Design and Implementation of Speech Denoising Algorithm Based on Matlab
Speech signal is a continuous signal with time variation. Due to the influence of recording equipment, transmission channel and environmental noise, there are often various noises in the speech signal, such as white noise, noise burst, mechanical noise, etc. These noises not only degrade the quality of speech signals, but also adversely affect subsequent signal processing and analysis. Therefore, how to denoise the speech signal is one of the hot research directions at present. This article will introduce a speech denoising algorithm based on Matlab, and give the corresponding source code implementation.
- Fundamental
The speech denoising problem can be regarded as a signal estimation problem under certain constraints. The least squares method is a commonly used signal estimation method, which can be realized by constructing a cost function that minimizes the square sum of estimation errors. In the speech denoising problem, we assume that the noise signal is independently and identically distributed in the entire frequency domain, and has the characteristics of a Gaussian distribution. Therefore, when performing voice denoising, a low-pass filter can be used to filter the voice signal to weaken or eliminate unnecessary high-frequency signals, thereby achieving the purpose of reducing noise.
- algorithm design
In this paper, we use the frequency domain representation of the speech signal, that is, the time domain signal of the speech signal can be obtained by Fourier transform to the frequency domain signal. This representation allows for convenient filtering operations. Suppose the frequency domain representation of the speech signal is Y ( ω ) Y(\omega)