Machine learning analysis demonstrates classification of emotional speech through acoustic features, indicating spectral tilt and pitch contour differentiate emotional valence.
This paper presents results from a study examining emotional speech using acoustic features and their use in automatic machine learning classification. In addition, we propose a classification scheme for the labeling of emotions on continuous scales. Our findings support those of previous research as well as indicate possible future directions utilizing spectral tilt and pitch contour to distinguish emotions in the valence dimension.
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Liscombe et al. (2003) studied this question.
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