DocumentCode :
2251301
Title :
Pitch period estimation of voice signal based on EEMD and Hilbert Transform
Author :
Feng, Zuzhen ; Ding, Xuanhao ; Jiang, Yingchun
Author_Institution :
Sch. of Math. & Comput. Sci., Guilin Univ. of Electron. Technol., Guilin, China
Volume :
1
fYear :
2010
fDate :
6-7 March 2010
Firstpage :
365
Lastpage :
368
Abstract :
An improved Empirical Mode Decomposition (EMD) named Ensemble Empirical Mode Decomposition (EEMD) is introduced to analyse voice signal. A brief review of EEMD and Hilbert Transform (HT) is given, and a flowchart of EMD/EEMD algorithm is proposed. With EEMD, a voice signal can be decomposed into a complete and finite set of adaptive basis functions defined as Intrinsic Mode Functions (IMFs), which admit well-behaved HT. Then the final presentation of the results is an energy-frequency-time distribution designated as the Hilbert Spectrum (HS), from which the pitch period of the voice signal can be perfectly estimated. The final experimental results show that HS plays a good performance and makes better results in the voice signal pitch period estimation.
Keywords :
Hilbert transforms; audio signal processing; estimation theory; voice communication; EEMD; Hilbert Transform; Hilbert spectrum; energy-frequency-time distribution; ensemble empirical mode decomposition; intrinsic mode functions; pitch period estimation; voice signal pitch; Asia; Flowcharts; Frequency; Noise cancellation; Robotics and automation; Signal analysis; Signal design; Signal processing; Speech analysis; Speech processing; Hilbert transform; ensemble empirical mode decomposition; pitch period estimation; voice signal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
ISSN :
1948-3414
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
Type :
conf
DOI :
10.1109/CAR.2010.5456821
Filename :
5456821
Link To Document :
بازگشت