Yong-won Shin

Low-complexity predictive trellis-coded quantization of speech line spectral frequencies

Low-complexity block-constrained trellis coded quantization (BC-TCQ) structures are studied, and a predictive BC-TCQ encoding method is developed for quantization of line spectrum frequency (LSF) parameters for speech coding applications. The performance is compared with the linear predictive coding (LPC) vector quantizers used in the AMR-WB (ITU-G.722.2) and IS-641 speech coding standards, demonstrating reduction in spectral distortion (SD) and significant reduction in encoding complexity.

A Fast Encoding Technique for Vector Quantization of LSF Parameters

A fast encoding technique is described for vector quantization (VQ) of line spectral frequency parameters. A reduction in VQ encoding complexity is achieved by using a preliminary test that reduces the necessary codebook search range. The test is performed based on two criteria. One criterion uses the distance between a specific single element of the input vector and the corresponding element of the codevectors in the codebook, The other criterion makes use of the ordering property of LSF parameters. The fast encoding technique is implemented in the enhanced variable rate codec (EVRC) encoding algorithm. Simulation results show that the average searching range of the codebook can be reduced by 44.50% for the EVRC without degradation of spectral distortion (SD).

Low-complexity predictive trellis coded quantization of wideband speech LSF parameters

In this paper, low-complexity block-constrained trellis coded quantization (BC-TCQ) structures are introduced, and a predictive BC-TCQ encoding method is developed for quantization of line spectrum frequencies (LSF) parameters for wideband speech coding applications. The performance is compared to the linear predictive coding (LPC) vector quantizers used in the AMR-WB (ITU-G.722.2) speech coding standard, demonstrating reduction in spectral distortion and significant reduction in encoding complexity.