Multi Switched Split Vector Quantizer

Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization, This is a hybrid of two product code vector quantization techniques namely the Multi stage vector quantization technique, and Switched split vector quantization technique,. Multi Switched Split Vector Quantization technique quantizes the linear predictive coefficients in terms of line spectral frequencies. From results it is proved that Multi Switched Split Vector Quantization provides better trade off between bitrate and spectral distortion performance, computational complexity and memory requirements when compared to Switched Split Vector Quantization, Multi stage vector quantization, and Split Vector Quantization techniques. By employing the switching technique at each stage of the vector quantizer the spectral distortion, computational complexity and memory requirements were greatly reduced. Spectral distortion was measured in dB, Computational complexity was measured in floating point operations (flops), and memory requirements was measured in (floats).

Authors:

• M. Satya Sai Ram
• P. Siddaiah
• M. Madhavi Latha

Keywords:

• Unconstrained vector quantization
• Linear predictiveCoding
• Split vector quantization
• Multi stage vector quantization
• Switched Split vector quantization
• Line Spectral Frequencies.

References:

[1] Atal. B.S, "The history of linear prediction," IEEE Signal Processing
Magazine, Vol 23, pp.154-161, March 2006.
[2] Harma, "A. Linear predictive coding with modified filter structures,"
IEEE Trans. Speech Audio Process, Vol 9, pp.769-777, Nov 2001.
[3] Viswanathan. R., Makhoul. J, "Quantization properties of transmission
parameters in linear predictive systems," IEEE Trans. on Acoustics,
Speech Signal Processing,vol 23, no.3, pp. 309-321, June1975.
[4] Gray.R.M., Neuhoff. D.L, "Quantization,". IEEE Trans. Inform. Theory,
pp.2325-2383,1998.
[5] Agiomyrgiannakis. Y, Stylianou. Y, "Conditional Vector Quantization
for Speech Coding," IEEE Trans. Speech Audio Process, Vol 15, no.2,
pp.377-386, Feb 2007.
[6] Bist.A, "Narrowband process quantization," Data Compression
Conference, 1995. DCC '95. Proceedings, March 1995.
[7] Stephen. So, & Paliwal. K. K, "Efficient product code vector
quantization using switched split vector quantizer," Digital Signal
Processing journal, Elsevier, Vol 17, pp.138-171, Jan 2007.
[8] Krishnan. V, Anderson. D.V, Truong. K.K, "Optimal multistage vector
quantization of LPC parameters over noisy channels," IEEE Trans.
Speech Audio Process, Vol 12, no.1, pp.1-8, Jan 2004.
[9] Biing-Hwang Juang Gray, A., Jr. "Multiple stage vector quantization
for speech coding". IEEE Conference on Acoustics, Speech Signal
Processing, vol 7, pp. 597-600, May 1982.
[10] Soong. F, Juang. B, "Line spectrum pair (LSP) and speech data
compression," IEEE Conference on Acoustics, Speech Signal
Processing, vol 9, no.1, pp. 37-40, Mar 1984.
[11] Bastiaan Kleijn. W, Tom Backstrom, & Paavo Alku. "On Line Spectral
Frequencies," IEEE Signal Processing Letters, Vol.10, no.3, 2003.
[12] P. Kabal, and P. Rama Chandran. "The Computation of Line Spectral
Frequencies Using Chebyshev polynomials," IEEE Trans. on Acoustics,
Speech Signal Processing, Vol 34, no.6, pp. 1419-1426, 1986.
[13] Paliwal. K.K, Atal. B.S, "Efficient vector quantization of LPC
Parameters at 24 bits/frame," IEEE Trans. Speech Audio Process, pp.3-
14,1993.
[14] Chatterjee. S, Sreenivas. T.V, "Conditional PDF-Based Split Vector
Quantization of Wideband LSF Parameters," IEEE Signal Processing
Letters, Vol.14, no.9, Sept 2007.
[15] Linde .Y, Buzo. A., & Gray. R.M, "An Algorithm for Vector Quantizer
Design," IEEE Trans.Commun, 28, pp. 84-95, Jan.1980.
[16] Sara Grassi., "Optimized Implementation of Speech Processing
Algorithms," Electronics and Signal Processing Laboratory, Institute of
Micro Technology, University of Neuchatel, Breguet 2, CH-
2000 Neuchatel, Switzerland, 1988.
[17] Thomas F. Quatieri, Discrete-Time Speech Signal Processing,
Pearson Education Inc, 2002.
[18] L.R.Rabiner and R.W.Schafer, Digital Processing of Speech Signals,
Prentice Hall, Englewood Cliffs, 1978.