speech feature peaks 语音特征峰
robust speech feature 稳健语音特征
extract speech feature 语音特征提取
speech feature parameter 语音特征参数
speech feature extraction 语音特征提取
speech feature parameters 语音特征参数
speech feature normalization 语音特征参数规整
feature-based speech recognition 基于特征的语音辨识
speech signal feature 语音特征参数
Based on deeply comprehension in the fundamentals of speech recognition, some kinds of widely-used speech feature coefficients are introduced firstly.
本文在深入理解语音识别基本原理的基础上，首先，介绍了几种被广泛应用的语音特征参数提取方法。
参考来源 - 基于WD/HMM的语音识别算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
During the experiment, MFCC (Mel Frequency Ceptral Coefficient) is adopted to speaker speech feature parameters.
实验中，采用美尔倒谱系数(MFCC)作为话者语音特征参数。
The chosen speech feature parameters have great effects on robustness and real-time of the speech recognition system.
特征参数的选取对整个语音识别系统的实时性、鲁棒性有很大的影响。
VAD algorithm based on RASTA-filter multi-dimensional speech feature and Support Vector Machine is presented. It applies to the speech detection under the low SNR conditions.
提出了一种基于RASTA滤波技术的多维语音特征和支持向量机分类的VAD算法，适用于低信噪比情况下的话音检测。
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