• Sep 17, 2018 News!Welcome to 2019 4th International Conference on Information and Network Technologies (ICINT 2019), which will be held in Kyoto, Japan during May 25-27, 2019.   [Click]
  • Jul 04, 2018 News!JACN Vol.6, No.1 has been published with online version.   [Click]
  • May 22, 2018 News!JACN has been included in EBSCO database.
General Information
    • ISSN: 1793-8244
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Dr. Ka Wai Gary Wong
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET),  Electronic Journals Library, Ulrich's Periodicals Directory, EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Editor-in-chief
Dr. Ka Wai Gary Wong
Division of Information and Technology Studies, Faculty of Education, The University of Hong Kong.
It's a honor to serve as the editor-in-chief of JACN. I'll work together with the editors and reviewers to help the journal progress
JACN 2014 Vol.2(1): 67-70 ISSN: 1793-8244
DOI: 10.7763/JACN.2014.V2.84

A Precision, Large Scale, Anti-Noise Method for Correction of Speech Fundamental Frequency

Mang Zhao, Xiangning Chen, Yun Ge, Shuang Yu, and Ying Chen
Abstract—The speech fundamental frequency (F0) is an important speech parameter which has significant effect in domains such as voiceprint analysis, speaker recognition, voice conversion and etc. The existing extraction methods of speech fundamental frequency are not satisfactory in terms of accuracy due to the limitations of the methods themselves and noise so that correction is essential for high-quality analysis, recognition, conversion. The effect of existing correction methods rely heavily on the accuracy of first extraction, and are sensitive to noise. This article proposes a new correction method which makes use of cross-correlation of original signal and estimated signal to convert the difference between their frequencies to phase difference, thereby gains the accurate fundamental frequency by measuring this phase difference. Experiments indicate that the proposed method is effective when the estimated frequency ranges from 70% to 190% of the actual frequency, and keeps the average error within -50dB (0.35%) when signal to noise ratio (SNR) reduces to 3dB.

Index Terms—Speech fundamental frequency, precision correction, large scale, anti-noise, phase difference.

The authors are with the School of Electronic Science and Engineering, Nanjing University, Nanjing, China (e-mail: zhaomangzheng@ gmail.com, shining@nju.edu.cn, geyun@nju.edu.cn).

[PDF]

Cite:Mang Zhao, Xiangning Chen, Yun Ge, Shuang Yu, and Ying Chen, "A Precision, Large Scale, Anti-Noise Method for Correction of Speech Fundamental Frequency," Journal of Advances in Computer Networks vol. 2, no. 1, pp. 67-70, 2014.

Copyright © 2008-2018. Journal of Advances in Computer Networks.  All rights reserved.
E-mail: jacn@ejournal.net