An adaptive autoregressive pre-whitener for speech and acoustic signals based on parametric NMF

A common assumption in many speech and acoustic processing methods is that the noise is white and Gaussian (WGN). Although making this assumption results in simple and computationally attractive methods, the assumption is often too simple and crude in many applications. In this paper, we introduce a...

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Published inSpeech communication Vol. 151; pp. 9 - 23
Main Authors Jaramillo, Alfredo Esquivel, Nielsen, Jesper Kjær, Christensen, Mads Græsbøll
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2023
Subjects
Colored
Enhancement
NMF
Pitch
Pre-whitening
TOA
Pitch
Colored
Pre-whitening
Enhancement
NMF
TOA
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Abstract A common assumption in many speech and acoustic processing methods is that the noise is white and Gaussian (WGN). Although making this assumption results in simple and computationally attractive methods, the assumption is often too simple and crude in many applications. In this paper, we introduce a general purpose and online pre-whitener which can be used as a pre-processor with methods based on the WGN assumption, improving their reliability and performance in applications with colored noise. The pre-whitener is a time-varying filter whose coefficients are found using a parametric non-negative matrix factorization (NMF), based on autoregressive (AR) mixture modeling of both the noise component and the signal component constituting the noisy signal. Compared to other types of pre-whiteners, we show that the proposed pre-whitener has the best performance, especially in applications with non-stationary noise. We also perform a large number of experiments to quantify the benefits of using a pre-whitener as a pre-processor for methods based on the WGN-assumption. The applications of interest were pitch estimation and time-of-arrival (TOA) estimation, where the WGN assumption is very popular. •A pre-processing scheme which renders noise closer to white is introduced.•The introduced pre-whitener simplifies the computations of parameter estimation in colored noise.•Pre-whitening based on parametric NMF offers benefit in nonstationary scenarios.•Pre-whitening is preferred over enhancement as a pre-processor for parametric pitch estimation.•Time of arrival estimation accuracy gets also benefit from pre-whitening.
AbstractList A common assumption in many speech and acoustic processing methods is that the noise is white and Gaussian (WGN). Although making this assumption results in simple and computationally attractive methods, the assumption is often too simple and crude in many applications. In this paper, we introduce a general purpose and online pre-whitener which can be used as a pre-processor with methods based on the WGN assumption, improving their reliability and performance in applications with colored noise. The pre-whitener is a time-varying filter whose coefficients are found using a parametric non-negative matrix factorization (NMF), based on autoregressive (AR) mixture modeling of both the noise component and the signal component constituting the noisy signal. Compared to other types of pre-whiteners, we show that the proposed pre-whitener has the best performance, especially in applications with non-stationary noise. We also perform a large number of experiments to quantify the benefits of using a pre-whitener as a pre-processor for methods based on the WGN-assumption. The applications of interest were pitch estimation and time-of-arrival (TOA) estimation, where the WGN assumption is very popular. •A pre-processing scheme which renders noise closer to white is introduced.•The introduced pre-whitener simplifies the computations of parameter estimation in colored noise.•Pre-whitening based on parametric NMF offers benefit in nonstationary scenarios.•Pre-whitening is preferred over enhancement as a pre-processor for parametric pitch estimation.•Time of arrival estimation accuracy gets also benefit from pre-whitening.
Author Christensen, Mads Græsbøll
Jaramillo, Alfredo Esquivel
Nielsen, Jesper Kjær
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Snippet A common assumption in many speech and acoustic processing methods is that the noise is white and Gaussian (WGN). Although making this assumption results in...
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SubjectTerms Colored
Enhancement
NMF
Pitch
Pre-whitening
TOA
Title An adaptive autoregressive pre-whitener for speech and acoustic signals based on parametric NMF
URI https://dx.doi.org/10.1016/j.specom.2023.04.002
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