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Tytuł artykułu

A hybrid method of person verification with use independent speech and facial asymmetry

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Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In a person identification or verification, the prime interest is not in recognizing the words but determining who is speaking the words. In systems of person identification, a test of signal from an unknown speaker is compared to all known speaker signals in the set. The signal that has the maximum probability is identified as the unknown speaker. In security systems based on person identification and verification, faultless identification has huge meaning for safety. In systems of person verification, a test of signal from a known speaker is compared to recorded signals in the set, connected with a known tested persons label. There are more than one recorded signals for every user in the set. In aim of increasing safety, in this work it was proposed own approach to person verification, based on independent speech and facial asymmetry. Extraction of the audio features of person's speech is done using mechanism of cepstral speech analysis. The idea of improvement of effectiveness of face recognition technique was based on processing information regarding face asymmetry in the most informative parts of the face the eyes region.
Rocznik
Strony
91--99
Opis fizyczny
Bibliogr. 12 poz., rys., tab.
Twórcy
autor
  • Czestochowa University of Technology, Institute of Computer and Information Science
autor
  • Czestochowa University of Technology, Institute of Computer and Information Science
Bibliografia
  • [1] Kubanek M. Analysis of Signal of Audio Speech and Process of Speech Recognition. Computing, Multimedia and Intelligent Techniques, 2, pp 5564, 2006.
  • [2] Kubanek M. Method of Speech Recognition and Speaker Identification with use Audio-Visual Polish Speech and Hidden Markov Models. Biometrics, Computer Security Systems and Artificial Intelligence Applications, Saeed K., Pejas J., Mosdorof R., Springer Science + Business Media, New York,pp 45-55, 2006.
  • [3] Chu Wai C. Speech coding algorithms. Foundation and Evolution of Standardized Coders. A John Wiley & Sons, New Jersey 2000.
  • [4] Rabiner L., Yuang B. H. Fundamentals of Speech Recognition. Prentice Hall Signal Processing Series, 1993.
  • [5] Wiśniewski A. M. Hidden Markov Models in Speech Recognition. Bulletin IAiR WAT, 7,Wroclaw 1997 [In Polish].
  • [6] Kanyak M. N. N., Zhi Q., Cheok A. D., Sengupta K., Chung K. C. Audio-Visual Modeling for Bimodal Speech Recognition. Proc. Symp. Time Series Analysis, 2001.
  • [7] Bogert B. P., Healy M. J. R., Tukey J. W. The Frequency Analysis of Time-Series for Echoes. Proc. 2001 International Fuzzy Systems Conference, pp 2-9-243, 1963.
  • [8] Wahab A., See NG G., Dickiyanto R. Speaker Verification System Based on Human Auditory and Fuzzy Neural Network System. Neurocomputing Manuscript Draft, Singapore.
  • [9] Liu Y., Schmidt K., Cohn J., Mitra S. Facial Asymmetry Quantification for Expression Invariant Human Identification. AFGR02, pp 198-204, 2002.
  • [10] Liu Y., Weaver R., Schmidt K., Serban N., Cohn J. Facial Asymmetry: A New Biometric. CMU-RI-TR, 2001.
  • [11] Mitra S., Liu Y. Local Facial Asymmetry for Expression Classification. Proc. of the 2004 IEEE Conference on Computer Vision and Pattern Recognition CVPR'04, 2004.
  • [12] Rydzek S. A Method to Automatically Authenticate a Person Based on the Asymmetry Measurements of the Eyes and/or Mouth. PhD thesis, Czestochowa University of Technology, 2007.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-acecb582-526a-44c2-94e5-520da7c90cc1
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