时域分析方法是最简单、最直观的方法，其中我们采用短时能量、短时过零率、短时自相关函数等方法来分析语音。
The time domain analysis is most simple and intuitionistic. The short-time energy, the short-time zero crossing rate and the short-time self-correlation are main analysis method in time domain.
通常的基于短时自相关的自适应线谱增强器（SABALSE）主要缺点是：输入信噪比低时，抑制高斯噪声性能差。
Traditional short-term autocorrelation-based adaptive line spectrum enhancer (SABALSE) becomes low in suppressing Gaussian noise when input signal-to-noise ratio becomes low.
对语音信号端点检测的主要方法，如基于短时能量的方法、基于HMM的方法、基于自相关相似距离的方法等进行了深入研究。
The main speech signal endpoint detection methods, such as short time energy based scheme, HMM based scheme, related alike scheme and so on are investigated deeply.
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