Name
Abstract | ||
|---|---|---|
While many efforts have been made in the audio signal classification field, the noise interruption problem is seldom concerned so far, especially in many telecommunication applications, where a real-time and noise robust approach is needed. This paper addresses this problem by proposing two novel robust features: average pitch density (APD) and relative tonal power density (RTPD). APD refers to the differences in tone characteristics of music and speech signals, and RTPD especially focuses on the distinct properties of the percussion instruments. The comparison experiments are implemented on two databases. The first one is reorganized from the corpus collected,. The second one consists of data collected from various recording situations. The novel features are compared with several state-of-the-art features and are found to achieve significant robustness. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICME.2009.5202561 | ICME |
Keywords | Field | DocType |
real cepstrum,novel robust feature,speech processing,distinct property,comparison experiment,novel feature,music,noise robust approach,real-time telecommunication,speech signal,spectral analysis,music discrimination,noise interruption problem,noise robust feature,percussion instrument,audio signal classification field,support vector machine,signal classification,average pitch density,relative tonal power density,audio classification,noise robust features,percussion instruments,real-time systems,musical system,speech,feature extraction,real time,real time systems,multiple signal classification,data collection,communications technology,power density,robustness,noise | Speech processing,Multiple signal classification,Telecommunications,Computer science,Robustness (computer science),Artificial intelligence,Signal classification,Pattern recognition,Support vector machine,Audio signal classification,Feature extraction,Speech recognition,Spectral analysis | Conference |
ISSN | ISBN | Citations |
1945-7871 E-ISBN : 978-1-4244-1291-1 | 978-1-4244-1291-1 | 2 |
PageRank | References | Authors |
0.41 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhong-Hua Fu | 1 | 52 | 9.96 |
| Jhing-fa Wang | 2 | 982 | 114.31 |
| Lei Xie | 3 | 425 | 64.87 |