语音活动检测对方言辨识系统的影响研究  

Study on Influence of Voice Activity Detection for Dialects Identification System

作　　者：张宁[1] 顾明亮[1,2] 朱俊梅[2] 周杰[1] 

机构地区：[1]江苏师范大学物理与电子工程学院,江苏徐州221116 [2]江苏师范大学语言科学学院,江苏徐州221116

出　　处：《计算机技术与发展》2012年第11期73-76,共4页Computer Technology and Development

基　　金：国家自然科学基金项目(61040053);江苏省普通高校研究生科研创新计划资助项目(CXZZ11_0903)

摘　　要：分别把基于阈值判断和基于统计模型的语音活动检测(VAD)应用于汉语方言辨识系统中,对比了系统识别率及运算时间。其中基于能量、过零率等阈值判断的方法以其算法简单、计算量少的优点在高信噪比噪声环境下取得较好的效果,但在低信噪比噪声环境下准确性及鲁棒性急剧下降。在相同测试环境下,采用统计模型的DD+Hang-over算法取代传统经典阈值算法。实验表明,基于统计模型的算法在高斯混合模型(GMM)系统下运算时间稍长,但抗噪声性能明显优越于基于阈值判断的算法,尤其在低信噪比的加性噪声环境下效果更显著。Voice active detection （VAD） based on threshold judgement and statistical-model is used in Chinese dialect identification sys tem respectively. The recognition accuracy and computing time have also be compared. Threshold-based methods such as short term en- ergy has achieved good results in a high SNR noisy environment with its simple algorithm and less computation. Wbereas,its performance declines sharply in the low SNR environment. Statistical model-based method with DD＋ Hang-over is used instead of the traditional threshold-based methods under the same test environment. Experiments with the system of GMM show that although statistical model. based method with DD＋Hang-over takes more time,it has better anti-noise performance, especially in the low SNR environment.

关 键 词：方言辨识 语音活动检测 DD+Hang-over算法 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]