Publication detail

Fast reconstruction of sparse relative impulse responses via second-order cone programming

RAJMIC, P. KOLDOVSKÝ, Z. DAŇKOVÁ, M.

Original Title

Fast reconstruction of sparse relative impulse responses via second-order cone programming

English Title

Fast reconstruction of sparse relative impulse responses via second-order cone programming

Type

conference paper

Language

en

Original Abstract

The paper addresses the estimation of the relative transfer function (RTF) using incomplete information. For example, an RTF estimate might be recognized as too inaccurate in a number of frequency bins. When these values are dropped, an incomplete RTF is obtained. The goal is then to reconstruct a complete RTF estimate, based on (1) the remaining values, and (2) the sparsity of the relative impulse response, which is the time-domain counterpart of the RTF. We propose two fast algorithms for the RTF reconstruction that solve a second-order cone program (SOCP), and show their advantages over the LASSO formulation previously proposed in the literature. Simulations with speech signals show that in terms of speed and accuracy, the proposed algorithms are comparable with the LASSO solution and considerably faster compared to the generic ECOS solver. The new algorithms are, moreover, easier to control through their parameters, which brings their improved stability when the number of reliable frequency bins is very low (less than 10%).

English abstract

The paper addresses the estimation of the relative transfer function (RTF) using incomplete information. For example, an RTF estimate might be recognized as too inaccurate in a number of frequency bins. When these values are dropped, an incomplete RTF is obtained. The goal is then to reconstruct a complete RTF estimate, based on (1) the remaining values, and (2) the sparsity of the relative impulse response, which is the time-domain counterpart of the RTF. We propose two fast algorithms for the RTF reconstruction that solve a second-order cone program (SOCP), and show their advantages over the LASSO formulation previously proposed in the literature. Simulations with speech signals show that in terms of speed and accuracy, the proposed algorithms are comparable with the LASSO solution and considerably faster compared to the generic ECOS solver. The new algorithms are, moreover, easier to control through their parameters, which brings their improved stability when the number of reliable frequency bins is very low (less than 10%).

Keywords

Beamforming; Relative Transfer Function; Relative Impulse Response; Sparsity; Proximal Algorithms; Convex Programming

Released

15.10.2017

Publisher

Institute of Electrical and Electronics Engineers Inc.

ISBN

978-1-5386-1631-4

Book

Proceedings of the 2017 Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

Pages from

364

Pages to

368

Pages count

5

BibTex


@inproceedings{BUT137930,
  author="Pavel {Rajmic} and Zbyněk {Koldovský} and Marie {Mangová}",
  title="Fast reconstruction of sparse relative impulse responses via second-order cone programming",
  annote="The paper addresses the estimation of the relative transfer function (RTF) using incomplete information. For example, an RTF estimate might be recognized as too inaccurate in a number of frequency bins. When these values are dropped, an incomplete RTF is obtained. The goal is then to reconstruct a complete RTF estimate, based on (1) the remaining values, and (2) the sparsity of the relative impulse response, which is the time-domain counterpart of the RTF. We propose two fast algorithms for the RTF reconstruction that solve a second-order cone program (SOCP), and show their advantages over the LASSO formulation previously proposed in the literature. Simulations with speech signals show that in terms of speed and accuracy, the proposed algorithms are comparable with the LASSO solution and considerably faster compared to the generic ECOS solver. The new algorithms are, moreover, easier to control through their parameters, which brings their improved stability when the number of reliable frequency bins is very low (less than 10%).",
  address="Institute of Electrical and Electronics Engineers Inc.",
  booktitle="Proceedings of the 2017 Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)",
  chapter="137930",
  doi="10.1109/WASPAA.2017.8170056",
  howpublished="electronic, physical medium",
  institution="Institute of Electrical and Electronics Engineers Inc.",
  year="2017",
  month="october",
  pages="364--368",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  type="conference paper"
}