Empirical mode decomposition and robust pitch detection based on recurrence analysis

被引:1
|
作者
Wang, Jingfang [1 ]
机构
[1] Hunan Int Econ Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China
关键词
Empirical Mode Decomposition; recursive analysis; elliptic filter; intrinsic mode function; pitch detection;
D O I
10.4028/www.scientific.net/AMM.303-306.1035
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A new pitch detection method is designed by the recurrence analysis in this paper, which is combined of Empirical Mode Decomposition (EMD) and Elliptic Filter (EF). The Empirical Mode Decomposition (EMD) of Hilbert-Huang Transform (HHT) are utilized tosolve the problem, and a noisy voice is first filtered on the elliptic band filter. The two Intrinsic Mode Functions (IMF) are synthesized by EMD with maximum correlation of voice, and then the pitch be easily divided. The results show that the new method performance is better than the conventional autocorrelation algorithm and cepstrum method, especially in the part that the surd and the sonant are not evident, and get a high robustness in noisy environment.
引用
收藏
页码:1035 / 1038
页数:4
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