Describing the emotional states that are expressed in speech

By R. Cowie, Randolph R. Cornelius. Speech Communication, 2003

792 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/22eb85db7a0cd6cdd05b40cb503eeb3f1b846a39

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

In Social Psychology

Citations in the corpus

Emotion Recognition Using Bio-sensors: First Steps towards an Automatic System (2004, background): “Two of the more researched methods include speech [12,14] and face recognition [15].”
Emotion Assessment: Arousal Evaluation Using EEG's and Peripheral Physiological Signals (2006, methodology): “Cowie used the valence/activation space, which is similar to the valence/arousal space, to model and assess emotions from speech [4], [5].”
Emotional speech synthesis: a review (2001, background): “: brilliance "-3"”
Emotion recognition from speech: a review (2012, background): “In the literature, mainly, pitch, energy, duration and their derivatives are used as the acoustic correlates of prosodic features (Banziger and Scherer 2005; Cowie and Cornelius 2003).”
Challenges in real-life emotion annotation and machine learning based detection (2005, neutral): “For a recent review, the reader is referred to Cowie and Cornelius (2003).”
Understanding the Processes that Regulate Positive Emotional Experience: Unsolved Problems and Future Directions for Theory and Research on Savoring (2011, methodology): “Cowie and Cornelius (2003) have reviewed methods, tools, and coding systems currently available for quantifying the emotional states conveyed in human speech.”
Automatic speech recognition and speech variability: A review (2007, background): “It is recognized that a speaker mood change has a considerable impact on the features extracted from his speech, hence directly affecting the basis of all speech recognition systems (Cowie and Cornelius, 2003; Scherer, 2003).”
BP4D-Spontaneous: a high-resolution spontaneous 3D dynamic facial expression database (2014, background): “These methods evoke a range of authentic emotions in a laboratory environment [11].”
Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond (2018, background): “The most frequently used emotion representation is the categorical one, including the seven basic categories, i.e., Anger, Disgust, Fear, Happiness, Sad-ness, Surprise and Neutral [14] [11].”
Analysis of Emotionally Salient Aspects of Fundamental Frequency for Emotion Detection (2009, background): “The boundaries between emotional categories are blurred [7] and do not account for different degrees of emotional intensity [40].”
Primitives-based evaluation and estimation of emotions in speech (2007, neutral): “These constituents will be referred to as primitives in this paper.”
Emotion Recognition (2009, background): “They are, moreover, often restricted to only a few emotions, such as joy or frustration [3, 5, 7].”
Events Detection for an Audio-Based Surveillance System (2005, background): “to symptomatic emotions occurring when the matter of survival is raised, including the various fear-related emotional states [10] from worry to panic.”
Aff-Wild: Valence and Arousal ‘In-the-Wild’ Challenge (2017, neutral): “, Anger, Disgust, Fear, Happiness, Sadness, Surprise and Neutral [13][10].”