Name
Abstract | ||
|---|---|---|
In this work we propose an efficient technique to quantize the immitance spectral frequency (ISF) in an algebraic code-excited linear prediction (ACELP) wideband codec. The Constrained Voicing-Based Vector Quantization (C-VBVQ) presented in this paper improves substantially the performance of the unconstrained-VBVQ approach for both clean and noisy speech. Both techniques reduce the codebook search time by almost one third. However, in the C-VBVQ training phase, the three codebooks that are indi- vidually designed for voiced, unvoiced and transition speech, are jointly reoptimized to impose a structural configuration. The proposed technique reduces the processing delay since it restricts the quantization of an input vector to only one smaller but optimal codebook. For each speech frame, one codebook is selected from the set of three codebooks based on the interframe correlation of the spectral information. The C-VBVQ was successfully implemented in an ACELP wideband coder. The objective and subjective performance are not only superior to that of the combination of the split vector quantization and multistage vector quantization but also to the unconstrained VBVQ. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.4304/jcm.4.2.71-77 | JCM |
Keywords | Field | DocType |
low-complexity isf quan- tization,index terms— wideband speech coding,constrained voicing-based vector quantization,code excited linear prediction,speech coding,indexing terms | Vector sum excited linear prediction,Code-excited linear prediction,Linde–Buzo–Gray algorithm,Computer science,Learning vector quantization,Speech recognition,Vector quantization,Quantization (signal processing),Algebraic code-excited linear prediction,Codebook | Journal |
Volume | Issue | Citations |
4 | 2 | 0 |
PageRank | References | Authors |
0.34 | 8 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Driss Guerchi | 1 | 28 | 4.93 |