SPEECH ENHANCEMENT BASED ON SHORT-TIME SPECTRAL AMPLITUDE ESTIMATION WITH 2-CHANNEL BEAMFORMER

In this paper, a new spectral subtraction technique with two microphon e inputs is proposed. In conventional spectral subtraction using a sin gle microphone, the averaged noise spectrum is subtracted from the obs erved short-time input spectrum. This results in reduction of mean val ue of noise spectrum only, the component Varying around the mean value remaining intact. In the method proposed in this paper, the short-tim e noise spectrum excluding the speech component is estimated by introd ucing the blocking matrix used in the Griffiths-Jim-type adaptive beam former with two microphone inputs, combined with the spectral compensa tion technique. By subtracting the estimated short-time noise spectrum from the input spectrum, not only the mean Value of the noise spectru m but also the component varying around the mean value can be reduced. This method can be interpreted as a ''partial'' construction of the a daptive beamformer where only the amplitude of the short-time noise sp ectrum is estimated, while the adaptive beamformer is equivalent to th e estimator of the complex short-time noise spectrum. By limiting the estimation to the amplitude spectrum, the proposed system achieves bet ter performance than the adaptive beamformer in the case when the numb er of sound sources exceeds the number of microphones.