Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (5): 92-97.doi: 10.11896/jsjkx.210400071

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Identification Method of Voiceprint Identity Based on ARIMA Prediction of MFCC Features

WANG Xue-guang1, ZHU Jun-wen1, ZHANG Ai-xin2   

  1. 1 College of Criminal Justice,East China University of Political Science and Law,Shanghai 200052,China
    2 School of Cyber Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China
  • Received:2021-04-07 Revised:2021-07-01 Online:2022-05-15 Published:2022-05-06
  • About author:WANG Xue-guang,born in 1975,Ph.D,professor,is a member of China Computer Federation.His main research interests include computer networks,big data application and electronic data.
  • Supported by:
    National Key R & D Program of China(2017YFB0802103).

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Abstract: The key of vocal pattern recognition technology is to extract the speech feature parameters with representative speaker characteristics from the speech signal.Considering that most of the contemporary determinations are made using the experience of the identifiers,combined with MFCC features,this paper proposes an ARIMA prediction-based vocal identity identification me-thod on the basis of previous study to improve the accuracy of the comparison between the examination materials with year gaps and the samples.This method uses an autoregressive integrated moving average seasonal series based on the Mel inverse spectral coefficient vocalic identity identification method,makes linear least mean square estimation,and improves the resonance peak characteristics containing vowels and loud consonants.It is demonstrated that the prediction results of ARIMA time series are good,and the accuracy of text-independent identity identification based on Mel inverse spectral coefficients using the modified ARIMA is high,with a similarity of more than 60%.

Key words: ARIMA prediction, Identity identification, Mel cepstrum coefficient, MFCC characteristics

CLC Number: 

  • TP391
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[1] WANG Xue-guang, ZHU Jun-wen, ZHANG Ai-xin. Identification Method of Voiceprint Identity Based on MFCC Features [J]. Computer Science, 2021, 48(12): 343-348.
[2] . ARIMA-based Weighted Clustering Algorithm for Prediction of Nodes' Location in Ad-hoc Network [J]. Computer Science, 2012, 39(3): 47-50.
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