An iterative spatio-temporal speech enhancement algorithm for microphone arrays

We present anew spatio-temporal algorithm for speech enhancement using microphone arrays. Our technique involves the development of an iterative method for computing the generalized eigenvectors of the multichannel data as measured from the microphone array. Coefficient adaptation is performed using the spatio-temporal correlation coefficient sequences of the observed data. The technique avoids large matrix-vector multiplications; hence, the computation time and computational resource requirements are significantly smaller than those of competing methods. The technique is applicable to a wide variety of noise types, including stationary correlated noise and non- stationary speech-like (babble) background noise, without requiring any noise-dependent parameter settings.