Name
Abstract | ||
|---|---|---|
This paper studied the algorithm of speech emotion recognition based on TWINsSVM (Twins Support Vector Machines). The algorithm tried to find the underlying structures of different emotions in speech signal. Different acoustic features are combined to test seven primary human emotions including anger, boredom, disgust,fear/anxiety, happiness, neutral, sadness. And the comparisons on classification algorithm between TWINsSVM and SSVM (Standard Support Vector Machines) are proposed. A series of experiments based on different speech emotion databases show that the more efficient and accurate results can be achieved using TWINsSVM. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICNC.2009.464 | ICNC (2) |
Keywords | Field | DocType |
support vector machine,speech recognition,speech,mel frequency cepstral coefficient,databases,support vector machines | Mel-frequency cepstrum,Sadness,Computer science,Disgust,Anxiety,Support vector machine,Speech recognition,Anger,Happiness,Boredom | Conference |
Volume | Issue | Citations |
2 | null | 4 |
PageRank | References | Authors |
0.41 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chengfu Yang | 1 | 4 | 0.75 |
| Luping Ji | 2 | 149 | 10.31 |
| Guisong Liu | 3 | 42 | 12.84 |