基于时频参数融合的自适应语音端点检测算法  

Self-adaptive voice activity detection algorithm based on fusion of time-frequency parameter

作　　者：王晓华[1] 屈雷[1] 

机构地区：[1]西安工程大学电子信息学院,西安710048

出　　处：《计算机工程与应用》2015年第20期203-207,212,共6页Computer Engineering and Applications

基　　金：西安工程大学控制科学与工程学科建设经费资助(No.107090811);国家自然科学基金(No.61301276)

摘　　要：为了解决低信噪比环境下传统的语音端点检测算法性能较差且不能自适应环境噪声,提出了一种基于时频参数融合的自适应语音端点检测算法。将对数能量与改进的Mel能量进行融合,获得了一种新的时频参数(TF),该参数能有效地区分语音段和噪声段。使用该参数在噪声段对阈值进行更新,采用门限检测法判定出语音端点。仿真实验表明,该算法具有较好的鲁棒性,且能够准确地检测出语音端点。当信噪比(SNR)为0 d B时,端点检测错误率仅为15%左右。In order to solve the inferior performance and sad self-adaptive of the traditional voice activity detection algo-rithm in an environment with low Signal to Noise Ratio（SNR）, a new self-adaptive voice activity detection algorithm based on TF parameters is put forward. After introducing the time-domain log-energy and improved mel-scale energy, the new Time-Frequency（TF）parameters are acquired by coalescing them, which make it possible for distinguishing speech from noise effectively. Then, the TF parameters are updated to predicate endpoint through the threshold test. Simulation experiments show that the algorithm has better robustness and more precise detection. When the SNR is 0 dB, the error rate of the algorithm is about 15%.

关 键 词：自适应 语音端点检测 Mel能量 时频参数 

分 类 号：TN912.3[电子电信—通信与信息系统]