Multi-Pulse Based Code Excited Linear Predictive Speech Coder with Fine Granularity Scalability for Tonal Language

Abstract

Problem statement: The flexible bit-rate speech coder plays an important role in the modern speech communication. The MP-CELP speech coder which is a candidate of the MPEG4 natural speech coder supports a flexible and wide bit-rate range. However, a fine scalability had not been included. To support finer scalability of the coding rate, it had been studied in this study. Approach: In this study, based on the MP-CELP speech coding with HPDR technique, Fine Granularity Scalability was introduced by adjusting the amount of transmitted fixed excitation information. The FGS feature aim at changing the bit rate of the conventional coding more finely and more smoothly. Results: Through performance analysis and computer simulation, the quality of scalability of the MP-CELP coding was presented with an improvement from conventional scalable MP-CELP. The HPDR technique is also applied to the MP-CELP to use for tonal language, meanwhile it can support the core coding rate of 4.2, 5.5, 7.5 kbps and additional scaled bit rates. Conclusion: The core coder with high pitch delay resolution technique and adaptive codebook for tonal speech quality improvement has been conducted and the FGS brings about further efficient scalability.