Contribution to Time and Frequency Analysis of Irregular Sleep Snoring

Abstract

The purpose of this paper is to give a summary
analysis of human snoring and its episodes. In particular, we
consider an acute snoring. In order to extract some frequency
information of snoring signal, we apply the Fast Fourier Transform
(FFT), Short Time Fourier Transform (STFT) algorithms,
Discrete Wavelet Technique, and Power Spectral Density (PSD).
Once irregular snoring characterized, we use a Voice Activity
Detection (VAD) for snoring episode detection. Furthermore,
we give comparative study of three types of thresholds that can
control the VAD approach, a fixed threshold, a soft threshold, and
a Gaussian threshold. Next, we use a Perceptual Evaluation of
Speech Quality (PESQ) method to evaluate the efficiency of the
VAD. We find that VAD based on Gaussian threshold is better.