基于经验模态分解的语音端点检测算法研究的中期报告.docx

基于经验模态分解的语音端点检测算法研究的中期报告 摘要： 语音信号是一种典型的非平稳信号，语音端点检测是语音信号处理的重要基础。基于经验模态分解的语音端点检测算法是近年来的研究热点之一。本文介绍了基于经验模态分解的语音端点检测算法的研究背景、目的和意义，并对已有的相关研究进行了综述。同时，本文还提出了一种基于经验模态分解的语音端点检测算法，并对该算法进行了应用实验，实验结果表明该算法具有良好的性能和实用价值。 关键词：经验模态分解，语音端点检测，非平稳信号，语音信号处理，实用价值。 Abstract: Speech signal is a typical non-stationary signal, and speech endpoint detection is an important foundation of speech signal processing. The research of speech endpoint detection algorithm based on empirical mode decomposition is one of the hot topics in recent years. This paper introduces the research background, purpose and significance of speech endpoint detection algorithm based on empirical mode decomposition, and summarizes the relevant research. Meanwhile, this paper proposes a speech endpoint detection algorithm based on empirical mode decomposition, and carries out application experiments on the algorithm. The experimental results show that the algorithm has good performance and practical value. Keywords: empirical mode decomposition, speech endpoint detection, non-stationary signal, speech signal processing, practical value.