Practical numerical algorithms for chaotic systems
Practical numerical algorithms for chaotic systems
A Speech Recognition System that Integrates Neural Nets and HMM
IWANN '91 Proceedings of the International Workshop on Artificial Neural Networks
Speech Communication - Special issue on speech and emotion
Vocal communication of emotion: a review of research paradigms
Speech Communication - Special issue on speech and emotion
Whence and Whither: The Automatic Recognition of Emotions in Speech (Invited Keynote)
PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
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The following paper examines a possibility of applying phone-pronunciation variability descriptors in emotion classification. The proposed group of descriptors comprises a set of statistical parameters of Poincare maps, which are derived for evolution of formant-frequencies and energy of voiced-speech segments. Poincare maps are represented by means of four different parameters that summarize various aspects of plot's scatter. It has been shown that incorporation of the proposed features into a set of commonly-used emotional-speech descriptors, results in a substantial, ten-percent increase in emotion classification performance - recognition rates are at the order of 80% for six-category, speaker independent experiments.