Optimization and implementation of digital signal processing technology in speech noise reduction 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

随着语音通信和语音识别技术的广泛应用，语音信号的降噪问题日益成为研究的重点。数字信号处理技术（DSP）在语音降噪算法中具有重要的应用价值，通过各种算法优化手段，能够有效抑制背景噪声、提高语音信号的清晰度与可懂度。本文旨在探讨数字信号处理技术在语音降噪中的优化方法与实现路径，主要关注频域处理、时域滤波与自适应噪声控制等技术，通过对不同降噪算法的分析，提出适应性更强、降噪效果更佳的优化方案。实验结果表明，基于数字信号处理的语音降噪算法，能够显著改善语音质量，并具备较好的实时性与鲁棒性。

Abstract

With the widespread application of speech communication and speech recognition technologies, the problem of speech signal noise reduction has increasingly become a research focus. Digital Signal Processing (DSP) technology holds significant application value in speech noise reduction algorithms. Through various algorithm optimization methods, it can effectively suppress background noise and improve the clarity and intelligibility of speech signals. This paper aims to explore the optimization methods and implementation paths of digital signal processing technology in speech noise reduction, mainly focusing on technologies such as frequency-domain processing, time-domain filtering, and adaptive noise control. By analyzing different noise reduction algorithms, an optimization scheme with stronger adaptability and better noise reduction effect is proposed. Experimental results show that the speech noise reduction algorithm based on digital signal processing can significantly improve speech quality and has good real-time performance and robustness.