,whereMSC is the magnitude squared coherence of the noise and interference components;Ŝññ is the auto power spectral density estimate of the common noise estimate;Ŝv,n1v,n1 is the auto power spectral density of the noise and interference components contained in the right microphone signal filtered by a blocking matrix; andŜv,n2v,n2 is the auto power spectral density of the noise and interference components contained in the left microphone signal filtered by the blocking matrix. 11. The acoustic signal processing system according to claim 10, which comprises a speech enhancement filter with filter weights that are calculated by using the bias reduced auto power spectral density estimate. 12. The acoustic signal processing system according to claim 9, which comprises a speech enhancement filter with filter weights that are calculated by using the bias reduced auto power spectral density estimate. 13. A hearing aid, comprising the acoustic signal processing system according to claim 9. 14. A computer program product, comprising a non-transitory computer program with computer-executable software means configured to execute the method according to claim 1 when the computer program is loaded onto and executed in a processing unit.