Abstract
This study addresses the perception of affect in vocal and glottal recordings of a singing voice. An experiment was made to rate the samples on four broad affect terms describing the two-dimensional model of emotion. A cross-tabulation between the singing expressions and affect scores revealed their relationship with affect dimensions. Prosodic as well as spectral acoustic cues were extracted and statistical analysis performed on 22 features revealed a set of cues whose means are statistically significant with respect to valence and arousal, namely SPR, F5, B1, B4, mean pitch, mean intensity, brightness, jitter, shimmer, mean autocorrelation, mean HNR, mean LTAS, RMS, SPL, LPH, and LTAS slope. Principal component analysis was made for vocal and glottal features: 2 components explained 78.1 % and 73.5 % of the original variance of prosodic cues, and 2 components explained 86.3 % and 86.7 % of the original variance of prosodic and spectral cues.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Boersma, P.: Praat, a system for doing phonetics by computer. Glot Int. 5(9/10), 341–345 (2001)
Boersma, P., Kovacic, G.: Spectral characteristics of three styles of croatian folk singing. J. Acoust. Soc. Am. 119, 1805–1816 (2006)
Cox, T.J.: Tutorial: Public Engagement Through Audio Internet Experiments. University of Salford, Salford (2011)
Grichkovtsova, I., Morel, M., Lacheret, A.: The role of voice quality and prosodic contour in affective speech perception. Speech Commun. 54(3), 414–429 (2012)
Ishi, C., Campbell, N.: Analysis of Acoustic-prosodic Features of Spontaneous Expressive Speech. Revista de Estudos da Linguagem 12(2), 38–49 (2012)
Jansens, S., Bloothooft, G., De Krom, G.: Perception and acoustics of emotions in singing. In: Proceedings of the 5th Eurospeech, vol. 4, pp. 2155–2158 (1997)
Joshi, A., Kaur, R.: A Study of speech emotion recognition methods. Int. J. Comput. Sci. Mob. Comput. (IJCSMC) 2(4), 28–31 (2013)
Lartillot, O., Toiviainen, P.: A Matlab toolbox for musical feature extraction from audio. In: Proceedings of the 10th International Conference on Digital Audio Effects (DAFx-07) (2007)
Lin E., Jayakody D., Looi V.: The singing power ratio and timbre-related acoustic analysis of singing vowels and musical instruments. In: Voice Foundation’s 38th Annual Symposium: Care of the Professional Voice (2009)
Lundy, D.S., Roy, S., Casiano, R., Xue, J., Evans, J.: Acoustic analysis of the singing and speaking voice in singing students. J. Voice 14(4), 490–493 (2000)
Millhouse, T., Clermont, F.: Perceptual characterisation of the singer’s formant region: a preliminary study. In: Proceedings of the Eleventh Australian International Conference on Speech Science and Technology, pp. 253–258 (2006)
Omori, K., Kacker, A., Carroll, L.M., Riley, W.D., Blaugrund, S.M.: Singing power ratio: quantitative evaluation of singing voice quality. J. Voice 10(3), 228–235 (1996)
Patel, S., Scherer, K.R., Björkner, E., Sundberg, J.: Mapping emotions into acoustic space: the role of voice production. Biol. Psychol. 87(1), 93–98 (2011)
Pittam, J., Gallois, C., Callan, V.: The long-term spectrum and perceived emotion. Speech Commun. 9(3), 177–187 (1990)
R development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing (2008)
Russel, J.: A circumplex model of affect. J. Pers. Soc. Psychol. 39(6), 1161–1178 (1980)
Scherer, K.R., Banse, R., Wallbott, H.G.: Emotion inferences from vocal expression correlate across languages and cultures. J. Cross Cult. Psychol. 32(1), 6–92 (2001)
Scherer, K.R.: Expression of emotion in voice and music. J. Voice 9(3), 235–248 (1995)
Scherer, K.R., Sundberg, J., Tamarit, L., Salomão, G.: Comparing the acoustic expression of emotion in the speaking and the singing voice. Comput. Speech Lang. 29(1), 218–235 (2013)
Schimmack, U., Grob, A.: Dimensional models of core affect: a quantitative comparison by means of structural equation modeling. Eur. J. Pers. 14, 325–345 (2000)
Sloboda, J.A., Juslin, P.: Psychological perspectives on music and emotion. In: Juslin, P.N., Sloboda, J.A. (eds.) Music and Emotion: Theory and Research, pp. 71–104. Oxford University Press, New York (2001)
Sundberg, J., Iwarsson, J., Hagegard, H.: A singer’s expression of emotions in sung performance. Vocal Fold Physiology: Voice Quality Control, pp. 217–231 (1995)
Sundberg, J., Patel, S., Bjorkner, E., Scherer, K.R.: Interdependencies among voice source parameters in emotional speech. IEEE Trans. Affect. Comput. 2(3), 162–174 (2011)
Watts, C., Barnes-Burroughs, K., Estis, J. Blanton, D.: The singing power ratio as an objective measure of singing voice quality in untrained talented and nontalented singers. J. Voice, 20(1), 82–88 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Mouawad, P., Desainte-Catherine, M., Gégout-Petit, A., Semal, C. (2014). On the Perception of Affect in the Singing Voice: A Study of Acoustic Cues. In: Aramaki, M., Derrien, O., Kronland-Martinet, R., Ystad, S. (eds) Sound, Music, and Motion. CMMR 2013. Lecture Notes in Computer Science(), vol 8905. Springer, Cham. https://doi.org/10.1007/978-3-319-12976-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-12976-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12975-4
Online ISBN: 978-3-319-12976-1
eBook Packages: Computer ScienceComputer Science (R0)