ABSTRACT
Acoustic variation in expressive speech at the syllable level is studied. As emotions or attitudes can be conveyed by short spoken words, analysis of paradigmatic variations in vowels is an important issue to characterize the expressive content of such speech segments. The corpus contains 160 sentences produced under seven expressive conditions (Neutral, Anger, Fear, Surprise, Sensuality, Joy, Sadness) acted by a French female speaker (a total of 1120 sentences, 13 140 vowels). Eleven base acoustic parameters are selected for voice source and vocal tract related feature analysis. An acoustic description of the expressions is drawn, using the dimensions of melodic range, intensity, noise, spectral tilt, vocalic space, and dynamic features. The first three functions of a discriminant analysis explain 95% of the variance in the data. These statistical dimensions are consistently associated with acoustic dimensions. Covariation of intensity and F0 explains over 80% of the variance, followed by noise features (8%), covariation of spectral tilt, and F0 (7%). On the basis of isolated vowels alone, expressions are classified with a mean accuracy of 78%.
