Short-term energy analysis based on wavelet neural network——Matlab implementation - Code World

Short-term energy analysis based on wavelet neural network——Matlab implementation

Language 2023-08-01 22:14:18 views: null

Short-term energy analysis based on wavelet neural network——Matlab implementation

Short-term energy is one of the commonly used characteristic parameters in speech signal processing, which can be used to describe the energy distribution of sound signals in the time dimension. It is widely used in speech signal recognition and speaker recognition. This article will introduce how to use wavelet neural network for short-term energy analysis, and give the source code of Matlab implementation.

To perform short-term energy analysis in Matlab, we need to preprocess the audio signal first, such as removing DC components, adding windows, etc. Next, we can calculate the energy value within each time window. Here we use wavelet neural network to classify short-term energy. Wavelet neural network is a deep learning network based on wavelet transform, which is similar to traditional neural network, but utilizes the excellent properties of wavelet transform to better process time series data.

The following is the code to implement the wavelet neural network in Matlab:

% 读入音频信号数据
[x, Fs] = audioread('test.wav');

% 预处理音频信号，去除直流分量、加窗
x = x

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Origin blog.csdn.net/CodeWG/article/details/132053387

Short-term energy analysis based on wavelet neural network——Matlab implementation

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