语音端点检测在实时语音截取中的应用  

Application of speech endpoint detection in real-time voice interception

作　　者：洪奕鑫 张浩川[1] 余荣[1] 吴哲顺 

机构地区：[1]广东工业大学自动化学院,广东广州510006

出　　处：《无线互联科技》2017年第22期50-53,共4页Wireless Internet Technology

基　　金：国家自然科学基金;项目编号:61422201

摘　　要：语音端点检测在语音识别系统中占有重要地位。针对在噪声多变的环境中实时截取完整语音信号存在困难,文章提出一种实时语音端点检测方法。该方法首先提取每帧信号的短时平均过零率与Mel频率倒谱系数;然后利用前N帧背景噪声的Mel频率倒谱系数对当前帧进行归一化,并以该特征矢量的L2范数作为另一特征;最后根据多特征分析对有效语音信号进行截取。实验结果表明,该方法在多变的噪声环境中,截取完整语音信号具有较高准确率。The speech endpoint detection plays an important role in speech recognition system. It is difficult to intercept the complete speech signal in real-time environment in noisy environment. This paper presents a real-time speech endpoint detection method. Firstly extracts the short-term average zero-crossing rate and Mel frequency cepstrum coefficient（MFCC）of each frame signal. Then, MFCC of the headmost N-frame background noise normalizes the current frame, a feature vector whose L2 norm as another feature. Finally, the effective speech signal was intercepted according to the multi-feature analysis. The experimental results show that the method has higher accuracy in intercepting the complete speech signal in the variable noise environment.

关 键 词：语音端点检测 MEL频率倒谱系数 短时平均过零率 多特征 

分 类 号：TN912.3[电子电信—通信与信息系统]