DocumentCode
624680
Title
Pitch detection using EMD-based AMDF
Author
Yuan Zong ; Yumin Zeng ; Mengchao Li ; Rui Zheng
Author_Institution
Sch. of Phys. & Technol., Nanjing Normal Univ., Nanjing, China
fYear
2013
fDate
9-11 June 2013
Firstpage
594
Lastpage
597
Abstract
This paper presents a new modified average magnitude difference function (AMDF) based on empirical mode decomposition (EMD) for pitch detection. We call it EMD-based AMDF (EMDAMDF). EMDAMDF inherits lots of advantages successfully from the conventional AMDF and eliminates the falling trend of the AMDF adaptively by means of EMD. Based on EMDAMDF, an effective pitch detection algorithm is proposed. The simulated results on Keele pitch reference database shows that the performance of the proposed EMDAMDF based pitch detection algorithm is obviously better than the original AMDF and its improvements (such as CAMDF and EAMDF) based algorithms.
Keywords
audio databases; spectral analysis; speech processing; CAMDF based algorithm; EAMDF based algorithm; EMD-Based AMDF; EMDAMDF based pitch detection algorithm; Keele pitch reference database; empirical mode decomposition; modified average magnitude difference function; Accuracy; Databases; Detection algorithms; Empirical mode decomposition; Market research; Signal to noise ratio; Speech; AMDF; EMD; EMDAMDF; pitch detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4673-6248-1
Type
conf
DOI
10.1109/ICICIP.2013.6568144
Filename
6568144
Link To Document