Real-Time Emotion Recognition Using Echo State Networks

Authors:
Stefan Scherer;Mohamed Oubbati;Friedhelm Schwenker;Günther Palm
Affiliations:
Institute of Neural Information Processing, Ulm University, Germany 89069;Institute of Neural Information Processing, Ulm University, Germany 89069;Institute of Neural Information Processing, Ulm University, Germany 89069;Institute of Neural Information Processing, Ulm University, Germany 89069
Venue:
PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
Year:
2008

Citing 3
Cited 1

Affective computing

Affective computing
Combining Pattern Classifiers: Methods and Algorithms

Combining Pattern Classifiers: Methods and Algorithms
Real-Time Emotion Recognition from Speech Using Echo State Networks

ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition

Emotional vocal expressions recognition using the COST 2102 italian database of emotional speech

COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony

Quantified Score

Hi-index	0.00

Visualization

Abstract

The goal of this work is the exploration of real-time emotion recognition from speech. In this approach a novel type of recurrent neural networks called echo state networks (ESN) are utilized. Biologically motivated features representing modulations of the speech signal are used as input to the ESNs. The standard Berlin Database of Emotional Speech is used to evaluate the performance of the proposed approach. However, in this paper ongoing work is being presented and the final architecture has yet to be determined.