In an earlier study, we analyzed how audio signals obtained from three professional opera singers varied when they sang one octave wide eight-tone scales in ten different emotional colors. The results showed systematic variations in voice source and long-term-average spectrum (LTAS) parameters associated with major emotion “families”. For two of the singers, subglottal pressure (PSub) also was recorded, thus allowing analysis of an additional main physiological voice control parameter, glottal resistance (defined as the ratio between PSub and glottal flow), and related to glottal adduction. In the present study, we analyze voice source and LTAS parameters derived from the audio signal and their correlation with Psub and glottal resistance. The measured parameters showed a systematic relationship with the four emotion families observed in our previous study. They also varied systematically with values of the ten emotions along the valence, power, and arousal dimensions; valence showed a significant correlation with the ratio between acoustic voice source energy and subglottal pressure, while Power varied significantly with sound level and two measures related to the spectral dominance of the lowest spectrum partial. the fundamental.

Background

Acoustic aspects of emotional expressivity in speech have been analyzed extensively during recent decades. Emotional coloring is an important if not the most important property of sung performance, and therefore strictly controlled. Hence, emotional expressivity in singing may promote a deeper insight into vocal signaling of emotions. Furthermore, physiological voice source parameters can be assumed to facilitate the understanding of acoustical characteristics.

Method

Three highly experienced professional male singers sang scales on the vowel /ae/ or /a/ in 10 emotional colors (Neutral, Sadness, Tender, Calm, Joy, Contempt, Fear, Pride, Love, Arousal, and Anger). Sixteen voice experts classified the scales in a forced-choice listening test, and the result was compared with long-term-average spectrum (LTAS) parameters and with voice source parameters, derived from flow glottograms (FLOGG) that were obtained from inverse filtering the audio signal.

Results

On the basis of component analysis, the emotions could be grouped into four “families”, Anger-Contempt, Joy-Love-Pride, Calm-Tender-Neutral and Sad-Fear. Recognition of the intended emotion families by listeners reached accuracy levels far beyond chance level. For the LTAS and FLOGG parameters, vocal loudness had a paramount influence on all. Also after partialing out this factor, some significant correlations were found between FLOGG and LTAS parameters. These parameters could be sorted into groups that were associated with the emotion families.

Conclusions

(i) Both LTAS and FLOGG parameters varied significantly with the enactment intentions of the singers. (ii) Some aspects of the voice source are reflected in LTAS parameters. (iii) LTAS parameters affect listener judgment of the enacted emotions and the accuracy of the intended emotional coloring.