Principal axis extracting vector excitation coding: high quality speech at 8 kb/s

Principal axis extracting vector excitation coding (PAVXC) is proposed in which an efficient codebook search method and an improved excitation modeling technique are used. A two-step codebook search using a small-size codebook of 20 dimensions (half the conventional size) can reduce the computational complexity by a factor of 64, maintaining the reproduced speech quality within a slight degradation of 0.9 dB in SNR seg. Multiple vector excitation using an impulse vector jointly with the conventional stochastic code vector can provide more precise representation of the excitation. The impulse vector is extracted from each code vector by principal axis extraction, and its gain is jointly optimized with the gain for the code vector. The improvement in SNR seg is 1.2 dB, which compensates for the degradation caused by the two-step codebook search. The quality of the reproduced speech using PAVXC is subjectively much better than that of conventional VXC, thanks especially to the improvement in voiced regions