Delayless soft-decision decoding of high-quality audio transmitted over awgn channels

Short-range wireless audio transmission with high quality on the one hand often encounters error-prone channels, while on the other hand decoding delay plays a critical role in the application. A lot of prior art in audio error concealment is either only intuitively motivated or adds too much delay to the transmission. In this paper we pro pose a framework for transmitted audio error concealment without any algorithmic delay. As a novelty, it strongly follows a Bayesian approach for quantized but uncompressed audio, which can in principle be applied to any type of wireless channel yielding some kind of reliability information. Two methods to compute audio prediction coefficients are presented, one based on the autocorrelation method, the other one on the normalized least-mean-square (NLMS) algorithm. Simulation results for additive white Gaussian noise (AWGN) channels show the significant effect of the proposed approaches.