JOURNAL ARTICLE

Wavelet denoising method based on improved threshold function

Kezhong SunYingchun LuLiansheng HuangXiaojiao ChenXiuqing ZhangShiying He

Year: 2022 Journal:   2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

Abstract

Voice signal is disturbed by environmental noise during recording, which reduces the clarity of voice signal and affects the acquisition of useful signals. The wavelet threshold de noising method is widely used in the field of signal de noising. However, the hard/soft thresholding function in traditional wavelet transform has some problems such as discontinuity and fixed deviation when filtering. Therefore, an improved wavelet thresholding function method is proposed and applied in speech signal denoising. Through theoretical analysis and simulation, the results show that the improved wavelet threshold denoising algorithm can not only improve the signal-to-noise ratio (SNR) of the voice signal, but also largely avoid the distortion of the voice signal.

Keywords:
Wavelet Noise reduction Thresholding Computer science SIGNAL (programming language) Pattern recognition (psychology) Wavelet transform Artificial intelligence Wavelet packet decomposition Speech recognition Noise (video) Distortion (music) Step detection Computer vision Filter (signal processing) Telecommunications Image (mathematics)

Metrics

7
Cited By
0.48
FWCI (Field Weighted Citation Impact)
13
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing

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