Low-complexity encoding of speech LSF parameters using constrained-storage TSVQ

Abstract

Tree structured vector quantization (TSVQ) is employed as a low-complexity approach to performing vector quantization of speech linear prediction coefficients, expressed for the purpose of quantization as line spectral frequency (LSF) parameters. Good tradeoffs between search complexity and distortion-rate performance are obtained using multiple-survivor encoding. The exponential storage-complexity of conventional TSVQ is circumvented by using multiple stages, where one or more tree codebooks may be used in each stage. Experimental results show that for rates between 23-25 bits/frame,the encoding complexity required to achieve "transparent coding" quality ranges from below two hundred to several hundred weighted-squared-error distortion computations per frame.<>