基于改进小波阈值函数在焊接环境下的语音降噪方法研究

Research on Speech Denoising Method in Welding Environment Based on Enhanced Wavelet Thresholding Function

焊接环境中的强噪声不仅会干扰语音通讯质量,还可能产生电磁干扰和多径声回音,严重影响语音的清晰度和可理解性。为解决焊接环境下语音交流困难的问题,展开了对焊接环境下语音降噪的研究。相比其他算法基于小波变换的语音降噪算法具有计算量小、不需要先验信息、同时可对本地化的时频特征进行多分辨分析等优点,被广泛应用于处理非平稳非稳态信号的降噪任务。基于小波变换的语音降噪算法,研究了不同的小波基、分解层数以及阈值函数的效果,发现传统的软阈值函数和硬阈值函数在去噪效果上并不理想。为了解决这个问题,提出一种自适应小波阈值函数,并在添加高斯白噪声的正弦信号、添加焊接噪声的英语语音和中文语音三个条件下分别进行了降噪处理实验。结果显示,相较于传统的固定阈值函数,文中提出的自适应阈值函数可以显著提高输出信噪比2 dB~4 dB,同时使信号的均方误差降低10%~35%,保留更多语音细节。这验证了自适应阈值函数在抑制焊接噪声的同时保护语音成分的优势。

In welding environments,strong noise not only interferes with the quality of speech communication but also generates electromagnetic interference and multipath sound echoes,severely affecting the clarity and intelligibility of speech.Due to its ability to perform localized time-frequency analysis,wavelet transform has been widely used for denoising tasks involving non-stationary and non-steady-state signals.This paper focuses on the issue of speech denoising in welding noise environments and investigates the effects of different wavelet bases,decomposition levels,and thresholding functions.It is found that traditional soft and hard thresholding functions do not yield satisfactory denoising results.To address this problem,we propose an adaptive wavelet thresholding function and conduct denoising experiments under three conditions:sine signals with added Gaussian white noise,English speech with added welding noise,and Chinese speech with added welding noise.The results demonstrate that compared to traditional fixed thresholding functions,the proposed adaptive thresholding function significantly improves the output signal-to-noise ratio by 2-4 dB and reduces the mean square error of the signal by 10-35%,preserving more speech details.This validates the advantage of the adaptive thresholding function in suppressing welding noise while preserving the speech components.