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Split matrix quantization of LPC parameters

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2 Author(s)
C. S. Xydeas ; Speech Process. Res. Lab., Manchester Univ., UK ; C. Papanastasiou

This paper examines in detail the design issues and performance characteristics of linear predictive coding (LPC) split matrix quantization (SMQ). This efficient LPC quantization method which was proposed by Xydeas and Papanastasiou (1995) can be viewed as an extension of the conventional split vector quantization (SVQ) process. SMQ removes existing interframe/intraframe line spectral frequency (LSF) redundancy by applying VQ principles on trajectories of smoothly evolving, with time, LSF coefficients. Using a 20 ms LPC analysis frame size, “transparent” quantization is achieved at 900 b/s, whereas “high quality” LSF quantization is easily obtained at 650 b/s, Furthermore, the SMQ methodology offers valuable flexibility in the way quantization of LPC coefficients is performed and leads into several schemes of varying computational complexity/storage characteristics

Published in:

IEEE Transactions on Speech and Audio Processing  (Volume:7 ,  Issue: 2 )