Parallel processing for computationally intensive speech analysis operations

Parallel processing is applied to the speech analysis tasks of homomorphic prediction for pole/zero spectral estimation and cepstrum pitch determination. A number of issues bearing on the feasibility of the use of large-scale parallel processing for speech applications are addressed. The speedup over serial implementations is analyzed. The processing task considered consists of a number of distinct algorithms, including FFTs, autocorrelation and covariance LPC analyses, and inverse filtering. The compatibility of adjacent algorithms in the processing sequence is considered in terms of the number of processors used by successive algorithms, the compatibility of the allocation of data to processors, and the type of interprocessor communication needed at the junctures between algorithms. Based on the analyses, the conditions under which the parallel implementation should be most efficient are derived.