<p>This thesis investigated whether vocal emotion expressions are conveyed as discrete emotions or as continuous dimensions. </p><p>Study I consisted of a meta-analysis of decoding accuracy of discrete emotions (anger, fear, happiness, love-tenderness, sadness) within and across cultures. Also, the literature on acoustic characteristics of expressions was reviewed. Results suggest that vocal expressions are universally recognized and that there exist emotion-specific patterns of voice-cues for discrete emotions.</p><p>In Study II, actors vocally portrayed anger, disgust, fear, happiness, and sadness with weak and strong emotion intensity. The portrayals were decoded by listeners and acoustically analyzed with respect to 20 voice-cues (e.g., speech rate, voice intensity, fundamental frequency, spectral energy distribution). Both the intended emotion and intensity of the portrayals were accurately decoded and had an impact on voice-cues. Listeners’ ratings of both emotion and intensity could be predicted from a selection of voice-cues.</p><p>In Study III, listeners rated the portrayals from Study II on emotion dimensions (activation, valence, potency, emotion intensity). All dimensions were correlated with several voice-cues. Listeners’ ratings could be successfully predicted from the voice-cues for all dimensions except valence.</p><p>In Study IV, continua of morphed expressions, ranging from one emotion to another in equal steps, were created using speech synthesis. Listeners identified the emotion of each expression and discriminated between pairs of expressions. The continua were perceived as two distinct sections separated by a sudden category boundary. Also, discrimination accuracy was generally higher for pairs of stimuli falling across category boundaries than for pairs belonging to the same category. This suggests that vocal expressions are categorically perceived.</p><p>Taken together, the results suggest that a discrete-emotions approach provides the best account of vocal expression. Previous difficulties in finding emotion-specific patterns of voice-cues may be explained in terms of limitations of previous studies and the coding of the communicative process.</p>

This thesis investigated whether vocal emotion expressions are conveyed as discrete emotions or as continuous dimensions. Study I consisted of a meta-analysis of decoding accuracy of discrete emotions (anger, fear, happiness, love-tenderness, sadness) within and across cultures. Also, the literature on acoustic characteristics of expressions was reviewed. Results suggest that vocal expressions are universally recognized and that there exist emotion-specific patterns of voice-cues for discrete emotions. In Study II, actors vocally portrayed anger, disgust, fear, happiness, and sadness with weak and strong emotion intensity. The portrayals were decoded by listeners and acoustically analyzed with respect to 20 voice-cues (e.g., speech rate, voice intensity, fundamental frequency, spectral energy distribution). Both the intended emotion and intensity of the portrayals were accurately decoded and had an impact on voice-cues. Listeners’ ratings of both emotion and intensity could be predicted from a selection of voice-cues. In Study III, listeners rated the portrayals from Study II on emotion dimensions (activation, valence, potency, emotion intensity). All dimensions were correlated with several voice-cues. Listeners’ ratings could be successfully predicted from the voice-cues for all dimensions except valence. In Study IV, continua of morphed expressions, ranging from one emotion to another in equal steps, were created using speech synthesis. Listeners identified the emotion of each expression and discriminated between pairs of expressions. The continua were perceived as two distinct sections separated by a sudden category boundary. Also, discrimination accuracy was generally higher for pairs of stimuli falling across category boundaries than for pairs belonging to the same category. This suggests that vocal expressions are categorically perceived. Taken together, the results suggest that a discrete-emotions approach provides the best account of vocal expression. Previous difficulties in finding emotion-specific patterns of voice-cues may be explained in terms of limitations of previous studies and the coding of the communicative process.