Name
Abstract | ||
|---|---|---|
We propose a maximum a posterior (MAP) estimation of channel bias to compensate for the channel mismatch in telephone speech recognition. For a telephone speech, the channel bias is estimated by maximizing a posterior probability. Because a posterior probability is composed of a likelihood function and a prior density, we introduce a scale factor to evaluate their weights in MAP estimation. To further improve the performance, a priori channel statistics is extended to multiple components and the channel mismatch is separately compensated for different segments. A rapid MAP estimation applied in the feature domain is also proposed for reducing computational complexity. Experiments show that the proposed method can significantly improve recognition rates and computational complexity |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1109/ICSLP.1996.607989 | ICSLP |
Keywords | Field | DocType |
likelihood function,speech recognition,channel bias estimation,maximum likelihood estimation,telephony,rapid map estimation,channel mismatch,telephone speech recognition,a posterior probability,a priori channel statistics,telecommunication channels,computational complexity,telecommunication computing,maximum a posterior estimation,recognition rates,feature domain,probability,posterior probability,statistics,background noise,decoding | Likelihood function,Computer science,Communication channel,Posterior probability,Speech recognition,Maximum a posteriori estimation,Estimation theory,Maximum likelihood sequence estimation,Telephony,Computational complexity theory | Conference |
Volume | ISBN | Citations |
3 | 0-7803-3555-4 | 6 |
PageRank | References | Authors |
0.51 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jen-Tzung Chien | 1 | 918 | 82.45 |
| Hsiao-Chuan Wang | 2 | 370 | 64.93 |
| Lee-Min Lee | 3 | 46 | 8.10 |