Joint source-channel MMSE-decoding of speech parameters

For speech transmission in digital land mobile telephony, effective compression algorithms have to be used to achieve a high bandwidth efficiency. Furthermore, a variety of adverse transmission effects make it necessary to employ powerful error control techniques to keep bit error rates tolerable low and thus to guarantee a high speech quality. Speech compression is designed to remove irrelevancy and redundancy from the speech signal. Yet measuring the statistical properties of speech parameters extracted by practical compression schemes shows, that a considerable amount of redundancy still remains, either in terms of non-uniform distribution or due to time-correlation of parameters extracted from subsequent speech segments. In this contribution, we propose a new Minimum Mean Square Error (MMSE) decoder for block-oriented trellis codes, that is able to exploit the time-correlation of subsequent parameter sets. The decoder yields non-discrete speech parameter Mean Square (MS) estimates. Thus it combines two recently published approaches to exploit residual redundancy: Source Controlled Channel Decoding (SCCD) [I] and Soft Bit Source Decoding (SBSD) [2] in one algorithm.