Name
Abstract | ||
|---|---|---|
Background environmental noises degrade the performance of speech-processing systems (e.g. speech coding, speech recognition). By modifying the processing according to the type of background noise, the performance can be enhanced. This requires noise classification. In this paper, four pattern-recognition frameworks have been used to design noise classification algorithms. Classification is done on a frame-by-frame basis (e.g. once every 20 ms). Five commonly encountered noises in mobile telephony (i.e. car, street, babble, factory, and bus) have been considered in our study. Our experimental results show that the line spectral frequencies (LSFs) are robust features in distinguishing the different classes of noises. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/ICASSP.1999.758106 | ICASSP |
Keywords | Field | DocType |
background environmental noise,noise classification algorithm,speech recognition,frame-by-frame basis,different class,noise classification,speech coding,background noise,frame level noise classification,mobile environment,line spectral frequency,performance,factory,noise pollution,classification algorithms,telephony,speech processing,algorithm design and analysis,bus,pattern recognition,mobile telephony,street,degradation | Speech processing,Noise classification,Background noise,Speech coding,Pattern recognition,Computer science,Speech recognition,Artificial intelligence,Spectral analysis,Noise pollution,Mobile telephony | Conference |
ISSN | ISBN | Citations |
1520-6149 | 0-7803-5041-3 | 24 |
PageRank | References | Authors |
2.97 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. El-Maleh | 1 | 77 | 5.98 |
| A. Samouelian | 2 | 24 | 2.97 |
| P. Kabal | 3 | 374 | 47.49 |