Name
Title | ||
|---|---|---|
Classification of emotional states in a woz scenario exploiting labeled and unlabeled bio-physiological data |
Abstract | ||
|---|---|---|
In this paper, a partially supervised machine learning approach is proposed for the recognition of emotional user states in HCI from bio-physiological data. To do so, an unsupervised learning preprocessing step is integrated into the training of a classifier. This makes it feasible to utilize unlabeled data or --- as it is conducted in this study --- data that is labeled in others than the considered categories. Thus, the data is transformed into a new representation and a standard classifier approach is subsequently applied. Experimental evidences that such an approach is beneficial in this particular setting is provided using classification experiments. Finally, the results are discussed and arguments when such an partially supervised approach is promising to yield robust and increased classification performances are given. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-28258-4_15 | PSL |
Keywords | Field | DocType |
emotional state,supervised machine,experimental evidence,supervised approach,classification experiment,woz scenario,emotional user state,bio-physiological data,new representation,unlabeled bio-physiological data,unlabeled data,increased classification performance,standard classifier approach | Semi-supervised learning,Pattern recognition,Computer science,Preprocessor,Unsupervised learning,Artificial intelligence,Classifier (linguistics),Machine learning,Mixture model | Conference |
Citations | PageRank | References |
7 | 0.46 | 10 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Schels | 1 | 277 | 15.88 |
| Markus Kächele | 2 | 222 | 14.76 |
| David Hrabal | 3 | 73 | 6.01 |
| Steffen Walter | 4 | 127 | 13.34 |
| Harald C. Traue | 5 | 129 | 13.48 |
| Friedhelm Schwenker | 6 | 1160 | 96.59 |