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Speech Resampling Detection Based on Inconsistency of Band Energy

Zhifeng Wang1, Diqun Yan1,*, Rangding Wang1, Li Xiang1, Tingting Wu1

College of Information Science and Engineering, Ningbo University, Feng Hua Road, No. 818, Ningbo, 315211, China.

* Corresponding Author: Diqun Yan. Email: email.

Computers, Materials & Continua 2018, 56(2), 247-259. https://doi.org/10.3970/cmc.2018.02902

Abstract

Speech resampling is a typical tempering behavior, which is often integrated into various speech forgeries, such as splicing, electronic disguising, quality faking and so on. By analyzing the principle of resampling, we found that, compared with natural speech, the inconsistency between the bandwidth of the resampled speech and its sampling ratio will be caused because the interpolation process in resampling is imperfect. Based on our observation, a new resampling detection algorithm based on the inconsistency of band energy is proposed. First, according to the sampling ratio of the suspected speech, a band-pass Butterworth filter is designed to filter out the residual signal. Then, the logarithmic ratio of band energy is calculated by the suspected speech and the filtered speech. Finally, with the logarithmic ratio, the resampled and original speech can be discriminated. The experimental results show that the proposed algorithm can effectively detect the resampling behavior under various conditions and is robust to MP3 compression.

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Cite This Article

APA Style
Wang, Z., Yan, D., Wang, R., Xiang, L., Wu, T. (2018). Speech resampling detection based on inconsistency of band energy. Computers, Materials & Continua, 56(2), 247-259. https://doi.org/10.3970/cmc.2018.02902
Vancouver Style
Wang Z, Yan D, Wang R, Xiang L, Wu T. Speech resampling detection based on inconsistency of band energy. Comput Mater Contin. 2018;56(2):247-259 https://doi.org/10.3970/cmc.2018.02902
IEEE Style
Z. Wang, D. Yan, R. Wang, L. Xiang, and T. Wu, “Speech Resampling Detection Based on Inconsistency of Band Energy,” Comput. Mater. Contin., vol. 56, no. 2, pp. 247-259, 2018. https://doi.org/10.3970/cmc.2018.02902



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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