A New Voice Activity Detection Method Using Maximized Sub-band SNR

摘要：

This paper presents a novel voice activity detection (VAD) method using Maximum Values of Sub-band SNR (MVSS) as the detection feature. The proposed new feature MVSS has different distributions between speech and non-speech signal, which is helpful for separating the speech signal from heavy noise. An adaptive threshold is applied to improve VAD accuracies and track the noisy signal rapidly without complex computation. Experimental results show that the proposed method achieves better performance than the conventional ETSI AMR VADs under the NOISEX 92 database.

作者: Weiwu Jiang Wai Kit Lo Helen Meng

作者单位: The Chinese University of Hong Kong

会议类型: 国际会议

会议名称: 第十届中国虚拟现实年会

会议地点: 上海

会议语种:英文

页码: 80-84

在线出版日期: 2010-10-20（万方平台首次上网日期，不代表论文的发表时间）