Name
Abstract | ||
|---|---|---|
In this paper, a noise reduction method with dual microphones, based on the prior knowledge, is proposed to reduce the residual noise especially in the period of target speech absence (TSA). First, two cases, i.e. target speech presence and target speech absence were modeled by Gaussian mixture model (GMM), respectively. Then, we calculated the frame-based target speech present probability (TSPP) using Bayesian classification. Finally, a mask filter was presented by modifying the gain function of the improved phase-error based filter (IPBF) method using TSPP. Simulation results show that the proposed method outperforms the reference methods and could reduce noise effectively, particularly in the period of TSA. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/APSIPA.2013.6694122 | Asia-Pacific Signal and Information Processing Association Annual Summit and Conference |
Keywords | Field | DocType |
noise abatement,gaussian processes,speech processing | Noise reduction,Speech processing,Pattern recognition,Naive Bayes classifier,Computer science,Noise control,Speech recognition,Gain function,Gaussian process,Artificial intelligence,Gaussian noise,Mixture model | Conference |
Volume | Issue | ISSN |
null | null | 2309-9402 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao Chen | 1 | 3 | 2.09 |
| Changchun Bao | 2 | 133 | 46.05 |
| Bingyin Xia | 3 | 5 | 3.64 |