http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Adaptive predictive coding of speech using trellis coded vector quantization
Adaptive predictive coding (APC) and trellis coded vector quantization (TCVQ) are combined to form an efficient medium-to-low bit rate speech coding system. The resulting system is called APC-TCVQ. Simulation results are presented for encoding rates of 16 and 9.6 kbits per second (kbps). For an encoding rate of 16 kbps, the perceptual quality of the reconstructed speech was judged as excellent communications quality. The quality of the 9.6 kbps APC-TCVQ reconstruction is clear and of very good quality. Signal-to-noise ratios (SNR's) and segmental SNR's as high as 24.4 and 23.77 dB, respectively, were obtained at an encoding rate of 16 kbps. The APC-TCVQ system presented in this dissertation uses both formant and pitch prediction to remove the short-term and long-term redundancy in the speech data. The predictors are updated using forward adaptation methods. Simulations involving prediction gains are used to select the formant predictor order and frame size. Several methods of efficiently encoding the formant predictor coefficients were examined. A vector predictive trellis coded quantization (TCQ) scheme operating on the line spectrum pair (LSP) parameters is developed. The performance of the LSP TCQ encoder is comparable to that of other LSP coders in the literature. A distortion rate bound for particular speech segment is estimated using a Gauss-Markov model. Comparisons are made between the distortion bounds and the performance of the APC-TCVQ systems for two encoding rates. The results of simulations involving channel errors are presented for several error probabilities. The APC-TCVQ system is shown to be equivalent to the efficient code-excited linear prediction (CELP) coder under certain conditions.
"Major subject: Electrical engineering."