基于小波变换的语音信号去噪算法优化
Optimization of Speech Signal Denoising Algorithm Based on Wavelet Transform
王红娟 1尚莹莹1
作者信息
- 1. 河南农业职业学院,河南 郑州 451450
- 折叠
摘要
深入研究基于小波变换的语音信号去噪方法,并针对传统方法在复杂噪声环境下处理效果不佳的问题,提出一种基于自适应阈值的小波变换去噪优化方法.首先,分析小波变换去噪的基本原理.其次,深入研究自适应阈值技术的数学模型,并将其应用于小波变换,通过动态调整阈值来适应不同噪声环境的需求.最后,采用Aurora数据集进行实验验证.实验结果表明,该方法能够有效去除噪声.
Abstract
This article delves into speech signal denoising methods based on wavelet transform, and proposes an adaptive threshold based wavelet transform denoising optimization method to address the problem of poor processing performance of traditional methods in complex noisy environments. Firstly, analyze the basic principle of wavelet transform denoising. Secondly, conduct in-depth research on the mathematical model of adaptive threshold technology and apply it to wavelet transform, dynamically adjusting the threshold to meet the needs of different noise environments. Finally, experimental validation was conducted using the Aurora dataset. The experimental results show that this method can effectively remove noise.
关键词
小波变换/语音去噪/自适应阈值/语音信号Key words
wavelet transform/speech denoising/adaptive threshold/speech signal引用本文复制引用
出版年
2024
NETL
NSTL
万方数据