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A mixed-excitation linear predictive (MELP) speech coder was selected as the US federal standard for 2400 b/s speech compression. This paper examines the quality of MELP-compressed speech when transmitted over noisy communication channels in conjunction with a variety of error-control schemes. The focus is on channel decoders that exploit the "residual redundancy" inherent in the MELP bitstream. This residual redundancy, which is manifested by the correlation in time and the nonuniform distribution of various MELP parameters, can be quantified by modeling the parameters as one-step Markov chains and computing the entropy rate of the Markov chains based on the relative frequencies of transitions. Moreover, this residual redundancy can be exploited by an appropriately "tuned" channel decoder to provide substantial coding gain when compared with decoders that do not exploit it. Channel coding schemes include conventional binary convolutional codes and iteratively-decoded parallel concatenated convolutional (turbo) codes.