We describe an adaptive speech enhancement technique based on selecting a set of pre-computed FIR filters t o process the compressed short-time power spectral trajectories of noisy speech. The responses of the pre-computed filters depend only on the signal t o noise ratios (SNRs) and does not depend on the center frequency of the subbands. This allows for a compact design in which the estimate of the SNR at the particular frequency channel is used as the filter selection criterium for that sub-band.
Abstract-In this paper, we rederive recursive maximum likelihood (RML) for an autoregressive (AR) time series using the Levinson decomposition. This decomposition produces a recursive update of the likelihood function for the AR parameters in terms of the reflection coefficients, prediction error variances, and forward and backward prediction errors. A fast algorithm for this recursive update is presented and compared with the recursive updates of the Burg algorithm. The comparison clarifies the connection between Burg's algorithm and RML.where I is the identity matrix, and J is the exchange matrix
c i Logk -Colorado 305 Interlocken Pkwy. Broomfield. CO 80021 (303) 464-6628 (303) 464-6776 FAX d e p t @colorpdo.cirrus.comIn this paper, we experimentally measure the nonstationary (non-Toeplitz) correlation matrix associated with media noise and fit it, in a least squares sense, to a simple, closed form, theoretical conelation matrix associated with a parametric media noise model [I] which is experimentally justified by [2,3]. We obtain estimates of thc media noise p a r a t e r s by finding the best correla-
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