Name
Title | ||
|---|---|---|
Coding of variable dimension speech spectral vectors using weighted nonsquare transform vector quantization |
Abstract | ||
|---|---|---|
This paper addresses the problem associated with variable-dimension vector quantization, and presents a new quantization technique that combines a variable-size nonsquare transform (NST) with a fixed-dimension vector quantizer. We show that all linear dimension conversion methods can be treated as special cases of a general approach for linear dimension conversion formulated as NST. By incorporating the speech perceptual properties, we introduce a technique called weighted nonsquare transform vector quantization (WNSTVQ) for the quantization of speech spectral vectors. We show that the total perceptual weighted distortion can be separated into the weighted modeling distortion, which is solely determined by the choice of transforms in WNSTVQ and the weighted quantizer distortion. We discuss the factors that influence the performance of the WNSTVQ system and provide a complexity analysis for two WNSTVQ implementations. Finally, experimental results are presented to show that the WNSTVQ system has the ability to trade performance for computational complexity and memory storage by selecting suitable transforms and/or the length of fixed-dimension vectors |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/89.943340 | IEEE Transactions on Speech and Audio Processing |
Keywords | Field | DocType |
fixed-dimension vector quantizer,total perceptual weighted distortion,weighted nonsquare transform vector quantization,linear dimension conversion methods,speech spectral vectors,fixed-dimension vectors,weighted modeling distortion,speech perceptual properties,vector quantisation,transform coding,variable-dimension vector quantization,variable dimension speech spectral vectors,wnstvq,computational complexity,weighted quantizer distortion,speech coding,variable-size nonsquare transform,memory storage,nst,performance,orthogonal transformation,frequency,bandwidth,decoding,spectral method,vector quantization,weighting,data compression,telephony,speech processing,sampling methods | Speech processing,Speech coding,Pattern recognition,Computer science,Learning vector quantization,Transform coding,Speech recognition,Vector quantization,Artificial intelligence,Quantization (signal processing),Distortion,Computational complexity theory | Journal |
Volume | Issue | ISSN |
9 | 6 | 1063-6676 |
Citations | PageRank | References |
5 | 0.57 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chun-Yan Li | 1 | 22 | 4.27 |
| P. Lupini | 2 | 5 | 0.57 |
| Eyal Shlomot | 3 | 191 | 18.79 |
| V. Cuperman | 4 | 5 | 0.57 |