Analysis of short-term average zero-crossing rate based on Matlab

Analysis of short-term average zero-crossing rate based on Matlab

I. Introduction
In the field of speech signal processing, the short-term average zero-crossing rate is a commonly used feature extraction method. It can be used in applications such as analysis, recognition and compression of speech signals. This article will introduce how to use Matlab to analyze the short-term average zero-crossing rate of speech signals, and attach the corresponding source code.

2. The principle of short-term average zero-crossing rate
The short-term average zero-crossing rate is a measure of the speed of change in the voice signal. It represents the number of times the signal passes through the zero point per unit time. Typically, higher frequency content in a speech signal results in a higher zero-crossing rate, while low-frequency content reduces the zero-crossing rate. Therefore, the phoneme information in the speech signal can be revealed by calculating the short-term average zero-crossing rate.

3. Matlab implementation

1. Preprocessing
   First, we need to read the speech signal into Matlab and perform preprocessing. Preprocessing includes steps such as file reading, sample rate conversion, and normalization.

% 读取语音文件
[y,fs] = audioread('speech.wav');

% 采样率转换
fs_new =