Simd Algorithms to Perform Linear Predictive Coding for Speech Processing Applications

نویسندگان

  • Leah J. Siegel
  • Howard Jay Siegel
  • Robert J. Safranek
  • Mark A. Yoder
چکیده

The use of the SIMD (single instruction stream multiple data stream) mode of parallelism to perform the speech analysis task of linear predictive coding is explored. Linear prediction represents one of the major analysis techniques for speech compression, transmission, and recognition applications. Parallel algorithms to perform linear prediction have been developed, and are evaluated in terms of the number of arithmetic operations and interprocessor data transfers needed. From the algorithms, architectural requirements such as machine size and interconnection network capability are analyzed.

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تاریخ انتشار 2005