Name
Abstract | ||
|---|---|---|
A noise suppression algorithm is proposed based on filtering the spectrotemporal modulations of noisy signals. The modulations are estimated from a multiscale representation of the signal spectrogram generated by a model of sound processing in the auditory system. A significant advantage of this method is its ability to suppress noise that has distinctive modulation patterns, despite being spectrally overlapping with the signal. The performance of the algorithm is evaluated using subjective and objective tests with contaminated speech signals and compared to traditional Wiener filtering method. The results demonstrate the efficacy of the spectrotemporal filtering approach in the conditions examined. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1155/2007/42357 | EURASIP J. Audio, Speech and Music Processing |
Keywords | Field | DocType |
distinctive modulation pattern,multiscale representation,significant advantage,auditory system,noisy signal,contaminated speech signal,signal spectrogram,spectrotemporal modulation,noise suppression algorithm,objective test | Noise reduction,Wiener filter,Pattern recognition,Spectrogram,Computer science,Filter (signal processing),Auditory system,Speech recognition,Modulation,Artificial intelligence,Audio signal processing,Modulation (music) | Journal |
Volume | Issue | ISSN |
2007 | 3 | 1687-4722 |
Citations | PageRank | References |
13 | 0.90 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nima Mesgarani | 1 | 256 | 22.43 |
| Shihab Shamma | 2 | 554 | 67.25 |