The nature of statistical learning theory
The nature of statistical learning theory
Overfitting in making comparisons between variable selection methods
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Ensemble methods for spoken emotion recognition in call-centres
Speech Communication
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Emotion aware mobile application
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part II
Spoken emotion recognition using hierarchical classifiers
Computer Speech and Language
Segment-based emotion recognition from continuous Mandarin Chinese speech
Computers in Human Behavior
Emotional states in judicial courtrooms: An experimental investigation
Speech Communication
Classification of emotional speech using 3DEC hierarchical classifier
Speech Communication
International Journal of Speech Technology
Speech emotional features extraction based on electroglottograph
Neural Computation
Class-specific multiple classifiers scheme to recognize emotions from speech signals
Computer Speech and Language
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In this paper we propose a new set of harmony features for automatic emotion recognition from speech signals. They are based on the psychoacoustic harmony perception known from music theory. Starting from the estimated pitch contour of an utterance, we calculate the circular autocorrelation of the pitch histogram on the logarithmic semitone scale. It measures the occurrence of different two-pitch intervals which cause a consonant or dissonant impression. Experiments of emotion recognition using these harmony parameters in addition to state of the art features show an improved recognition performance.