Weighted noise subtraction and adaptive soft-thresholding approach to speech enhancement

Das, Somlal; Hamid, Md. Ekramul; Hirose, Keikichi; Molla, Md. Khademul Islam

doi:10.1109/iscas.2011.5938090

Cited by 1 publication

(1 citation statement)

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“…In the late 1990's a new signal decomposition called empirical mode decomposition was developed [18] and later applied into the solution of several signal processing applications including speech enhancement (e.g. [19]- [21]). The EMD performs decomposition without regard to the characteristics of the signal, thereby making it a logical fit for non-linear, nonstationary signals, i.e.…”

Section: Introductionmentioning

confidence: 99%

Speech enhancement of color noise using empirical mode decomposition

Koh

Rodriguez-Marek

2012

2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)

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This paper introduces a new speech enhancement algorithm, which is efficient for color noises such as pink and babble noises. The algorithm applies the minimum variance estimator (MVE) into each intrinsic mode function (IMF) obtained by the empirical mode decomposition (EMD). Typical signal subspace approaches to speech enhancement assume the corrupting noise is white, thereby making a pre-whitening step mandatory when faced with various color noises. The algorithm presented in this paper is applicable into color noises, such as pink and babble noises, without the need to apply the whitening process. This is a result of the noises' variances in each IMF signal showing smaller fluctuations than without the application of the EMD. Experimental data demonstrates the effectiveness of the algorithm to combat color noises.

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Section: Introductionmentioning

confidence: 99%