Name
Abstract | ||
|---|---|---|
Recently, it has been proposed to use the minimum-variance distortionless-response (MVDR) approach in single-channel speech enhancement in the short-time frequency domain. By applying optimal FIR filters to each subband signal, these filters reduce additive noise components with less speech distortion compared to conventional approaches. An important ingredient to these filters is the temporal correlation of the speech signals. We derive algorithms to provide a blind estimation of this quantity based on a maximum-likelihood and maximum a-posteriori estimation. To derive proper models for the inter-frame correlation of the speech and noise signals, we investigate their statistics on a large dataset. If the speech correlation is properly estimated, the previously derived subband filters discussed in this work show significantly less speech distortion compared to conventional noise reduction algorithms. Therefore, the focus of the experimental parts of this work lies on the quality and intelligibility of the processed signals. To evaluate the performance of the subband filters in combination with the clean speech inter-frame correlation estimators, we predict the speech quality and intelligibility by objective measures. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TASLP.2014.2329633 | Audio, Speech, and Language Processing, IEEE/ACM Transactions |
Keywords | Field | DocType |
FIR filters,correlation methods,maximum likelihood estimation,signal denoising,speech enhancement,speech intelligibility,MVDR processing,additive noise component reduction,blind estimation,interframe correlation,maximum a-posteriori estimation,maximum likelihood estimation,minimum variance distortionless response,noise reduction,optimal FIR filter,short time frequency domain,single channel speech enhancement,speech distortion,speech intelligibility,speech quality,subband signal,subband speech correlation estimation,Noise reduction,Wiener filter,speech enhancement,speech intelligibility,speech quality,subband filtering | Speech enhancement,Frequency domain,Wiener filter,Noise reduction,Speech coding,Computer science,Speech recognition,Linear predictive coding,Intelligibility (communication),Estimator | Journal |
Volume | Issue | ISSN |
22 | 9 | 2329-9290 |
Citations | PageRank | References |
10 | 0.72 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Schasse, A. | 1 | 17 | 1.97 |
| Rainer Martin | 2 | 1029 | 91.14 |