Name
Abstract | ||
|---|---|---|
The increasing popularity of miniature devices and loud-speakers has fuelled research in non-linear acoustic echo cancellation (NAEC). This paper reports a novel approach to NAEC based on empirical mode decomposition (EMD), a recently developed technique in non-linear and non-stationary signal analysis. EMD decomposes any signal into a finite number of time varying sub-band signals termed intrinsic mode functions (IMFs). The new approach to NAEC presented here incorporates this multi-resolution analysis with conventional power filtering to estimate non-linear echo in each IMF. Comparative experiments with a competitive baseline approach to NAEC based on pure power filtering show that the new EMD approach achieves greater non-linear echo reduction and faster convergence. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICASSP.2015.7178042 | 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
Echo cancellation, non-linear modelling, empirical mode decomposition (EMD), intrinsic mode functions (IMF) | Convergence (routing),Signal processing,Finite set,Nonlinear system,Computer science,Artificial intelligence,Loudspeaker,Pattern recognition,Filter (signal processing),Algorithm,Speech recognition,Telecommunications link,Hilbert–Huang transform | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
16 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leela K. Gudupudi | 1 | 0 | 0.68 |
| Navin Chatlani | 2 | 44 | 5.04 |
| Christophe Beaugeant | 3 | 148 | 20.60 |
| nicholas evans | 4 | 594 | 54.41 |