Title :
Adaptive block transform coding of speech based on LPC vector quantization
Author :
Hussain, Yunus ; Farvardin, Nariman
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., College Part, MD, USA
fDate :
12/1/1991 12:00:00 AM
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 short-term 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, entropy-coded zero-memory quantization of the transform coefficients is considered as an alternative to Lloyd-Max quantization. An adaptive BTC scheme based on LPCVQ and using entropy-coded quantizers is developed. Extensive simulations are used to evaluate the performance of this scheme
Keywords :
data compression; encoding; filtering and prediction theory; speech analysis and processing; transforms; LPC parameters; adaptive block transform; code vector; coder; entropy-coded zero-memory quantization; linear predictive coding; optimal bit allocation; overhead information; performance evaluation; pitch information; short-term spectrum; simulations; speech coding systems; speech spectrum; transform coefficients; vector quantization; Bit rate; Encoding; Hidden Markov models; Linear predictive coding; Signal design; Signal to noise ratio; Speech coding; State estimation; Transform coding; Vector quantization;
Journal_Title :
Signal Processing, IEEE Transactions on