NDLI: A pitch tracking method mixing ACF & AMDF algorithms based on correlations

Content Provider	IEEE Xplore Digital Library
Author	Yingjie Yang Huanhuan Zhang Xiue Guo
Copyright Year	2011
Description	Author affiliation: Information Engineering, Northeast Dianli University, Jilin 132012, China (Yingjie Yang; Huanhuan Zhang; Xiue Guo)
Abstract	By analyzing the periodicity of autocorrelation functions (ACF) and average magnitude difference functions (AMDF), we present a pitch tracking method based on correlations of mixing ACF & AMDF algorithms. First, we calculate the normalized autocorrelation functions and normalized average magnitude difference functions, and then select a reasonable interpolation parameter from the experiments, and then last, we do linear interpolation. It effectively solves the problem that pitch period is difficult to extract, as the features are not obvious. Meanwhile, through simulation, we proved the accuracy of pitch tracking and the feasibility of implementation using this method for isolated words.
Starting Page	553
Ending Page	556
File Size	562029
Page Count	4
File Format	PDF
ISBN	9781612848792
e-ISBN	9781612848815
DOI	10.1109/IASP.2011.6109105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	short-time autocorrelation Correlation Accuracy Estimation Speech Feature extraction Educational institutions pitch period average magnitude difference functions Delay
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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