Kazunori Mano

Noise post processing based on a stationary noise generator

The paper presents a newly developed noise post-processing (NPP) algorithm for improving subjective performance of low bit-rate code excited linear prediction (CELP) decoding. The algorithm is based on a stationary noise generator and improves subjective quality of a noisy signal input. A backward adaptive detector defines noisy input signal segments from decoded line spectral frequency (LSF), energy, and pitch parameters. By using LSF and energy parameters from the past, the noise generator estimates and produces stationary noise. The algorithm is independent of the main codec algorithm and is applicable to any CELP decoder. When applied to G.729 and G.723.1, our test results show that the algorithm improves subjective performance at around 0.2-0.8 in degradation category rating (DCR) mean opinion score (DMOS) under several background noise conditions.

Dual-Pulse CS-CELP: a toll-quality low-complexity speech coder at 7.8 kbit/s

Low-cost highly-efficient speech coding is important for personal multimedia communications. In this paper we propose a new low-complexity speech coding method called Dual-Pulse CS-CELP (DP-CS-CELP) at 7.8 kbit/s. This method is based on ITU-T G.729. To reduce the complexity, we applied a new excitation model to the random code vectors and simplified the LPC coding, adaptive codebook search, perceptual weighting, and the other structures. The number of operations for this encoder is 3.80 MOPS, which achieves real-time speech coding and decoding on personal computers. Although the efficiency of this coder is a little lower than that of G.729, the MOS listening test showed that the subjective quality was equivalent to or a little better than that of G.726 (32-kbit/s ADPCM).