Generalized predictive trellis coded quantization of speech

Trellis-coded quantization (TCQ) is incorporated into a generalized predicted (noise feedback) structure for encoding sampled speech. Adaptive residual encoding and adaptive prediction are used to obtain signal-to-noise ratios (SNR) in the range of 17.5 to 21.5 dB for encoding sampled speech with 2 bits/sample (16 kb/s). Spectral noise shaping is achieved with this coding structure by using a bandwidth-expanded version of the predictor as a noise feedback filter. This has the effect of reducing the SNR of the encoding by a small amount but improving the perceptual quality of the reconstructed speech. The result is of excellent communications quality. A modified Viterbi algorithm is used for the trellis search to allow flexibility in the choice of symbol release rule. The effects of varying the encoding delay and the number of symbols released per trace-back on system performance and complexity are investigated. It is shown that excellent SNR performance can be obtained with modest encoding delays.<<ETX>>

[1]  W. Pearlman.  Sliding-Block and Random Source Coding with Constrained Size Reproduction Alphabets , 1982, IEEE Trans. Commun..

[2]  Robert M. Gray,et al.  The Design of Predictive Trellis Waveform Coders Using the Generalized Lloyd Algorithm , 1986, IEEE Trans. Commun..

[3]  S. Wilson,et al.  Trellis encoding of continuous-amplitude memoryless sources (Corresp.) , 1977, IEEE Trans. Inf. Theory.

[4]  Michael W. Marcellin,et al.  Predictive trellis coded quantization of speech , 1990, IEEE Trans. Acoust. Speech Signal Process..

[5]  Michael W. Marcellin,et al.  Trellis coded quantization of memoryless and Gauss-Markov sources , 1990, IEEE Trans. Commun..

[6]  Robert M. Gray,et al.  Time-invariant trellis encoding of ergodic discrete-time sources with a fidelity criterion , 1977, IEEE Trans. Inf. Theory.

[7]  William A. Pearlman,et al.  Source coding bounds using quantizer reproduction levels , 1984, IEEE Trans. Inf. Theory.

[8]  Joel Max,et al.  Quantizing for minimum distortion , 1960, IRE Trans. Inf. Theory.

[9]  Jerry D. Gibson,et al.  Backward Adaptive Lattice and Transversal Predictors in ADPCM , 1985, IEEE Trans. Commun..

[10]  P. Kabal,et al.  A low delay 16 kbits/sec speech coder , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[11]  William A. Pearlman,et al.  Optimal encoding of discrete-time continuous-amplitude memoryless sources with finite output alphabets , 1980, IEEE Trans. Inf. Theory.

[12]  Jr. G. Forney,et al.  The viterbi algorithm , 1973 .

[13]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[14]  Andrew J. Viterbi,et al.  Trellis Encoding of memoryless discrete-time sources with a fidelity criterion , 1974, IEEE Trans. Inf. Theory.

[15]  Gottfried Ungerboeck,et al.  Channel coding with multilevel/phase signals , 1982, IEEE Trans. Inf. Theory.

[16]  Peter No,et al.  Digital Coding of Waveforms , 1986 .

[17]  Thomas R. Fischer,et al.  Variance estimation and adaptive quantization , 1985, IEEE Trans. Inf. Theory.

[18]  N. Jayant.  Adaptive quantization with a one-word memory , 1973 .

[19]  John B. Anderson,et al.  Sequential Coding Algorithms: A Survey and Cost Analysis , 1984, IEEE Trans. Commun..

[20]  Robert M. Gray,et al.  The Design of Trellis Waveform Coders , 1982, IEEE Trans. Commun..