Name
Abstract | ||
|---|---|---|
Audio processing applications such as rate determination, bandwidth extension, compression, and noise reduction make use of loudness metries. Most loudness estimation algorithms are computationally expensive and often not suitable for real time applications. In this paper, we present a low-complexity loudness estimation algorithm applicable to both steady and time-varying sounds. The model computes an estimate of the excitation pattern by simultaneously pruning the frequency components and detector locations. Comparative results indicate that the proposed algorithm performs consistently well for different types of audio signals at a reduced complexity. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICASSP.2008.4517621 | ICASSP |
Keywords | Field | DocType |
audio signal processing,loudness,time-varying systems,audio processing,audio signals,excitation pattern,loudness estimation algorithm,loudness metrics,steady sounds,time-varying sounds,audio coding,loudness,psychoacoustics | Noise reduction,Loudness,Audio signal,Psychoacoustics,Pattern recognition,Computer science,Bandwidth extension,Algorithm,Artificial intelligence,Audio signal processing,Detector | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.40 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Harish Krishnamoorthi | 1 | 13 | 2.46 |
| Visar Berisha | 2 | 76 | 22.38 |
| Andreas S. Spanias | 3 | 528 | 87.90 |