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138
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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
15 years 11 days ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
130
Voted
CVPR
2005
IEEE
16 years 4 months ago
Diagram Structure Recognition by Bayesian Conditional Random Fields
Hand-drawn diagrams present a complex recognition problem. Elements of the diagram are often individually ambiguous, and require context to be interpreted. We present a recognitio...
Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka
112
Voted
IEAAIE
2004
Springer
15 years 8 months ago
Recognition of Emotional States in Spoken Dialogue with a Robot
For flexible interactions between a robot and humans, we address the issue of automatic recognition of human emotions during the interaction such as embarrassment, pleasure, and af...
Kazunori Komatani, Ryosuke Ito, Tatsuya Kawahara, ...
109
Voted
ECAI
2004
Springer
15 years 6 months ago
Instance-Based Prediction with Guaranteed Confidence
Instance-based learning (IBL) algorithms have proved to be successful in many applications. However, as opposed to standard statistical methods, a prediction in IBL is usually give...
Eyke Hüllermeier
117
Voted
LCN
2005
IEEE
15 years 8 months ago
Automated Traffic Classification and Application Identification using Machine Learning
The dynamic classification and identification of network applications responsible for network traffic flows offers substantial benefits to a number of key areas in IP network engi...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...