基于帧间相关性的语音活动检测方法

Voice activity detection method based on inter-frame correlation

为了提高统计模型似然比测试的语音活动检测(VAD)的检测性能,利用前后语音帧间存在的统计相关特性,提出一种改进VAD算法。通过前帧语音频谱分量对先验信噪比进行递归估计,然后利用前一帧的语音检测状态来设计判决阈值,建立了双阈值隐马尔可夫模型语音活动判决规则。实验表明,此帧间相关性VAD算法的检测指标值优于Sohn算法。

To enhance the detection performance of statistical model-based Voice Activity Detection（VAD） using likelihood ratio test,an improved VAD was proposed by utilizing the correlation between tandem speech frames.First a priori Signal-to-Noise Ratio（SNR） was estimated using recursive estimation method based on the result of the previous speech frame instead of the traditional decision-directed method.Secondly double thresholds were designed by depending on the previous frame＇s detention result.Finally a detection rule was presented based on two-state Hidden Markov Model（HMM） coupled with double thresholds.The experimental results show that the inter-frame correlation based VAD scheme gets better performance than the Sohn＇s VAD.