Room impulse response estimation by iterative weighted L1-norm

Room impulse response estimation by iterative weighted L1-norm. Crocco, M. & Del Bue, A. In 2015 23rd European Signal Processing Conference (EUSIPCO), pages 1895-1899, Aug, 2015.

Paper doi abstract bibtex

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.

@InProceedings{7362713,
  author = {M. Crocco and A. {Del Bue}},
  booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},
  title = {Room impulse response estimation by iterative weighted L1-norm},
  year = {2015},
  pages = {1895-1899},
  abstract = {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.},
  keywords = {iterative methods;telecommunication channels;transient response;room impulse response estimation;iterative weighted L1-norm;RIR estimation;blind channel identification;iterative procedure;standard l1-norm constraint;iteration;l1-norm penalty approaches;Cost function;Microphones;Robustness;Estimation;Minimization;Europe;Signal processing;Room Impulse Response;Blind System Identification;Sparsity;Non-negative Priors;TDOA Estimation},
  doi = {10.1109/EUSIPCO.2015.7362713},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570099235.pdf},
}

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