提出了一个基于最小统计及谱减法的语音增强方法。
In this paper, a speech enhancement approach using minimum estimate and spectral subtraction is proposed.
算法提高了谱减法的适用范围，还在一般谱相减方法的基础上提出了改进的谱相减算法。
The application range of the spectral subtraction is expanded by the new noise estimation method.
针对语音识别中的加性噪声进行研究，提出了动态自适应多模板谱减法和多模板谱加训练补偿法。
This paper proposes two methods for speech recognition under the additive noise environment, namely dynamic adaptation multi model spectral subtraction and multi model spectral addition.
算法提高了谱减法的适用范围，还在一般谱相减方法的基础上提出了改进的谱相减算法。
An improved non-linear spectral subtraction algorithm is also put forward. The application range of the spectral subtraction is expanded by the new noise estimation method.
本文提出了基于谱熵和谱减法相结合的带噪语音端点检测改进算法以及端点检测的判决准则。
In this paper, we propose a new approach based on spectral entropy and spectral subtraction for noisy speech endpoint detection, and discriminative rules with robustness.
第二阶段，提出了经过修改的谱减法算法，用于提取房颤信号。
Then, a modified spectral subtraction approach was proposed to extract the atrial fibrillation signal.
第二阶段，提出了经过修改的谱减法算法，用于提取房颤信号。
Then, a modified spectral subtraction approach was proposed to extract the atrial fibrillation signal.
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