Optimization and implementation of digital signal processing technology in speech denoising algorithms
数字信号处理技术在语音降噪算法中的优化与实现

摘要

数字信号处理技术在语音降噪算法中的应用日益广泛，尤其是在提升语音信号清晰度和有效抑制噪声方面，发挥着重要作用。随着语音处理需求的多样化，传统的降噪方法已难以满足高效、精准的要求。本文探讨了数字信号处理技术在语音降噪中的优化路径，重点分析了滤波技术、时频分析方法及深度学习在降噪中的应用。通过对比不同优化算法的性能，提出了适合实际环境的降噪方案，以期为语音处理领域提供有效的技术支持。实验结果表明，优化后的算法在降噪效果和计算效率上均有所提升，为语音清晰度的提升提供了理论依据和技术保障。

Abstract

Digital signal processing technology is increasingly widely used in speech denoising algorithms, and it plays a crucial role especially in improving the clarity of speech signals and effectively suppressing noise. With the diversification of speech processing needs, traditional denoising methods have been difficult to meet the requirements of high efficiency and accuracy. This paper explores the optimization paths of digital signal processing technology in speech denoising, with a focus on analyzing the applications of filtering technology, time-frequency analysis methods, and deep learning in denoising. By comparing the performance of different optimized algorithms, a denoising scheme suitable for real-world environments is proposed, aiming to provide effective technical support for the field of speech processing. Experimental results show that the optimized algorithm has improved both in denoising effect and computational efficiency, providing a theoretical basis and technical guarantee for enhancing speech clarity.