Algebraic vector quantization of LSF parameters with low storage and computational complexity

This correspondence presents an algebraic vector-quantization scheme for encoding line spectral frequency (LSF) parameters used in linear predictive coding (LPC) of speech. The scheme is based on low-dimensionality regular-point lattices. The algebraic codebook need not be stored, and the optimum codevector is found through simple rounding of the input vector. Thus, the scheme results in significant savings of memory and reduced computational complexity when compared to traditional vector-quantizer solutions. The quantizer achieves an average spectral distortion of about 1 dB at 28 b/frame for the telephone bandwidth.