Joint source-turbo coding and its application for real-time low-bit-rate speech transmission

A new algorithm for optimal design of joint source-channel coding over coded communication systems is presented. The source coder and decoder (codec) based on the vector quantization (VQ) technique are optimized for the coded system by minimizing the end-to-end system distortion. The channel codec is realized with a turbo code. The proposed algorithm is derived based on a discrete-input analog-output additive white Gaussian noise (AWGN) channel model. Maximum a posteriori (MAP) are used for soft-output channel decoding. The soft output signals are applied directly to the designed optimal source decoder for source decoding. Applications of the proposed algorithm for wireless low-bit-rate speech transmission is also given. Simulation results show that, the proposed algorithm can objectively gain 4-5 dB improvement of decoded source SNR (DSSNR) for a first-order Gauss-Markov source, and subjectively achieve 2-3 mean-opinion scores (MOS) enhancement for the decoded speech quality relative to the traditional system with hard decoding outputs, especially over the low SNR channels