Statistical Model-Based Voice Activity Detection Algorithm in DCT Transformation Domain

摘要：

A statistical model-based voice activity detection (VAD) algorithm in discrete cosine transformed (DCT) domain is proposed. This algorithm uses a Hidden Markov Model (HMM) with two states to estimate the probability of voice activity and employs the decision-directed (DD) parameter estimation method for the likelihood ratio test. Tiicu develops a smoothed likelihood ratio (SLR) instead of conventional likelihood ratio (LR) in order to alleviate the delayed term of LR. Simulation results show that the proposed VAD outperforms the G.729 B VAD and the traditional discrete Fourier transformation (DFT) based VAD in various noise environments.

关键词： voice activity detection discrete cosine transform decision-directed method smoothed likelihood ratio Hidden Markov model

作者: Ou Shifeng Gao Ying

作者单位: Institute of Science and Technology for Opto-electronic Information, Yantai University, Yantai, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Technology and Industrial Engineering(2010年信息技术与工业工程国际学术会议 ITIE 2010)

会议地点: 武汉

会议语种:英文

页码: 673-677

在线出版日期: 2010-06-06（万方平台首次上网日期，不代表论文的发表时间）