Tonal Language Speech Compression Based on a Bitrate Scalable Multi-Pulse Based Code Excited Linear Prediction Coder

Abstract

Problem statement: Speech compression is an important issue in the modern digital speech communication. The functionality of bitrates scalability also plays significant role, since the capacity of communication system varies all the time. When considering tonal speech, such as Thai, tone plays important role on the naturalness and the intelligibility of the speech, it must be treated appropriately. Therefore these issues are taken into account in this study. Approach: This study proposes a modification of flexible Multi-Pulse based Code Excited Linear Predictive (MP-CELP) coder with bitrates scalabilities for tonal language speech in the multimedia applications. The coder consists of a core coder and bitrates scalable tools. The high pitch delay resolutions are applied to the adaptive codebook of core coder for tonal language speech quality improvement. The bitrates scalable tool employs multi-stage excitation coding based on an embedded-coding approach. The multi-pulse excitation codebook at each stage is adaptively produced depending on the selected excitation signal at the previous stage. Results: The experimental results show that the speech quality of the proposed coder is improved above the speech quality of the conventional coder without pitch-resolution adaptation. Conclusion: From the study, the proposed approach is able to improve the speech compression quality for tonal language and the functionality of bitrates scalability is also developed.