Name
Abstract | ||
|---|---|---|
The paper combines the Jayant adaptive quantization (Jayant, N.S., Bell Syst. Tech. J., vol.52, p.1119-44, 1973) and the gain prediction of G.728 to propose a scheme suitable for designing the gain codebook of LD-CELP, in which the exact gain value is adaptively predicted and adaptively quantized. In this method, for adaptive quantization gain of 3 bit and 4 bit, the SNR has been increased by 0.5 dB and 6 dB, respectively, compared to that of G.728. If 4-bit adaptive quantization and the shape codebook of 64 codevectors are adopted, the complexity of G.728 could be reduced by 20% while SNR has 1 dB improvement compared with G.728. When the order of the synthesis filter is reduced from 50 to 30, the SNR is not changed and the complexity of G.728 is decreased by 40%. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ICASSP.2003.1202316 | ICASSP (2) |
Keywords | Field | DocType |
optimisation,linear predictive coding,g.728 gain prediction,synthesis filter,quantisation (signal),adaptive prediction,computational complexity,gain codebook optimization,complexity,speech coding,shape codebook,celp,filtering theory,snr,jayant adaptive quantization,codevectors,adaptive filters,quantization,shape,decoding,speech synthesis | Speech coding,Linde–Buzo–Gray algorithm,Computer science,Adaptive filter,Artificial intelligence,Linear predictive coding,Code-excited linear prediction,Pattern recognition,Algorithm,Speech recognition,Decoding methods,Quantization (signal processing),Codebook | Conference |
Volume | Issue | ISSN |
2 | null | 1520-6149 |
ISBN | Citations | PageRank |
0-7803-7663-3 | 2 | 0.63 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gang Zhang | 1 | 18 | 9.28 |
| Keming Xie | 2 | 36 | 20.98 |
| Xueying Zhang | 3 | 2 | 0.63 |
| Liying Huangfu | 4 | 2 | 0.63 |