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2016
The recognition of emotional signals from all sensory modalities is a critical component of human social interactions. It is through the understanding of the affective states of others that we can guide our own behavioral responses. Notably, facial expression provides the greatest amount of emotional cues that are useful in recognizing emotions, such ...
Bharti W. Gawali +2 more
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The recognition of emotional signals from all sensory modalities is a critical component of human social interactions. It is through the understanding of the affective states of others that we can guide our own behavioral responses. Notably, facial expression provides the greatest amount of emotional cues that are useful in recognizing emotions, such ...
Bharti W. Gawali +2 more
openaire +3 more sources
The automaticity of emotion recognition.
Emotion, 2008Evolutionary accounts of emotion typically assume that humans evolved to quickly and efficiently recognize emotion expressions because these expressions convey fitness-enhancing messages. The present research tested this assumption in 2 studies. Specifically, the authors examined (a) how quickly perceivers could recognize expressions of anger, contempt,
Jessica L. Tracy, Richard W. Robins
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IEEE Transactions on Cognitive and Developmental Systems, 2021
Multimodal signals are powerful for emotion recognition since they can represent emotions comprehensively. In this article, we compare the recognition performance and robustness of two multimodal emotion recognition models: 1) deep canonical correlation ...
Wei Liu +3 more
semanticscholar +1 more source
Multimodal signals are powerful for emotion recognition since they can represent emotions comprehensively. In this article, we compare the recognition performance and robustness of two multimodal emotion recognition models: 1) deep canonical correlation ...
Wei Liu +3 more
semanticscholar +1 more source
Cues and channels in emotion recognition.
Journal of Personality and Social Psychology, 1986This article addresses methodological issues pertinent to judgment studies in nonverbal communication research, in general, and to the perception and attribution of emotions, in particular. We investigated which behavioral cues are used in portraying various emotions and to what extent the channel of presentation and encoding differences between actors
Wallbott, Harald G., Scherer, Klaus R.
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A Bi-Hemisphere Domain Adversarial Neural Network Model for EEG Emotion Recognition
IEEE Transactions on Affective Computing, 2021In this paper, we propose a novel neural network model, called bi-hemisphere domain adversarial neural network (BiDANN) model, for electroencephalograph (EEG) emotion recognition.
Yang Li +5 more
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Application of Emotion Recognition and Modification for Emotional Telugu Speech Recognition
Mobile Networks and Applications, 2018Majority of the automatic speech recognition systems (ASR) are trained with neutral speech and the performance of these systems are affected due to the presence of emotional content in the speech. The recognition of these emotions in human speech is considered to be the crucial aspect of human-machine interaction.
Krishna Gurugubelli +2 more
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CTNet: Conversational Transformer Network for Emotion Recognition
IEEE/ACM Transactions on Audio Speech and Language Processing, 2021Emotion recognition in conversation is a crucial topic for its widespread applications in the field of human-computer interactions. Unlike vanilla emotion recognition of individual utterances, conversational emotion recognition requires modeling both ...
Zheng Lian, Bin Liu, J. Tao
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Towards authentic emotion recognition
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005In human computer interaction, the ultimate goal is to have effortless and natural communication. In the research literature significant effort has been directed toward understanding the functional aspects of the communication. However, it is well known that the functional aspect is insufficient for natural interactions.
Sebe, Niculae +5 more
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Bimodal emotion recognition [PDF]
Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580), 2002 This paper describes the use of statistical techniques and hidden Markov models (HMM) in the recognition of emotions. The method aims to classify 6 basic emotions (anger, dislike, fear, happiness, sadness and surprise) from both facial expressions (video) and emotional speech (audio). The emotions of 2 human subjects were recorded and analyzed.
L.C. De Silva, Pei Chi Ng
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The Journal of the Acoustical Society of America, 2012
An emotion recognition apparatus performs accurate and stable speech-based emotion recognition, irrespective of individual, regional, and language differences of prosodic information. The emotion recognition apparatus includes: a speech recognition unit which recognizes types of phonemes included in the input speech; a characteristic tone detection ...
Yoshihisa Nakatoh +3 more
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An emotion recognition apparatus performs accurate and stable speech-based emotion recognition, irrespective of individual, regional, and language differences of prosodic information. The emotion recognition apparatus includes: a speech recognition unit which recognizes types of phonemes included in the input speech; a characteristic tone detection ...
Yoshihisa Nakatoh +3 more
openaire +2 more sources