Spectral Subtractive-Type Algorithms for Enhancement of Noisy Speech: An Integrative Review

Abstract

-The spectral subtraction method is a classical approach for enhancement of speech degraded by additive background noise. The basic principle of this method is to estimate the short-time spectral magnitude of speech by subtracting estimated noise spectrum from the noisy speech spectrum. This is also achieved by multiplying the noisy speech spectrum with a gain function and later combining it with the phase of the noisy speech. Besides reducing the background noise, this method introduces an annoying perceptible tonal characteristic in the enhanced speech and affects the human listening, known as remnant musical noise. Several variations and implementations of this method have been adopted in past decades to address the limitations of spectral subtraction method. These variations constitute a family of subtractive-type algorithms and operate in frequency domain. The objective of this paper is to provide an extensive overview of spectral subtractive-type algorithms for enhancement of noisy speech. After the review, this paper is concluded by mentioning a future direction of speech enhancement research from spectral subtraction perspective.

A perceptually motivated stationary wavelet packet filter-bank utilizing improved spectral over-subtraction algorithm for enhancing speech in non-stationary environments

“…In recent years, a number of speech enhancement algorithms have been proposed which deal with the modifications of the spectral subtraction method to combat the problem of remnant musical noise artifacts [6][7][8] and improve the quality of speech in noisy environments. These frequency-domain speech enhancement algorithms constitute a family of spectral subtractive-type algorithms and are based on subtracting the estimated STSM of the noise from the STSM of noisy speech or by multiplying the noisy spectrum with gain functions and to combine it with the phase of the noisy speech [9].…”

Study on De-Noising Methods for Soil Compressive Stress Signal During Vibration Compaction

“…The fundamental principle of spectrum subtraction is that we subtract the power spectrum of the noise from that of the signal in frequency domain, then obtain the power spectrum estimation of the de-noised signal [5,[14][15][16]. It is essentially a modification of the amplitude of signal by subtracting from its power spectrum while retaining the original phase information.…”

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“…The LMMSE estimate of the channel attenuations h, from the received data y and the transmitted symbols X is [14]   …”

“…LSE [13], MMSE [14] and LMMSE [15] channel estimators are accustomed to give randomly varying channel state information (CSI) [15] to the transmitter by way of a feedback, as shown in Fig. 1.…”