Polar plane blockquantization of speech signals using bit-pattern matching techniques

Fourier Transformation and blockquantization offers a good tool for decorrelation and data compression of speech signals as well as for correlated random processes. Polar plane quantization versus cartesian quantization is presented and the objective and subjective performance is discussed according to the effects of introducing phase errors. The theoretical and practical limits for voiced and unvoiced segmentation using two distinct bit patterns in blockquantization are outlined. Useful constraints for implementing a transform encoder on a fast digital signal processor are derived with computer simulations, demonstrating high speech qualities for data rates downto 8-16 kbit/s .