Sciweavers

Share
ICMCS
2005
IEEE

Comparing Feature Sets for Acted and Spontaneous Speech in View of Automatic Emotion Recognition

11 years 5 months ago
Comparing Feature Sets for Acted and Spontaneous Speech in View of Automatic Emotion Recognition
We present a data-mining experiment on feature selection for automatic emotion recognition. Starting from more than 1000 features derived from pitch, energy and MFCC time series, the most relevant features in respect to the data are selected from this set by removing correlated features. The features selected for acted and realistic emotions are analysed and show significant differences. All features are computed automatically and we also contrast automatically with manually units of analysis. A higher degree of automation did not prove to be a disadvantage in terms of recognition accuracy.
Thurid Vogt, Elisabeth André
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICMCS
Authors Thurid Vogt, Elisabeth André
Comments (0)
books