摘要
语音信号是一种非平稳信号,基音周期是语音信号最重要的参数之一,传统的基音检测方法存在一些缺陷。小波变换鲁棒性强、能很好地反映信号的时频特性,非常适合处理非平稳信号。为准确提取基音频率,提出了一种基于小波变换的基音周期检测方法。检测前在小波域上用Teager能量算子分离出语音信号的浊音段,然后对浊音段采用空域相关函数降噪,并用模极大值法提取其基音周期。结果表明,该方法比传统的自相关函数法具有更高的准确性和更好的鲁棒性。
Speech signal is a non-stationary signal and pitch period is one of the most important parameters of it. Traditional pitch detection methods have some defects. Wavelet transform has a strong robustness, and well reflects the time-frequency characteristics, is very suitable for non-stationary signal processing. In order to extract pitch frequencies accurately, a pitch period detection method based on wavelet transform is proposed. A voiced regions detection algorithm based on wavelet transform and Teager energy operator is proposed firstly. Then suppressing noise using spatial correlation function and estimating pitch period based on wavelet modulus maximum algorithm is presented. Finally experiments show that this algorithm has a better robustness and more precision compared with auto-correlated function.
出处
《电子测试》
2011年第7期11-15,共5页
Electronic Test
基金
山西省自然科学基金资助项目(2008011026-2)
关键词
小波变换
清浊音分割
基音检测
TEAGER能量算子
空域相关函数
wavelet transformation
voiced-unvoiced segmentation
pitch detection
teager energy operator
spatial correlation function
