Comparing feature sets for acted and spontaneous speech in view of automatic emotion recognition

被引：93
|
作者：
Vogt, T [1 ]
André, E [1 ]
机构：
[1] Univ Augsburg, D-8900 Augsburg, Germany
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), VOLS 1 AND 2 | 2005年
关键词：
D O I：
10.1109/ICME.2005.1521463
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：474 / 477
页数：4
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