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.