Robust Voice Activity Detection Using the Combination of Short-Term and Long-Term Spectral Patterns

摘要：

　　In this paper,we present a robust voice activity detection (VAD) algorithm using the combination of short-term and long-term spectral patterns.We analyze the benefit of short-term and long-term spectral patterns,respectively,when applied to robust VAD.Based on the analysis,we find the combination of short-term and long-term spectral patterns can be used to achieve a higher VAD accuracy than one of them only in noisy environments.We evaluate its performance under four types of noises and six types of signal-to-noise ratio (SNR) conditions.Compared with standard VAD schemes,the evaluation almost demonstrates promising results with the proposed scheme being comparable or favorable over the whole test set for various criterions of the VAD evaluation.

关键词： short-term spectral patterns long-term spectral patterns robust voice activity detection peak-valley difference

作者: Yingwei Tan Wenju Liu

作者单位: National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China

会议类型: 国际会议

会议名称: Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)

会议地点: 长沙

会议语种:英文

页码: 428-435

在线出版日期: 2014-11-01（万方平台首次上网日期，不代表论文的发表时间）