Estimation of the Fundamental Frequency of the Speech Signal Compressed by G.723.1 Algorithm Applying PCC Interpolation

Zoran Milivojević 1  and Darko Brodić 2
  • 1 Technical College, Aleksandra Medvedeva 20, Niš, Serbia
  • 2 Technical Faculty Bor, University of Belgrade, Vojske Jugoslavije 12, 19210 Bor, Serbia

Estimation of the Fundamental Frequency of the Speech Signal Compressed by G.723.1 Algorithm Applying PCC Interpolation

In this paper the results of the estimation of the fundamental frequency of the speech signal modeled by the G.723.1 method are analyzed. The estimation of the fundamental frequency was performed by the Peaking-Peaks algorithm with the implemented Parametric Cubic Convolution (PCC) interpolation. The efficiency of PCC was tested for Keys, Greville and Greville two-parametric kernel. Depending on MSE a window that gives optimal results was chosen.

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  • ITU-T Rec. G.723.1: Dual-rate Speech Coder For Multimedia Communications Transmitting at 5.3 and 6.3 kbit/s, 1996.

  • KARAPANTAZIS, S.—PAVLIDOU, F. : VoIP: A Comprehensive Survey on a Promising Technology, Computer Networks 53 (2009), 2050-2090.

  • REGUERA, V.—PALIZA, F.—GODOY, W.—FERNANDEZ, E. : On the Impact of Active Queue Management on VoIP Quality of Service, Computer Communications 31 (2008), 73-87.

  • KAOSAR, G.—SHELTAMI, T. : Voice Transmission over ad hoc Network Adapting Optimum Approaches to Maximize the Performance, Computer Communications 32 (2009), 634-639.

  • ZOLGHADR, A.—GOODARZI, E.—MOOSAVINEZHAD, M. : Real-Time Implementation of G.723.1 Speech Coder, Iranian Journal of Information Science and Technology 2 No. 1 (2004), 3-12.

  • JOEN, B.—KANG, S.—BAEK, S.—SUNG, K. : Filtering of a Dissonant Frequency Based on Improved Fundamental Frequency Estimation for Speech Enhancement, IEICE Trans. Fundamentals E86-A No. 8 (Aug 2003), 2063-2064.

  • MILIVOJEVIC, Z.—BALANESKOVIC, D. : Enhancement of the Perceptive Quality of the Noisy Speech Signal by Using of DFF-FBC Algorithm, Facta Universitatis, Ser.: Elec. Energ. 22 No. 3 (Dec 2009), 379=-392.

  • QIU, L.—YANG, H.—KOH, S. : Fundamental Frequency Determination on Instantaneous Frequency Estimation, IEEE Signal Process. 44 (1995), 233-241.

  • CHEVEIGNE, A.—KAWAHARA, H. : YIN, a Fundamental Frequency Estimator for Speech and Music, J. Acoust. Soc. Am. 111 No. 4 (April 2002), 1917-1930.

  • MURAKAMI, T.—ISHIDA. Y. : Fundamental Frequency Estimation of Speech Signal Using MUSIC Algorithm, Acoust. Sci. & Tech. 22 (2001), 293-297.

  • KACHAA,—GRENEZ, F.—BENMAHAMMED, K. : TimeFrequency Analysis and Instantaneous Frequency Estimation Using Two-Sided Linear Prediction, IEEE Signal Processing 85 (2005), 491-503.

  • KEYS, R. : Cubic Convolution Interpolation for Digital Image Processing, IEEE Trans. Acoust., Speech & Signal Process 29 (1981), 1153-1160.

  • PARK, K.—SCHOWENGERDT, R. : Image Reconstruction by Parametric Cubic Convolution, Computer Vision, Graphics & Image Processing 23 (1983), 258-272.

  • REICHENBACH, S. : Two-Dimensional Cubic Convolution, IEEE Transactions on Image Processing 12 No. 8 (Aug 2003), 857-865.

  • PANG, H.—BAEK, S.—SUNG, K. : Improved Fundamental Frequency Estimation Using Parametric Cubic Convolution, IEICE Trans. Fundamentals E83-A (2000), 2747-2750.

  • MILIVOJEVIC, Z.—MIRKOVIC, D.—MILIVOJEVIC, S. : An Estimate of Fundamental Frequency Using PCC Interpolation - Comparative Analysis, Information Technology and Control 35 (2006), 131-136.

  • MILIVOJEVIC, Z.—MIRKOVIC, M. : Estimation of the Fundamental Frequency of the Speech Signal Modeled by the SYMPES Method, Int. J. Electron. Commun. (AEÜ) 63 (2009), 200-208.


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