Adaptive block transform coding of speech based on LPC vector quantization
Abstract
The authors describe several adaptive block transform speech coding systems based on vector quantization of linear predictive coding (LPC) parameters. Specifically, the authors vector quantize the LPC parameters (LPCVQ) associated with each speech block and transmit the index of the code vector as overhead information. This code vector will determine the shortterm spectrum of the block and, in turn, can be used for optimal bit allocation among the transform coefficients. In order to get a better estimate of the speech spectrum, the authors also consider the possibility of incorporating pitch information in the coder. In addition, entropycoded zeromemory quantization of the transform coefficients is considered as an alternative to LloydMax quantization. An adaptive BTC scheme based on LPCVQ and using entropycoded quantizers is developed. Extensive simulations are used to evaluate the performance of this scheme.
 Publication:

IEEE Transactions on Signal Processing
 Pub Date:
 December 1991
 DOI:
 10.1109/78.107411
 Bibcode:
 1991ITSP...39.2611H
 Keywords:

 Linear Prediction;
 Signal Encoding;
 Speech Recognition;
 Vector Quantization;
 Voice Control;
 Computerized Simulation;
 GaussMarkov Theorem;
 Transformations (Mathematics);
 Communications and Radar