Patent ID: 7149683

Claim:
Apparatus comprising a switched predictive vector quantizer having an input for receiving an input Linear Prediction (LP) parameter vector z and a first processor for removing a vector of mean LP parameters μ from the input LP parameter vector z to produce a mean-removed LP parameter vector x, a second processor for determining a prediction vector p and a third processor for removing the prediction vector p from the mean-removed LP parameter vector x to produce a prediction error vector e, further comprising a fourth processor responsive to frame classification information such that if a frame corresponding to the input LP parameter vector z is stationary voiced then autoregressive (AR) prediction is used and the error vector e is scaled by a certain factor to obtain a scaled prediction error vector e′, whereas if the frame is not stationary voiced moving average (MA) prediction is used and the scaling factor is equal to one; further comprising a fifth processor coupled to receive the scaled prediction error vector e′ and operable to vector quantize the scaled prediction error vector e′ to produce a quantized scaled prediction error vector ê′ and a sixth processor coupled to receive the quantized scaled prediction error vector ê′ for applying a scaling inverse to that applied by said fourth processor to the quantized scaled prediction error vector ê′ to produce the quantized prediction error vector ê; where said second processor determines the prediction vector p in one of an MA predictor or an AR predictor depending on the frame classification information such that if the frame is stationary voiced then the prediction vector p is equal to the output of the AR predictor else the prediction vector p is equal to the output of the MA predictor, where said MA predictor operates on quantized prediction error vectors from previous frames and said AR predictor operates on quantized input LP parameter vectors from previous frames; and where the quantized input LP parameter vector (mean-removed) is constructed by adding the quantized prediction error vector ê to the prediction vector p: {circumflex over (x)}=ê+p.