Sphere-packings, lattices, and groups
Sphere-packings, lattices, and groups
Vector quantization and signal compression
Vector quantization and signal compression
Speech Coding and Synthesis
On Suboptimal Multidimensional Companding
DCC '98 Proceedings of the Conference on Data Compression
Embedded algebraic vector quantizers (EAVQ) with application to wideband speech coding
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Predictive multiple-scale lattice VQ for LSF quantization
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Stochastic-algebraic wideband LSF quantization
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Lattice vector quantization of generalized Gaussian sources
IEEE Transactions on Information Theory
Two-stage vector quantization-lattice vector quantization
IEEE Transactions on Information Theory
Lattice labeling algorithms for vector quantization
IEEE Transactions on Circuits and Systems for Video Technology
Robust indexing of lattices and permutation codes over binary symmetric channels
Signal Processing - From signal processing theory to implementation
Spherical logarithmic quantization
IEEE Transactions on Audio, Speech, and Language Processing
Hi-index | 0.08 |
In this study we introduce two new quantization structures, namely the multiple scale leader-lattice vector quantization (MSLLVQ) using different lattice truncations and (MSLLVQ) using different unions of leader vectors. The design methods and the corresponding encoding algorithms are presented for each structure. We first focus on the search in a truncated lattice and in a leader class of a lattice and we then propose two new search methods for pyramidal (l1-) truncations and l1/2-truncations. The encoding algorithms have low memory and computational requirements. The new schemes outperform in terms of SNR other lattice quantization structures presented in the literature in the case of generalized Gaussian source densities with decay parameters 0.5, 1 and 2. In addition, when used for LSF quantization they can achieve a mean spectral distortion below 1 dB at only 19 bits, being superior to the G.729 speech coder.