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A new adaptive quantizer which uses a combination of instantaneous and syllabic adaptation is presented for use in speech codecs. It can be designed to adapt to changes in the mean, variance, and pdf shape of its input signal, and to quantize the signal using one or more bits/sample. It is therefore called the generalized hybrid adaptive quantizer (GHAQ). An efficient procedure for optimizing the GHAQ using a training sequence of signal samples is described, and the effects on the performance of the GHAQ of varying the memory length and the syllabic compandor time constant are investigated. It is found that an optimized version of the two-bit GHAQ offers improved signal-to-noise ratio over Jayant's adaptive quantizer with a one-word memory when it is used in a predictive speech codec with a zero-, first-, or second-order fixed predictor. > |
