Speech signal detection in noisy environement using a local entropic criterion

A speech pause detection algorithm is an important and sensitive part of most single-microphone noise reduction schemes for enhancement of speech signals corrupted by additive noise as an estimate of the background noise is usually determined when speech is absent. An algorithm is proposed which detects speech pauses by adaptively tracking minima in a noisy signal's power envelope both for the broadband signal and for the high-pass and low-pass filtered signal. In poor signal-to-noise ratios (SNRs), the proposed algorithm maintains a low false-alarm rate in the detection of speech pauses while the standardized algorithm of ITU G.729 shows an increasing false-alarm rate in unfavorable situations. These characteristics are found with different types of noise and indicate that the proposed algorithm is better suited to be used for noise estimation in noise reduction algorithms, as speech deteriorations may thus be kept at a low level. It is shown that in connection with the Ephraim-Malah noise reduction scheme [1], the speech pause detection performance can even be further increased by using the noise-reduced signal instead of the noisy signal as input for the speech pause decision unit.

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Selection of Optimal Decomposition Level Based on Entropy for Speech Denoising Using Wavelet Packet

Jaffery¹,

Ahmad²,

Sharma³

2012

j bioinform intelli control

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Speech signal detection in noisy environement using a local entropic criterion

Cited by 6 publications

References 5 publications

Wavelet Based Clustering of Acoustic Emission Hits to Characterize Damage Mechanisms in Composites

Wavelet Based Clustering of Acoustic Emission Hits to Characterize Damage Mechanisms in Composites

Speech pause detection for noise spectrum estimation by tracking power envelope dynamics

Selection of Optimal Decomposition Level Based on Entropy for Speech Denoising Using Wavelet Packet

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