针对低信噪比条件下的语音信号检测性能差的问题,提出了一种基于多窗口时频图的语音活动检测方法.首先,基于多窗口的时频分析计算得到语音信号的时频图,根据语音信号与背景噪声的特征差构造语音测试统计特征.其次,采用动态的双门限处理进行初步检测,在此基础上通过K均值聚类得到全局的双门限值.最后,根据序贯判决的思想进行检测得到该方法的判决结果输出.实验结果表明,低信噪比条件下,基于多窗口时频图的语音活动检测方法获得了良好的检测性能,并且在各种信噪比条件和背景噪声下,其性能总体优于传统的检测方法.该方法具有复杂度低、鲁棒性强、对不同种类语言适应性强等优点.“,”Aiming at the poor performance of speech signal detection at low signal-to-noise ratio (SNR),a method is proposed to detect active speech frames based on multi-window time-frequency (T-F) diagrams.First,the T-F diagram of the signal is calculated based on a multi-window T-F analysis,and a speech test statistic is constructed based on the characteristic difference between the signal and background noise.Second,the dynamic double-threshold processing is used for preliminary detection,and then the global double-threshold value is obtained using K-means clustering.Finally,the detection results are obtained by sequential decision.The experimental results show that the overall performance of the method is better than that of traditional methods under various SNR conditions and background noises.This method also has the advantages of low complexity,strong robustness,and adaptability to multi-national languages.