Room impulse response estimation by iterative weighted L1-norm
Marco Crocco, Alessio Del Bue · 2015
This paper presents a novel method to solve for the challenging problem of acoustic Room Impulse Response estimation (RIR). The approach formulates the RIR estimation as a Blind Channel Identification (BCI) problem and it exploits sparsity and non-negativity priors to reduce illposedness and to increase robustness of the solution to noise. This provides an iterative procedure based on a reweighted l1-norm penalty and a standard l1-norm constraint. The proposed method guarantees the convexity of the problem at each iteration, it avoids drawbacks related to anchor constraints and it enforces sparsity in a more effective way with respect to standard l1-norm penalty approaches. Experiments show that our approach outperform current state of the art methods on speech and non-speech real signals.