Name
Abstract | ||
|---|---|---|
The Code-Excited Linear Prediction (CELP) model is very efficient in coding speech at low bit rates. However, if the bit rate of the coder is increased, the CELP model does not gain in quality as quickly as other approaches. Moreover, the computational complexity of the CELP model generally increases significantly at higher bit rates. In this paper we focus on a technique that aims to overcome these limitations by means of a special transform-domain codebook within the CELP model. We show by the example of the AMR-WB codec that the CELP model with the new flexible and scalable codebook improves the quality at high bit rates at no additional complexity cost. |
Year | Venue | Keywords |
|---|---|---|
2017 | European Signal Processing Conference | Speech coding,ACELP,AMR-WB |
Field | DocType | ISSN |
Code-excited linear prediction,Vector sum excited linear prediction,Computer science,Algorithm,Speech recognition,Linear prediction,Harmonic Vector Excitation Coding,Low bit,Codec,Computational complexity theory,Codebook | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vaclav Eksler | 1 | 32 | 5.92 |
| Bruno Bessette | 2 | 42 | 11.14 |
| Milan Jelínek | 3 | 36 | 4.19 |
| Tommy Vaillancourt | 4 | 83 | 8.83 |