PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Discrete cosine transform based de-noising of glottal pulses

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Reliable estimates of the glottal function are of major importance in speech/voice processing for the characterization of voicing conditions, description of various phonation types, and identification of their parameters. This paper presents a new method for de-noising glottal wavelets (Differentiated Glottal Volume Velocity Pulses) and separation of the noise component, based on an approximation of their Discrete Cosine Transform as a sum of Exponentially Damped Sinusoids. The identification of the Exponentials' parameters leads to convenient estimation of ''clean'' glottal wavelets and thus separation of noise disturbances. The method is compared to standard Low-pass filtering and Wavelet de-noising using Monte Carlo simulations on synthetic Liljencrants-Fant glottal pulse models. As shown, the method supercedes for lower SNRs. Moreover, the method does not require exact determination of control parameters thus offering ease of implementation.
Słowa kluczowe
Rocznik
Strony
35--43
Opis fizyczny
Bibliogr. 23 poz., tab., wykr.
Twórcy
autor
  • Laboratory of Electroacoustics, Electrical and Computer Engineering Dept., Polytechnic School, Aristotle University of Thessaloniki, Greece
  • Laboratory of Electroacoustics, Electrical and Computer Engineering Dept., Polytechnic School, Aristotle University of Thessaloniki, Greece
Bibliografia
  • [1] P. BADIN, E. CASTELLI, Y. P. T. NGOC, Acoustic transfer functions for vowels and consonants, Speech Maps (Esprit/br No 6975), Appendix D, 1–19 (1992).
  • [2] S. BURRUS, R. A. GOPINATH, H. GUO, Introduction to wavelets and wavelet transforms, Prentice Hall, New Jersey 1998.
  • [3] E. CASTELLI, P. BADIN, Time and frequency domain acoustic models of the vocal tract, Speech Maps (Esprit/br No 6975), Appendix B, 1-25 (1992).
  • [4] D. G. CHILDERS, C. K. LEE, Vocal quality factors: analysis, synthesis, and perception, JASA, 90, 5, 2394–2410, November (1991).
  • [5] D. G. CHILDERS, Speech processing and synthesis toolboxes, John Wiley & Sons, New York 2000.
  • [6] C. H. COKER, M. H. KRANE, B. Y. REIS, R. A. KUBLI, Search for unexplored effects in speech production, Proc. ICSLP, 1996.
  • [7] P. R. COOK, Identification of control parameters in an articulatory vocal tract model, with applications to the synthesis of singing, Ph.D. Thesis, Princeton, September 1991.
  • [8] L. HADJILEONTIADIS, C. LIATSOS, C. MAVROGIANNIS, T. ROKKAS, S. PANAS, Enhancement of bowel sounds by wavelet-based filtering, IEEE Trans. Biomedical Eng., 47, 7, 1–11, July (2000).
  • [9] Y. HUA, T. SARKAR, Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise, IEEE Trans ASSP, 38, 5, 814–824, May (1990).
  • [10] G. KALLIRIS, New techniques for restoration of speech and music, Ph.D. Dissertation, Aristotle University of Thessaloniki, 1995.
  • [11] S. KAY, Modern spectral estimation, Prentice Hall PTR, Signal Processing series, New Jersey 1988.
  • [12] L. LJUNG, System identification, Prentice Hall PTR, Signal Processing series, New Jersey 1987.
  • [13] P. A. NELSON, S. J. ELLIOTT, Active control of sound, Academic Press, London 1992.
  • [14] A. OPPENHEIM, R. SCHAFER, J. BUCK, Discrete time signal processing, Prentice Hall PTR, Signal Processing Series, New Jersey 1998.
  • [15] C. K. PAPADOPOULOS, C. L. NIKIAS, Parameter estimation of exponentially damped sinusoids using higher order statistics, IEEE Trans. ASSP, 38, 8, 1424–1435, August (1990).
  • [16] C. PASTIADIS, Contemporary voice analysis techniques for the speech impaired, Ph.D. Dissertation, Aristotle University of Thessaloniki, 2002.
  • [17] C. PASTIADIS, G. PAPANIKOLAOU, A preliminary study on greek esophageal speech and a method for quality and intelligibility enhancement, Archives of Acoustics, 24, 1, 25–38 (1999).
  • [18] C. PASTIADIS, G. PAPANIKOLAOU, Higher-order statistics based inverse filtering for analysis of esophageal voice production, 104-th Audio Engineering Society Convention, May 1998.
  • [19] C. PASTIADIS, A. PRINTZA, S. METAXAS, I. DANIILIDIS, G. PAPANIKOLAOU, Acoustic voice analysis in the evaluation of vocal fold polyps, Proc. AFEA 2001, Athens, June 2001.
  • [20] B. PORAT, B. FRIEDLANDER, A modification of the Kumaresan–Tufts method for estimating rational impulse response, IEEE Trans. ASSP, 34, 5, 1336–1338, October (1986).
  • [21] D. TSOUKALAS-STATHAKIS, Noise subtraction from speech and noise signals, Ph.D. Dissertation, University of Patras, 1997.
  • [22] S. VAN HUFFEL, H. CHEN, C. DECANNIERE, P. VAN HECKE, Total least squares based algorithm for time-domain NMR data fitting, ESAT Laboratory-Katholieke Universiteit Leuven 1994.
  • [23] T. VERMA, S. LEVINE, T. MENG, Transient modeling synthesis: a flexible analysis/synthesis tool for transient signals, Proc. ICMC 97, Thessaloniki 1997.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT3-0004-0003
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.