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Matrix of Polynomials Model based Polynomial Dictionary Learning Method for Acoustic Impulse Response Modeling

Guan, J, Wang, X, Feng, P, Dong, J and Wang, Wenwu (2017) Matrix of Polynomials Model based Polynomial Dictionary Learning Method for Acoustic Impulse Response Modeling In: 18th Annual Conference of the International Speech Communication Association (Interspeech 2017 ), 20 - 24 August 2017, Stockholm, Sweden.


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We study the problem of dictionary learning for signals that can be represented as polynomials or polynomial matrices, such as convolutive signals with time delays or acoustic impulse responses. Recently, we developed a method for polynomial dictionary learning based on the fact that a polynomial matrix can be expressed as a polynomial with matrix coefficients, where the coefficient of the polynomial at each time lag is a scalar matrix. However, a polynomial matrix can be also equally represented as a matrix with polynomial elements. In this paper, we develop an alternative method for learning a polynomial dictionary and a sparse representation method for polynomial signal reconstruction based on this model. The proposed methods can be used directly to operate on the polynomial matrix without having to access its coefficients matrices. We demonstrate the performance of the proposed method for acoustic impulse response modeling.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Date : 24 August 2017
Funders : EPSRC
Copyright Disclaimer : Copyright 2017 The Author(s). Reproduced here with permission of The International Speech Communication Association (ISCA)
Uncontrolled Keywords : polynomial dictionary learning, sparse representation, acoustic modeling, denoising
Depositing User : Melanie Hughes
Date Deposited : 25 May 2017 12:49
Last Modified : 21 Feb 2018 12:16

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