Name
Abstract | ||
|---|---|---|
We propose a novel real-time affect classification system based on features extracted from the acoustic speech signal. The proposed system analyses the speech signal and provides a real-time classification of the speakerýs perceived affective state. A neural network is trained and tested using a database of 391 authentic emotional utterances from 11 speakers. Two emotions, anger and neutral, are considered. The system is designed to be speaker and text-independent and is to be deployed in a call-centre environment to assist in the handling of customer inquiries. We achieve a success rate of 80.1% accuracy in our preliminary results. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICITA.2005.231 | Information Technology and Applications, 2005. ICITA 2005. Third International Conference |
Keywords | Field | DocType |
acoustic signal processing,call centres,neural nets,signal classification,speech processing,speech recognition,acoustic speech signal,call-centres,neural network,real-time classification,real-time spoken affect classification | Real time classification,Speech processing,Computer science,Emotion recognition,Speech recognition,Feature extraction,Natural language processing,Anger,Artificial intelligence,Affect (psychology),Artificial neural network,Acoustical engineering | Conference |
Volume | ISBN | Citations |
1 | 0-7695-2316-1 | 10 |
PageRank | References | Authors |
0.96 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Morrison, D. | 1 | 10 | 0.96 |
| Ruili Wang | 2 | 446 | 50.35 |
| De Silva, L.C. | 3 | 10 | 1.29 |
| Xu, W.L. | 4 | 10 | 0.96 |