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General Information
    • ISSN: 1793-8244 (Print)
    • Abbreviated Title:  J. Adv. Comput. Netw.
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Professor Haklin Kimm
    • Executive Editor: Ms. Cherry Chan
    • Abstracting/ Indexing: EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Professor Haklin Kimm
East Stroudsburg University, USA
I'm happy to take on the position of editor in chief of JACN. We encourage authors to submit papers on all aspects of computer networks.

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).


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.

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