Trellis coded vector quantization (TCVQ) and forward adaptive predictive coding (APC) are used to form an efficient speech coding system operating at bit rates of 16 and 9.6 kb/s. The effectiveness of the system is studied for a variety of system parameters and utterances. Simulation results indicate that segmental signal-to-noise ratios as high as 23.8 and 15.4 dB are obtainable at 16 and 9.6 kb/s respectively. The quality of the reconstructed speech is deemed to be excellent at 16 kb/s and very good at 9.6 kb/s. An algorithm for optimizing the residual codebooks is presented.>

Speech coders employing forward adaptive predictive coding (APC) and operating at medium-to-low bit rates necessitate efficient encoding of the linear predictive coding (LPC) coefficients. Line spectrum pair (LSP) parameters are currently one of the most efficient choices of transmission parameters for the LPC coefficients. The authors briefly reviews LSP parameters and presents several low-delay coding schemes for the parameters. The coders are simulated using data generated from both the autocorrelation and covariance LPC analysis methods. The performances of the coders are given for a variety of rates and LPC analysis conditions. The most efficient scheme developed uses a uses a predictive form of trellis-coded quantization (TCQ). Its performance is comparable or superior to that of other low-delay LSP coding schemes. An enumeration scheme that reduces the rate of a given scalar quantization structure without decreasing coder performance is also presented.>

Motivated by the implicit geometry of a stationary, ergodic process, a vector quantizer (VQ) design algorithm is proposed, based on a contour of constant probability density. The approach is explicitly related to the differential entropy of the source, and uses this characteristic of the source to provide structure for the location of VQ output, vectors. A correlated Gaussian source is treated in detail and used as an appropriate model for the design of a contour gain VQ for speech. The resulting mean-square error performance is competitive with alternative VQ based results in the literature.