Journal ArticleDOI
CELP coding using trellis-coded vector quantization of the excitation
Reads0
Chats0
TLDR
The results show thatTCVQ performs significantly better than VQ, with reasonable complexity, which makes TCVQ a fair choice for trading quality against complexity and/or delay.Abstract:
We analyze the performance of a CELP coder where the vector quantization (VQ) of the excitation is replaced with trellis-coded vector quantization (TCVQ). Our results show that TCVQ performs significantly better than VQ, with reasonable complexity. This makes TCVQ a fair choice for trading quality against complexity and/or delay. We describe a systematic procedure to replace VQ with TCVQ for existing CELP coders. We propose an optimization algorithm to appropriately populate the trellis. We show how pseudo-Gray coding can be applied to the TCVQ codebook to improve intrinsic coder robustness to channel errors. Finally, we evaluate the complexity and performance of the method.read more
Citations
More filters
Proceedings ArticleDOI
Reverse water-filling in predictive encoding of speech
S.V. Andersen,W.B. Kleijn +1 more
TL;DR: Reverse water-filling applies to predictive encoding of speech for vector analysis-by-synthesis encoding based on a first order autoregressive signal model and the use of a synthesis filter derived from reverse water- filling resulted in consistently improved segmental SNR measures.
Journal ArticleDOI
Optimized trellis coded vector quantization of LSF parameters, application to the 4.8 kbps FS1016 speech coder
TL;DR: An optimized trellis coded vector quantization (TCVQ) scheme for encoding the LSF parameters is developed and it is shown that the incorporated LSF TCVQ encoder performs better than the 34 bits/frame LSF scalar quantizer used originally in the FS1016 coder.
Patent
Vector search method
Yuji Maeda,Shuichi Maeda +1 more
TL;DR: In this article, a change ΔG u obtained between a noise signed vector and a noise sign vector based on a signed word i of the binary Gray code was used to increase the vector search speed.
Journal ArticleDOI
Optimisation de la quantification vectorielle codée par treillis: application au codage des paramètres LSF
Merouane Bouzid,Amar Djeradi +1 more
TL;DR: An optimized trellis coded vector quantization (Tcvq) scheme for encoding theLsf parameters is presented and objective and subjective evaluation results show that the incorporatedLsf tcvq encoder performs better than the 34 bits/frameLsf scalar quantizer used originally in the fs1016 coder.
Journal ArticleDOI
An error correction approach based on maximum likelihood estimation combined with hidden Markov models
TL;DR: The robustness to error can be improved without adding error-correcting code by applying the proposed method to the preprocessing of the existing code system.
References
More filters
Journal ArticleDOI
The viterbi algorithm
TL;DR: This paper gives a tutorial exposition of the Viterbi algorithm and of how it is implemented and analyzed, and increasing use of the algorithm in a widening variety of areas is foreseen.
Journal ArticleDOI
Channel coding with multilevel/phase signals
TL;DR: A coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth by channel coding with expanded sets of multilevel/phase signals in a manner which increases free Euclidean distance.
Proceedings ArticleDOI
Code-excited linear prediction(CELP): High-quality speech at very low bit rates
Manfred R. Schroeder,B. S. Atal +1 more
TL;DR: A code-excited linear predictive coder in which the optimum innovation sequence is selected from a code book of stored sequences to optimize a given fidelity criterion, indicating that a random code book has a slight speech quality advantage at low bit rates.
Journal ArticleDOI
Convolutional codes I: Algebraic structure
TL;DR: Minimal encoders are shown to be immune to catastrophic error propagation and, in fact, to lead in a certain sense to the shortest decoded error sequences possible per error event.
Journal ArticleDOI
Trellis coded quantization of memoryless and Gauss-Markov sources
TL;DR: The authors adopt the notions of signal set expansion, set partitioning, and branch labeling of TCM, but modify the techniques to account for the source distribution, to design TCQ coders of low complexity with excellent mean-squared-error (MSE) performance.
Related Papers (5)
Predictive coding of speech using microphone/speaker adaptation and vector quantization
A.I. Aarskog,H.C. Guren +1 more