• Corpus ID: 14212085

Multimodal Emotion Recognition Integrating Affective Speech with Facial Expression

@inproceedings{Zhao2014MultimodalER,
  title={Multimodal Emotion Recognition Integrating Affective Speech with Facial Expression},
  author={Xiaoming Zhao and Shiqing Zhang and Xiaohua Wang and Gang Zhang},
  year={2014}
}
In recent years, emotion recognition has attracted extensive interest in signal processing, artificial intelligence and pattern recognition due to its potential applications to human-computer-interaction (HCI). Most previously published works in the field of emotion recognition devote to performing emotion recognition by using either affective speech or facial expression. However, Affective speech and facial expression are mainly two important ways of human emotion expression, as they are the… 
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References

SHOWING 1-10 OF 53 REFERENCES
Human emotion recognition system using optimally designed SVM with different facial feature extraction techniques
TLDR
All six universally recognized basic emotions namely angry, disgust, fear, happy, sad and surprise along with neutral one are recognized in this research.
Speech Emotion Recognition Using an Enhanced Kernel Isomap for Human-Robot Interaction
TLDR
A new nonlinear dimensionality reduction method, called ‘enhanced kernel isometric mapping’ (EKIsomap), is proposed and applied for speech emotion recognition in human-robot interaction and is used to nonlinearly extract the low-dimensional discriminating embedded data representations from the original high-dimensional speech features with a striking improvement of performance on thespeech emotion recognition tasks.
Speech emotion recognition approaches in human computer interaction
TLDR
A wide range of features employed for speech emotion recognition and the acoustic characteristics of those features are presented and some important parameters such as: precision, recall, F-measure and recognition rate of the features are analyzed.
Emotion recognition in speech signal: experimental study, development, and application
TLDR
An emotion recognition agent was created that is able to analyze telephone quality speech signal and distinguish between two emotional states --"agitation" and "calm" -with the accuracy of 77%.
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Speech emotion recognition using hidden Markov models
This paper introduces a first approach to emotion recognition using RAMSES, the UPC’s speech recognition system. The approach is based on standard speech recognition technology using hidden…
Facial expression recognition based on local binary patterns and local fisher discriminant analysis
TLDR
This paper shows that the presented facial expression recognition method based on LBP and LFDA obtains the best recognition accuracy of 90.7% with 11 reduced features, outperforming the other used methods such as principal component analysis (PCA), linear discriminant analysis (LDA), locality preserving projection (LPP).
Facial Expression Recognition Using Sparse Representation
TLDR
Experimental results on two popular facial expression databases demonstrate the promising performance of the presented SRC method on facial expression recognition tasks, outperforming the other used methods.
Local binary patterns for multi-view facial expression recognition
Facial Expression Recognition
TLDR
This chapter describes the problem space for facial expression analysis, which includes multiple dimensions: level of description, individual differences in subjects, transitions among expressions, intensity of facial expression, deliberate versus spontaneous expression, head orientation and scene complexity, image acquisition and resolution, reliability of ground truth, databases, and the relation to other facial behaviors or nonfacial behaviors.
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