What size net gives valid generalization?
Neural Computation
Instance-Based Learning Algorithms
Machine Learning
Affective computing
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vocal communication of emotion: a review of research paradigms
Speech Communication - Special issue on speech and emotion
Understanding Digital Signal Processing (2nd Edition)
Understanding Digital Signal Processing (2nd Edition)
Ensemble methods for spoken emotion recognition in call-centres
Speech Communication
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Unobtrusive Sensing of Emotions (USE)
Journal of Ambient Intelligence and Smart Environments
Ubiquitous Computing Fundamentals
Ubiquitous Computing Fundamentals
Ubiquitous Computing Fundamentals
Ubiquitous Computing Fundamentals
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatic speech emotion recognition using modulation spectral features
Speech Communication
Infinite Reality: Avatars, Eternal Life, New Worlds, and the Dawn of the Virtual Revolution
Infinite Reality: Avatars, Eternal Life, New Worlds, and the Dawn of the Virtual Revolution
Sensing Emotions: The impact of context on experience measurements (Philips Research Book Series)
Sensing Emotions: The impact of context on experience measurements (Philips Research Book Series)
Tune in to your emotions: a robust personalized affective music player
User Modeling and User-Adapted Interaction
Detecting stress during real-world driving tasks using physiological sensors
IEEE Transactions on Intelligent Transportation Systems
Speech Emotion Analysis: Exploring the Role of Context
IEEE Transactions on Multimedia
IEEE Transactions on Information Theory
Ubiquitous emotion-aware computing
Personal and Ubiquitous Computing
Affective Signal Processing (ASP): Unraveling the mystery of emotions, by Egon L. van den Broek
Journal of Ambient Intelligence and Smart Environments
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This study explores the feasibility of objective and ubiquitous stress assessment. 25 post-traumatic stress disorder patients participated in a controlled storytelling (ST) study and an ecologically valid reliving (RL) study. The two studies were meant to represent an early and a late therapy session, and each consisted of a "happy" and a "stress triggering" part. Two instruments were chosen to assess the stress level of the patients at various point in time during therapy: (i) speech, used as an objective and ubiquitous stress indicator and (ii) the subjective unit of distress (SUD), a clinically validated Likert scale. In total, 13 statistical parameters were derived from each of five speech features: amplitude, zero-crossings, power, high-frequency power, and pitch. To model the emotional state of the patients, 28 parameters were selected from this set by means of a linear regression model and, subsequently, compressed into 11 principal components. The SUD and speech model were cross-validated, using 3 machine learning algorithms. Between 90% (2 SUD levels) and 39% (10 SUD levels) correct classification was achieved. The two sessions could be discriminated in 89% (for ST) and 77% (for RL) of the cases. This report fills a gap between laboratory and clinical studies, and its results emphasize the usefulness of Computer Aided Diagnostics (CAD) for mental health care.