An efficient tree-structured codebook design for embedded vector quantization

Abstract

This paper proposes an efficient codebook design for treestructured vector quantization (TSVQ), which is embedded in nature. We modify two speech coding standards by replacing their original quantizers for line spectral frequencies (LSF's) and or Fourier magnitudes quantization with TSVQ-based quantizers. The modified coders are fine-granular bit-rate scalable with gradual change in quality for the synthetic speech.

A Hybrid Vector Quantization Combining a Tree Structure and a Voronoi Diagram

“…However, the codeword determined by TSVQ is not sufficiently near the input vector, yielding poor quality of the reconstructed multimedia data. To improve TSVQ performance, multistage (MTSVQ) [18] and closest-couple TSVQ [19] have been used to determine the optimum codeword by enlarging the search space. However, these approaches may traverse wrong direction paths caused by the decision criteria in each node, degrading performance.…”

Low Bit Rate Speech Coding Using Lattice Vector Quantization and Time-Scale Modification

“…Objective and Subjective Test Results. To measure the performance of vocoder, objective quality evaluation is done here through the PESQ test [11] [12]. Speech materials lasting four hours which were spoken by eight male and eight female speakers of TIMIT database are used for evaluation.…”