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.

This paper presents a new and efficient method for modeling voiced, mixed excitation spectra in sinusoidal (SC) and prototype interpolation coding (PIC) systems. Speech harmonics are classified as "weak-voiced" or "strong-voiced" by simply examining the short-term residual magnitude spectrum. This information is encoded effectively in terms of fixed width frequency bands and is used to control sets of periodic and random sine wave oscillators which model the short-term mixed excitation nature of speech. In this way the model allows the mixing of periodic and random signal energy on a harmonic basis. The proposed methodology has been used in a 2.4 Kbits/sec speech coder, whose recovered speech quality is better than that of the 4.8 Kbits/sec DoD standard.

This paper presents a new and efficient LPC quantisation scheme called split matrix quantisation (SMQ). The proposed method can be viewed as an extension of the conventional split vector quantisation process. It operates over N consecutive LPC frames and effectively divides a p/spl times/N LSP matrix into K submatrices which are then vector quantised independently. SMQ exploits the interframe redundancy that exists between consecutive sets of LSP coefficients and achieves "transparent" quantisation at 900 bits/sec. "High quality" LSP quantisation can be easily obtained at 750 bits/sec. These bit rates are based in a 20 msec LPC analysis frame size. Furthermore, SMQ is characterised by relatively low complexity and low storage requirements.