Adaptive on-line neural network retraining for real life multimodal emotion recognition

Authors:
Spiros Ioannou;Loic Kessous;George Caridakis;Kostas Karpouzis;Vered Aharonson;Stefanos Kollias
Affiliations:
School of Electrical and Computer Engineering, National Technical University of Athens, Politechnioupoli, Zographou, Greece;Tel Aviv Academic College of Engineering, Tel Aviv, Israel;School of Electrical and Computer Engineering, National Technical University of Athens, Politechnioupoli, Zographou, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Politechnioupoli, Zographou, Greece;Tel Aviv Academic College of Engineering, Tel Aviv, Israel;School of Electrical and Computer Engineering, National Technical University of Athens, Politechnioupoli, Zographou, Greece
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Year:
2006

Citing 5
Cited 6

Affective computing

Affective computing
SVM-based Nonparametric Discriminant Analysis, An Application to Face Detection

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
2005 Special Issue: Emotion recognition through facial expression analysis based on a neurofuzzy network

Neural Networks - Special issue: Emotion and brain
Parameterized facial expression synthesis based on MPEG-4

EURASIP Journal on Applied Signal Processing
On-line retrainable neural networks: improving the performance of neural networks in image analysis problems

IEEE Transactions on Neural Networks

Automatic emotional stimulus identification from facial expressions

SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
Semantic Adaptation of Neural Network Classifiers in Image Segmentation

ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Automatic emotional stimulus identification from facial expressions

SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
eMotion: un outil pour personnaliser la reconnaissance d'émotions

Proceedings of the Ergonomie et Informatique Avancee Conference
A neural network based retrainable framework for robust object recognition with application to mobile robotics

Applied Intelligence
A dynamic tonal perception model for optimal pitch stylization

Computer Speech and Language

Quantified Score

Hi-index	0.00

Visualization

Abstract

Emotions play a major role in human-to-human communication enabling people to express themselves beyond the verbal domain. In recent years, important advances have been made in unimodal speech and video emotion analysis where facial expression information and prosodic audio features are treated independently. The need however to combine the two modalities in a naturalistic context, where adaptation to specific human characteristics and expressivity is required, and where single modalities alone cannot provide satisfactory evidence, is clear. Appropriate neural network classifiers are proposed for multimodal emotion analysis in this paper, in an adaptive framework, which is able to activate retraining of each modality, whenever deterioration of the respective performance is detected. Results are presented based on the IST HUMAINE NoE naturalistic database; both facial expression information and prosodic audio features are extracted from the same data and feature-based emotion analysis is performed through the proposed adaptive neural network methodology.