一种基于灰关联分析法的语音激活检测算法

为在有色非高斯噪声背景下实时、有效地区分语音信号与各种背景噪声,提出了一种基于灰关联分析的语音激活检测(VAD)算法.该算法提取语音信号过零率、线性预测系数、倒谱系数和转移倒谱系数4种特征参数作为关联参数,通过跟踪语音与噪声灰关联度的变化确定判决门限,实现语音激活检测.仿真结果表明:该算法在无噪声背景中识别率为100%,在-5 dB噪声背景环境,识别率可达80%以上.此算法对有色非高斯背景噪声不敏感,而且计算简单、可靠性高,在语音激活检测中具有可行性.

Voice activity detection method based on gray correlation analysis algorithm

To real-time classify voice and noise under non-stationary nongaussian noise effectively,a voice activity detection(VAD) method based on the gray correlation analysis algorithm was proposed by analyzing ZCR(zero crossing vate),LPC(liner prediction cofficient),LPCC(liner prediction cepstrum coefficient) and LPCC(liner prediction cepstrum coefficient) characteristics from voice.Simulation results indicate that the detection rate reached 100% under the clean voice and more than 80% corresponding the noise level of-5 dB.This algorithm is effective under non-stationary nongaussian noise and the detection efficiency and performance are superior to other algorithms.