Name
Title | ||
|---|---|---|
Dimensionality reduction and classification analysis on the audio section of the SEMAINE database |
Abstract | ||
|---|---|---|
This paper presents an analysis of the audio section of the SEMAINE database for affect detection. Chi-square and principal component analysis techniques are used to reduce the dimensionality of the audio datasets. After dimensionality reduction, different classification techniques are used to perform emotion classification at the word level. Additionally, for unbalanced training sets, class re-sampling is performed to improve the model's classification results. Overall, the final results indicate that Support Vector Machines (SVM) performed best for all data sets. Results show promise for the SEMAINE database as an interesting corpus to study affect detection. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-24571-8_43 | ACII (2) |
Keywords | Field | DocType |
support vector machines,semaine database,emotion classification,different classification technique,principal component analysis technique,dimensionality reduction,audio section,classification result,audio datasets,affect detection,classification analysis,speech processing | Speech processing,Data set,Dimensionality reduction,Pattern recognition,Computer science,Support vector machine,Emotion classification,Curse of dimensionality,Artificial intelligence,Database,Principal component analysis,Machine learning | Conference |
Volume | ISSN | Citations |
6975 | 0302-9743 | 3 |
PageRank | References | Authors |
0.39 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo A. Calix | 1 | 27 | 7.75 |
| Mehdi A. Khazaeli | 2 | 3 | 0.73 |
| Leili Javadpour | 3 | 7 | 1.18 |
| Gerald M. Knapp | 4 | 55 | 7.35 |