Name
Abstract | ||
|---|---|---|
In this letter, we propose a novel residual echo suppression (RES) algorithm based on a statistical model constructed in the acoustic echo cancellation framework. In the proposed approach, all the possible near-end and far-end signal conditions are classified into four distinct hypotheses, and the power spectral density estimation is carried out according to the result of hypothesis testing. The d... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/LSP.2007.896452 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Echo cancellers,Acoustic testing,Speech enhancement,Frequency domain analysis,Parametric statistics,Performance evaluation,Adaptive filters,Attenuation,Background noise,Standards development | Residual,Parametric model,Likelihood-ratio test,Pattern recognition,Signal-to-noise ratio,Spectral density,Artificial intelligence,Adaptive filter,Statistical model,Statistical hypothesis testing,Mathematics | Journal |
Volume | Issue | ISSN |
14 | 10 | 1070-9908 |
Citations | PageRank | References |
11 | 0.80 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seung Yeol Lee | 1 | 32 | 3.98 |
| Nam Soo Kim | 2 | 275 | 29.16 |