SD optimization of spectral coders

Abstract

In spectral coding of speech, several different criteria are in use for designing and evaluating quantizers. One measure, spectral distortion (SD), has become dominant for comparisons between coders. At run-time, a coder normally quantizes vectors according to other measures, e.g. line spectrum frequency (LSF) distance, in order to keep computational complexity down. In this study, we adopt the SD criterion both in coder design and for quantizer operation. The quantizer is optimized to give minimal average SD scores, This allows us to address the question, is average SD measure really a good criterion, matching subjective ratings. We perform a few objective and subjective tests based on SD optimized coding and some versions thereof. Our tests imply that minimizing average SD may not lead to the best subjective scoring.