[1]宗 源,李 平,曾毓敏,等.基于EMD的ACF基音检测改进算法[J].南京师大学报(自然科学版),2013,36(03):42-47.
 Zong Yuan,Li Ping,Zeng Yumin,et al.A Modified ACF Pitch Detection Algorithm Based on EMD[J].Journal of Nanjing Normal University(Natural Science Edition),2013,36(03):42-47.
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基于EMD的ACF基音检测改进算法()
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《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

卷:
第36卷
期数:
2013年03期
页码:
42-47
栏目:
物理学
出版日期:
2013-09-30

文章信息/Info

Title:
A Modified ACF Pitch Detection Algorithm Based on EMD
作者:
宗 源1李 平2曾毓敏1胡政权1李梦超1
(1.南京师范大学物理科学与技术学院,江苏 南京 210023) (2.泰州职业技术学院信息工程学院,江苏 泰州 225300)
Author(s):
Zong Yuan1Li Ping2Zeng Yumin1Hu Zhengquan1Li Mengchao1
(1.School of Physics and Technology,Nanjing Normal University,Nanjing 210023,China) (2.Department of Electronic and Information Engineering,Taizhou Polytechnic College,Taizhou 225300,China)
关键词:
基音经验模式分解自相关函数本征模式函数
Keywords:
pitchempirical mode decompositionautocorrelation functionintrinsic mode functions
分类号:
TN912
摘要:
针对传统的自相关函数基音检测算法容易出现倍频错误的问题,本文提出了一种基于经验模式分解的ACF基音检测改进算法.该改进算法利用EMD将一帧语音信号的ACF分解成多个本征模式函数和残余分量,同时根据IMF的累积能量分布情况找出含有基音信息的IMF,最后通过该IMF准确地估计出该语音帧的基音.仿真实验结果表明:本文所提算法性能明显优于传统ACF算法; 相比较于检测效果较好的WAC算法,本文所提算法的性能依然有了一定的提升.
Abstract:
This paper presents an Autocorrelation Function(ACF)pitch detection algorithm based on Empirical Mode Decomposition to conquer the defect of the conventional Autocorrelation Function which may generate double pitch.Firstly,the ACF of a speech frame is decomposed into a finite set of Intrinsic Mode Functions(IMFs)and a residual component.Then based on the distribution of accumulated energy of all IMFs,the IMF with the pitch information is selected successfully.Finally,the pitch is detected from the selected IMF accurately.The simulated pitch detection results show that the performance of the proposed algorithm is obviously better than that of the conventional ACF algorithm and slightly better than that of WAC algorithm which is outstanding.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2012-10-13.
基金项目:江苏省自然科学基金(BK2010546).
通讯联系人:曾毓敏,博士,教授,研究方向:语音信号处理.E-mail:zengyumin@njnu.edu.cn
更新日期/Last Update: 2013-09-30